From sebastian at sipsolutions.net  Fri Jan  1 21:54:19 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Fri, 01 Jan 2021 20:54:19 -0600
Subject: [Numpy-discussion] updated backwards compatibility and
 deprecation policy NEP
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Message-ID: <a46e92f99deb319a2f5006ae2d81b2095bf8a93c.camel@sipsolutions.net>

On Wed, 2020-12-30 at 11:43 -0600, Sebastian Berg wrote:
> On Wed, 2020-12-30 at 16:27 +0100, Ralf Gommers wrote:
<snip>
> > 
> > That's very hard to describe, since it relies so much on previous
> > experience and qualitative judgements. That's the main reason why I
> > had
> > more examples before, but they just led to more discussion about
> > those
> > examples - so that didn't quite have the intended effect.
<snip>
> I only took a short course and used this very little. I am sure there
> are many here with industry experience where the use of Q&A is every
> day work.
> 
> 
> One concept from there is to create a risk/danger and probability
> assessment, which can be ad-hoc for your product.? An example just to
> make something up:


I am not sure anyone finds this interesting or if fits to the NEP
specifically [1], but I truly think it can be useful (although maybe it
doesn't need to be formalized). So I fleshed it
out:?https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw?(also pasted it below)

My reasoning for suggesting it is that a process/formalism (no matter
how ridiculous it may seem at first) for how to assess the impact of a
backward compatible change can be helpful by:?conceptualizing, clearly
separating backward incompatible impact assessment from benefits
assessment, making it easier to follow a decision/thought processes,
and allowing some nuance [2].

I actually believe that it can help with difficult decisions, even if
only applied occasionally, and that it is not a burden because it
provides fairly steps. Will it be useful often? Maybe not. But every
time there is a proposal and we pause and hesitate because it is
unclear whether it is worth the backcompat impact, I think this can
provide a way to discuss it and come to a decision as objectively as
possible. (And no, I do not think that any of the categories or
mitigation strategies are an exact science.)

Cheers,

Sebastian


[1] This is additional to the proposed promises such as a two releases
of deprecations and discussing most/all deprecations on the mailing
list, which are unrelated. It is rather to provide a formalism where
currently only the examples give points of reference.
[2] There is a reason that also the Python version is short and
intentionally
fuzzy:?https://www.python.org/dev/peps/pep-0387/?and?https://discuss.python.org/t/pep-387-backwards-compatibilty-policy/4421
?There are just few definite rules that can be formalized, so a
framework for diligent assessment seems the best we can do (if we want
to).





Assessing impactHere ?impact? means how unmodified code may be negatively affected by a
change ignoring any deprecation period.

To get an idea about how much impact a change has, try to list all
potential impacts. This will often be just a single item (user of
function?x?has to replace it with?y), but it could be multiple
different ones.?After?listing all potential impacts rank them on the
following two scales (do not yet think about how to make the transition
easier):
   1. Severity?(How bad is the impact for an affected user?)Minor: A
      performance regression or change in (undocumented) warning/error
      category will fall here. This type of change would normally not require
      a deprecation cycle or special consideration.Typical: Code must be
      updated to avoid an error, the update is simple to do in a way that
      works both on existing and future NumPy versions.Severe: Code will
      error or crash, and there is no simple work around or fix.Critical:
      Code returns incorrect results. A change requiring massive effort may
      fall here. A hard crash (e.g. segfault) in itself is
      typically?not?critical.
   2. Likelihood?(How many users does the change affect?)Rare: Change has
      very few impacted users (or even no known users after a code search).
      The normal assumption is that there is always someone affected, but a
      rarely used keyword argument of an already rarely used function will
      fall here.Limited: Change is in a rarely used function or function
      argument. Another possibility is that it affects only a small group of
      very advanced users.Common: Change affects a bigger audience or
      multiple large downstream libraries.Ubiquitous: Change affects a large
      fraction of NumPy users.
The categories will not always be perfectly clear. That is OK. Rather
than establishing precise guidelines, the purpose is a
structured?processes?that can be reviewed.?When the impact is
exceptionally difficult to assess, it is often feasible to try a change
on the development branch while signalling willigness to revert it.
Downstream libraries test against it (and the release candidate) which
gives a chance to correct an originally optimistic assessment.

After assessing each impact, it will fall somewhere on the following
table:
Severity\LikelyhoodRareLimitedCommonUbiquitousMinorokokok?Typicalok?no?Severeno?noCriticalno?nonono
Note that all changes should normally follow the two release
deprecation warning policy (except ?minor? ones). The ?no? fields means
a change is clearly unacceptable, although a NEP can always overrule
it. This table only assesses the ?impact?. It does not assess how the
impact compares to the benefits of the proposed change. This must be
favourable no matter how small the impact is. However, by assessing the
impact, it will be easier to weigh it against the benefit.?(Note that
the table is not symmetric. An impact with ?critical? severity is
unlikely to be considered even when no known users are impacted.)
Mitigation and arguing of benefitsAny change falling outside the ?ok? fields requires careful
consideration. When an impact is larger, you can try to mitigate it and
?move? on the table. Some possible reasons for this are:
 * A avoidable warning for at least two releases (the policy for any
   change that modifies behaviour) reduces a change one category (usually
   from ?typical? to ?minor? severity).
 * The severity category may be reduced by creating an easy work around
   (i.e. to move it from ?sever? to ?typical?).
 * Sometimes a change may break working code, but also fix?existing?bugs,
   this can offset the severity. In extreme cases, this may warrant
   classifying a change as a bug-fix.
 * For particularly noisy changes (i.e. ubiquitous category) considering
   fixing downstream packages, delay the warning (or use
   a?PendingDeprecationWarning). Simply prolonging the the deprecation
   period is also an option. This reduces how many users struggle with the
   change and smoothens the transition.
 * Exceptionally clear documentation and communication could be used to
   ensure that the impact is more acceptable. This may not be enough to
   move a ?category? by itself, but also helps.
After mitigation, the benefits can be assessed:
 * Any benefit of the change can be argued to ?offset? the impact. If this
   is necessary, a broad community discussion on the mailing list is
   required. It should be clear that this does not actually ?mitigate? the
   impact but rather argues that the benefit outweighs it.
These are not a fixed set of rules, but provide a framework to assess
and then try to mitigate the impact of a proposed change to an
acceptable level. Arguing that a benefit can overcome multiple ?impact?
categories will require exceptionally large benefits, and most likely a
NEP. For example a change with an initial impact classification of
?severe? and ?ubiquitous? is unlikely to even be considered unless the
severity can be reduced.
Many deprecations will fall somewhere below or equal to a ?typical and
limited? impact (i.e. removal of an uncommon function argument). They
recieve a deprecation warning to make the impact acceptable with a
brief discussiong that the change itself is worthwhile (i.e. the API is
much cleaner afterwards). Any more disruptive change requires broad
community discussion. This needs at least a discussion on the NumPy
mailing list and it is likely that the person proposing it will be
asked to write a NEP.
Summary and reasoning for this processessThe aim of this process and table is to provide a loose formalism with
the goal of:
 * Diligence:?Following this process ensures detailed assessment of its
   impact without being distracted by the benefits. This is achieved by
   following well defined steps:Listing each potential impact (usually
   one).Assessing the severity.Assessing the likelihood.Discussing what
   steps are/can be taken to lower the impact?ignoring any benefits.If the
   impact is not low at this point, this should prompt considering and
   listing of alternatives.Argue that the benefits outweigh the remaining
   impact. (This is a distinct step: the original impact assessment stands
   as it was.)
 * Transparency:?Using this process for difficult decisions makes it
   easier for the reviewer and community to follow how a decision was made
   and criticize it.
 * Nuance:?When the it is clear that an impact is larger than typical with
   will prompt more care and thought. In some cases it may also clarify
   that a change is lower impact than expected on first sight.
 * Experience:?Using a similar formalism for many changes makes it easier
   to learn from past decisions by providing an approach to compare and
   conceptualize them.
We aim to follow these steps in the future for difficult decisions. In
general, any reviewer and community member may ask for this process to
be followed for a proposed change, if the change is difficult, it will
be worth the effort. If it is very low impact it will be quick to
clarify why.
NOTE: At this time the process is new and is expected to require
clarification.
ExamplesIt should be stressed again, that the categories will rarely be clear
and intentially are categorized with some uncertainty below. Even
unclear categories can help in forming a more clear idea of a change.
HistogramThe ?histogram? example doesn?t really add much with respect to this
process. But noting the duplicate effort/impact would move probably
move it into a more severe category than most deprecations.?That makes
it a more difficult decision and indicates that careful thought should
be spend on alternatives.
Integer indexing requirement * Severity: Typical?Severe (although fairly easy, users often had to do
   many changes)
 * Likelihood: Ubiquitous
How ubiquitous it really was became probably only clear after the (rc?)
release. The change would now probably go through a NEP as it initially
falls into the lower right part of the table.?To get into the
?acceptable? part of the table we note that:
   1. Real bugs were caught in the processes (argued to reduce severity)
   2. The deprecation was delayed and longer than normally (argued to
      mitigate the number of affected users by giving much more time)
Even with these considerations, it still has a larger impact and
clearly requires careful thought and community discussion about the
benefits.
Removing financial functions * Severity: Severe (on the high end)
 * Likelihood: Limited (maybe common)
While not used by a large user base (limited), the removal is
disurptive (severe). The change ultimately required a NEP, since it is
not easy to weigh the maintainence advantage of removing the functions
against the impact to their users.
The NEP included the reduction of the severity by providing a work-
around: A pip installable package as a drop-in replacement (reducing
the severity). For heavy users of these functions this will still be
more severe than most deprecations, but it lowered the impact
assessment enough to consider the benefit of removal to outweigh the
impact.
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From melissawm at gmail.com  Sat Jan  2 13:03:02 2021
From: melissawm at gmail.com (=?UTF-8?Q?Melissa_Mendon=C3=A7a?=)
Date: Sat, 2 Jan 2021 15:03:02 -0300
Subject: [Numpy-discussion] Documentation Team meeting - Monday January 4
In-Reply-To: <CAC7J6Va3n9Hdym+RmscOkDyf1ukH+DDtCv7N9D8y0cX1a+uC-A@mail.gmail.com>
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Hi all! Happy new year!

Our next Documentation Team meeting will be on *Monday, January 4* at ***4PM
UTC***. All are welcome - you don't need to already be a contributor to
join. If you have questions or are curious about what we're doing, we'll be
happy to meet you!

If you wish to join on Zoom, use this link:

https://zoom.us/j/96219574921?pwd=VTRNeGwwOUlrYVNYSENpVVBRRjlkZz09
<https://zoom.us/j/420005230>

Here's the permanent hackmd document with the meeting notes (still being
updated in the next few days!):

https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg
<https://www.google.com/url?q=https%3A%2F%2Fhackmd.io%2FoB_boakvRqKR-_2jRV-Qjg&sa=D&usd=2&usg=AFQjCNGIOzVwlfDFd6YAgBwVUjmjQKWRSw>

Hope to see you around!

** You can click this link to get the correct time at your timezone:
https://www.timeanddate.com/worldclock/fixedtime.html?msg=NumPy+Documentation+Team+Meeting&iso=20210104T16&p1=1440&ah=1


- Melissa
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From ralf.gommers at gmail.com  Sat Jan  2 12:06:16 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Sat, 2 Jan 2021 18:06:16 +0100
Subject: [Numpy-discussion] updated backwards compatibility and
 deprecation policy NEP
In-Reply-To: <a46e92f99deb319a2f5006ae2d81b2095bf8a93c.camel@sipsolutions.net>
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On Sat, Jan 2, 2021 at 3:55 AM Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> On Wed, 2020-12-30 at 11:43 -0600, Sebastian Berg wrote:
>
> On Wed, 2020-12-30 at 16:27 +0100, Ralf Gommers wrote:
>
> <snip>
>
>
> That's very hard to describe, since it relies so much on previous
> experience and qualitative judgements. That's the main reason why I
> had
> more examples before, but they just led to more discussion about
> those
> examples - so that didn't quite have the intended effect.
>
> <snip>
>
> I only took a short course and used this very little. I am sure there
> are many here with industry experience where the use of Q&A is every
> day work.
>
>
Thanks for thinking about this Sebastian.

I used to use such a risk management approach fairly regularly, and it can
be useful. In general it's something you do for a larger design change or
new product, rather than for an individual change. It helps get an overview
of the main risks, and prompts thinking about risks you may have missed.


>
> One concept from there is to create a risk/danger and probability
> assessment, which can be ad-hoc for your product.  An example just to
> make something up:
>
>
>
> I am not sure anyone finds this interesting or if fits to the NEP
> specifically [1], but I truly think it can be useful (although maybe it
> doesn't need to be formalized). So I fleshed it out:
> https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw (also pasted it below)
>

I'd be happy to try it. It does feel a bit too much to put all that content
into the NEP though. Maybe we can just add a more brief "assess severity
and likelihood and severity of your proposed change, and include that
assessment when proposing a deprecation. See <here> for more details". And
then we can link to a wiki page or separate doc page, that we can then
easily update without it being a NEP revision.

Cheers,
Ralf


> My reasoning for suggesting it is that a process/formalism (no matter how
> ridiculous it may seem at first) for how to assess the impact of a backward
> compatible change can be helpful by: conceptualizing, clearly separating
> backward incompatible impact assessment from benefits assessment, making it
> easier to follow a decision/thought processes, and allowing some nuance [2].
>
> I actually believe that it can help with difficult decisions, even if only
> applied occasionally, and that it is not a burden because it provides
> fairly steps. Will it be useful often? Maybe not. But every time there is a
> proposal and we pause and hesitate because it is unclear whether it is
> worth the backcompat impact, I think this can provide a way to discuss it
> and come to a decision as objectively as possible. (And no, I do not think
> that any of the categories or mitigation strategies are an exact science.)
>
> Cheers,
>
> Sebastian
>
>
> [1] This is additional to the proposed promises such as a two releases of
> deprecations and discussing most/all deprecations on the mailing list,
> which are unrelated. It is rather to provide a formalism where currently
> only the examples give points of reference.
> [2] There is a reason that also the Python version is short and
> intentionally fuzzy: https://www.python.org/dev/peps/pep-0387/ and
> https://discuss.python.org/t/pep-387-backwards-compatibilty-policy/4421 There
> are just few definite rules that can be formalized, so a framework for
> diligent assessment seems the best we can do (if we want to).
>
>
>
>
>
> Assessing impact
> Here ?impact? means how unmodified code may be negatively affected by a
> change ignoring any deprecation period.
>
> To get an idea about how much impact a change has, try to list all
> potential impacts. This will often be just a single item (user of function
>  x has to replace it with y), but it could be multiple different ones.
> *After* listing all potential impacts rank them on the following two
> scales (do not yet think about how to make the transition easier):
>
>    1. *Severity* (How bad is the impact for an affected user?)
>    - Minor: A performance regression or change in (undocumented)
>       warning/error category will fall here. This type of change would normally
>       not require a deprecation cycle or special consideration.
>       - Typical: Code must be updated to avoid an error, the update is
>       simple to do in a way that works both on existing and future NumPy versions.
>       - Severe: Code will error or crash, and there is no simple work
>       around or fix.
>       - Critical: Code returns incorrect results. A change requiring
>       massive effort may fall here. A hard crash (e.g. segfault) in itself is
>       typically *not* critical.
>    2. *Likelihood* (How many users does the change affect?)
>    - Rare: Change has very few impacted users (or even no known users
>       after a code search). The normal assumption is that there is always someone
>       affected, but a rarely used keyword argument of an already rarely used
>       function will fall here.
>       - Limited: Change is in a rarely used function or function
>       argument. Another possibility is that it affects only a small group of very
>       advanced users.
>       - Common: Change affects a bigger audience or multiple large
>       downstream libraries.
>       - Ubiquitous: Change affects a large fraction of NumPy users.
>
> The categories will not always be perfectly clear. That is OK. Rather than
> establishing precise guidelines, the purpose is a structured *processes* that
> can be reviewed. When the impact is exceptionally difficult to assess, it
> is often feasible to try a change on the development branch while
> signalling willigness to revert it. Downstream libraries test against it
> (and the release candidate) which gives a chance to correct an originally
> optimistic assessment.
>
> After assessing each impact, it will fall somewhere on the following table:
> Severity\LikelyhoodRareLimitedCommonUbiquitous
> *Minor* ok ok ok?
> *Typical* ok? no?
> *Severe* no? no
> *Critical* no? no no no
> Note that all changes should normally follow the two release deprecation
> warning policy (except ?minor? ones). The ?no? fields means a change is
> clearly unacceptable, although a NEP can always overrule it. This table
> only assesses the ?impact?. It does not assess how the impact compares to
> the benefits of the proposed change. This must be favourable no matter how
> small the impact is. However, by assessing the impact, it will be easier to
> weigh it against the benefit. (Note that the table is not symmetric. An
> impact with ?critical? severity is unlikely to be considered even when no
> known users are impacted.)
>
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Mitigation-and-arguing-of-benefits>Mitigation
> and arguing of benefits
> Any change falling outside the ?ok? fields requires careful consideration.
> When an impact is larger, you can try to mitigate it and ?move? on the
> table. Some possible reasons for this are:
>
>    - A avoidable warning for at least two releases (the policy for any
>    change that modifies behaviour) reduces a change one category (usually from
>    ?typical? to ?minor? severity).
>    - The severity category may be reduced by creating an easy work around
>    (i.e. to move it from ?sever? to ?typical?).
>    - Sometimes a change may break working code, but also fix *existing* bugs,
>    this can offset the severity. In extreme cases, this may warrant
>    classifying a change as a bug-fix.
>    - For particularly noisy changes (i.e. ubiquitous category)
>    considering fixing downstream packages, delay the warning (or use a
>    PendingDeprecationWarning). Simply prolonging the the deprecation
>    period is also an option. This reduces how many users struggle with the
>    change and smoothens the transition.
>    - Exceptionally clear documentation and communication could be used to
>    ensure that the impact is more acceptable. This may not be enough to move a
>    ?category? by itself, but also helps.
>
> After mitigation, the benefits can be assessed:
>
>    - Any benefit of the change can be argued to ?offset? the impact. If
>    this is necessary, a broad community discussion on the mailing list is
>    required. It should be clear that this does not actually ?mitigate? the
>    impact but rather argues that the benefit outweighs it.
>
> These are not a fixed set of rules, but provide a framework to assess and
> then try to mitigate the impact of a proposed change to an acceptable
> level. Arguing that a benefit can overcome multiple ?impact? categories
> will require exceptionally large benefits, and most likely a NEP. For
> example a change with an initial impact classification of ?severe? and
> ?ubiquitous? is unlikely to even be considered unless the severity can be
> reduced.
> Many deprecations will fall somewhere below or equal to a ?typical and
> limited? impact (i.e. removal of an uncommon function argument). They
> recieve a deprecation warning to make the impact acceptable with a brief
> discussiong that the change itself is worthwhile (i.e. the API is much
> cleaner afterwards). Any more disruptive change requires broad community
> discussion. This needs at least a discussion on the NumPy mailing list and
> it is likely that the person proposing it will be asked to write a NEP.
>
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Summary-and-reasoning-for-this-processess>Summary
> and reasoning for this processess
> The aim of this process and table is to provide a loose formalism with the
> goal of:
>
>    - *Diligence:* Following this process ensures detailed assessment of
>    its impact without being distracted by the benefits. This is achieved by
>    following well defined steps:
>       1. Listing each potential impact (usually one).
>       2. Assessing the severity.
>       3. Assessing the likelihood.
>       4. Discussing what steps are/can be taken to lower the impact *ignoring
>       any benefits*.
>       5. If the impact is not low at this point, this should prompt
>       considering and listing of alternatives.
>       6. Argue that the benefits outweigh the remaining impact. (This is
>       a distinct step: the original impact assessment stands as it was.)
>    - *Transparency:* Using this process for difficult decisions makes it
>    easier for the reviewer and community to follow how a decision was made and
>    criticize it.
>    - *Nuance:* When the it is clear that an impact is larger than typical
>    with will prompt more care and thought. In some cases it may also clarify
>    that a change is lower impact than expected on first sight.
>    - *Experience:* Using a similar formalism for many changes makes it
>    easier to learn from past decisions by providing an approach to compare and
>    conceptualize them.
>
> We aim to follow these steps in the future for difficult decisions. In
> general, any reviewer and community member may ask for this process to be
> followed for a proposed change, if the change is difficult, it will be
> worth the effort. If it is very low impact it will be quick to clarify why.
> NOTE: At this time the process is new and is expected to require
> clarification.
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Examples>Examples
> It should be stressed again, that the categories will rarely be clear and
> intentially are categorized with some uncertainty below. Even unclear
> categories can help in forming a more clear idea of a change.
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Histogram>Histogram
> The ?histogram? example doesn?t really add much with respect to this
> process. But noting the duplicate effort/impact would move probably move it
> into a more severe category than most deprecations. That makes it a more
> difficult decision and indicates that careful thought should be spend on
> alternatives.
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Integer-indexing-requirement>Integer
> indexing requirement
>
>    - Severity: Typical?Severe (although fairly easy, users often had to
>    do many changes)
>    - Likelihood: Ubiquitous
>
> How ubiquitous it really was became probably only clear after the (rc?)
> release. The change would now probably go through a NEP as it initially
> falls into the lower right part of the table. To get into the
> ?acceptable? part of the table we note that:
>
>    1. Real bugs were caught in the processes (argued to reduce severity)
>    2. The deprecation was delayed and longer than normally (argued to
>    mitigate the number of affected users by giving much more time)
>
> Even with these considerations, it still has a larger impact and clearly
> requires careful thought and community discussion about the benefits.
> <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Removing-financial-functions>Removing
> financial functions
>
>    - Severity: Severe (on the high end)
>    - Likelihood: Limited (maybe common)
>
> While not used by a large user base (limited), the removal is disurptive
> (severe). The change ultimately required a NEP, since it is not easy to
> weigh the maintainence advantage of removing the functions against the
> impact to their users.
> The NEP included the reduction of the severity by providing a work-around:
> A pip installable package as a drop-in replacement (reducing the severity).
> For heavy users of these functions this will still be more severe than most
> deprecations, but it lowered the impact assessment enough to consider the
> benefit of removal to outweigh the impact.
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From sebastian at sipsolutions.net  Sat Jan  2 14:10:54 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Sat, 02 Jan 2021 13:10:54 -0600
Subject: [Numpy-discussion] updated backwards compatibility and
 deprecation policy NEP
In-Reply-To: <CABL7CQicxronymH+iS1JyATBjFxwQmkqxei2gQVZcQ5K9eZ=hw@mail.gmail.com>
References: <CABL7CQinr0yVkxKwrRfz5v4QKB1YJtuJN8Mkq0WRS9jqoBOJVQ@mail.gmail.com>
 <CAEBuzr_Y9B=jr71=JDix90AF0ettXN0YYU6t8esuPYbsFZhngA@mail.gmail.com>
 <CABL7CQiFhQPCybpO=4mk6Ao-RdqiFHP-bKE=t09obRf05iK1_w@mail.gmail.com>
 <b5c5a08b98f8e835be475f7760bca6ee1ff75462.camel@sipsolutions.net>
 <a46e92f99deb319a2f5006ae2d81b2095bf8a93c.camel@sipsolutions.net>
 <CABL7CQicxronymH+iS1JyATBjFxwQmkqxei2gQVZcQ5K9eZ=hw@mail.gmail.com>
Message-ID: <d04ccc5c1339254f51ddc6ed01837d41fb2bb448.camel@sipsolutions.net>

On Sat, 2021-01-02 at 18:06 +0100, Ralf Gommers wrote:
> On Sat, Jan 2, 2021 at 3:55 AM Sebastian Berg <
> sebastian at sipsolutions.net>
> wrote:
> 
> > On Wed, 2020-12-30 at 11:43 -0600, Sebastian Berg wrote:
> > 
> > On Wed, 2020-12-30 at 16:27 +0100, Ralf Gommers wrote:
> > 
> > <snip>
> > 
> > 
> > That's very hard to describe, since it relies so much on previous
> > experience and qualitative judgements. That's the main reason why I
> > had
> > more examples before, but they just led to more discussion about
> > those
> > examples - so that didn't quite have the intended effect.
> > 
> > <snip>
> > 
> > I only took a short course and used this very little. I am sure
> > there
> > are many here with industry experience where the use of Q&A is
> > every
> > day work.
> > 
> > 
> Thanks for thinking about this Sebastian.
> 
> I used to use such a risk management approach fairly regularly, and
> it can
> be useful. In general it's something you do for a larger design
> change or
> new product, rather than for an individual change. It helps get an
> overview
> of the main risks, and prompts thinking about risks you may have
> missed.
> 

Yeah, I guess its for new products mostly, to compile many risks and
make it easier to compare them.  And yes, we do not have "many" risks,
unless you would compile this for the complete changelog between one or
more versions.

> 
> > 
> > One concept from there is to create a risk/danger and probability
> > assessment, which can be ad-hoc for your product.? An example just
> > to
> > make something up:
> > 
> > 
> > 
> > I am not sure anyone finds this interesting or if fits to the NEP
> > specifically [1], but I truly think it can be useful (although
> > maybe it
> > doesn't need to be formalized). So I fleshed it out:
> > https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw?(also pasted it below)
> > 
> 
> I'd be happy to try it. It does feel a bit too much to put all that
> content
> into the NEP though. Maybe we can just add a more brief "assess
> severity
> and likelihood and severity of your proposed change, and include that
> assessment when proposing a deprecation. See <here> for more
> details". And
> then we can link to a wiki page or separate doc page, that we can
> then
> easily update without it being a NEP revision.

Yes, it adds a lot of content and I don't want to force it on anyone or
into the NEP, in that sense it is more brainstorming than a very
concrete proposal.  And I am also fine with just dropping it, whatever
others think is useful.  I fleshed it out a bit, because I actually
think it ends up representing fairly well how I currently try to
approach this and I think it may be useful when a proposal gets stuck
because it is unclear whether it is worth the pain/risk.

Cheers,

Sebastian

> 
> Cheers,
> Ralf
> 
> 
> > My reasoning for suggesting it is that a process/formalism (no
> > matter how
> > ridiculous it may seem at first) for how to assess the impact of a
> > backward
> > compatible change can be helpful by: conceptualizing, clearly
> > separating
> > backward incompatible impact assessment from benefits assessment,
> > making it
> > easier to follow a decision/thought processes, and allowing some
> > nuance [2].
> > 
> > I actually believe that it can help with difficult decisions, even
> > if only
> > applied occasionally, and that it is not a burden because it
> > provides
> > fairly steps. Will it be useful often? Maybe not. But every time
> > there is a
> > proposal and we pause and hesitate because it is unclear whether it
> > is
> > worth the backcompat impact, I think this can provide a way to
> > discuss it
> > and come to a decision as objectively as possible. (And no, I do
> > not think
> > that any of the categories or mitigation strategies are an exact
> > science.)
> > 
> > Cheers,
> > 
> > Sebastian
> > 
> > 
> > [1] This is additional to the proposed promises such as a two
> > releases of
> > deprecations and discussing most/all deprecations on the mailing
> > list,
> > which are unrelated. It is rather to provide a formalism where
> > currently
> > only the examples give points of reference.
> > [2] There is a reason that also the Python version is short and
> > intentionally fuzzy: https://www.python.org/dev/peps/pep-0387/?and
> >  
> > https://discuss.python.org/t/pep-387-backwards-compatibilty-policy/4421
> > ?There
> > are just few definite rules that can be formalized, so a framework
> > for
> > diligent assessment seems the best we can do (if we want to).
> > 
> > 
> > 
> > 
> > 
> > Assessing impact
> > Here ?impact? means how unmodified code may be negatively affected
> > by a
> > change ignoring any deprecation period.
> > 
> > To get an idea about how much impact a change has, try to list all
> > potential impacts. This will often be just a single item (user of
> > function
> > ?x has to replace it with y), but it could be multiple different
> > ones.
> > *After* listing all potential impacts rank them on the following
> > two
> > scales (do not yet think about how to make the transition easier):
> > 
> > ?? 1. *Severity* (How bad is the impact for an affected user?)
> > ?? - Minor: A performance regression or change in (undocumented)
> > ????? warning/error category will fall here. This type of change
> > would normally
> > ????? not require a deprecation cycle or special consideration.
> > ????? - Typical: Code must be updated to avoid an error, the update
> > is
> > ????? simple to do in a way that works both on existing and future
> > NumPy versions.
> > ????? - Severe: Code will error or crash, and there is no simple
> > work
> > ????? around or fix.
> > ????? - Critical: Code returns incorrect results. A change
> > requiring
> > ????? massive effort may fall here. A hard crash (e.g. segfault) in
> > itself is
> > ????? typically *not* critical.
> > ?? 2. *Likelihood* (How many users does the change affect?)
> > ?? - Rare: Change has very few impacted users (or even no known
> > users
> > ????? after a code search). The normal assumption is that there is
> > always someone
> > ????? affected, but a rarely used keyword argument of an already
> > rarely used
> > ????? function will fall here.
> > ????? - Limited: Change is in a rarely used function or function
> > ????? argument. Another possibility is that it affects only a small
> > group of very
> > ????? advanced users.
> > ????? - Common: Change affects a bigger audience or multiple large
> > ????? downstream libraries.
> > ????? - Ubiquitous: Change affects a large fraction of NumPy users.
> > 
> > The categories will not always be perfectly clear. That is OK.
> > Rather than
> > establishing precise guidelines, the purpose is a structured
> > *processes* that
> > can be reviewed. When the impact is exceptionally difficult to
> > assess, it
> > is often feasible to try a change on the development branch while
> > signalling willigness to revert it. Downstream libraries test
> > against it
> > (and the release candidate) which gives a chance to correct an
> > originally
> > optimistic assessment.
> > 
> > After assessing each impact, it will fall somewhere on the
> > following table:
> > Severity\LikelyhoodRareLimitedCommonUbiquitous
> > *Minor* ok ok ok?
> > *Typical* ok? no?
> > *Severe* no? no
> > *Critical* no? no no no
> > Note that all changes should normally follow the two release
> > deprecation
> > warning policy (except ?minor? ones). The ?no? fields means a
> > change is
> > clearly unacceptable, although a NEP can always overrule it. This
> > table
> > only assesses the ?impact?. It does not assess how the impact
> > compares to
> > the benefits of the proposed change. This must be favourable no
> > matter how
> > small the impact is. However, by assessing the impact, it will be
> > easier to
> > weigh it against the benefit. (Note that the table is not
> > symmetric. An
> > impact with ?critical? severity is unlikely to be considered even
> > when no
> > known users are impacted.)
> > 
> > < 
> > https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Mitigation-and-arguing-of-benefits
> > >Mitigation
> > and arguing of benefits
> > Any change falling outside the ?ok? fields requires careful
> > consideration.
> > When an impact is larger, you can try to mitigate it and ?move? on
> > the
> > table. Some possible reasons for this are:
> > 
> > ?? - A avoidable warning for at least two releases (the policy for
> > any
> > ?? change that modifies behaviour) reduces a change one category
> > (usually from
> > ?? ?typical? to ?minor? severity).
> > ?? - The severity category may be reduced by creating an easy work
> > around
> > ?? (i.e. to move it from ?sever? to ?typical?).
> > ?? - Sometimes a change may break working code, but also fix
> > *existing* bugs,
> > ?? this can offset the severity. In extreme cases, this may warrant
> > ?? classifying a change as a bug-fix.
> > ?? - For particularly noisy changes (i.e. ubiquitous category)
> > ?? considering fixing downstream packages, delay the warning (or
> > use a
> > ?? PendingDeprecationWarning). Simply prolonging the the
> > deprecation
> > ?? period is also an option. This reduces how many users struggle
> > with the
> > ?? change and smoothens the transition.
> > ?? - Exceptionally clear documentation and communication could be
> > used to
> > ?? ensure that the impact is more acceptable. This may not be
> > enough to move a
> > ?? ?category? by itself, but also helps.
> > 
> > After mitigation, the benefits can be assessed:
> > 
> > ?? - Any benefit of the change can be argued to ?offset? the
> > impact. If
> > ?? this is necessary, a broad community discussion on the mailing
> > list is
> > ?? required. It should be clear that this does not actually
> > ?mitigate? the
> > ?? impact but rather argues that the benefit outweighs it.
> > 
> > These are not a fixed set of rules, but provide a framework to
> > assess and
> > then try to mitigate the impact of a proposed change to an
> > acceptable
> > level. Arguing that a benefit can overcome multiple ?impact?
> > categories
> > will require exceptionally large benefits, and most likely a NEP.
> > For
> > example a change with an initial impact classification of ?severe?
> > and
> > ?ubiquitous? is unlikely to even be considered unless the severity
> > can be
> > reduced.
> > Many deprecations will fall somewhere below or equal to a ?typical
> > and
> > limited? impact (i.e. removal of an uncommon function argument).
> > They
> > recieve a deprecation warning to make the impact acceptable with a
> > brief
> > discussiong that the change itself is worthwhile (i.e. the API is
> > much
> > cleaner afterwards). Any more disruptive change requires broad
> > community
> > discussion. This needs at least a discussion on the NumPy mailing
> > list and
> > it is likely that the person proposing it will be asked to write a
> > NEP.
> > 
> > < 
> > https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Summary-and-reasoning-for-this-processess
> > >Summary
> > and reasoning for this processess
> > The aim of this process and table is to provide a loose formalism
> > with the
> > goal of:
> > 
> > ?? - *Diligence:* Following this process ensures detailed
> > assessment of
> > ?? its impact without being distracted by the benefits. This is
> > achieved by
> > ?? following well defined steps:
> > ????? 1. Listing each potential impact (usually one).
> > ????? 2. Assessing the severity.
> > ????? 3. Assessing the likelihood.
> > ????? 4. Discussing what steps are/can be taken to lower the impact
> > *ignoring
> > ????? any benefits*.
> > ????? 5. If the impact is not low at this point, this should prompt
> > ????? considering and listing of alternatives.
> > ????? 6. Argue that the benefits outweigh the remaining impact.
> > (This is
> > ????? a distinct step: the original impact assessment stands as it
> > was.)
> > ?? - *Transparency:* Using this process for difficult decisions
> > makes it
> > ?? easier for the reviewer and community to follow how a decision
> > was made and
> > ?? criticize it.
> > ?? - *Nuance:* When the it is clear that an impact is larger than
> > typical
> > ?? with will prompt more care and thought. In some cases it may
> > also clarify
> > ?? that a change is lower impact than expected on first sight.
> > ?? - *Experience:* Using a similar formalism for many changes makes
> > it
> > ?? easier to learn from past decisions by providing an approach to
> > compare and
> > ?? conceptualize them.
> > 
> > We aim to follow these steps in the future for difficult decisions.
> > In
> > general, any reviewer and community member may ask for this process
> > to be
> > followed for a proposed change, if the change is difficult, it will
> > be
> > worth the effort. If it is very low impact it will be quick to
> > clarify why.
> > NOTE: At this time the process is new and is expected to require
> > clarification.
> > <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Examples>Examples
> > It should be stressed again, that the categories will rarely be
> > clear and
> > intentially are categorized with some uncertainty below. Even
> > unclear
> > categories can help in forming a more clear idea of a change.
> > <https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Histogram>Histogram
> > The ?histogram? example doesn?t really add much with respect to
> > this
> > process. But noting the duplicate effort/impact would move probably
> > move it
> > into a more severe category than most deprecations. That makes it a
> > more
> > difficult decision and indicates that careful thought should be
> > spend on
> > alternatives.
> > < 
> > https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Integer-indexing-requirement
> > >Integer
> > indexing requirement
> > 
> > ?? - Severity: Typical?Severe (although fairly easy, users often
> > had to
> > ?? do many changes)
> > ?? - Likelihood: Ubiquitous
> > 
> > How ubiquitous it really was became probably only clear after the
> > (rc?)
> > release. The change would now probably go through a NEP as it
> > initially
> > falls into the lower right part of the table. To get into the
> > ?acceptable? part of the table we note that:
> > 
> > ?? 1. Real bugs were caught in the processes (argued to reduce
> > severity)
> > ?? 2. The deprecation was delayed and longer than normally (argued
> > to
> > ?? mitigate the number of affected users by giving much more time)
> > 
> > Even with these considerations, it still has a larger impact and
> > clearly
> > requires careful thought and community discussion about the
> > benefits.
> > < 
> > https://hackmd.io/WuS1rCzrTYOTgzUfRJUOnw#Removing-financial-functions
> > >Removing
> > financial functions
> > 
> > ?? - Severity: Severe (on the high end)
> > ?? - Likelihood: Limited (maybe common)
> > 
> > While not used by a large user base (limited), the removal is
> > disurptive
> > (severe). The change ultimately required a NEP, since it is not
> > easy to
> > weigh the maintainence advantage of removing the functions against
> > the
> > impact to their users.
> > The NEP included the reduction of the severity by providing a work-
> > around:
> > A pip installable package as a drop-in replacement (reducing the
> > severity).
> > For heavy users of these functions this will still be more severe
> > than most
> > deprecations, but it lowered the impact assessment enough to
> > consider the
> > benefit of removal to outweigh the impact.
> > _______________________________________________
> > NumPy-Discussion mailing list
> > NumPy-Discussion at python.org
> > https://mail.python.org/mailman/listinfo/numpy-discussion
> > 
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From matti.picus at gmail.com  Sun Jan  3 02:42:51 2021
From: matti.picus at gmail.com (Matti Picus)
Date: Sun, 3 Jan 2021 09:42:51 +0200
Subject: [Numpy-discussion] proposal for NumPy sponsorship guidelines
 (NEP 46)
In-Reply-To: <CABL7CQgePO5hFLeHCFG+TPQvFN6wu6RNCDqAmKkbFYRmOqpRZA@mail.gmail.com>
References: <CABL7CQgePO5hFLeHCFG+TPQvFN6wu6RNCDqAmKkbFYRmOqpRZA@mail.gmail.com>
Message-ID: <f711a82a-9e7d-00aa-0689-7c1fdc61f2d5@gmail.com>


On 12/29/20 1:27 PM, Ralf Gommers wrote:
> Entities who fall under "significant active supporter" we'll call Sponsor.
> The minimum level of support given to NumPy to be considered a Sponsor 
> are:
>
> - $30,000/yr for unrestricted financial contributions
> - $60,000/yr for financial contributions for a particular purpose
> - $100,000/yr for in-kind contributions


How would this work for one-time contributions, or for sponsors that 
stop contributing? For instance, if an entity gives a $60,000 one-time 
unrestricted contribution (unlikely, but who knows?) would they be 
listed as sponsors for 24 months after the contribution and then have 
their name removed?


Also, the implementation should explicitly mention a mechanism to keep 
track of received contributions.


Matti


From ralf.gommers at gmail.com  Sun Jan  3 05:44:56 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Sun, 3 Jan 2021 11:44:56 +0100
Subject: [Numpy-discussion] proposal for NumPy sponsorship guidelines
 (NEP 46)
In-Reply-To: <f711a82a-9e7d-00aa-0689-7c1fdc61f2d5@gmail.com>
References: <CABL7CQgePO5hFLeHCFG+TPQvFN6wu6RNCDqAmKkbFYRmOqpRZA@mail.gmail.com>
 <f711a82a-9e7d-00aa-0689-7c1fdc61f2d5@gmail.com>
Message-ID: <CABL7CQhp4pO5JDC99J2GtKcBRRMaOqPMoKf54hy38jx+=PQSKw@mail.gmail.com>

On Sun, Jan 3, 2021 at 8:43 AM Matti Picus <matti.picus at gmail.com> wrote:

>
> On 12/29/20 1:27 PM, Ralf Gommers wrote:
> > Entities who fall under "significant active supporter" we'll call
> Sponsor.
> > The minimum level of support given to NumPy to be considered a Sponsor
> > are:
> >
> > - $30,000/yr for unrestricted financial contributions
> > - $60,000/yr for financial contributions for a particular purpose
> > - $100,000/yr for in-kind contributions
>
>
> How would this work for one-time contributions, or for sponsors that
> stop contributing? For instance, if an entity gives a $60,000 one-time
> unrestricted contribution (unlikely, but who knows?) would they be
> listed as sponsors for 24 months after the contribution and then have
> their name removed?
>

That could indeed be explained more clearly. What I intended with "active
support" on a yearly basis is that >1 yr after the donation takes place,
the acknowledgement can be moved from the Sponsor placements to the less
prominent historical acknowledgements page. We should specify a time period
for that, because sometimes renewals take time and there's no benefit to us
being in a hurry with decreasing the visibility of acknowledgements.

So how about:
- one year after a one-off donation is received, or at the end of a grant
period, we consider that support "inactive"
- we leave the acknowledgement in its place for at least another 6 months.
If appropriate, the funding team can discuss opportunities for renewal with
the sponsor
- after those 6 months, acknowledgement may be moved to the historical
overview. with exact timing at the discretion of the funding team, because
there may be reasons to keep it in the more prominent place for longer.

That way there's no fixed formula for amounts, but we can do things that
make sense for the project given amounts received, relationship with
sponsor, etc. I'm not a fan of $60k gives you 24 months, $90k 36 months -
that would be similar to "tiered sponsorship levels" discussed in the
Alternatives section.


>
>
> Also, the implementation should explicitly mention a mechanism to keep
> track of received contributions.
>

If we have a page on the website listing all support received since the
start of the project, that's automatically a tracking mechanism.

Cheers,
Ralf
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From felix.stamm at rwth-aachen.de  Mon Jan  4 06:00:52 2021
From: felix.stamm at rwth-aachen.de (Stamm, Felix)
Date: Mon, 4 Jan 2021 11:00:52 +0000
Subject: [Numpy-discussion] Speedups for intersect1d in numpy.lib
Message-ID: <b6694fd12c104039b70aed7c7f52460c@rwth-aachen.de>

Hello mailing list,


I would like to open a PR that improves the speed of intersect1d in particular for large arrays of potentially unequal sizes. As parts of the change would involve a new keyword I think I should write to this mailing list first (correct me if I am wrong).


Lets start with the current implementation of intersect1d. The steps are (roughly): I) concatenate both arrays II) sort that large array and III) keep only duplicates. This is a simple but not necessary fast implementation. In particular it has has complexity O( (len1 + len2) log(len1 + len2)).


I have two suggestions one of which can greatly improve the runtime (1) while the other has some minor improvements (2). Lets start with the major one.

1) Adding assume_sorted as keyword argument.
    If you can already assume that the arrays are sorted you can improve the runtime to min(len1, len2)*log(max(len1, len2)) which is orders of magnitude faster especially when the arrays intersected are unequal in size.
    The implementation basically is I) figure out which is the smaller array II) make that array unique III) use np.searchsorted to find duplicates of the smaller in the larger.

    I think that having assume_sorted as a keyword argument is quite useful, especially as the result of assume_sorted is always sorted. So chaining multiple intersections together can be made much faster.


2) Improve the performance in the case that we cannot assume sorted arrays

     In the case that we cannot assume that both arrays are already sorted we can still gain advantages. Mainly by sorting the arrays separately and then using np.searchsorted again. This brings the complexity down to O( len1 log(len1)  + len2 log(len2)) + min(len1, len2)*log(max(len1, len2)).


I already mention this in the issue 16964: https://github.com/numpy/numpy/issues/16964


Looking forward for your feedback.


Have a great day and stay safe


Felix Stamm

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From charlesr.harris at gmail.com  Mon Jan  4 11:05:07 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Mon, 4 Jan 2021 09:05:07 -0700
Subject: [Numpy-discussion] Sayed Adel has joined the developer team.
Message-ID: <CAB6mnx+meRhoQZjWnh2iydLHL+2QWb+oDxR=M35PXdNVzjKFBg@mail.gmail.com>

Hi All,

Sayed Adel is now part of the developer team. His SIMD work has been
substantial and ongoing, may it long continue. Welcome Sayed.

Chuck
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From matti.picus at gmail.com  Mon Jan  4 11:35:28 2021
From: matti.picus at gmail.com (Matti Picus)
Date: Mon, 4 Jan 2021 18:35:28 +0200
Subject: [Numpy-discussion] Sayed Adel has joined the developer team.
In-Reply-To: <CAB6mnx+meRhoQZjWnh2iydLHL+2QWb+oDxR=M35PXdNVzjKFBg@mail.gmail.com>
References: <CAB6mnx+meRhoQZjWnh2iydLHL+2QWb+oDxR=M35PXdNVzjKFBg@mail.gmail.com>
Message-ID: <8a71b0df-af12-1411-74d7-309d3a6aa971@gmail.com>


On 1/4/21 6:05 PM, Charles R Harris wrote:
> Hi All,
>
> Sayed Adel is now part of the developer team. His SIMD work has been 
> substantial and ongoing, may it long continue. Welcome Sayed.
>
> Chuck
>
Welcome Sayed.

Matti


From ralf.gommers at gmail.com  Mon Jan  4 11:52:29 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Mon, 4 Jan 2021 17:52:29 +0100
Subject: [Numpy-discussion] Sayed Adel has joined the developer team.
In-Reply-To: <8a71b0df-af12-1411-74d7-309d3a6aa971@gmail.com>
References: <CAB6mnx+meRhoQZjWnh2iydLHL+2QWb+oDxR=M35PXdNVzjKFBg@mail.gmail.com>
 <8a71b0df-af12-1411-74d7-309d3a6aa971@gmail.com>
Message-ID: <CABL7CQgWPhp7mh1FYU1GGiE2czWsMQSqfgpwJgeaNnBZu5Ujcg@mail.gmail.com>

On Mon, Jan 4, 2021 at 5:35 PM Matti Picus <matti.picus at gmail.com> wrote:

>
> On 1/4/21 6:05 PM, Charles R Harris wrote:
> > Hi All,
> >
> > Sayed Adel is now part of the developer team. His SIMD work has been
> > substantial and ongoing, may it long continue. Welcome Sayed.
> >
> > Chuck
> >
> Welcome Sayed.
>

Very well-deserved, thanks for all the great work Sayed!

Cheers,
Ralf
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From charlesr.harris at gmail.com  Tue Jan  5 09:26:38 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Tue, 5 Jan 2021 07:26:38 -0700
Subject: [Numpy-discussion] Welcome Chunlin to the NumPy development team.
Message-ID: <CAB6mnxJbJbiJypb+Dxc0FQ4YVLinNqi=81OHpdtukZfYLiKSUw@mail.gmail.com>

Hi All,

Welcome Chunlin Fang, aka Qiyu8, to the NumPy development team. He has made
substantial contributions to the SIMD infrastructure, both code and
reviews, and we look forward to his continuing work.

Chuck
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From ralf.gommers at gmail.com  Tue Jan  5 11:14:01 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Tue, 5 Jan 2021 17:14:01 +0100
Subject: [Numpy-discussion] Welcome Chunlin to the NumPy development
 team.
In-Reply-To: <CAB6mnxJbJbiJypb+Dxc0FQ4YVLinNqi=81OHpdtukZfYLiKSUw@mail.gmail.com>
References: <CAB6mnxJbJbiJypb+Dxc0FQ4YVLinNqi=81OHpdtukZfYLiKSUw@mail.gmail.com>
Message-ID: <CABL7CQivKhO+e8Rz4JR6Apma=bKC8i16Pz2fZYsSA6XKUVu6Bw@mail.gmail.com>

On Tue, Jan 5, 2021 at 3:27 PM Charles R Harris <charlesr.harris at gmail.com>
wrote:

> Hi All,
>
> Welcome Chunlin Fang, aka Qiyu8, to the NumPy development team. He has
> made substantial contributions to the SIMD infrastructure, both code and
> reviews, and we look forward to his continuing work.
>

Awesome. Thanks for all the great work Chunlin!

Cheers,
Ralf
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From charlesr.harris at gmail.com  Tue Jan  5 13:05:35 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Tue, 5 Jan 2021 11:05:35 -0700
Subject: [Numpy-discussion] NumPy 1.19.5 released
Message-ID: <CAB6mnxJ_h_v+UX7biCDTGvXmc9JWqBRuDm8Gea_mDXauC4NCRQ@mail.gmail.com>

Hi All,

On behalf of the NumPy team I am pleased to announce the release of NumPy
1.19.5. NumPy 1.19.5 is a short bugfix release. Apart from fixing several
bugs, the main improvement is an update to OpenBLAS 0.3.13 that works
around the Windows 2004 fmod bug while not breaking execution on other
platforms. This release supports Python 3.6-3.9 and is planned to be the
last release in the 1.19.x cycle. NumPy Wheels can be downloaded from PyPI
<https://pypi.org/project/numpy/1.19.5/>, source archives, release notes,
and wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v1.19.5>. Linux users will
need pip >= 0.19.3 in order to install manylinux2010 and manylinux2014
wheels.

*Contributors*

A total of 8 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.


   - Charles Harris
   - Christoph Gohlke
   - Matti Picus
   - Raghuveer Devulapalli
   - Sebastian Berg
   - Simon Graham +
   - Veniamin Petrenko +
   - Bernie Gray +


*Pull requests merged*

A total of 11 pull requests were merged for this release.

   - #17756: BUG: Fix segfault due to out of bound pointer in floatstatus...
   - #17774: BUG: fix np.timedelta64('nat').__format__ throwing an exception
   - #17775: BUG: Fixed file handle leak in array_tofile.
   - #17786: BUG: Raise recursion error during dimension discovery
   - #17917: BUG: Fix subarray dtype used with too large count in fromfile
   - #17918: BUG: 'bool' object has no attribute 'ndim'
   - #17919: BUG: ensure _UFuncNoLoopError can be pickled
   - #17924: BLD: use BUFFERSIZE=20 in OpenBLAS
   - #18026: BLD: update to OpenBLAS 0.3.13
   - #18036: BUG: make a variable volatile to work around clang compiler bug
   - #18114: REL: Prepare for the NumPy 1.19.5 release.

Cheers,

Charles Harris
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From sebastian at sipsolutions.net  Tue Jan  5 18:17:31 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Tue, 05 Jan 2021 17:17:31 -0600
Subject: [Numpy-discussion] NumPy Community Meeting Wednesday
Message-ID: <9b6e811a36194e250a362c7918ab46aef3eb08bf.camel@sipsolutions.net>

Hi all,

There will be a NumPy Community meeting Wednesday January 6th at 12pm
Pacific Time (20:00 UTC). Everyone is invited and encouraged to
join in and edit the work-in-progress meeting topics and notes at:

https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both

Best wishes

Sebastian

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From mikofski at berkeley.edu  Tue Jan  5 19:23:22 2021
From: mikofski at berkeley.edu (Dr. Mark Alexander Mikofski PhD)
Date: Tue, 5 Jan 2021 16:23:22 -0800
Subject: [Numpy-discussion] ANN: pvlib-0.8.1 released
Message-ID: <CAEqRcW1=YJL=nMFwqpw1Em8P2-KZBv1T-sodQLj_SZNt2Ya1+Q@mail.gmail.com>

Dear Pythonistas and solar power enthusiasts,

On behalf of the maintainers, we're happy to announce a new release of
pvlib python:
software for simulating performance of photovoltaic solar energy systems.

*See what's new for v0.8.1:*
* https://pvlib-python.readthedocs.io/en/stable/whatsnew.html

*Releases are available from PyPI and the conda-forge channel:*
* https://pypi.org/project/pvlib/
* https://anaconda.org/conda-forge/pvlib-python

*Read the Documentation:*
* https://pvlib-python.readthedocs.io/en/stable/index.html

*Report issues & contribute:*
* https://github.com/pvlib/pvlib-python

*Highlights:*
* AirSpeed Velocity benchmarks are now available!
https://pvlib-benchmarker.github.io/pvlib-benchmarks/
* A numpy-based implementation of the SPECTRL2 spectral irradiance model
and a usage example in the gallery.
https://pvlib-python.readthedocs.io/en/stable/auto_examples/plot_spectrl2_fig51A.html
* New functions for modeling inverters with multiple MPPTs.
* The Liu-Jordan irradiance function is deprecated, and will be removed in
v0.9. Please use the newer Campbell-Norman function instead, but note it
expects some different arguments.
* Added the option of fetching 5 and 15-minute PSM3 data using a new
"attributes" keyword argument.
* Clear-sky detection now uses centered rolling windows instead of
left-aligned rolling windows.

*The maintainers thank you for using pvlib python!*

-- 
Mark Mikofski, PhD (2005)
*Fiat Lux*
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From sebastian at sipsolutions.net  Thu Jan  7 16:01:04 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Thu, 07 Jan 2021 15:01:04 -0600
Subject: [Numpy-discussion] =?utf-8?q?NEP_43_=E2=80=93_How_should_ufunc_?=
 =?utf-8?q?=28inner_loops=29_be_designed=3F?=
Message-ID: <f4e37d9d86d7deaec066ee7da08059021e5c2d18.camel@sipsolutions.net>

Hi all,

I would like to nudge a discuss on NEP 43. Right now, mainly the first
part: That is everything up to "Promotion and dispatching". (This is
because promotion and dispatching should be the last bigger step in
refactoring NumPy.)

The full text is at: https://numpy.org/neps/nep-0043-extensible-ufuncs.html
which includes more information and gives some background to help
understand what is going on.


I personally believe that the `ArrayMethod` concept is pretty much
necessary to group dtype resolution with the loop functionality (and
other things currently handled by the `ufunc` which may be specific to
the dtypes involved, e.g. the `identity` could go here).


But how exactly it should look like and especially how we want the
inner-loop signature to be defined is flexible.

So comments on all parts of the NEP are very welcome! My main focus
would be on the `strided_inner_loop`. That is largely a continuation of
this old, but pretty insightful discussion:
    https://github.com/numpy/numpy/issues/12518


My current proposal (C-API) is this:

    def strided_inner_loop(
            context, data, dimensions, strides, innerloop_data):
        return 0  # or -1 on error

Where `context` is a structure holding some useful information:
 * The `ArrayMethod` itself (pretty much the `self`)
 * the dtypes/descriptors of all arrays
 * the original caller/ufunc (if applicable, useful for backcompat and
   error messages)
 * anything else that may come up in the future and should be passed
here (e.g. the Python interpreter state).
 * (Possibly gufunc signature unless we duplicate it on
   the ArrayMethod.)

Context may seem a bit weird, but passing dtypes is very convenient
e.g. for strings, passing `self`, the ArrayMethod (so to speak) may
also be necessary (e.g. for Python wrapping). And a struct means we
could expand it in the future, with some care [1].
Admittedly, numeric ufuncs can simply ignore this completely.

`data, dimensions, strides` is the main part of the existing signature.

`innerloop_data` is a user allocated/defined struct that is passed in
(and has its own "free" slot).  We currently use this for casting in
NumPy (so it does not need to be public right away, `context` should be
good enough for most things).
In the NEP I am considering that to pass `npy_intp *scratch_var = 0`
when this is unused.  That would allow persistent flags (e.g. whether a
warning was already given), which otherwise would require a lot of
additional complexity.
How this `innerloop_data` should look like is maybe the thing I am
least sold on myself. The current proposal just keeps around what is
already there as private API.


There are many more issues and potential future additions and I am
happy to discuss those as well. I am singling out the signature a bit,
because it seems particularly central and painful to change again in
the future.
Another example is how the signature of `get_loop()` should look like,
since it would be nice to eventually make it public (or even allow
overriding it) [2].  That is lower priority though, since we could get
away with keeping it private API for a while.

Cheers,

Sebastian



[1] That may need some thought: If others provide the struct (and not
just consume it like a ufunc/dtype author), they would need to ensure
ABI compatibility with NumPy and always "catch up" when NumPy extends
the struct.  I expect that can be managed, but I have not planned on
how do achieve it.  The thought is that e.g. sparse arrays could use
the NumPy ArrayMethod/loops directly, and then they would have to
provide the struct.  (Those projects probably can easily catch up, but
you would need to ensure a good error when a NumPy version happens to
be too new and is thus incompatible.)


[2] The things I am worried about there are:

* How we do alignment, largest power-of-two alignment would seem nice,
but that is really per-operand:
https://github.com/numpy/numpy/issues/17359

* The `move_references` is probably useful flag for buffering of data
that contains Python objects/references (it is used because the buffer
can be cleared out immediately).  For now we can say that this is only
relevant for NumPy itself.  But the mechanism itself does probably make
sense in the context of buffered loops (i.e. casting) ? I am honestly
not certain that it is actually worth much in performance/memory to
clear out buffers in one go.
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From sdupree at speakeasy.net  Fri Jan  8 20:33:15 2021
From: sdupree at speakeasy.net (Samuel Dupree)
Date: Fri, 8 Jan 2021 20:33:15 -0500
Subject: [Numpy-discussion] Compilation failures in f2py
Message-ID: <9728d48d-e417-d789-7a65-11ef0485a5ea@speakeasy.net>

I'm attempting to wrap a Fortran-77 source member library using f2py. 
I'm running he Anaconda distribution for Python 3.7.6 on a Mac Pro 
(2019) under Mac OS X Big Sur (ver. 11.1). The version of Xcode.app I'm 
running is 12.3. The version of NumPy I'm running is 1.18.3.

The errors I'm getting are from header files the compiler can't find as 
captured in the attached log file. A sample of the kind of errors I'm 
seeing are captured below.

compile options: 
'-I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7 
-I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include 
-I/Users/user/opt/anaconda3/include/python3.7m -c'
gcc: 
/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
gcc: 
/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c
In file included from 
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
 ???????????????? from 
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
 ???????????????? from 
/Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
 ???????????????? from 
/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61: 
error: no include path in which to search for limits.h
 ? 195 | #include_next <limits.h>? /* recurse down to the real one */
|???????????????????????????????????????????????????????????? ^
In file included from 
/Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
 ???????????????? from 
/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10: 
fatal error: _stdio.h: No such file or directory
 ?? 78 | #include <_stdio.h>
 ????? |????????? ^~~~~~~~~~
compilation terminated.

Any suggestions?

Sam Dupree.


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(base) user at Mac-Pro ~ % cd SOFA_Issue_2022_07_21_f2py/f77/src                                                                   
(base) user at Mac-Pro src % f2py3 -c sofapy.f --f77flags="-c -O -Wall"  -m sofapy 
running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands --compiler options
running config_fc
unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options
running build_src
build_src
building extension "sofapy" sources
f2py options: []
f2py:> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
Reading fortran codes...
	Reading file 'sofapy.f' (format:fix,strict)
{'before': '', 'this': 'intent', 'after': '(in) sp, theta, elong, phi, hm, xp, yp,'}
Line #3958 in sofapy.f:"        intent(in) SP, THETA, ELONG, PHI, HM, XP, YP,"
	analyzeline: no name pattern found in intent statement for ''. Skipping.
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
rmbadname1: Replacing "type" with "type_bn".
Line #12790 in sofapy.f:"      DATA ((IDAT(M,N),M=1,2),DATS(N),(DRIFT(M,N),M=1,2),N=1,14)  / 1960,  1,  1.4178180D0, 37300D0, 0.001296D0,    1961,  1,  1.4228180D0, 37300D0, 0.001296D0,    1961,  8,  1.3728180D0, 37300D0, 0.001296D0,    1962,  1,  1.8458580D0, 37665D0, 0.0011232D0,    1963, 11,  1.9458580D0, 37665D0, 0.0011232D0,    1964,  1,  3.2401300D0, 38761D0, 0.001296D0,    1964,  4,  3.3401300D0, 38761D0, 0.001296D0,    1964,  9,  3.4401300D0, 38761D0, 0.001296D0,    1965,  1,  3.5401300D0, 38761D0, 0.001296D0,    1965,  3,  3.6401300D0, 38761D0, 0.001296D0,    1965,  7,  3.7401300D0, 38761D0, 0.001296D0,    1965,  9,  3.8401300D0, 38761D0, 0.001296D0,    1966,  1,  4.3131700D0, 39126D0, 0.002592D0,    1968,  2,  4.2131700D0, 39126D0, 0.002592D0 /"
	analyzeline: implied-DO list "((idat(m,n),m=1,2),dats(n),(drift(m,n),m=1,2),n=1,14)" is not supported. Skipping.
Line #12808 in sofapy.f:"      DATA ((IDAT(M,N),M=1,2),DATS(N),N=15,30)  / 1972,  1, 10D0,    1972,  7, 11D0,    1973,  1, 12D0,    1974,  1, 13D0,    1975,  1, 14D0,    1976,  1, 15D0,    1977,  1, 16D0,    1978,  1, 17D0,    1979,  1, 18D0,    1980,  1, 19D0,    1981,  7, 20D0,    1982,  7, 21D0,    1983,  7, 22D0,    1985,  7, 23D0,    1988,  1, 24D0,    1990,  1, 25D0 /"
	analyzeline: implied-DO list "((idat(m,n),m=1,2),dats(n),n=15,30)" is not supported. Skipping.
Line #12823 in sofapy.f:"      DATA ((IDAT(M,N),M=1,2),DATS(N),N=31,NDAT)  / 1991,  1, 26D0,    1992,  7, 27D0,    1993,  7, 28D0,    1994,  7, 29D0,    1996,  1, 30D0,    1997,  7, 31D0,    1999,  1, 32D0,    2006,  1, 33D0,    2009,  1, 34D0,    2012,  7, 35D0,    2015,  7, 36D0,    2017,  1, 37D0 /"
	analyzeline: implied-DO list "((idat(m,n),m=1,2),dats(n),n=31,ndat)" is not supported. Skipping.
Line #13218 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=  1, 10) / 1656.674564D-6,    6283.075849991D0, 6.240054195D0,   22.417471D-6,    5753.384884897D0, 4.296977442D0,   13.839792D-6,   12566.151699983D0, 6.196904410D0,    4.770086D-6,     529.690965095D0, 0.444401603D0,    4.676740D-6,    6069.776754553D0, 4.021195093D0,    2.256707D-6,     213.299095438D0, 5.543113262D0,    1.694205D-6,      -3.523118349D0, 5.025132748D0,    1.554905D-6,   77713.771467920D0, 5.198467090D0,    1.276839D-6,    7860.419392439D0, 5.988822341D0,    1.193379D-6,    5223.693919802D0, 3.649823730D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #13229 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 11, 20) /    1.115322D-6,    3930.209696220D0, 1.422745069D0,    0.794185D-6,   11506.769769794D0, 2.322313077D0,    0.447061D-6,      26.298319800D0, 3.615796498D0,    0.435206D-6,    -398.149003408D0, 4.349338347D0,    0.600309D-6,    1577.343542448D0, 2.678271909D0,    0.496817D-6,    6208.294251424D0, 5.696701824D0,    0.486306D-6,    5884.926846583D0, 0.520007179D0,    0.432392D-6,      74.781598567D0, 2.435898309D0,    0.468597D-6,    6244.942814354D0, 5.866398759D0,    0.375510D-6,    5507.553238667D0, 4.103476804D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #13240 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 21, 30) /    0.243085D-6,    -775.522611324D0, 3.651837925D0,    0.173435D-6,   18849.227549974D0, 6.153743485D0,    0.230685D-6,    5856.477659115D0, 4.773852582D0,    0.203747D-6,   12036.460734888D0, 4.333987818D0,    0.143935D-6,    -796.298006816D0, 5.957517795D0,    0.159080D-6,   10977.078804699D0, 1.890075226D0,    0.119979D-6,      38.133035638D0, 4.551585768D0,    0.118971D-6,    5486.777843175D0, 1.914547226D0,    0.116120D-6,    1059.381930189D0, 0.873504123D0,    0.137927D-6,   11790.629088659D0, 1.135934669D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #13251 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 31, 40) /    0.098358D-6,    2544.314419883D0, 0.092793886D0,    0.101868D-6,   -5573.142801634D0, 5.984503847D0,    0.080164D-6,     206.185548437D0, 2.095377709D0,    0.079645D-6,    4694.002954708D0, 2.949233637D0,    0.062617D-6,      20.775395492D0, 2.654394814D0,    0.075019D-6,    2942.463423292D0, 4.980931759D0,    0.064397D-6,    5746.271337896D0, 1.280308748D0,    0.063814D-6,    5760.498431898D0, 4.167901731D0,    0.048042D-6,    2146.165416475D0, 1.495846011D0,    0.048373D-6,     155.420399434D0, 2.251573730D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #13262 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 41, 50) /    0.058844D-6,     426.598190876D0, 4.839650148D0,    0.046551D-6,      -0.980321068D0, 0.921573539D0,    0.054139D-6,   17260.154654690D0, 3.411091093D0,    0.042411D-6,    6275.962302991D0, 2.869567043D0,    0.040184D-6,      -7.113547001D0, 3.565975565D0,    0.036564D-6,    5088.628839767D0, 3.324679049D0,    0.040759D-6,   12352.852604545D0, 3.981496998D0,    0.036507D-6,     801.820931124D0, 6.248866009D0,    0.036955D-6,    3154.687084896D0, 5.071801441D0,    0.042732D-6,     632.783739313D0, 5.720622217D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #13273 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 51, 60) /    0.042560D-6,  161000.685737473D0, 1.270837679D0,    0.040480D-6,   15720.838784878D0, 2.546610123D0,    0.028244D-6,   -6286.598968340D0, 5.069663519D0,    0.033477D-6,    6062.663207553D0, 4.144987272D0,    0.034867D-6,     522.577418094D0, 5.210064075D0,    0.032438D-6,    6076.890301554D0, 0.749317412D0,    0.030215D-6,    7084.896781115D0, 3.389610345D0,    0.029247D-6,  -71430.695617928D0, 4.183178762D0,    0.033529D-6,    9437.762934887D0, 2.404714239D0,    0.032423D-6,    8827.390269875D0, 5.541473556D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #13284 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 61, 70) /    0.027567D-6,    6279.552731642D0, 5.040846034D0,    0.029862D-6,   12139.553509107D0, 1.770181024D0,    0.022509D-6,   10447.387839604D0, 1.460726241D0,    0.020937D-6,    8429.241266467D0, 0.652303414D0,    0.020322D-6,     419.484643875D0, 3.735430632D0,    0.024816D-6,   -1194.447010225D0, 1.087136918D0,    0.025196D-6,    1748.016413067D0, 2.901883301D0,    0.021691D-6,   14143.495242431D0, 5.952658009D0,    0.017673D-6,    6812.766815086D0, 3.186129845D0,    0.022567D-6,    6133.512652857D0, 3.307984806D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #13295 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 71, 80) /    0.016155D-6,   10213.285546211D0, 1.331103168D0,    0.014751D-6,    1349.867409659D0, 4.308933301D0,    0.015949D-6,    -220.412642439D0, 4.005298270D0,    0.015974D-6,   -2352.866153772D0, 6.145309371D0,    0.014223D-6,   17789.845619785D0, 2.104551349D0,    0.017806D-6,      73.297125859D0, 3.475975097D0,    0.013671D-6,    -536.804512095D0, 5.971672571D0,    0.011942D-6,    8031.092263058D0, 2.053414715D0,    0.014318D-6,   16730.463689596D0, 3.016058075D0,    0.012462D-6,     103.092774219D0, 1.737438797D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #13306 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 81, 90) /    0.010962D-6,       3.590428652D0, 2.196567739D0,    0.015078D-6,   19651.048481098D0, 3.969480770D0,    0.010396D-6,     951.718406251D0, 5.717799605D0,    0.011707D-6,   -4705.732307544D0, 2.654125618D0,    0.010453D-6,    5863.591206116D0, 1.913704550D0,    0.012420D-6,    4690.479836359D0, 4.734090399D0,    0.011847D-6,    5643.178563677D0, 5.489005403D0,    0.008610D-6,    3340.612426700D0, 3.661698944D0,    0.011622D-6,    5120.601145584D0, 4.863931876D0,    0.010825D-6,     553.569402842D0, 0.842715011D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #13317 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J= 91,100) /    0.008666D-6,    -135.065080035D0, 3.293406547D0,    0.009963D-6,     149.563197135D0, 4.870690598D0,    0.009858D-6,    6309.374169791D0, 1.061816410D0,    0.007959D-6,     316.391869657D0, 2.465042647D0,    0.010099D-6,     283.859318865D0, 1.942176992D0,    0.007147D-6,    -242.728603974D0, 3.661486981D0,    0.007505D-6,    5230.807466803D0, 4.920937029D0,    0.008323D-6,   11769.853693166D0, 1.229392026D0,    0.007490D-6,   -6256.777530192D0, 3.658444681D0,    0.009370D-6,  149854.400134205D0, 0.673880395D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j= 91,100)" is not supported. Skipping.
Line #13328 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=101,110) /    0.007117D-6,      38.027672636D0, 5.294249518D0,    0.007857D-6,   12168.002696575D0, 0.525733528D0,    0.007019D-6,    6206.809778716D0, 0.837688810D0,    0.006056D-6,     955.599741609D0, 4.194535082D0,    0.008107D-6,   13367.972631107D0, 3.793235253D0,    0.006731D-6,    5650.292110678D0, 5.639906583D0,    0.007332D-6,      36.648562930D0, 0.114858677D0,    0.006366D-6,    4164.311989613D0, 2.262081818D0,    0.006858D-6,    5216.580372801D0, 0.642063318D0,    0.006919D-6,    6681.224853400D0, 6.018501522D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=101,110)" is not supported. Skipping.
Line #13339 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=111,120) /    0.006826D-6,    7632.943259650D0, 3.458654112D0,    0.005308D-6,   -1592.596013633D0, 2.500382359D0,    0.005096D-6,   11371.704689758D0, 2.547107806D0,    0.004841D-6,    5333.900241022D0, 0.437078094D0,    0.005582D-6,    5966.683980335D0, 2.246174308D0,    0.006304D-6,   11926.254413669D0, 2.512929171D0,    0.006603D-6,   23581.258177318D0, 5.393136889D0,    0.005123D-6,      -1.484472708D0, 2.999641028D0,    0.004648D-6,    1589.072895284D0, 1.275847090D0,    0.005119D-6,    6438.496249426D0, 1.486539246D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=111,120)" is not supported. Skipping.
Line #13350 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=121,130) /    0.004521D-6,    4292.330832950D0, 6.140635794D0,    0.005680D-6,   23013.539539587D0, 4.557814849D0,    0.005488D-6,      -3.455808046D0, 0.090675389D0,    0.004193D-6,    7234.794256242D0, 4.869091389D0,    0.003742D-6,    7238.675591600D0, 4.691976180D0,    0.004148D-6,    -110.206321219D0, 3.016173439D0,    0.004553D-6,   11499.656222793D0, 5.554998314D0,    0.004892D-6,    5436.993015240D0, 1.475415597D0,    0.004044D-6,    4732.030627343D0, 1.398784824D0,    0.004164D-6,   12491.370101415D0, 5.650931916D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=121,130)" is not supported. Skipping.
Line #13361 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=131,140) /    0.004349D-6,   11513.883316794D0, 2.181745369D0,    0.003919D-6,   12528.018664345D0, 5.823319737D0,    0.003129D-6,    6836.645252834D0, 0.003844094D0,    0.004080D-6,   -7058.598461315D0, 3.690360123D0,    0.003270D-6,      76.266071276D0, 1.517189902D0,    0.002954D-6,    6283.143160294D0, 4.447203799D0,    0.002872D-6,      28.449187468D0, 1.158692983D0,    0.002881D-6,     735.876513532D0, 0.349250250D0,    0.003279D-6,    5849.364112115D0, 4.893384368D0,    0.003625D-6,    6209.778724132D0, 1.473760578D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=131,140)" is not supported. Skipping.
Line #13372 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=141,150) /    0.003074D-6,     949.175608970D0, 5.185878737D0,    0.002775D-6,    9917.696874510D0, 1.030026325D0,    0.002646D-6,   10973.555686350D0, 3.918259169D0,    0.002575D-6,   25132.303399966D0, 6.109659023D0,    0.003500D-6,     263.083923373D0, 1.892100742D0,    0.002740D-6,   18319.536584880D0, 4.320519510D0,    0.002464D-6,     202.253395174D0, 4.698203059D0,    0.002409D-6,       2.542797281D0, 5.325009315D0,    0.003354D-6,  -90955.551694697D0, 1.942656623D0,    0.002296D-6,    6496.374945429D0, 5.061810696D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=141,150)" is not supported. Skipping.
Line #13383 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=151,160) /    0.003002D-6,    6172.869528772D0, 2.797822767D0,    0.003202D-6,   27511.467873537D0, 0.531673101D0,    0.002954D-6,   -6283.008539689D0, 4.533471191D0,    0.002353D-6,     639.897286314D0, 3.734548088D0,    0.002401D-6,   16200.772724501D0, 2.605547070D0,    0.003053D-6,  233141.314403759D0, 3.029030662D0,    0.003024D-6,   83286.914269554D0, 2.355556099D0,    0.002863D-6,   17298.182327326D0, 5.240963796D0,    0.002103D-6,   -7079.373856808D0, 5.756641637D0,    0.002303D-6,   83996.847317911D0, 2.013686814D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=151,160)" is not supported. Skipping.
Line #13394 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=161,170) /    0.002303D-6,   18073.704938650D0, 1.089100410D0,    0.002381D-6,      63.735898303D0, 0.759188178D0,    0.002493D-6,    6386.168624210D0, 0.645026535D0,    0.002366D-6,       3.932153263D0, 6.215885448D0,    0.002169D-6,   11015.106477335D0, 4.845297676D0,    0.002397D-6,    6243.458341645D0, 3.809290043D0,    0.002183D-6,    1162.474704408D0, 6.179611691D0,    0.002353D-6,    6246.427287062D0, 4.781719760D0,    0.002199D-6,    -245.831646229D0, 5.956152284D0,    0.001729D-6,    3894.181829542D0, 1.264976635D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=161,170)" is not supported. Skipping.
Line #13405 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=171,180) /    0.001896D-6,   -3128.388765096D0, 4.914231596D0,    0.002085D-6,      35.164090221D0, 1.405158503D0,    0.002024D-6,   14712.317116458D0, 2.752035928D0,    0.001737D-6,    6290.189396992D0, 5.280820144D0,    0.002229D-6,     491.557929457D0, 1.571007057D0,    0.001602D-6,   14314.168113050D0, 4.203664806D0,    0.002186D-6,     454.909366527D0, 1.402101526D0,    0.001897D-6,   22483.848574493D0, 4.167932508D0,    0.001825D-6,   -3738.761430108D0, 0.545828785D0,    0.001894D-6,    1052.268383188D0, 5.817167450D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=171,180)" is not supported. Skipping.
Line #13416 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=181,190) /    0.001421D-6,      20.355319399D0, 2.419886601D0,    0.001408D-6,   10984.192351700D0, 2.732084787D0,    0.001847D-6,   10873.986030480D0, 2.903477885D0,    0.001391D-6,   -8635.942003763D0, 0.593891500D0,    0.001388D-6,      -7.046236698D0, 1.166145902D0,    0.001810D-6,  -88860.057071188D0, 0.487355242D0,    0.001288D-6,   -1990.745017041D0, 3.913022880D0,    0.001297D-6,   23543.230504682D0, 3.063805171D0,    0.001335D-6,    -266.607041722D0, 3.995764039D0,    0.001376D-6,   10969.965257698D0, 5.152914309D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=181,190)" is not supported. Skipping.
Line #13427 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=191,200) /    0.001745D-6,  244287.600007027D0, 3.626395673D0,    0.001649D-6,   31441.677569757D0, 1.952049260D0,    0.001416D-6,    9225.539273283D0, 4.996408389D0,    0.001238D-6,    4804.209275927D0, 5.503379738D0,    0.001472D-6,    4590.910180489D0, 4.164913291D0,    0.001169D-6,    6040.347246017D0, 5.841719038D0,    0.001039D-6,    5540.085789459D0, 2.769753519D0,    0.001004D-6,    -170.672870619D0, 0.755008103D0,    0.001284D-6,   10575.406682942D0, 5.306538209D0,    0.001278D-6,      71.812653151D0, 4.713486491D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=191,200)" is not supported. Skipping.
Line #13438 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=201,210) /    0.001321D-6,   18209.330263660D0, 2.624866359D0,    0.001297D-6,   21228.392023546D0, 0.382603541D0,    0.000954D-6,    6282.095528923D0, 0.882213514D0,    0.001145D-6,    6058.731054289D0, 1.169483931D0,    0.000979D-6,    5547.199336460D0, 5.448375984D0,    0.000987D-6,   -6262.300454499D0, 2.656486959D0,    0.001070D-6, -154717.609887482D0, 1.827624012D0,    0.000991D-6,    4701.116501708D0, 4.387001801D0,    0.001155D-6,     -14.227094002D0, 3.042700750D0,    0.001176D-6,     277.034993741D0, 3.335519004D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=201,210)" is not supported. Skipping.
Line #13449 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=211,220) /    0.000890D-6,   13916.019109642D0, 5.601498297D0,    0.000884D-6,   -1551.045222648D0, 1.088831705D0,    0.000876D-6,    5017.508371365D0, 3.969902609D0,    0.000806D-6,   15110.466119866D0, 5.142876744D0,    0.000773D-6,   -4136.910433516D0, 0.022067765D0,    0.001077D-6,     175.166059800D0, 1.844913056D0,    0.000954D-6,   -6284.056171060D0, 0.968480906D0,    0.000737D-6,    5326.786694021D0, 4.923831588D0,    0.000845D-6,    -433.711737877D0, 4.749245231D0,    0.000819D-6,    8662.240323563D0, 5.991247817D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=211,220)" is not supported. Skipping.
Line #13460 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=221,230) /    0.000852D-6,     199.072001436D0, 2.189604979D0,    0.000723D-6,   17256.631536341D0, 6.068719637D0,    0.000940D-6,    6037.244203762D0, 6.197428148D0,    0.000885D-6,   11712.955318231D0, 3.280414875D0,    0.000706D-6,   12559.038152982D0, 2.824848947D0,    0.000732D-6,    2379.164473572D0, 2.501813417D0,    0.000764D-6,   -6127.655450557D0, 2.236346329D0,    0.000908D-6,     131.541961686D0, 2.521257490D0,    0.000907D-6,   35371.887265976D0, 3.370195967D0,    0.000673D-6,    1066.495477190D0, 3.876512374D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=221,230)" is not supported. Skipping.
Line #13471 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=231,240) /    0.000814D-6,   17654.780539750D0, 4.627122566D0,    0.000630D-6,      36.027866677D0, 0.156368499D0,    0.000798D-6,     515.463871093D0, 5.151962502D0,    0.000798D-6,     148.078724426D0, 5.909225055D0,    0.000806D-6,     309.278322656D0, 6.054064447D0,    0.000607D-6,     -39.617508346D0, 2.839021623D0,    0.000601D-6,     412.371096874D0, 3.984225404D0,    0.000646D-6,   11403.676995575D0, 3.852959484D0,    0.000704D-6,   13521.751441591D0, 2.300991267D0,    0.000603D-6,  -65147.619767937D0, 4.140083146D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=231,240)" is not supported. Skipping.
Line #13482 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=241,250) /    0.000609D-6,   10177.257679534D0, 0.437122327D0,    0.000631D-6,    5767.611978898D0, 4.026532329D0,    0.000576D-6,   11087.285125918D0, 4.760293101D0,    0.000674D-6,   14945.316173554D0, 6.270510511D0,    0.000726D-6,    5429.879468239D0, 6.039606892D0,    0.000710D-6,   28766.924424484D0, 5.672617711D0,    0.000647D-6,   11856.218651625D0, 3.397132627D0,    0.000678D-6,   -5481.254918868D0, 6.249666675D0,    0.000618D-6,   22003.914634870D0, 2.466427018D0,    0.000738D-6,    6134.997125565D0, 2.242668890D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=241,250)" is not supported. Skipping.
Line #13493 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=251,260) /    0.000660D-6,     625.670192312D0, 5.864091907D0,    0.000694D-6,    3496.032826134D0, 2.668309141D0,    0.000531D-6,    6489.261398429D0, 1.681888780D0,    0.000611D-6, -143571.324284214D0, 2.424978312D0,    0.000575D-6,   12043.574281889D0, 4.216492400D0,    0.000553D-6,   12416.588502848D0, 4.772158039D0,    0.000689D-6,    4686.889407707D0, 6.224271088D0,    0.000495D-6,    7342.457780181D0, 3.817285811D0,    0.000567D-6,    3634.621024518D0, 1.649264690D0,    0.000515D-6,   18635.928454536D0, 3.945345892D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=251,260)" is not supported. Skipping.
Line #13504 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=261,270) /    0.000486D-6,    -323.505416657D0, 4.061673868D0,    0.000662D-6,   25158.601719765D0, 1.794058369D0,    0.000509D-6,     846.082834751D0, 3.053874588D0,    0.000472D-6,  -12569.674818332D0, 5.112133338D0,    0.000461D-6,    6179.983075773D0, 0.513669325D0,    0.000641D-6,   83467.156352816D0, 3.210727723D0,    0.000520D-6,   10344.295065386D0, 2.445597761D0,    0.000493D-6,   18422.629359098D0, 1.676939306D0,    0.000478D-6,    1265.567478626D0, 5.487314569D0,    0.000472D-6,     -18.159247265D0, 1.999707589D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=261,270)" is not supported. Skipping.
Line #13515 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=271,280) /    0.000559D-6,   11190.377900137D0, 5.783236356D0,    0.000494D-6,    9623.688276691D0, 3.022645053D0,    0.000463D-6,    5739.157790895D0, 1.411223013D0,    0.000432D-6,   16858.482532933D0, 1.179256434D0,    0.000574D-6,   72140.628666286D0, 1.758191830D0,    0.000484D-6,   17267.268201691D0, 3.290589143D0,    0.000550D-6,    4907.302050146D0, 0.864024298D0,    0.000399D-6,      14.977853527D0, 2.094441910D0,    0.000491D-6,     224.344795702D0, 0.878372791D0,    0.000432D-6,   20426.571092422D0, 6.003829241D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=271,280)" is not supported. Skipping.
Line #13526 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=281,290) /    0.000481D-6,    5749.452731634D0, 4.309591964D0,    0.000480D-6,    5757.317038160D0, 1.142348571D0,    0.000485D-6,    6702.560493867D0, 0.210580917D0,    0.000426D-6,    6055.549660552D0, 4.274476529D0,    0.000480D-6,    5959.570433334D0, 5.031351030D0,    0.000466D-6,   12562.628581634D0, 4.959581597D0,    0.000520D-6,   39302.096962196D0, 4.788002889D0,    0.000458D-6,   12132.439962106D0, 1.880103788D0,    0.000470D-6,   12029.347187887D0, 1.405611197D0,    0.000416D-6,   -7477.522860216D0, 1.082356330D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=281,290)" is not supported. Skipping.
Line #13537 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=291,300) /    0.000449D-6,   11609.862544012D0, 4.179989585D0,    0.000465D-6,   17253.041107690D0, 0.353496295D0,    0.000362D-6,   -4535.059436924D0, 1.583849576D0,    0.000383D-6,   21954.157609398D0, 3.747376371D0,    0.000389D-6,      17.252277143D0, 1.395753179D0,    0.000331D-6,   18052.929543158D0, 0.566790582D0,    0.000430D-6,   13517.870106233D0, 0.685827538D0,    0.000368D-6,   -5756.908003246D0, 0.731374317D0,    0.000330D-6,   10557.594160824D0, 3.710043680D0,    0.000332D-6,   20199.094959633D0, 1.652901407D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=291,300)" is not supported. Skipping.
Line #13548 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=301,310) /    0.000384D-6,   11933.367960670D0, 5.827781531D0,    0.000387D-6,   10454.501386605D0, 2.541182564D0,    0.000325D-6,   15671.081759407D0, 2.178850542D0,    0.000318D-6,     138.517496871D0, 2.253253037D0,    0.000305D-6,    9388.005909415D0, 0.578340206D0,    0.000352D-6,    5749.861766548D0, 3.000297967D0,    0.000311D-6,    6915.859589305D0, 1.693574249D0,    0.000297D-6,   24072.921469776D0, 1.997249392D0,    0.000363D-6,    -640.877607382D0, 5.071820966D0,    0.000323D-6,   12592.450019783D0, 1.072262823D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=301,310)" is not supported. Skipping.
Line #13559 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=311,320) /    0.000341D-6,   12146.667056108D0, 4.700657997D0,    0.000290D-6,    9779.108676125D0, 1.812320441D0,    0.000342D-6,    6132.028180148D0, 4.322238614D0,    0.000329D-6,    6268.848755990D0, 3.033827743D0,    0.000374D-6,   17996.031168222D0, 3.388716544D0,    0.000285D-6,    -533.214083444D0, 4.687313233D0,    0.000338D-6,    6065.844601290D0, 0.877776108D0,    0.000276D-6,      24.298513841D0, 0.770299429D0,    0.000336D-6,   -2388.894020449D0, 5.353796034D0,    0.000290D-6,    3097.883822726D0, 4.075291557D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=311,320)" is not supported. Skipping.
Line #13570 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=321,330) /    0.000318D-6,     709.933048357D0, 5.941207518D0,    0.000271D-6,   13095.842665077D0, 3.208912203D0,    0.000331D-6,    6073.708907816D0, 4.007881169D0,    0.000292D-6,     742.990060533D0, 2.714333592D0,    0.000362D-6,   29088.811415985D0, 3.215977013D0,    0.000280D-6,   12359.966151546D0, 0.710872502D0,    0.000267D-6,   10440.274292604D0, 4.730108488D0,    0.000262D-6,     838.969287750D0, 1.327720272D0,    0.000250D-6,   16496.361396202D0, 0.898769761D0,    0.000325D-6,   20597.243963041D0, 0.180044365D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=321,330)" is not supported. Skipping.
Line #13581 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=331,340) /    0.000268D-6,    6148.010769956D0, 5.152666276D0,    0.000284D-6,    5636.065016677D0, 5.655385808D0,    0.000301D-6,    6080.822454817D0, 2.135396205D0,    0.000294D-6,    -377.373607916D0, 3.708784168D0,    0.000236D-6,    2118.763860378D0, 1.733578756D0,    0.000234D-6,    5867.523359379D0, 5.575209112D0,    0.000268D-6, -226858.238553767D0, 0.069432392D0,    0.000265D-6,  167283.761587465D0, 4.369302826D0,    0.000280D-6,   28237.233459389D0, 5.304829118D0,    0.000292D-6,   12345.739057544D0, 4.096094132D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=331,340)" is not supported. Skipping.
Line #13592 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=341,350) /    0.000223D-6,   19800.945956225D0, 3.069327406D0,    0.000301D-6,   43232.306658416D0, 6.205311188D0,    0.000264D-6,   18875.525869774D0, 1.417263408D0,    0.000304D-6,   -1823.175188677D0, 3.409035232D0,    0.000301D-6,     109.945688789D0, 0.510922054D0,    0.000260D-6,     813.550283960D0, 2.389438934D0,    0.000299D-6,  316428.228673312D0, 5.384595078D0,    0.000211D-6,    5756.566278634D0, 3.789392838D0,    0.000209D-6,    5750.203491159D0, 1.661943545D0,    0.000240D-6,   12489.885628707D0, 5.684549045D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=341,350)" is not supported. Skipping.
Line #13603 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=351,360) /    0.000216D-6,    6303.851245484D0, 3.862942261D0,    0.000203D-6,    1581.959348283D0, 5.549853589D0,    0.000200D-6,    5642.198242609D0, 1.016115785D0,    0.000197D-6,     -70.849445304D0, 4.690702525D0,    0.000227D-6,    6287.008003254D0, 2.911891613D0,    0.000197D-6,     533.623118358D0, 1.048982898D0,    0.000205D-6,   -6279.485421340D0, 1.829362730D0,    0.000209D-6,  -10988.808157535D0, 2.636140084D0,    0.000208D-6,    -227.526189440D0, 4.127883842D0,    0.000191D-6,     415.552490612D0, 4.401165650D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=351,360)" is not supported. Skipping.
Line #13614 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=361,370) /    0.000190D-6,   29296.615389579D0, 4.175658539D0,    0.000264D-6,   66567.485864652D0, 4.601102551D0,    0.000256D-6,   -3646.350377354D0, 0.506364778D0,    0.000188D-6,   13119.721102825D0, 2.032195842D0,    0.000185D-6,    -209.366942175D0, 4.694756586D0,    0.000198D-6,   25934.124331089D0, 3.832703118D0,    0.000195D-6,    4061.219215394D0, 3.308463427D0,    0.000234D-6,    5113.487598583D0, 1.716090661D0,    0.000188D-6,    1478.866574064D0, 5.686865780D0,    0.000222D-6,   11823.161639450D0, 1.942386641D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=361,370)" is not supported. Skipping.
Line #13625 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=371,380) /    0.000181D-6,   10770.893256262D0, 1.999482059D0,    0.000171D-6,    6546.159773364D0, 1.182807992D0,    0.000206D-6,      70.328180442D0, 5.934076062D0,    0.000169D-6,   20995.392966449D0, 2.169080622D0,    0.000191D-6,   10660.686935042D0, 5.405515999D0,    0.000228D-6,   33019.021112205D0, 4.656985514D0,    0.000184D-6,   -4933.208440333D0, 3.327476868D0,    0.000220D-6,    -135.625325010D0, 1.765430262D0,    0.000166D-6,   23141.558382925D0, 3.454132746D0,    0.000191D-6,    6144.558353121D0, 5.020393445D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=371,380)" is not supported. Skipping.
Line #13636 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=381,390) /    0.000180D-6,    6084.003848555D0, 0.602182191D0,    0.000163D-6,   17782.732072784D0, 4.960593133D0,    0.000225D-6,   16460.333529525D0, 2.596451817D0,    0.000222D-6,    5905.702242076D0, 3.731990323D0,    0.000204D-6,     227.476132789D0, 5.636192701D0,    0.000159D-6,   16737.577236597D0, 3.600691544D0,    0.000200D-6,    6805.653268085D0, 0.868220961D0,    0.000187D-6,   11919.140866668D0, 2.629456641D0,    0.000161D-6,     127.471796607D0, 2.862574720D0,    0.000205D-6,    6286.666278643D0, 1.742882331D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=381,390)" is not supported. Skipping.
Line #13647 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=391,400) /    0.000189D-6,     153.778810485D0, 4.812372643D0,    0.000168D-6,   16723.350142595D0, 0.027860588D0,    0.000149D-6,   11720.068865232D0, 0.659721876D0,    0.000189D-6,    5237.921013804D0, 5.245313000D0,    0.000143D-6,    6709.674040867D0, 4.317625647D0,    0.000146D-6,    4487.817406270D0, 4.815297007D0,    0.000144D-6,    -664.756045130D0, 5.381366880D0,    0.000175D-6,    5127.714692584D0, 4.728443327D0,    0.000162D-6,    6254.626662524D0, 1.435132069D0,    0.000187D-6,   47162.516354635D0, 1.354371923D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=391,400)" is not supported. Skipping.
Line #13658 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=401,410) /    0.000146D-6,   11080.171578918D0, 3.369695406D0,    0.000180D-6,    -348.924420448D0, 2.490902145D0,    0.000148D-6,     151.047669843D0, 3.799109588D0,    0.000157D-6,    6197.248551160D0, 1.284375887D0,    0.000167D-6,     146.594251718D0, 0.759969109D0,    0.000133D-6,   -5331.357443741D0, 5.409701889D0,    0.000154D-6,      95.979227218D0, 3.366890614D0,    0.000148D-6,   -6418.140930027D0, 3.384104996D0,    0.000128D-6,   -6525.804453965D0, 3.803419985D0,    0.000130D-6,   11293.470674356D0, 0.939039445D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=401,410)" is not supported. Skipping.
Line #13669 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=411,420) /    0.000152D-6,   -5729.506447149D0, 0.734117523D0,    0.000138D-6,     210.117701700D0, 2.564216078D0,    0.000123D-6,    6066.595360816D0, 4.517099537D0,    0.000140D-6,   18451.078546566D0, 0.642049130D0,    0.000126D-6,   11300.584221356D0, 3.485280663D0,    0.000119D-6,   10027.903195729D0, 3.217431161D0,    0.000151D-6,    4274.518310832D0, 4.404359108D0,    0.000117D-6,    6072.958148291D0, 0.366324650D0,    0.000165D-6,   -7668.637425143D0, 4.298212528D0,    0.000117D-6,   -6245.048177356D0, 5.379518958D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=411,420)" is not supported. Skipping.
Line #13680 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=421,430) /    0.000130D-6,   -5888.449964932D0, 4.527681115D0,    0.000121D-6,    -543.918059096D0, 6.109429504D0,    0.000162D-6,    9683.594581116D0, 5.720092446D0,    0.000141D-6,    6219.339951688D0, 0.679068671D0,    0.000118D-6,   22743.409379516D0, 4.881123092D0,    0.000129D-6,    1692.165669502D0, 0.351407289D0,    0.000126D-6,    5657.405657679D0, 5.146592349D0,    0.000114D-6,     728.762966531D0, 0.520791814D0,    0.000120D-6,      52.596639600D0, 0.948516300D0,    0.000115D-6,      65.220371012D0, 3.504914846D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=421,430)" is not supported. Skipping.
Line #13691 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=431,440) /    0.000126D-6,    5881.403728234D0, 5.577502482D0,    0.000158D-6,  163096.180360983D0, 2.957128968D0,    0.000134D-6,   12341.806904281D0, 2.598576764D0,    0.000151D-6,   16627.370915377D0, 3.985702050D0,    0.000109D-6,    1368.660252845D0, 0.014730471D0,    0.000131D-6,    6211.263196841D0, 0.085077024D0,    0.000146D-6,    5792.741760812D0, 0.708426604D0,    0.000146D-6,     -77.750543984D0, 3.121576600D0,    0.000107D-6,    5341.013788022D0, 0.288231904D0,    0.000138D-6,    6281.591377283D0, 2.797450317D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=431,440)" is not supported. Skipping.
Line #13702 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=441,450) /    0.000113D-6,   -6277.552925684D0, 2.788904128D0,    0.000115D-6,    -525.758811831D0, 5.895222200D0,    0.000138D-6,    6016.468808270D0, 6.096188999D0,    0.000139D-6,   23539.707386333D0, 2.028195445D0,    0.000146D-6,   -4176.041342449D0, 4.660008502D0,    0.000107D-6,   16062.184526117D0, 4.066520001D0,    0.000142D-6,   83783.548222473D0, 2.936315115D0,    0.000128D-6,    9380.959672717D0, 3.223844306D0,    0.000135D-6,    6205.325306007D0, 1.638054048D0,    0.000101D-6,    2699.734819318D0, 5.481603249D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=441,450)" is not supported. Skipping.
Line #13713 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=451,460) /    0.000104D-6,    -568.821874027D0, 2.205734493D0,    0.000103D-6,    6321.103522627D0, 2.440421099D0,    0.000119D-6,    6321.208885629D0, 2.547496264D0,    0.000138D-6,    1975.492545856D0, 2.314608466D0,    0.000121D-6,     137.033024162D0, 4.539108237D0,    0.000123D-6,   19402.796952817D0, 4.538074405D0,    0.000119D-6,   22805.735565994D0, 2.869040566D0,    0.000133D-6,   64471.991241142D0, 6.056405489D0,    0.000129D-6,     -85.827298831D0, 2.540635083D0,    0.000131D-6,   13613.804277336D0, 4.005732868D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=451,460)" is not supported. Skipping.
Line #13724 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=461,470) /    0.000104D-6,    9814.604100291D0, 1.959967212D0,    0.000112D-6,   16097.679950283D0, 3.589026260D0,    0.000123D-6,    2107.034507542D0, 1.728627253D0,    0.000121D-6,   36949.230808424D0, 6.072332087D0,    0.000108D-6,  -12539.853380183D0, 3.716133846D0,    0.000113D-6,   -7875.671863624D0, 2.725771122D0,    0.000109D-6,    4171.425536614D0, 4.033338079D0,    0.000101D-6,    6247.911759770D0, 3.441347021D0,    0.000113D-6,    7330.728427345D0, 0.656372122D0,    0.000113D-6,   51092.726050855D0, 2.791483066D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=461,470)" is not supported. Skipping.
Line #13737 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=471,480) /    0.000106D-6,    5621.842923210D0, 1.815323326D0,    0.000101D-6,     111.430161497D0, 5.711033677D0,    0.000103D-6,     909.818733055D0, 2.812745443D0,    0.000101D-6,    1790.642637886D0, 1.965746028D0,  102.156724D-6,    6283.075849991D0, 4.249032005D0,    1.706807D-6,   12566.151699983D0, 4.205904248D0,    0.269668D-6,     213.299095438D0, 3.400290479D0,    0.265919D-6,     529.690965095D0, 5.836047367D0,    0.210568D-6,      -3.523118349D0, 6.262738348D0,    0.077996D-6,    5223.693919802D0, 4.670344204D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=471,480)" is not supported. Skipping.
Line #13748 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=481,490) /    0.054764D-6,    1577.343542448D0, 4.534800170D0,    0.059146D-6,      26.298319800D0, 1.083044735D0,    0.034420D-6,    -398.149003408D0, 5.980077351D0,    0.032088D-6,   18849.227549974D0, 4.162913471D0,    0.033595D-6,    5507.553238667D0, 5.980162321D0,    0.029198D-6,    5856.477659115D0, 0.623811863D0,    0.027764D-6,     155.420399434D0, 3.745318113D0,    0.025190D-6,    5746.271337896D0, 2.980330535D0,    0.022997D-6,    -796.298006816D0, 1.174411803D0,    0.024976D-6,    5760.498431898D0, 2.467913690D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=481,490)" is not supported. Skipping.
Line #13759 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=491,500) /    0.021774D-6,     206.185548437D0, 3.854787540D0,    0.017925D-6,    -775.522611324D0, 1.092065955D0,    0.013794D-6,     426.598190876D0, 2.699831988D0,    0.013276D-6,    6062.663207553D0, 5.845801920D0,    0.011774D-6,   12036.460734888D0, 2.292832062D0,    0.012869D-6,    6076.890301554D0, 5.333425680D0,    0.012152D-6,    1059.381930189D0, 6.222874454D0,    0.011081D-6,      -7.113547001D0, 5.154724984D0,    0.010143D-6,    4694.002954708D0, 4.044013795D0,    0.009357D-6,    5486.777843175D0, 3.416081409D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=491,500)" is not supported. Skipping.
Line #13770 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=501,510) /    0.010084D-6,     522.577418094D0, 0.749320262D0,    0.008587D-6,   10977.078804699D0, 2.777152598D0,    0.008628D-6,    6275.962302991D0, 4.562060226D0,    0.008158D-6,    -220.412642439D0, 5.806891533D0,    0.007746D-6,    2544.314419883D0, 1.603197066D0,    0.007670D-6,    2146.165416475D0, 3.000200440D0,    0.007098D-6,      74.781598567D0, 0.443725817D0,    0.006180D-6,    -536.804512095D0, 1.302642751D0,    0.005818D-6,    5088.628839767D0, 4.827723531D0,    0.004945D-6,   -6286.598968340D0, 0.268305170D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=501,510)" is not supported. Skipping.
Line #13781 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=511,520) /    0.004774D-6,    1349.867409659D0, 5.808636673D0,    0.004687D-6,    -242.728603974D0, 5.154890570D0,    0.006089D-6,    1748.016413067D0, 4.403765209D0,    0.005975D-6,   -1194.447010225D0, 2.583472591D0,    0.004229D-6,     951.718406251D0, 0.931172179D0,    0.005264D-6,     553.569402842D0, 2.336107252D0,    0.003049D-6,    5643.178563677D0, 1.362634430D0,    0.002974D-6,    6812.766815086D0, 1.583012668D0,    0.003403D-6,   -2352.866153772D0, 2.552189886D0,    0.003030D-6,     419.484643875D0, 5.286473844D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=511,520)" is not supported. Skipping.
Line #13792 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=521,530) /    0.003210D-6,      -7.046236698D0, 1.863796539D0,    0.003058D-6,    9437.762934887D0, 4.226420633D0,    0.002589D-6,   12352.852604545D0, 1.991935820D0,    0.002927D-6,    5216.580372801D0, 2.319951253D0,    0.002425D-6,    5230.807466803D0, 3.084752833D0,    0.002656D-6,    3154.687084896D0, 2.487447866D0,    0.002445D-6,   10447.387839604D0, 2.347139160D0,    0.002990D-6,    4690.479836359D0, 6.235872050D0,    0.002890D-6,    5863.591206116D0, 0.095197563D0,    0.002498D-6,    6438.496249426D0, 2.994779800D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=521,530)" is not supported. Skipping.
Line #13803 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=531,540) /    0.001889D-6,    8031.092263058D0, 3.569003717D0,    0.002567D-6,     801.820931124D0, 3.425611498D0,    0.001803D-6,  -71430.695617928D0, 2.192295512D0,    0.001782D-6,       3.932153263D0, 5.180433689D0,    0.001694D-6,   -4705.732307544D0, 4.641779174D0,    0.001704D-6,   -1592.596013633D0, 3.997097652D0,    0.001735D-6,    5849.364112115D0, 0.417558428D0,    0.001643D-6,    8429.241266467D0, 2.180619584D0,    0.001680D-6,      38.133035638D0, 4.164529426D0,    0.002045D-6,    7084.896781115D0, 0.526323854D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=531,540)" is not supported. Skipping.
Line #13814 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=541,550) /    0.001458D-6,    4292.330832950D0, 1.356098141D0,    0.001437D-6,      20.355319399D0, 3.895439360D0,    0.001738D-6,    6279.552731642D0, 0.087484036D0,    0.001367D-6,   14143.495242431D0, 3.987576591D0,    0.001344D-6,    7234.794256242D0, 0.090454338D0,    0.001438D-6,   11499.656222793D0, 0.974387904D0,    0.001257D-6,    6836.645252834D0, 1.509069366D0,    0.001358D-6,   11513.883316794D0, 0.495572260D0,    0.001628D-6,    7632.943259650D0, 4.968445721D0,    0.001169D-6,     103.092774219D0, 2.838496795D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=541,550)" is not supported. Skipping.
Line #13825 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=551,560) /    0.001162D-6,    4164.311989613D0, 3.408387778D0,    0.001092D-6,    6069.776754553D0, 3.617942651D0,    0.001008D-6,   17789.845619785D0, 0.286350174D0,    0.001008D-6,     639.897286314D0, 1.610762073D0,    0.000918D-6,   10213.285546211D0, 5.532798067D0,    0.001011D-6,   -6256.777530192D0, 0.661826484D0,    0.000753D-6,   16730.463689596D0, 3.905030235D0,    0.000737D-6,   11926.254413669D0, 4.641956361D0,    0.000694D-6,    3340.612426700D0, 2.111120332D0,    0.000701D-6,    3894.181829542D0, 2.760823491D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=551,560)" is not supported. Skipping.
Line #13836 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=561,570) /    0.000689D-6,    -135.065080035D0, 4.768800780D0,    0.000700D-6,   13367.972631107D0, 5.760439898D0,    0.000664D-6,    6040.347246017D0, 1.051215840D0,    0.000654D-6,    5650.292110678D0, 4.911332503D0,    0.000788D-6,    6681.224853400D0, 4.699648011D0,    0.000628D-6,    5333.900241022D0, 5.024608847D0,    0.000755D-6,    -110.206321219D0, 4.370971253D0,    0.000628D-6,    6290.189396992D0, 3.660478857D0,    0.000635D-6,   25132.303399966D0, 4.121051532D0,    0.000534D-6,    5966.683980335D0, 1.173284524D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=561,570)" is not supported. Skipping.
Line #13847 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=571,580) /    0.000543D-6,    -433.711737877D0, 0.345585464D0,    0.000517D-6,   -1990.745017041D0, 5.414571768D0,    0.000504D-6,    5767.611978898D0, 2.328281115D0,    0.000485D-6,    5753.384884897D0, 1.685874771D0,    0.000463D-6,    7860.419392439D0, 5.297703006D0,    0.000604D-6,     515.463871093D0, 0.591998446D0,    0.000443D-6,   12168.002696575D0, 4.830881244D0,    0.000570D-6,     199.072001436D0, 3.899190272D0,    0.000465D-6,   10969.965257698D0, 0.476681802D0,    0.000424D-6,   -7079.373856808D0, 1.112242763D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=571,580)" is not supported. Skipping.
Line #13858 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=581,590) /    0.000427D-6,     735.876513532D0, 1.994214480D0,    0.000478D-6,   -6127.655450557D0, 3.778025483D0,    0.000414D-6,   10973.555686350D0, 5.441088327D0,    0.000512D-6,    1589.072895284D0, 0.107123853D0,    0.000378D-6,   10984.192351700D0, 0.915087231D0,    0.000402D-6,   11371.704689758D0, 4.107281715D0,    0.000453D-6,    9917.696874510D0, 1.917490952D0,    0.000395D-6,     149.563197135D0, 2.763124165D0,    0.000371D-6,    5739.157790895D0, 3.112111866D0,    0.000350D-6,   11790.629088659D0, 0.440639857D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=581,590)" is not supported. Skipping.
Line #13869 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=591,600) /    0.000356D-6,    6133.512652857D0, 5.444568842D0,    0.000344D-6,     412.371096874D0, 5.676832684D0,    0.000383D-6,     955.599741609D0, 5.559734846D0,    0.000333D-6,    6496.374945429D0, 0.261537984D0,    0.000340D-6,    6055.549660552D0, 5.975534987D0,    0.000334D-6,    1066.495477190D0, 2.335063907D0,    0.000399D-6,   11506.769769794D0, 5.321230910D0,    0.000314D-6,   18319.536584880D0, 2.313312404D0,    0.000424D-6,    1052.268383188D0, 1.211961766D0,    0.000307D-6,      63.735898303D0, 3.169551388D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=591,600)" is not supported. Skipping.
Line #13880 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=601,610) /    0.000329D-6,      29.821438149D0, 6.106912080D0,    0.000357D-6,    6309.374169791D0, 4.223760346D0,    0.000312D-6,   -3738.761430108D0, 2.180556645D0,    0.000301D-6,     309.278322656D0, 1.499984572D0,    0.000268D-6,   12043.574281889D0, 2.447520648D0,    0.000257D-6,   12491.370101415D0, 3.662331761D0,    0.000290D-6,     625.670192312D0, 1.272834584D0,    0.000256D-6,    5429.879468239D0, 1.913426912D0,    0.000339D-6,    3496.032826134D0, 4.165930011D0,    0.000283D-6,    3930.209696220D0, 4.325565754D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=601,610)" is not supported. Skipping.
Line #13891 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=611,620) /    0.000241D-6,   12528.018664345D0, 3.832324536D0,    0.000304D-6,    4686.889407707D0, 1.612348468D0,    0.000259D-6,   16200.772724501D0, 3.470173146D0,    0.000238D-6,   12139.553509107D0, 1.147977842D0,    0.000236D-6,    6172.869528772D0, 3.776271728D0,    0.000296D-6,   -7058.598461315D0, 0.460368852D0,    0.000306D-6,   10575.406682942D0, 0.554749016D0,    0.000251D-6,   17298.182327326D0, 0.834332510D0,    0.000290D-6,    4732.030627343D0, 4.759564091D0,    0.000261D-6,    5884.926846583D0, 0.298259862D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=611,620)" is not supported. Skipping.
Line #13902 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=621,630) /    0.000249D-6,    5547.199336460D0, 3.749366406D0,    0.000213D-6,   11712.955318231D0, 5.415666119D0,    0.000223D-6,    4701.116501708D0, 2.703203558D0,    0.000268D-6,    -640.877607382D0, 0.283670793D0,    0.000209D-6,    5636.065016677D0, 1.238477199D0,    0.000193D-6,   10177.257679534D0, 1.943251340D0,    0.000182D-6,    6283.143160294D0, 2.456157599D0,    0.000184D-6,    -227.526189440D0, 5.888038582D0,    0.000182D-6,   -6283.008539689D0, 0.241332086D0,    0.000228D-6,   -6284.056171060D0, 2.657323816D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=621,630)" is not supported. Skipping.
Line #13913 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=631,640) /    0.000166D-6,    7238.675591600D0, 5.930629110D0,    0.000167D-6,    3097.883822726D0, 5.570955333D0,    0.000159D-6,    -323.505416657D0, 5.786670700D0,    0.000154D-6,   -4136.910433516D0, 1.517805532D0,    0.000176D-6,   12029.347187887D0, 3.139266834D0,    0.000167D-6,   12132.439962106D0, 3.556352289D0,    0.000153D-6,     202.253395174D0, 1.463313961D0,    0.000157D-6,   17267.268201691D0, 1.586837396D0,    0.000142D-6,   83996.847317911D0, 0.022670115D0,    0.000152D-6,   17260.154654690D0, 0.708528947D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=631,640)" is not supported. Skipping.
Line #13924 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=641,650) /    0.000144D-6,    6084.003848555D0, 5.187075177D0,    0.000135D-6,    5756.566278634D0, 1.993229262D0,    0.000134D-6,    5750.203491159D0, 3.457197134D0,    0.000144D-6,    5326.786694021D0, 6.066193291D0,    0.000160D-6,   11015.106477335D0, 1.710431974D0,    0.000133D-6,    3634.621024518D0, 2.836451652D0,    0.000134D-6,   18073.704938650D0, 5.453106665D0,    0.000134D-6,    1162.474704408D0, 5.326898811D0,    0.000128D-6,    5642.198242609D0, 2.511652591D0,    0.000160D-6,     632.783739313D0, 5.628785365D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=641,650)" is not supported. Skipping.
Line #13935 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=651,660) /    0.000132D-6,   13916.019109642D0, 0.819294053D0,    0.000122D-6,   14314.168113050D0, 5.677408071D0,    0.000125D-6,   12359.966151546D0, 5.251984735D0,    0.000121D-6,    5749.452731634D0, 2.210924603D0,    0.000136D-6,    -245.831646229D0, 1.646502367D0,    0.000120D-6,    5757.317038160D0, 3.240883049D0,    0.000134D-6,   12146.667056108D0, 3.059480037D0,    0.000137D-6,    6206.809778716D0, 1.867105418D0,    0.000141D-6,   17253.041107690D0, 2.069217456D0,    0.000129D-6,   -7477.522860216D0, 2.781469314D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=651,660)" is not supported. Skipping.
Line #13946 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=661,670) /    0.000116D-6,    5540.085789459D0, 4.281176991D0,    0.000116D-6,    9779.108676125D0, 3.320925381D0,    0.000129D-6,    5237.921013804D0, 3.497704076D0,    0.000113D-6,    5959.570433334D0, 0.983210840D0,    0.000122D-6,    6282.095528923D0, 2.674938860D0,    0.000140D-6,     -11.045700264D0, 4.957936982D0,    0.000108D-6,   23543.230504682D0, 1.390113589D0,    0.000106D-6,  -12569.674818332D0, 0.429631317D0,    0.000110D-6,    -266.607041722D0, 5.501340197D0,    0.000115D-6,   12559.038152982D0, 4.691456618D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=661,670)" is not supported. Skipping.
Line #13959 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=671,680) /    0.000134D-6,   -2388.894020449D0, 0.577313584D0,    0.000109D-6,   10440.274292604D0, 6.218148717D0,    0.000102D-6,    -543.918059096D0, 1.477842615D0,    0.000108D-6,   21228.392023546D0, 2.237753948D0,    0.000101D-6,   -4535.059436924D0, 3.100492232D0,    0.000103D-6,      76.266071276D0, 5.594294322D0,    0.000104D-6,     949.175608970D0, 5.674287810D0,    0.000101D-6,   13517.870106233D0, 2.196632348D0,    0.000100D-6,   11933.367960670D0, 4.056084160D0,    4.322990D-6,    6283.075849991D0, 2.642893748D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=671,680)" is not supported. Skipping.
Line #13970 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=681,690) /    0.406495D-6,       0.000000000D0, 4.712388980D0,    0.122605D-6,   12566.151699983D0, 2.438140634D0,    0.019476D-6,     213.299095438D0, 1.642186981D0,    0.016916D-6,     529.690965095D0, 4.510959344D0,    0.013374D-6,      -3.523118349D0, 1.502210314D0,    0.008042D-6,      26.298319800D0, 0.478549024D0,    0.007824D-6,     155.420399434D0, 5.254710405D0,    0.004894D-6,    5746.271337896D0, 4.683210850D0,    0.004875D-6,    5760.498431898D0, 0.759507698D0,    0.004416D-6,    5223.693919802D0, 6.028853166D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=681,690)" is not supported. Skipping.
Line #13981 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=691,700) /    0.004088D-6,      -7.113547001D0, 0.060926389D0,    0.004433D-6,   77713.771467920D0, 3.627734103D0,    0.003277D-6,   18849.227549974D0, 2.327912542D0,    0.002703D-6,    6062.663207553D0, 1.271941729D0,    0.003435D-6,    -775.522611324D0, 0.747446224D0,    0.002618D-6,    6076.890301554D0, 3.633715689D0,    0.003146D-6,     206.185548437D0, 5.647874613D0,    0.002544D-6,    1577.343542448D0, 6.232904270D0,    0.002218D-6,    -220.412642439D0, 1.309509946D0,    0.002197D-6,    5856.477659115D0, 2.407212349D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=691,700)" is not supported. Skipping.
Line #13992 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=701,710) /    0.002897D-6,    5753.384884897D0, 5.863842246D0,    0.001766D-6,     426.598190876D0, 0.754113147D0,    0.001738D-6,    -796.298006816D0, 2.714942671D0,    0.001695D-6,     522.577418094D0, 2.629369842D0,    0.001584D-6,    5507.553238667D0, 1.341138229D0,    0.001503D-6,    -242.728603974D0, 0.377699736D0,    0.001552D-6,    -536.804512095D0, 2.904684667D0,    0.001370D-6,    -398.149003408D0, 1.265599125D0,    0.001889D-6,   -5573.142801634D0, 4.413514859D0,    0.001722D-6,    6069.776754553D0, 2.445966339D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=701,710)" is not supported. Skipping.
Line #14003 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=711,720) /    0.001124D-6,    1059.381930189D0, 5.041799657D0,    0.001258D-6,     553.569402842D0, 3.849557278D0,    0.000831D-6,     951.718406251D0, 2.471094709D0,    0.000767D-6,    4694.002954708D0, 5.363125422D0,    0.000756D-6,    1349.867409659D0, 1.046195744D0,    0.000775D-6,     -11.045700264D0, 0.245548001D0,    0.000597D-6,    2146.165416475D0, 4.543268798D0,    0.000568D-6,    5216.580372801D0, 4.178853144D0,    0.000711D-6,    1748.016413067D0, 5.934271972D0,    0.000499D-6,   12036.460734888D0, 0.624434410D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=711,720)" is not supported. Skipping.
Line #14014 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=721,730) /    0.000671D-6,   -1194.447010225D0, 4.136047594D0,    0.000488D-6,    5849.364112115D0, 2.209679987D0,    0.000621D-6,    6438.496249426D0, 4.518860804D0,    0.000495D-6,   -6286.598968340D0, 1.868201275D0,    0.000456D-6,    5230.807466803D0, 1.271231591D0,    0.000451D-6,    5088.628839767D0, 0.084060889D0,    0.000435D-6,    5643.178563677D0, 3.324456609D0,    0.000387D-6,   10977.078804699D0, 4.052488477D0,    0.000547D-6,  161000.685737473D0, 2.841633844D0,    0.000522D-6,    3154.687084896D0, 2.171979966D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=721,730)" is not supported. Skipping.
Line #14025 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=731,740) /    0.000375D-6,    5486.777843175D0, 4.983027306D0,    0.000421D-6,    5863.591206116D0, 4.546432249D0,    0.000439D-6,    7084.896781115D0, 0.522967921D0,    0.000309D-6,    2544.314419883D0, 3.172606705D0,    0.000347D-6,    4690.479836359D0, 1.479586566D0,    0.000317D-6,     801.820931124D0, 3.553088096D0,    0.000262D-6,     419.484643875D0, 0.606635550D0,    0.000248D-6,    6836.645252834D0, 3.014082064D0,    0.000245D-6,   -1592.596013633D0, 5.519526220D0,    0.000225D-6,    4292.330832950D0, 2.877956536D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=731,740)" is not supported. Skipping.
Line #14036 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=741,750) /    0.000214D-6,    7234.794256242D0, 1.605227587D0,    0.000205D-6,    5767.611978898D0, 0.625804796D0,    0.000180D-6,   10447.387839604D0, 3.499954526D0,    0.000229D-6,     199.072001436D0, 5.632304604D0,    0.000214D-6,     639.897286314D0, 5.960227667D0,    0.000175D-6,    -433.711737877D0, 2.162417992D0,    0.000209D-6,     515.463871093D0, 2.322150893D0,    0.000173D-6,    6040.347246017D0, 2.556183691D0,    0.000184D-6,    6309.374169791D0, 4.732296790D0,    0.000227D-6,  149854.400134205D0, 5.385812217D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=741,750)" is not supported. Skipping.
Line #14047 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=751,760) /    0.000154D-6,    8031.092263058D0, 5.120720920D0,    0.000151D-6,    5739.157790895D0, 4.815000443D0,    0.000197D-6,    7632.943259650D0, 0.222827271D0,    0.000197D-6,      74.781598567D0, 3.910456770D0,    0.000138D-6,    6055.549660552D0, 1.397484253D0,    0.000149D-6,   -6127.655450557D0, 5.333727496D0,    0.000137D-6,    3894.181829542D0, 4.281749907D0,    0.000135D-6,    9437.762934887D0, 5.979971885D0,    0.000139D-6,   -2352.866153772D0, 4.715630782D0,    0.000142D-6,    6812.766815086D0, 0.513330157D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=751,760)" is not supported. Skipping.
Line #14060 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=761,770) /    0.000120D-6,   -4705.732307544D0, 0.194160689D0,    0.000131D-6,  -71430.695617928D0, 0.000379226D0,    0.000124D-6,    6279.552731642D0, 2.122264908D0,    0.000108D-6,   -6256.777530192D0, 0.883445696D0,    0.143388D-6,    6283.075849991D0, 1.131453581D0,    0.006671D-6,   12566.151699983D0, 0.775148887D0,    0.001480D-6,     155.420399434D0, 0.480016880D0,    0.000934D-6,     213.299095438D0, 6.144453084D0,    0.000795D-6,     529.690965095D0, 2.941595619D0,    0.000673D-6,    5746.271337896D0, 0.120415406D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=761,770)" is not supported. Skipping.
Line #14071 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=771,780) /    0.000672D-6,    5760.498431898D0, 5.317009738D0,    0.000389D-6,    -220.412642439D0, 3.090323467D0,    0.000373D-6,    6062.663207553D0, 3.003551964D0,    0.000360D-6,    6076.890301554D0, 1.918913041D0,    0.000316D-6,     -21.340641002D0, 5.545798121D0,    0.000315D-6,    -242.728603974D0, 1.884932563D0,    0.000278D-6,     206.185548437D0, 1.266254859D0,    0.000238D-6,    -536.804512095D0, 4.532664830D0,    0.000185D-6,     522.577418094D0, 4.578313856D0,    0.000245D-6,   18849.227549974D0, 0.587467082D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=771,780)" is not supported. Skipping.
Line #14085 in sofapy.f:"      DATA ((FAIRHD(I,J),I=1,3),J=781,787) /    0.000180D-6,     426.598190876D0, 5.151178553D0,    0.000200D-6,     553.569402842D0, 5.355983739D0,    0.000141D-6,    5223.693919802D0, 1.336556009D0,    0.000104D-6,    5856.477659115D0, 4.239842759D0,    0.003826D-6,    6283.075849991D0, 5.705257275D0,    0.000303D-6,   12566.151699983D0, 5.407132842D0,    0.000209D-6,     155.420399434D0, 1.989815753D0 /"
	analyzeline: implied-DO list "((fairhd(i,j),i=1,3),j=781,787)" is not supported. Skipping.
Line #15859 in sofapy.f:"      DATA ( ( KE0(I,J), I=1,8), J=1,10 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  2, -2,  3,  0,  0,  0,  0,  0,  2, -2,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  3,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  1,  0,  0,  1,  0,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ke0(i,j), i=1,8), j=1,10 )" is not supported. Skipping.
Line #15870 in sofapy.f:"      DATA ( ( KE0(I,J), I=1,8), J=11,20 ) /  1,  0,  0,  0, -1,  0,  0,  0,  1,  0,  0,  0,  1,  0,  0,  0,  0,  1,  2, -2,  3,  0,  0,  0,  0,  1,  2, -2,  1,  0,  0,  0,  0,  0,  4, -4,  4,  0,  0,  0,  0,  0,  1, -1,  1, -8, 12,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  1,  0,  2,  0,  3,  0,  0,  0,  1,  0,  2,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ke0(i,j), i=1,8), j=11,20 )" is not supported. Skipping.
Line #15881 in sofapy.f:"      DATA ( ( KE0(I,J), I=1,8), J=21,30 ) /  0,  0,  2, -2,  0,  0,  0,  0,  0,  1, -2,  2, -3,  0,  0,  0,  0,  1, -2,  2, -1,  0,  0,  0,  0,  0,  0,  0,  0,  8,-13, -1,  0,  0,  0,  2,  0,  0,  0,  0,  2,  0, -2,  0, -1,  0,  0,  0,  1,  0,  0, -2,  1,  0,  0,  0,  0,  1,  2, -2,  2,  0,  0,  0,  1,  0,  0, -2, -1,  0,  0,  0,  0,  0,  4, -2,  4,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ke0(i,j), i=1,8), j=21,30 )" is not supported. Skipping.
Line #15887 in sofapy.f:"      DATA ( ( KE0(I,J), I=1,8), J=31,NE0 ) /  0,  0,  2, -2,  4,  0,  0,  0,  1,  0, -2,  0, -3,  0,  0,  0,  1,  0, -2,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ke0(i,j), i=1,8), j=31,ne0 )" is not supported. Skipping.
Line #15891 in sofapy.f:"      DATA ( ( KE1(I,J), I=1,8), J=1,NE1 ) /  0,  0,  0,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ke1(i,j), i=1,8), j=1,ne1 )" is not supported. Skipping.
Line #15902 in sofapy.f:"      DATA ( ( SE0(I,J), I=1,2), J =    1,   10 ) /            +2640.96D-6,          -0.39D-6,              +63.52D-6,          -0.02D-6,              +11.75D-6,          +0.01D-6,              +11.21D-6,          +0.01D-6,               -4.55D-6,          +0.00D-6,               +2.02D-6,          +0.00D-6,               +1.98D-6,          +0.00D-6,               -1.72D-6,          +0.00D-6,               -1.41D-6,          -0.01D-6,               -1.26D-6,          -0.01D-6 /"
	analyzeline: implied-DO list "( ( se0(i,j), i=1,2), j =    1,   10 )" is not supported. Skipping.
Line #15913 in sofapy.f:"      DATA ( ( SE0(I,J), I=1,2), J =   11,   20 ) /               -0.63D-6,          +0.00D-6,               -0.63D-6,          +0.00D-6,               +0.46D-6,          +0.00D-6,               +0.45D-6,          +0.00D-6,               +0.36D-6,          +0.00D-6,               -0.24D-6,          -0.12D-6,               +0.32D-6,          +0.00D-6,               +0.28D-6,          +0.00D-6,               +0.27D-6,          +0.00D-6,               +0.26D-6,          +0.00D-6 /"
	analyzeline: implied-DO list "( ( se0(i,j), i=1,2), j =   11,   20 )" is not supported. Skipping.
Line #15924 in sofapy.f:"      DATA ( ( SE0(I,J), I=1,2), J =   21,   30 ) /               -0.21D-6,          +0.00D-6,               +0.19D-6,          +0.00D-6,               +0.18D-6,          +0.00D-6,               -0.10D-6,          +0.05D-6,               +0.15D-6,          +0.00D-6,               -0.14D-6,          +0.00D-6,               +0.14D-6,          +0.00D-6,               -0.14D-6,          +0.00D-6,               +0.14D-6,          +0.00D-6,               +0.13D-6,          +0.00D-6 /"
	analyzeline: implied-DO list "( ( se0(i,j), i=1,2), j =   21,   30 )" is not supported. Skipping.
Line #15930 in sofapy.f:"      DATA ( ( SE0(I,J), I=1,2), J =   31,  NE0 ) /               -0.11D-6,          +0.00D-6,               +0.11D-6,          +0.00D-6,               +0.11D-6,          +0.00D-6 /"
	analyzeline: implied-DO list "( ( se0(i,j), i=1,2), j =   31,  ne0 )" is not supported. Skipping.
Line #15933 in sofapy.f:"      DATA ( ( SE1(I,J), I=1,2), J =    1,  NE1 ) /               -0.87D-6,          +0.00D-6 /"
	analyzeline: implied-DO list "( ( se1(i,j), i=1,2), j =    1,  ne1 )" is not supported. Skipping.
Line #17486 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=  1, 10) /  0.9998292878132D+00, 0.1753485171504D+01, 0.6283075850446D+01,  0.8352579567414D-02, 0.1710344404582D+01, 0.1256615170089D+02,  0.5611445335148D-02, 0.0000000000000D+00, 0.0000000000000D+00,  0.1046664295572D-03, 0.1667225416770D+01, 0.1884922755134D+02,  0.3110842534677D-04, 0.6687513390251D+00, 0.8399684731857D+02,  0.2552413503550D-04, 0.5830637358413D+00, 0.5296909721118D+00,  0.2137207845781D-04, 0.1092330954011D+01, 0.1577343543434D+01,  0.1680240182951D-04, 0.4955366134987D+00, 0.6279552690824D+01,  0.1679012370795D-04, 0.6153014091901D+01, 0.6286599010068D+01,  0.1445526946777D-04, 0.3472744100492D+01, 0.2352866153506D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #17497 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 11, 20) /  0.1091038246184D-04, 0.3689845786119D+01, 0.5223693906222D+01,  0.9344399733932D-05, 0.6073934645672D+01, 0.1203646072878D+02,  0.8993182910652D-05, 0.3175705249069D+01, 0.1021328554739D+02,  0.5665546034116D-05, 0.2152484672246D+01, 0.1059381944224D+01,  0.6844146703035D-05, 0.1306964099750D+01, 0.5753384878334D+01,  0.7346610905565D-05, 0.4354980070466D+01, 0.3981490189893D+00,  0.6815396474414D-05, 0.2218229211267D+01, 0.4705732307012D+01,  0.6112787253053D-05, 0.5384788425458D+01, 0.6812766822558D+01,  0.4518120711239D-05, 0.6087604012291D+01, 0.5884926831456D+01,  0.4521963430706D-05, 0.1279424524906D+01, 0.6256777527156D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #17508 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 21, 30) /  0.4497426764085D-05, 0.5369129144266D+01, 0.6309374173736D+01,  0.4062190566959D-05, 0.5436473303367D+00, 0.6681224869435D+01,  0.5412193480192D-05, 0.7867838528395D+00, 0.7755226100720D+00,  0.5469839049386D-05, 0.1461440311134D+01, 0.1414349524433D+02,  0.5205264083477D-05, 0.4432944696116D+01, 0.7860419393880D+01,  0.2149759935455D-05, 0.4502237496846D+01, 0.1150676975667D+02,  0.2279109618501D-05, 0.1239441308815D+01, 0.7058598460518D+01,  0.2259282939683D-05, 0.3272430985331D+01, 0.4694002934110D+01,  0.2558950271319D-05, 0.2265471086404D+01, 0.1216800268190D+02,  0.2561581447555D-05, 0.1454740653245D+01, 0.7099330490126D+00 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #17519 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 31, 40) /  0.1781441115440D-05, 0.2962068630206D+01, 0.7962980379786D+00,  0.1612005874644D-05, 0.1473255041006D+01, 0.5486777812467D+01,  0.1818630667105D-05, 0.3743903293447D+00, 0.6283008715021D+01,  0.1818601377529D-05, 0.6274174354554D+01, 0.6283142985870D+01,  0.1554475925257D-05, 0.1624110906816D+01, 0.2513230340178D+02,  0.2090948029241D-05, 0.5852052276256D+01, 0.1179062909082D+02,  0.2000176345460D-05, 0.4072093298513D+01, 0.1778984560711D+02,  0.1289535917759D-05, 0.5217019331069D+01, 0.7079373888424D+01,  0.1281135307881D-05, 0.4802054538934D+01, 0.3738761453707D+01,  0.1518229005692D-05, 0.8691914742502D+00, 0.2132990797783D+00 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #17530 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 41, 50) /  0.9450128579027D-06, 0.4601859529950D+01, 0.1097707878456D+02,  0.7781119494996D-06, 0.1844352816694D+01, 0.8827390247185D+01,  0.7733407759912D-06, 0.3582790154750D+01, 0.5507553240374D+01,  0.7350644318120D-06, 0.2695277788230D+01, 0.1589072916335D+01,  0.6535928827023D-06, 0.3651327986142D+01, 0.1176985366291D+02,  0.6324624183656D-06, 0.2241302375862D+01, 0.6262300422539D+01,  0.6298565300557D-06, 0.4407122406081D+01, 0.6303851278352D+01,  0.8587037089179D-06, 0.3024307223119D+01, 0.1672837615881D+03,  0.8299954491035D-06, 0.6192539428237D+01, 0.3340612434717D+01,  0.6311263503401D-06, 0.2014758795416D+01, 0.7113454667900D-02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #17541 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 51, 60) /  0.6005646745452D-06, 0.3399500503397D+01, 0.4136910472696D+01,  0.7917715109929D-06, 0.2493386877837D+01, 0.6069776770667D+01,  0.7556958099685D-06, 0.4159491740143D+01, 0.6496374930224D+01,  0.6773228244949D-06, 0.4034162934230D+01, 0.9437762937313D+01,  0.5370708577847D-06, 0.1562219163734D+01, 0.1194447056968D+01,  0.5710804266203D-06, 0.2662730803386D+01, 0.6282095334605D+01,  0.5709824583726D-06, 0.3985828430833D+01, 0.6284056366286D+01,  0.5143950896447D-06, 0.1308144688689D+01, 0.6290189305114D+01,  0.5088010604546D-06, 0.5352817214804D+01, 0.6275962395778D+01,  0.4960369085172D-06, 0.2644267922349D+01, 0.6127655567643D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #17552 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 61, 70) /  0.4803137891183D-06, 0.4008844192080D+01, 0.6438496133249D+01,  0.5731747768225D-06, 0.3794550174597D+01, 0.3154687086868D+01,  0.4735947960579D-06, 0.6107118308982D+01, 0.3128388763578D+01,  0.4808348796625D-06, 0.4771458618163D+01, 0.8018209333619D+00,  0.4115073743137D-06, 0.3327111335159D+01, 0.8429241228195D+01,  0.5230575889287D-06, 0.5305708551694D+01, 0.1336797263425D+02,  0.5133977889215D-06, 0.5784230738814D+01, 0.1235285262111D+02,  0.5065815825327D-06, 0.2052064793679D+01, 0.1185621865188D+02,  0.4339831593868D-06, 0.3644994195830D+01, 0.1726015463500D+02,  0.3952928638953D-06, 0.4930376436758D+01, 0.5481254917084D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #17563 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 71, 80) /  0.4898498111942D-06, 0.4542084219731D+00, 0.9225539266174D+01,  0.4757490209328D-06, 0.3161126388878D+01, 0.5856477690889D+01,  0.4727701669749D-06, 0.6214993845446D+00, 0.2544314396739D+01,  0.3800966681863D-06, 0.3040132339297D+01, 0.4265981595566D+00,  0.3257301077939D-06, 0.8064977360087D+00, 0.3930209696940D+01,  0.3255810528674D-06, 0.1974147981034D+01, 0.2146165377750D+01,  0.3252029748187D-06, 0.2845924913135D+01, 0.4164311961999D+01,  0.3255505635308D-06, 0.3017900824120D+01, 0.5088628793478D+01,  0.2801345211990D-06, 0.6109717793179D+01, 0.1256967486051D+02,  0.3688987740970D-06, 0.2911550235289D+01, 0.1807370494127D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #17574 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 81, 90) /  0.2475153429458D-06, 0.2179146025856D+01, 0.2629832328990D-01,  0.3033457749150D-06, 0.1994161050744D+01, 0.4535059491685D+01,  0.2186743763110D-06, 0.5125687237936D+01, 0.1137170464392D+02,  0.2764777032774D-06, 0.4822646860252D+00, 0.1256262854127D+02,  0.2199028768592D-06, 0.4637633293831D+01, 0.1255903824622D+02,  0.2046482824760D-06, 0.1467038733093D+01, 0.7084896783808D+01,  0.2611209147507D-06, 0.3044718783485D+00, 0.7143069561767D+02,  0.2286079656818D-06, 0.4764220356805D+01, 0.8031092209206D+01,  0.1855071202587D-06, 0.3383637774428D+01, 0.1748016358760D+01,  0.2324669506784D-06, 0.6189088449251D+01, 0.1831953657923D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #17585 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J= 91,100) /  0.1709528015688D-06, 0.5874966729774D+00, 0.4933208510675D+01,  0.2168156875828D-06, 0.4302994009132D+01, 0.1044738781244D+02,  0.2106675556535D-06, 0.3800475419891D+01, 0.7477522907414D+01,  0.1430213830465D-06, 0.1294660846502D+01, 0.2942463415728D+01,  0.1388396901944D-06, 0.4594797202114D+01, 0.8635942003952D+01,  0.1922258844190D-06, 0.4943044543591D+00, 0.1729818233119D+02,  0.1888460058292D-06, 0.2426943912028D+01, 0.1561374759853D+03,  0.1789449386107D-06, 0.1582973303499D+00, 0.1592596075957D+01,  0.1360803685374D-06, 0.5197240440504D+01, 0.1309584267300D+02,  0.1504038014709D-06, 0.3120360916217D+01, 0.1649636139783D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j= 91,100)" is not supported. Skipping.
Line #17596 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=101,110) /  0.1382769533389D-06, 0.6164702888205D+01, 0.7632943190217D+01,  0.1438059769079D-06, 0.1437423770979D+01, 0.2042657109477D+02,  0.1326303260037D-06, 0.3609688799679D+01, 0.1213955354133D+02,  0.1159244950540D-06, 0.5463018167225D+01, 0.5331357529664D+01,  0.1433118149136D-06, 0.6028909912097D+01, 0.7342457794669D+01,  0.1234623148594D-06, 0.3109645574997D+01, 0.6279485555400D+01,  0.1233949875344D-06, 0.3539359332866D+01, 0.6286666145492D+01,  0.9927196061299D-07, 0.1259321569772D+01, 0.7234794171227D+01,  0.1242302191316D-06, 0.1065949392609D+01, 0.1511046609763D+02,  0.1098402195201D-06, 0.2192508743837D+01, 0.1098880815746D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=101,110)" is not supported. Skipping.
Line #17607 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=111,120) /  0.1158191395315D-06, 0.4054411278650D+01, 0.5729506548653D+01,  0.9048475596241D-07, 0.5429764748518D+01, 0.9623688285163D+01,  0.8889853269023D-07, 0.5046586206575D+01, 0.6148010737701D+01,  0.1048694242164D-06, 0.2628858030806D+01, 0.6836645152238D+01,  0.1112308378646D-06, 0.4177292719907D+01, 0.1572083878776D+02,  0.8631729709901D-07, 0.1601345232557D+01, 0.6418140963190D+01,  0.8527816951664D-07, 0.2463888997513D+01, 0.1471231707864D+02,  0.7892139456991D-07, 0.3154022088718D+01, 0.2118763888447D+01,  0.1051782905236D-06, 0.4795035816088D+01, 0.1349867339771D+01,  0.1048219943164D-06, 0.2952983395230D+01, 0.5999216516294D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=111,120)" is not supported. Skipping.
Line #17618 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=121,130) /  0.7435760775143D-07, 0.5420547991464D+01, 0.6040347114260D+01,  0.9869574106949D-07, 0.3695646753667D+01, 0.6566935184597D+01,  0.9156886364226D-07, 0.3922675306609D+01, 0.5643178611111D+01,  0.7006834356188D-07, 0.1233968624861D+01, 0.6525804586632D+01,  0.9806170182601D-07, 0.1919542280684D+01, 0.2122839202813D+02,  0.9052289673607D-07, 0.4615902724369D+01, 0.4690479774488D+01,  0.7554200867893D-07, 0.1236863719072D+01, 0.1253985337760D+02,  0.8215741286498D-07, 0.3286800101559D+00, 0.1097355562493D+02,  0.7185178575397D-07, 0.5880942158367D+01, 0.6245048154254D+01,  0.7130726476180D-07, 0.7674871987661D+00, 0.6321103546637D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=121,130)" is not supported. Skipping.
Line #17629 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=131,140) /  0.6650894461162D-07, 0.6987129150116D+00, 0.5327476111629D+01,  0.7396888823688D-07, 0.3576824794443D+01, 0.5368044267797D+00,  0.7420588884775D-07, 0.5033615245369D+01, 0.2354323048545D+02,  0.6141181642908D-07, 0.9449927045673D+00, 0.1296430071988D+02,  0.6373557924058D-07, 0.6206342280341D+01, 0.9517183207817D+00,  0.6359474329261D-07, 0.5036079095757D+01, 0.1990745094947D+01,  0.5740173582646D-07, 0.6105106371350D+01, 0.9555997388169D+00,  0.7019864084602D-07, 0.7237747359018D+00, 0.5225775174439D+00,  0.6398054487042D-07, 0.3976367969666D+01, 0.2407292145756D+02,  0.7797092650498D-07, 0.4305423910623D+01, 0.2200391463820D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=131,140)" is not supported. Skipping.
Line #17640 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=141,150) /  0.6466760000900D-07, 0.3500136825200D+01, 0.5230807360890D+01,  0.7529417043890D-07, 0.3514779246100D+01, 0.1842262939178D+02,  0.6924571140892D-07, 0.2743457928679D+01, 0.1554202828031D+00,  0.6220798650222D-07, 0.2242598118209D+01, 0.1845107853235D+02,  0.5870209391853D-07, 0.2332832707527D+01, 0.6398972393349D+00,  0.6263953473888D-07, 0.2191105358956D+01, 0.6277552955062D+01,  0.6257781390012D-07, 0.4457559396698D+01, 0.6288598745829D+01,  0.5697304945123D-07, 0.3499234761404D+01, 0.1551045220144D+01,  0.6335438746791D-07, 0.6441691079251D+00, 0.5216580451554D+01,  0.6377258441152D-07, 0.2252599151092D+01, 0.5650292065779D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=141,150)" is not supported. Skipping.
Line #17651 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=151,160) /  0.6484841818165D-07, 0.1992812417646D+01, 0.1030928125552D+00,  0.4735551485250D-07, 0.3744672082942D+01, 0.1431416805965D+02,  0.4628595996170D-07, 0.1334226211745D+01, 0.5535693017924D+00,  0.6258152336933D-07, 0.4395836159154D+01, 0.2608790314060D+02,  0.6196171366594D-07, 0.2587043007997D+01, 0.8467247584405D+02,  0.6159556952126D-07, 0.4782499769128D+01, 0.2394243902548D+03,  0.4987741172394D-07, 0.7312257619924D+00, 0.7771377146812D+02,  0.5459280703142D-07, 0.3001376372532D+01, 0.6179983037890D+01,  0.4863461189999D-07, 0.3767222128541D+01, 0.9027992316901D+02,  0.5349912093158D-07, 0.3663594450273D+01, 0.6386168663001D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=151,160)" is not supported. Skipping.
Line #17662 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=161,170) /  0.5673725607806D-07, 0.4331187919049D+01, 0.6915859635113D+01,  0.4745485060512D-07, 0.5816195745518D+01, 0.6282970628506D+01,  0.4745379005326D-07, 0.8323672435672D+00, 0.6283181072386D+01,  0.4049002796321D-07, 0.3785023976293D+01, 0.6254626709878D+01,  0.4247084014515D-07, 0.2378220728783D+01, 0.7875671926403D+01,  0.4026912363055D-07, 0.2864103423269D+01, 0.6311524991013D+01,  0.4062935011774D-07, 0.2415408595975D+01, 0.3634620989887D+01,  0.5347771048509D-07, 0.3343479309801D+01, 0.2515860172507D+02,  0.4829494136505D-07, 0.2821742398262D+01, 0.5760498333002D+01,  0.4342554404599D-07, 0.5624662458712D+01, 0.7238675589263D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=161,170)" is not supported. Skipping.
Line #17673 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=171,180) /  0.4021599184361D-07, 0.5557250275009D+00, 0.1101510648075D+02,  0.4104900474558D-07, 0.3296691780005D+01, 0.6709674010002D+01,  0.4376532905131D-07, 0.3814443999443D+01, 0.6805653367890D+01,  0.3314590480650D-07, 0.3560229189250D+01, 0.1259245002418D+02,  0.3232421839643D-07, 0.5185389180568D+01, 0.1066495398892D+01,  0.3541176318876D-07, 0.3921381909679D+01, 0.9917696840332D+01,  0.3689831242681D-07, 0.4190658955386D+01, 0.1192625446156D+02,  0.3890605376774D-07, 0.5546023371097D+01, 0.7478166569050D-01,  0.3038559339780D-07, 0.6231032794494D+01, 0.1256621883632D+02,  0.3137083969782D-07, 0.6207063419190D+01, 0.4292330755499D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=171,180)" is not supported. Skipping.
Line #17684 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=181,190) /  0.4024004081854D-07, 0.1195257375713D+01, 0.1334167431096D+02,  0.3300234879283D-07, 0.1804694240998D+01, 0.1057540660594D+02,  0.3635399155575D-07, 0.5597811343500D+01, 0.6208294184755D+01,  0.3032668691356D-07, 0.3191059366530D+01, 0.1805292951336D+02,  0.2809652069058D-07, 0.4094348032570D+01, 0.3523159621801D-02,  0.3696955383823D-07, 0.5219282738794D+01, 0.5966683958112D+01,  0.3562894142503D-07, 0.1037247544554D+01, 0.6357857516136D+01,  0.3510598524148D-07, 0.1430020816116D+01, 0.6599467742779D+01,  0.3617736142953D-07, 0.3002911403677D+01, 0.6019991944201D+01,  0.2624524910730D-07, 0.2437046757292D+01, 0.6702560555334D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=181,190)" is not supported. Skipping.
Line #17695 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=191,200) /  0.2535824204490D-07, 0.1581594689647D+01, 0.3141537925223D+02,  0.3519787226257D-07, 0.5379863121521D+01, 0.2505706758577D+03,  0.2578406709982D-07, 0.4904222639329D+01, 0.1673046366289D+02,  0.3423887981473D-07, 0.3646448997315D+01, 0.6546159756691D+01,  0.2776083886467D-07, 0.3307829300144D+01, 0.1272157198369D+02,  0.3379592818379D-07, 0.1747541251125D+01, 0.1494531617769D+02,  0.3050255426284D-07, 0.1784689432607D-01, 0.4732030630302D+01,  0.2652378350236D-07, 0.4420055276260D+01, 0.5863591145557D+01,  0.2374498173768D-07, 0.3629773929208D+01, 0.2388894113936D+01,  0.2716451255140D-07, 0.3079623706780D+01, 0.1202934727411D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=191,200)" is not supported. Skipping.
Line #17706 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=201,210) /  0.3038583699229D-07, 0.3312487903507D+00, 0.1256608456547D+02,  0.2220681228760D-07, 0.5265520401774D+01, 0.1336244973887D+02,  0.3044156540912D-07, 0.4766664081250D+01, 0.2908881142201D+02,  0.2731859923561D-07, 0.5069146530691D+01, 0.1391601904066D+02,  0.2285603018171D-07, 0.5954935112271D+01, 0.6076890225335D+01,  0.2025006454555D-07, 0.4061789589267D+01, 0.4701116388778D+01,  0.2012597519804D-07, 0.2485047705241D+01, 0.6262720680387D+01,  0.2003406962258D-07, 0.4163779209320D+01, 0.6303431020504D+01,  0.2207863441371D-07, 0.6923839133828D+00, 0.6489261475556D+01,  0.2481374305624D-07, 0.5944173595676D+01, 0.1204357418345D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=201,210)" is not supported. Skipping.
Line #17717 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=211,220) /  0.2130923288870D-07, 0.4641013671967D+01, 0.5746271423666D+01,  0.2446370543391D-07, 0.6125796518757D+01, 0.1495633313810D+00,  0.1932492759052D-07, 0.2234572324504D+00, 0.1352175143971D+02,  0.2600122568049D-07, 0.4281012405440D+01, 0.4590910121555D+01,  0.2431754047488D-07, 0.1429943874870D+00, 0.1162474756779D+01,  0.1875902869209D-07, 0.9781803816948D+00, 0.6279194432410D+01,  0.1874381139426D-07, 0.5670368130173D+01, 0.6286957268481D+01,  0.2156696047173D-07, 0.2008985006833D+01, 0.1813929450232D+02,  0.1965076182484D-07, 0.2566186202453D+00, 0.4686889479442D+01,  0.2334816372359D-07, 0.4408121891493D+01, 0.1002183730415D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=211,220)" is not supported. Skipping.
Line #17728 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=221,230) /  0.1869937408802D-07, 0.5272745038656D+01, 0.2427287361862D+00,  0.2436236460883D-07, 0.4407720479029D+01, 0.9514313292143D+02,  0.1761365216611D-07, 0.1943892315074D+00, 0.1351787002167D+02,  0.2156289480503D-07, 0.1418570924545D+01, 0.6037244212485D+01,  0.2164748979255D-07, 0.4724603439430D+01, 0.2301353951334D+02,  0.2222286670853D-07, 0.2400266874598D+01, 0.1266924451345D+02,  0.2070901414929D-07, 0.5230348028732D+01, 0.6528907488406D+01,  0.1792745177020D-07, 0.2099190328945D+01, 0.6819880277225D+01,  0.1841802068445D-07, 0.3467527844848D+00, 0.6514761976723D+02,  0.1578401631718D-07, 0.7098642356340D+00, 0.2077542790660D-01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=221,230)" is not supported. Skipping.
Line #17739 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=231,240) /  0.1561690152531D-07, 0.5943349620372D+01, 0.6272439236156D+01,  0.1558591045463D-07, 0.7040653478980D+00, 0.6293712464735D+01,  0.1737356469576D-07, 0.4487064760345D+01, 0.1765478049437D+02,  0.1434755619991D-07, 0.2993391570995D+01, 0.1102062672231D+00,  0.1482187806654D-07, 0.2278049198251D+01, 0.1052268489556D+01,  0.1424812827089D-07, 0.1682114725827D+01, 0.1311972100268D+02,  0.1380282448623D-07, 0.3262668602579D+01, 0.1017725758696D+02,  0.1811481244566D-07, 0.3187771221777D+01, 0.1887552587463D+02,  0.1504446185696D-07, 0.5650162308647D+01, 0.7626583626240D-01,  0.1740776154137D-07, 0.5487068607507D+01, 0.1965104848470D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=231,240)" is not supported. Skipping.
Line #17750 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=241,250) /  0.1374339536251D-07, 0.5745688172201D+01, 0.6016468784579D+01,  0.1761377477704D-07, 0.5748060203659D+01, 0.2593412433514D+02,  0.1535138225795D-07, 0.6226848505790D+01, 0.9411464614024D+01,  0.1788140543676D-07, 0.6189318878563D+01, 0.3301902111895D+02,  0.1375002807996D-07, 0.5371812884394D+01, 0.6327837846670D+00,  0.1242115758632D-07, 0.1471687569712D+01, 0.3894181736510D+01,  0.1450977333938D-07, 0.4143836662127D+01, 0.1277945078067D+02,  0.1297579575023D-07, 0.9003477661957D+00, 0.6549682916313D+01,  0.1462667934821D-07, 0.5760505536428D+01, 0.1863592847156D+02,  0.1381774374799D-07, 0.1085471729463D+01, 0.2379164476796D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=241,250)" is not supported. Skipping.
Line #17761 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=251,260) /  0.1682333169307D-07, 0.5409870870133D+01, 0.1620077269078D+02,  0.1190812918837D-07, 0.1397205174601D+01, 0.1149965630200D+02,  0.1221434762106D-07, 0.9001804809095D+00, 0.1257326515556D+02,  0.1549934644860D-07, 0.4262528275544D+01, 0.1820933031200D+02,  0.1252138953050D-07, 0.1411642012027D+01, 0.6993008899458D+01,  0.1237078905387D-07, 0.2844472403615D+01, 0.2435678079171D+02,  0.1446953389615D-07, 0.5295835522223D+01, 0.3813291813120D-01,  0.1388446457170D-07, 0.4969428135497D+01, 0.2458316379602D+00,  0.1019339179228D-07, 0.2491369561806D+01, 0.6112403035119D+01,  0.1258880815343D-07, 0.4679426248976D+01, 0.5429879531333D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=251,260)" is not supported. Skipping.
Line #17772 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=261,270) /  0.1297768238261D-07, 0.1074509953328D+01, 0.1249137003520D+02,  0.9913505718094D-08, 0.4735097918224D+01, 0.6247047890016D+01,  0.9830453155969D-08, 0.4158649187338D+01, 0.6453748665772D+01,  0.1192615865309D-07, 0.3438208613699D+01, 0.6290122169689D+01,  0.9835874798277D-08, 0.1913300781229D+01, 0.6319103810876D+01,  0.9639087569277D-08, 0.9487683644125D+00, 0.8273820945392D+01,  0.1175716107001D-07, 0.3228141664287D+01, 0.6276029531202D+01,  0.1018926508678D-07, 0.2216607854300D+01, 0.1254537627298D+02,  0.9500087869225D-08, 0.2625116459733D+01, 0.1256517118505D+02,  0.9664192916575D-08, 0.5860562449214D+01, 0.6259197520765D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=261,270)" is not supported. Skipping.
Line #17783 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=271,280) /  0.9612858712203D-08, 0.7885682917381D+00, 0.6306954180126D+01,  0.1117645675413D-07, 0.3932148831189D+01, 0.1779695906178D+02,  0.1158864052160D-07, 0.9995605521691D+00, 0.1778273215245D+02,  0.9021043467028D-08, 0.5263769742673D+01, 0.6172869583223D+01,  0.8836134773563D-08, 0.1496843220365D+01, 0.1692165728891D+01,  0.1045872200691D-07, 0.7009039517214D+00, 0.2204125344462D+00,  0.1211463487798D-07, 0.4041544938511D+01, 0.8257698122054D+02,  0.8541990804094D-08, 0.1447586692316D+01, 0.6393282117669D+01,  0.1038720703636D-07, 0.4594249718112D+00, 0.1550861511662D+02,  0.1126722351445D-07, 0.3925550579036D+01, 0.2061856251104D+00 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=271,280)" is not supported. Skipping.
Line #17794 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=281,290) /  0.8697373859631D-08, 0.4411341856037D+01, 0.9491756770005D+00,  0.8869380028441D-08, 0.2402659724813D+01, 0.3903911373650D+01,  0.9247014693258D-08, 0.1401579743423D+01, 0.6267823317922D+01,  0.9205062930950D-08, 0.5245978000814D+01, 0.6298328382969D+01,  0.8000745038049D-08, 0.3590803356945D+01, 0.2648454860559D+01,  0.9168973650819D-08, 0.2470150501679D+01, 0.1498544001348D+03,  0.1075444949238D-07, 0.1328606161230D+01, 0.3694923081589D+02,  0.7817298525817D-08, 0.6162256225998D+01, 0.4804209201333D+01,  0.9541469226356D-08, 0.3942568967039D+01, 0.1256713221673D+02,  0.9821910122027D-08, 0.2360246287233D+00, 0.1140367694411D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=281,290)" is not supported. Skipping.
Line #17805 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=291,300) /  0.9897822023777D-08, 0.4619805634280D+01, 0.2280573557157D+02,  0.7737289283765D-08, 0.3784727847451D+01, 0.7834121070590D+01,  0.9260204034710D-08, 0.2223352487601D+01, 0.2787043132925D+01,  0.7320252888486D-08, 0.1288694636874D+01, 0.6282655592598D+01,  0.7319785780946D-08, 0.5359869567774D+01, 0.6283496108294D+01,  0.7147219933778D-08, 0.5516616675856D+01, 0.1725663147538D+02,  0.7946502829878D-08, 0.2630459984567D+01, 0.1241073141809D+02,  0.9001711808932D-08, 0.2849815827227D+01, 0.6281591679874D+01,  0.8994041507257D-08, 0.3795244450750D+01, 0.6284560021018D+01,  0.8298582787358D-08, 0.5236413127363D+00, 0.1241658836951D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=291,300)" is not supported. Skipping.
Line #17816 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=301,310) /  0.8526596520710D-08, 0.4794605424426D+01, 0.1098419223922D+02,  0.8209822103197D-08, 0.1578752370328D+01, 0.1096996532989D+02,  0.6357049861094D-08, 0.5708926113761D+01, 0.1596186371003D+01,  0.7370473179049D-08, 0.3842402530241D+01, 0.4061219149443D+01,  0.7232154664726D-08, 0.3067548981535D+01, 0.1610006857377D+03,  0.6328765494903D-08, 0.1313930030069D+01, 0.1193336791622D+02,  0.8030064908595D-08, 0.3488500408886D+01, 0.8460828644453D+00,  0.6275464259232D-08, 0.1532061626198D+01, 0.8531963191132D+00,  0.7051897446325D-08, 0.3285859929993D+01, 0.5849364236221D+01,  0.6161593705428D-08, 0.1477341999464D+01, 0.5573142801433D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=301,310)" is not supported. Skipping.
Line #17827 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=311,320) /  0.7754683957278D-08, 0.1586118663096D+01, 0.8662240327241D+01,  0.5889928990701D-08, 0.1304887868803D+01, 0.1232342296471D+02,  0.5705756047075D-08, 0.4555333589350D+01, 0.1258692712880D+02,  0.5964178808332D-08, 0.3001762842062D+01, 0.5333900173445D+01,  0.6712446027467D-08, 0.4886780007595D+01, 0.1171295538178D+02,  0.5941809275464D-08, 0.4701509603824D+01, 0.9779108567966D+01,  0.5466993627395D-08, 0.4588357817278D+01, 0.1884211409667D+02,  0.6340512090980D-08, 0.1164543038893D+01, 0.5217580628120D+02,  0.6325505710045D-08, 0.3919171259645D+01, 0.1041998632314D+02,  0.6164789509685D-08, 0.2143828253542D+01, 0.6151533897323D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=311,320)" is not supported. Skipping.
Line #17838 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=321,330) /  0.5263330812430D-08, 0.6066564434241D+01, 0.1885275071096D+02,  0.5597087780221D-08, 0.2926316429472D+01, 0.4337116142245D+00,  0.5396556236817D-08, 0.3244303591505D+01, 0.6286362197481D+01,  0.5396615148223D-08, 0.3404304703662D+01, 0.6279789503410D+01,  0.7091832443341D-08, 0.8532377803192D+00, 0.4907302013889D+01,  0.6572352589782D-08, 0.4901966774419D+01, 0.1176433076753D+02,  0.5960236060795D-08, 0.1874672315797D+01, 0.1422690933580D-01,  0.5125480043511D-08, 0.3735726064334D+01, 0.1245594543367D+02,  0.5928241866410D-08, 0.4502033899935D+01, 0.6414617803568D+01,  0.5249600357424D-08, 0.4372334799878D+01, 0.1151388321134D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=321,330)" is not supported. Skipping.
Line #17849 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=331,340) /  0.6059171276087D-08, 0.2581617302908D+01, 0.6062663316000D+01,  0.5295235081662D-08, 0.2974811513158D+01, 0.3496032717521D+01,  0.5820561875933D-08, 0.1796073748244D+00, 0.2838593341516D+00,  0.4754696606440D-08, 0.1981998136973D+01, 0.3104930017775D+01,  0.6385053548955D-08, 0.2559174171605D+00, 0.6133512519065D+01,  0.6589828273941D-08, 0.2750967106776D+01, 0.4087944051283D+02,  0.5383376567189D-08, 0.6325947523578D+00, 0.2248384854122D+02,  0.5928941683538D-08, 0.1672304519067D+01, 0.1581959461667D+01,  0.4816060709794D-08, 0.3512566172575D+01, 0.9388005868221D+01,  0.6003381586512D-08, 0.5610932219189D+01, 0.5326786718777D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=331,340)" is not supported. Skipping.
Line #17860 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=341,350) /  0.5504225393105D-08, 0.4037501131256D+01, 0.6503488384892D+01,  0.5353772620129D-08, 0.6122774968240D+01, 0.1735668374386D+03,  0.5786253768544D-08, 0.5527984999515D+01, 0.1350651127443D+00,  0.5065706702002D-08, 0.9980765573624D+00, 0.1248988586463D+02,  0.5972838885276D-08, 0.6044489493203D+01, 0.2673594526851D+02,  0.5323585877961D-08, 0.3924265998147D+01, 0.4171425416666D+01,  0.5210772682858D-08, 0.6220111376901D+01, 0.2460261242967D+02,  0.4726549040535D-08, 0.3716043206862D+01, 0.7232251527446D+01,  0.6029425105059D-08, 0.8548704071116D+00, 0.3227113045244D+03,  0.4481542826513D-08, 0.1426925072829D+01, 0.5547199253223D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=341,350)" is not supported. Skipping.
Line #17871 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=351,360) /  0.5836024505068D-08, 0.7135651752625D-01, 0.7285056171570D+02,  0.4137046613272D-08, 0.5330767643283D+01, 0.1087398597200D+02,  0.5171977473924D-08, 0.4494262335353D+00, 0.1884570439172D+02,  0.5694429833732D-08, 0.2952369582215D+01, 0.9723862754494D+02,  0.4009158925298D-08, 0.3500003416535D+01, 0.6244942932314D+01,  0.4784939596873D-08, 0.6196709413181D+01, 0.2929661536378D+02,  0.3983725022610D-08, 0.5103690031897D+01, 0.4274518229222D+01,  0.3870535232462D-08, 0.3187569587401D+01, 0.6321208768577D+01,  0.5140501213951D-08, 0.1668924357457D+01, 0.1232032006293D+02,  0.3849034819355D-08, 0.4445722510309D+01, 0.1726726808967D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=351,360)" is not supported. Skipping.
Line #17882 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=361,370) /  0.4002383075060D-08, 0.5226224152423D+01, 0.7018952447668D+01,  0.3890719543549D-08, 0.4371166550274D+01, 0.1491901785440D+02,  0.4887084607881D-08, 0.5973556689693D+01, 0.1478866649112D+01,  0.3739939287592D-08, 0.2089084714600D+01, 0.6922973089781D+01,  0.5031925918209D-08, 0.4658371936827D+01, 0.1715706182245D+02,  0.4387748764954D-08, 0.4825580552819D+01, 0.2331413144044D+03,  0.4147398098865D-08, 0.3739003524998D+01, 0.1376059875786D+02,  0.3719089993586D-08, 0.1148941386536D+01, 0.6297302759782D+01,  0.3934238461056D-08, 0.1559893008343D+01, 0.7872148766781D+01,  0.3672471375622D-08, 0.5516145383612D+01, 0.6268848941110D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=361,370)" is not supported. Skipping.
Line #17893 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=371,380) /  0.3768911277583D-08, 0.6116053700563D+01, 0.4157198507331D+01,  0.4033388417295D-08, 0.5076821746017D+01, 0.1567108171867D+02,  0.3764194617832D-08, 0.8164676232075D+00, 0.3185192151914D+01,  0.4840628226284D-08, 0.1360479453671D+01, 0.1252801878276D+02,  0.4949443923785D-08, 0.2725622229926D+01, 0.1617106187867D+03,  0.4117393089971D-08, 0.6054459628492D+00, 0.5642198095270D+01,  0.3925754020428D-08, 0.8570462135210D+00, 0.2139354194808D+02,  0.3630551757923D-08, 0.3552067338279D+01, 0.6294805223347D+01,  0.3627274802357D-08, 0.3096565085313D+01, 0.6271346477544D+01,  0.3806143885093D-08, 0.6367751709777D+00, 0.1725304118033D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=371,380)" is not supported. Skipping.
Line #17904 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=381,390) /  0.4433254641565D-08, 0.4848461503937D+01, 0.7445550607224D+01,  0.3712319846576D-08, 0.1331950643655D+01, 0.4194847048887D+00,  0.3849847534783D-08, 0.4958368297746D+00, 0.9562891316684D+00,  0.3483955430165D-08, 0.2237215515707D+01, 0.1161697602389D+02,  0.3961912730982D-08, 0.3332402188575D+01, 0.2277943724828D+02,  0.3419978244481D-08, 0.5785600576016D+01, 0.1362553364512D+02,  0.3329417758177D-08, 0.9812676559709D-01, 0.1685848245639D+02,  0.4207206893193D-08, 0.9494780468236D+00, 0.2986433403208D+02,  0.3268548976410D-08, 0.1739332095686D+00, 0.5749861718712D+01,  0.3321880082685D-08, 0.1423354800666D+01, 0.6279143387820D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=381,390)" is not supported. Skipping.
Line #17915 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=391,400) /  0.4503173010852D-08, 0.2314972675293D+00, 0.1385561574497D+01,  0.4316599090954D-08, 0.1012646782616D+00, 0.4176041334900D+01,  0.3283493323850D-08, 0.5233306881265D+01, 0.6287008313071D+01,  0.3164033542343D-08, 0.4005597257511D+01, 0.2099539292909D+02,  0.4159720956725D-08, 0.5365676242020D+01, 0.5905702259363D+01,  0.3565176892217D-08, 0.4284440620612D+01, 0.3932462625300D-02,  0.3514440950221D-08, 0.4270562636575D+01, 0.7335344340001D+01,  0.3540596871909D-08, 0.5953553201060D+01, 0.1234573916645D+02,  0.2960769905118D-08, 0.1115180417718D+01, 0.2670964694522D+02,  0.2962213739684D-08, 0.3863811918186D+01, 0.6408777551755D+00 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=391,400)" is not supported. Skipping.
Line #17926 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=401,410) /  0.3883556700251D-08, 0.1268617928302D+01, 0.6660449441528D+01,  0.2919225516346D-08, 0.4908605223265D+01, 0.1375773836557D+01,  0.3115158863370D-08, 0.3744519976885D+01, 0.3802769619140D-01,  0.4099438144212D-08, 0.4173244670532D+01, 0.4480965020977D+02,  0.2899531858964D-08, 0.5910601428850D+01, 0.2059724391010D+02,  0.3289733429855D-08, 0.2488050078239D+01, 0.1081813534213D+02,  0.3933075612875D-08, 0.1122363652883D+01, 0.3773735910827D+00,  0.3021403764467D-08, 0.4951973724904D+01, 0.2982630633589D+02,  0.2798598949757D-08, 0.5117057845513D+01, 0.1937891852345D+02,  0.3397421302707D-08, 0.6104159180476D+01, 0.6923953605621D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=401,410)" is not supported. Skipping.
Line #17937 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=411,420) /  0.3720398002179D-08, 0.1184933429829D+01, 0.3066615496545D+02,  0.3598484186267D-08, 0.3505282086105D+01, 0.6147450479709D+01,  0.3694594027310D-08, 0.2286651088141D+01, 0.2636725487657D+01,  0.2680444152969D-08, 0.1871816775482D+00, 0.6816289982179D+01,  0.3497574865641D-08, 0.3143251755431D+01, 0.6418701221183D+01,  0.3130274129494D-08, 0.2462167316018D+01, 0.1235996607578D+02,  0.3241119069551D-08, 0.4256374004686D+01, 0.1652265972112D+02,  0.2601960842061D-08, 0.4970362941425D+01, 0.1045450126711D+02,  0.2690601527504D-08, 0.2372657824898D+01, 0.3163918923335D+00,  0.2908688152664D-08, 0.4232652627721D+01, 0.2828699048865D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=411,420)" is not supported. Skipping.
Line #17948 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=421,430) /  0.3120456131875D-08, 0.3925747001137D+00, 0.2195415756911D+02,  0.3148855423384D-08, 0.3093478330445D+01, 0.1172006883645D+02,  0.3051044261017D-08, 0.5560948248212D+01, 0.6055599646783D+01,  0.2826006876660D-08, 0.5072790310072D+01, 0.5120601093667D+01,  0.3100034191711D-08, 0.4998530231096D+01, 0.1799603123222D+02,  0.2398771640101D-08, 0.2561739802176D+01, 0.6255674361143D+01,  0.2384002842728D-08, 0.4087420284111D+01, 0.6310477339748D+01,  0.2842146517568D-08, 0.2515048217955D+01, 0.5469525544182D+01,  0.2847674371340D-08, 0.5235326497443D+01, 0.1034429499989D+02,  0.2903722140764D-08, 0.1088200795797D+01, 0.6510552054109D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=421,430)" is not supported. Skipping.
Line #17959 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=431,440) /  0.3187610710605D-08, 0.4710624424816D+01, 0.1693792562116D+03,  0.3048869992813D-08, 0.2857975896445D+00, 0.8390110365991D+01,  0.2860216950984D-08, 0.2241619020815D+01, 0.2243449970715D+00,  0.2701117683113D-08, 0.6651573305272D-01, 0.6129297044991D+01,  0.2509891590152D-08, 0.1285135324585D+01, 0.1044027435778D+02,  0.2623200252223D-08, 0.2981229834530D+00, 0.6436854655901D+01,  0.2622541669202D-08, 0.6122470726189D+01, 0.9380959548977D+01,  0.2818435667099D-08, 0.4251087148947D+01, 0.5934151399930D+01,  0.2365196797465D-08, 0.3465070460790D+01, 0.2470570524223D+02,  0.2358704646143D-08, 0.5791603815350D+01, 0.8671969964381D+01 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=431,440)" is not supported. Skipping.
Line #17970 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=441,450) /  0.2388299481390D-08, 0.4142483772941D+01, 0.7096626156709D+01,  0.1996041217224D-08, 0.2101901889496D+01, 0.1727188400790D+02,  0.2687593060336D-08, 0.1526689456959D+01, 0.7075506709219D+02,  0.2618913670810D-08, 0.2397684236095D+01, 0.6632000300961D+01,  0.2571523050364D-08, 0.5751929456787D+00, 0.6206810014183D+01,  0.2582135006946D-08, 0.5595464352926D+01, 0.4873985990671D+02,  0.2372530190361D-08, 0.5092689490655D+01, 0.1590676413561D+02,  0.2357178484712D-08, 0.4444363527851D+01, 0.3097883698531D+01,  0.2451590394723D-08, 0.3108251687661D+01, 0.6612329252343D+00,  0.2370045949608D-08, 0.2608133861079D+01, 0.3459636466239D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=441,450)" is not supported. Skipping.
Line #17981 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=451,460) /  0.2268997267358D-08, 0.3639717753384D+01, 0.2844914056730D-01,  0.1731432137906D-08, 0.1741898445707D+00, 0.2019909489111D+02,  0.1629869741622D-08, 0.3902225646724D+01, 0.3035599730800D+02,  0.2206215801974D-08, 0.4971131250731D+01, 0.6281667977667D+01,  0.2205469554680D-08, 0.1677462357110D+01, 0.6284483723224D+01,  0.2148792362509D-08, 0.4236259604006D+01, 0.1980482729015D+02,  0.1873733657847D-08, 0.5926814998687D+01, 0.2876692439167D+02,  0.2026573758959D-08, 0.4349643351962D+01, 0.2449240616245D+02,  0.1807770325110D-08, 0.5700940482701D+01, 0.2045286941806D+02,  0.1881174408581D-08, 0.6601286363430D+00, 0.2358125818164D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=451,460)" is not supported. Skipping.
Line #17992 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=461,470) /  0.1368023671690D-08, 0.2211098592752D+01, 0.2473415438279D+02,  0.1720017916280D-08, 0.4942488551129D+01, 0.1679593901136D+03,  0.1702427665131D-08, 0.1452233856386D+01, 0.3338575901272D+03,  0.1414032510054D-08, 0.5525357721439D+01, 0.1624205518357D+03,  0.1652626045364D-08, 0.4108794283624D+01, 0.8956999012000D+02,  0.1642957769686D-08, 0.7344335209984D+00, 0.5267006960365D+02,  0.1614952403624D-08, 0.3541213951363D+01, 0.3332657872986D+02,  0.1535988291188D-08, 0.4031094072151D+01, 0.3852657435933D+02,  0.1593193738177D-08, 0.4185136203609D+01, 0.2282781046519D+03,  0.1074569126382D-08, 0.1720485636868D+01, 0.8397383534231D+02 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=461,470)" is not supported. Skipping.
Line #18003 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=471,480) /  0.1074408214509D-08, 0.2758613420318D+01, 0.8401985929482D+02,  0.9700199670465D-09, 0.4216686842097D+01, 0.7826370942180D+02,  0.1258433517061D-08, 0.2575068876639D+00, 0.3115650189215D+03,  0.1240303229539D-08, 0.4800844956756D+00, 0.1784300471910D+03,  0.9018345948127D-09, 0.3896756361552D+00, 0.5886454391678D+02,  0.1135301432805D-08, 0.3700805023550D+00, 0.7842370451713D+02,  0.9215887951370D-09, 0.4364579276638D+01, 0.1014262087719D+03,  0.1055401054147D-08, 0.2156564222111D+01, 0.5660027930059D+02,  0.1008725979831D-08, 0.5454015785234D+01, 0.4245678405627D+02,  0.7217398104321D-09, 0.1597772562175D+01, 0.2457074661053D+03 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=471,480)" is not supported. Skipping.
Line #18014 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=481,490) /  0.6912033134447D-09, 0.5824090621461D+01, 0.1679936946371D+03,  0.6833881523549D-09, 0.3578778482835D+01, 0.6053048899753D+02,  0.4887304205142D-09, 0.3724362812423D+01, 0.9656299901946D+02,  0.5173709754788D-09, 0.5422427507933D+01, 0.2442876000072D+03,  0.4671353097145D-09, 0.2396106924439D+01, 0.1435713242844D+03,  0.5652608439480D-09, 0.2804028838685D+01, 0.8365903305582D+02,  0.5604061331253D-09, 0.1638816006247D+01, 0.8433466158131D+02,  0.4712723365400D-09, 0.8979003224474D+00, 0.3164282286739D+03,  0.4909967465112D-09, 0.3210426725516D+01, 0.4059982187939D+03,  0.4771358267658D-09, 0.5308027211629D+01, 0.1805255418145D+03 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=481,490)" is not supported. Skipping.
Line #18025 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=491,500) /  0.3943451445989D-09, 0.2195145341074D+01, 0.2568537517081D+03,  0.3952109120244D-09, 0.5081189491586D+01, 0.2449975330562D+03,  0.3788134594789D-09, 0.4345171264441D+01, 0.1568131045107D+03,  0.3738330190479D-09, 0.2613062847997D+01, 0.3948519331910D+03,  0.3099866678136D-09, 0.2846760817689D+01, 0.1547176098872D+03,  0.2002962716768D-09, 0.4921360989412D+01, 0.2268582385539D+03,  0.2198291338754D-09, 0.1130360117454D+00, 0.1658638954901D+03,  0.1491958330784D-09, 0.4228195232278D+01, 0.2219950288015D+03,  0.1475384076173D-09, 0.3005721811604D+00, 0.3052819430710D+03,  0.1661626624624D-09, 0.7830125621203D+00, 0.2526661704812D+03 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=491,500)" is not supported. Skipping.
Line #18029 in sofapy.f:"      DATA ((E0(I,J,1),I=1,3),J=501,NE0X) /  0.9015823460025D-10, 0.3807792942715D+01, 0.4171445043968D+03 /"
	analyzeline: implied-DO list "((e0(i,j,1),i=1,3),j=501,ne0x)" is not supported. Skipping.
Line #18040 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J=  1, 10) /  0.1234046326004D-05, 0.0000000000000D+00, 0.0000000000000D+00,  0.5150068824701D-06, 0.6002664557501D+01, 0.1256615170089D+02,  0.1290743923245D-07, 0.5959437664199D+01, 0.1884922755134D+02,  0.1068615564952D-07, 0.2015529654209D+01, 0.6283075850446D+01,  0.2079619142538D-08, 0.1732960531432D+01, 0.6279552690824D+01,  0.2078009243969D-08, 0.4915604476996D+01, 0.6286599010068D+01,  0.6206330058856D-09, 0.3616457953824D+00, 0.4705732307012D+01,  0.5989335313746D-09, 0.3802607304474D+01, 0.6256777527156D+01,  0.5958495663840D-09, 0.2845866560031D+01, 0.6309374173736D+01,  0.4866923261539D-09, 0.5213203771824D+01, 0.7755226100720D+00 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18051 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 11, 20) /  0.4267785823142D-09, 0.4368189727818D+00, 0.1059381944224D+01,  0.4610675141648D-09, 0.1837249181372D-01, 0.7860419393880D+01,  0.3626989993973D-09, 0.2161590545326D+01, 0.5753384878334D+01,  0.3563071194389D-09, 0.1452631954746D+01, 0.5884926831456D+01,  0.3557015642807D-09, 0.4470593393054D+01, 0.6812766822558D+01,  0.3210412089122D-09, 0.5195926078314D+01, 0.6681224869435D+01,  0.2875473577986D-09, 0.5916256610193D+01, 0.2513230340178D+02,  0.2842913681629D-09, 0.1149902426047D+01, 0.6127655567643D+01,  0.2751248215916D-09, 0.5502088574662D+01, 0.6438496133249D+01,  0.2481432881127D-09, 0.2921989846637D+01, 0.5486777812467D+01 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #18062 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 21, 30) /  0.2059885976560D-09, 0.3718070376585D+01, 0.7079373888424D+01,  0.2015522342591D-09, 0.5979395259740D+01, 0.6290189305114D+01,  0.1995364084253D-09, 0.6772087985494D+00, 0.6275962395778D+01,  0.1957436436943D-09, 0.2899210654665D+01, 0.5507553240374D+01,  0.1651609818948D-09, 0.6228206482192D+01, 0.1150676975667D+02,  0.1822980550699D-09, 0.1469348746179D+01, 0.1179062909082D+02,  0.1675223159760D-09, 0.3813910555688D+01, 0.7058598460518D+01,  0.1706491764745D-09, 0.3004380506684D+00, 0.7113454667900D-02,  0.1392952362615D-09, 0.1440393973406D+01, 0.7962980379786D+00,  0.1209868266342D-09, 0.4150425791727D+01, 0.4694002934110D+01 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #18073 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 31, 40) /  0.1009827202611D-09, 0.3290040429843D+01, 0.3738761453707D+01,  0.1047261388602D-09, 0.4229590090227D+01, 0.6282095334605D+01,  0.1047006652004D-09, 0.2418967680575D+01, 0.6284056366286D+01,  0.9609993143095D-10, 0.4627943659201D+01, 0.6069776770667D+01,  0.9590900593873D-10, 0.1894393939924D+01, 0.4136910472696D+01,  0.9146249188071D-10, 0.2010647519562D+01, 0.6496374930224D+01,  0.8545274480290D-10, 0.5529846956226D-01, 0.1194447056968D+01,  0.8224377881194D-10, 0.1254304102174D+01, 0.1589072916335D+01,  0.6183529510410D-10, 0.3360862168815D+01, 0.8827390247185D+01,  0.6259255147141D-10, 0.4755628243179D+01, 0.8429241228195D+01 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #18084 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 41, 50) /  0.5539291694151D-10, 0.5371746955142D+01, 0.4933208510675D+01,  0.7328259466314D-10, 0.4927699613906D+00, 0.4535059491685D+01,  0.6017835843560D-10, 0.5776682001734D-01, 0.1255903824622D+02,  0.7079827775243D-10, 0.4395059432251D+01, 0.5088628793478D+01,  0.5170358878213D-10, 0.5154062619954D+01, 0.1176985366291D+02,  0.4872301838682D-10, 0.6289611648973D+00, 0.6040347114260D+01,  0.5249869411058D-10, 0.5617272046949D+01, 0.3154687086868D+01,  0.4716172354411D-10, 0.3965901800877D+01, 0.5331357529664D+01,  0.4871214940964D-10, 0.4627507050093D+01, 0.1256967486051D+02,  0.4598076850751D-10, 0.6023631226459D+01, 0.6525804586632D+01 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #18095 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 51, 60) /  0.4562196089485D-10, 0.4138562084068D+01, 0.3930209696940D+01,  0.4325493872224D-10, 0.1330845906564D+01, 0.7632943190217D+01,  0.5673781176748D-10, 0.2558752615657D+01, 0.5729506548653D+01,  0.3961436642503D-10, 0.2728071734630D+01, 0.7234794171227D+01,  0.5101868209058D-10, 0.4113444965144D+01, 0.6836645152238D+01,  0.5257043167676D-10, 0.6195089830590D+01, 0.8031092209206D+01,  0.5076613989393D-10, 0.2305124132918D+01, 0.7477522907414D+01,  0.3342169352778D-10, 0.5415998155071D+01, 0.1097707878456D+02,  0.3545881983591D-10, 0.3727160564574D+01, 0.4164311961999D+01,  0.3364063738599D-10, 0.2901121049204D+00, 0.1137170464392D+02 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #18106 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 61, 70) /  0.3357039670776D-10, 0.1652229354331D+01, 0.5223693906222D+01,  0.4307412268687D-10, 0.4938909587445D+01, 0.1592596075957D+01,  0.3405769115435D-10, 0.2408890766511D+01, 0.3128388763578D+01,  0.3001926198480D-10, 0.4862239006386D+01, 0.1748016358760D+01,  0.2778264787325D-10, 0.5241168661353D+01, 0.7342457794669D+01,  0.2676159480666D-10, 0.3423593942199D+01, 0.2146165377750D+01,  0.2954273399939D-10, 0.1881721265406D+01, 0.5368044267797D+00,  0.3309362888795D-10, 0.1931525677349D+01, 0.8018209333619D+00,  0.2810283608438D-10, 0.2414659495050D+01, 0.5225775174439D+00,  0.3378045637764D-10, 0.4238019163430D+01, 0.1554202828031D+00 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #18118 in sofapy.f:"      DATA ((E1(I,J,1),I=1,3),J= 71,NE1X) /  0.2558134979840D-10, 0.1828225235805D+01, 0.5230807360890D+01,  0.2273755578447D-10, 0.5858184283998D+01, 0.7084896783808D+01,  0.2294176037690D-10, 0.4514589779057D+01, 0.1726015463500D+02,  0.2533506099435D-10, 0.2355717851551D+01, 0.5216580451554D+01,  0.2716685375812D-10, 0.2221003625100D+01, 0.8635942003952D+01,  0.2419043435198D-10, 0.5955704951635D+01, 0.4690479774488D+01,  0.2521232544812D-10, 0.1395676848521D+01, 0.5481254917084D+01,  0.2630195021491D-10, 0.5727468918743D+01, 0.2629832328990D-01,  0.2548395840944D-10, 0.2628351859400D-03, 0.1349867339771D+01 /"
	analyzeline: implied-DO list "((e1(i,j,1),i=1,3),j= 71,ne1x)" is not supported. Skipping.
Line #18126 in sofapy.f:"      DATA ((E2(I,J,1),I=1,3),J=  1,NE2X) / -0.4143818297913D-10, 0.0000000000000D+00, 0.0000000000000D+00,  0.2171497694435D-10, 0.4398225628264D+01, 0.1256615170089D+02,  0.9845398442516D-11, 0.2079720838384D+00, 0.6283075850446D+01,  0.9256833552682D-12, 0.4191264694361D+01, 0.1884922755134D+02,  0.1022049384115D-12, 0.5381133195658D+01, 0.8399684731857D+02 /"
	analyzeline: implied-DO list "((e2(i,j,1),i=1,3),j=  1,ne2x)" is not supported. Skipping.
Line #18137 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=  1, 10) /  0.9998921098898D+00, 0.1826583913846D+00, 0.6283075850446D+01, -0.2442700893735D-01, 0.0000000000000D+00, 0.0000000000000D+00,  0.8352929742915D-02, 0.1395277998680D+00, 0.1256615170089D+02,  0.1046697300177D-03, 0.9641423109763D-01, 0.1884922755134D+02,  0.3110841876663D-04, 0.5381140401712D+01, 0.8399684731857D+02,  0.2570269094593D-04, 0.5301016407128D+01, 0.5296909721118D+00,  0.2147389623610D-04, 0.2662510869850D+01, 0.1577343543434D+01,  0.1680344384050D-04, 0.5207904119704D+01, 0.6279552690824D+01,  0.1679117312193D-04, 0.4582187486968D+01, 0.6286599010068D+01,  0.1440512068440D-04, 0.1900688517726D+01, 0.2352866153506D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18148 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 11, 20) /  0.1135139664999D-04, 0.5273108538556D+01, 0.5223693906222D+01,  0.9345482571018D-05, 0.4503047687738D+01, 0.1203646072878D+02,  0.9007418719568D-05, 0.1605621059637D+01, 0.1021328554739D+02,  0.5671536712314D-05, 0.5812849070861D+00, 0.1059381944224D+01,  0.7451401861666D-05, 0.2807346794836D+01, 0.3981490189893D+00,  0.6393470057114D-05, 0.6029224133855D+01, 0.5753384878334D+01,  0.6814275881697D-05, 0.6472990145974D+00, 0.4705732307012D+01,  0.6113705628887D-05, 0.3813843419700D+01, 0.6812766822558D+01,  0.4503851367273D-05, 0.4527804370996D+01, 0.5884926831456D+01,  0.4522249141926D-05, 0.5991783029224D+01, 0.6256777527156D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #18159 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 21, 30) /  0.4501794307018D-05, 0.3798703844397D+01, 0.6309374173736D+01,  0.5514927480180D-05, 0.3961257833388D+01, 0.5507553240374D+01,  0.4062862799995D-05, 0.5256247296369D+01, 0.6681224869435D+01,  0.5414900429712D-05, 0.5499032014097D+01, 0.7755226100720D+00,  0.5463153987424D-05, 0.6173092454097D+01, 0.1414349524433D+02,  0.5071611859329D-05, 0.2870244247651D+01, 0.7860419393880D+01,  0.2195112094455D-05, 0.2952338617201D+01, 0.1150676975667D+02,  0.2279139233919D-05, 0.5951775132933D+01, 0.7058598460518D+01,  0.2278386100876D-05, 0.4845456398785D+01, 0.4694002934110D+01,  0.2559088003308D-05, 0.6945321117311D+00, 0.1216800268190D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #18170 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 31, 40) /  0.2561079286856D-05, 0.6167224608301D+01, 0.7099330490126D+00,  0.1792755796387D-05, 0.1400122509632D+01, 0.7962980379786D+00,  0.1818715656502D-05, 0.4703347611830D+01, 0.6283142985870D+01,  0.1818744924791D-05, 0.5086748900237D+01, 0.6283008715021D+01,  0.1554518791390D-05, 0.5331008042713D-01, 0.2513230340178D+02,  0.2063265737239D-05, 0.4283680484178D+01, 0.1179062909082D+02,  0.1497613520041D-05, 0.6074207826073D+01, 0.5486777812467D+01,  0.2000617940427D-05, 0.2501426281450D+01, 0.1778984560711D+02,  0.1289731195580D-05, 0.3646340599536D+01, 0.7079373888424D+01,  0.1282657998934D-05, 0.3232864804902D+01, 0.3738761453707D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #18181 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 41, 50) /  0.1528915968658D-05, 0.5581433416669D+01, 0.2132990797783D+00,  0.1187304098432D-05, 0.5453576453694D+01, 0.9437762937313D+01,  0.7842782928118D-06, 0.2823953922273D+00, 0.8827390247185D+01,  0.7352892280868D-06, 0.1124369580175D+01, 0.1589072916335D+01,  0.6570189360797D-06, 0.2089154042840D+01, 0.1176985366291D+02,  0.6324967590410D-06, 0.6704855581230D+00, 0.6262300422539D+01,  0.6298289872283D-06, 0.2836414855840D+01, 0.6303851278352D+01,  0.6476686465855D-06, 0.4852433866467D+00, 0.7113454667900D-02,  0.8587034651234D-06, 0.1453511005668D+01, 0.1672837615881D+03,  0.8068948788113D-06, 0.9224087798609D+00, 0.6069776770667D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #18192 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 51, 60) /  0.8353786011661D-06, 0.4631707184895D+01, 0.3340612434717D+01,  0.6009324532132D-06, 0.1829498827726D+01, 0.4136910472696D+01,  0.7558158559566D-06, 0.2588596800317D+01, 0.6496374930224D+01,  0.5809279504503D-06, 0.5516818853476D+00, 0.1097707878456D+02,  0.5374131950254D-06, 0.6275674734960D+01, 0.1194447056968D+01,  0.5711160507326D-06, 0.1091905956872D+01, 0.6282095334605D+01,  0.5710183170746D-06, 0.2415001635090D+01, 0.6284056366286D+01,  0.5144373590610D-06, 0.6020336443438D+01, 0.6290189305114D+01,  0.5103108927267D-06, 0.3775634564605D+01, 0.6275962395778D+01,  0.4960654697891D-06, 0.1073450946756D+01, 0.6127655567643D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #18203 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 61, 70) /  0.4786385689280D-06, 0.2431178012310D+01, 0.6438496133249D+01,  0.6109911263665D-06, 0.5343356157914D+01, 0.3154687086868D+01,  0.4839898944024D-06, 0.5830833594047D-01, 0.8018209333619D+00,  0.4734822623919D-06, 0.4536080134821D+01, 0.3128388763578D+01,  0.4834741473290D-06, 0.2585090489754D+00, 0.7084896783808D+01,  0.5134858581156D-06, 0.4213317172603D+01, 0.1235285262111D+02,  0.5064004264978D-06, 0.4814418806478D+00, 0.1185621865188D+02,  0.3753476772761D-06, 0.1599953399788D+01, 0.8429241228195D+01,  0.4935264014283D-06, 0.2157417556873D+01, 0.2544314396739D+01,  0.3950929600897D-06, 0.3359394184254D+01, 0.5481254917084D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #18214 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 71, 80) /  0.4895849789777D-06, 0.5165704376558D+01, 0.9225539266174D+01,  0.4215241688886D-06, 0.2065368800993D+01, 0.1726015463500D+02,  0.3796773731132D-06, 0.1468606346612D+01, 0.4265981595566D+00,  0.3114178142515D-06, 0.3615638079474D+01, 0.2146165377750D+01,  0.3260664220838D-06, 0.4417134922435D+01, 0.4164311961999D+01,  0.3976996123008D-06, 0.4700866883004D+01, 0.5856477690889D+01,  0.2801459672924D-06, 0.4538902060922D+01, 0.1256967486051D+02,  0.3638931868861D-06, 0.1334197991475D+01, 0.1807370494127D+02,  0.2487013269476D-06, 0.3749275558275D+01, 0.2629832328990D-01,  0.3034165481994D-06, 0.4236622030873D+00, 0.4535059491685D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #18225 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 81, 90) /  0.2676278825586D-06, 0.5970848007811D+01, 0.3930209696940D+01,  0.2764903818918D-06, 0.5194636754501D+01, 0.1256262854127D+02,  0.2485149930507D-06, 0.1002434207846D+01, 0.5088628793478D+01,  0.2199305540941D-06, 0.3066773098403D+01, 0.1255903824622D+02,  0.2571106500435D-06, 0.7588312459063D+00, 0.1336797263425D+02,  0.2049751817158D-06, 0.3444977434856D+01, 0.1137170464392D+02,  0.2599707296297D-06, 0.1873128542205D+01, 0.7143069561767D+02,  0.1785018072217D-06, 0.5015891306615D+01, 0.1748016358760D+01,  0.2324833891115D-06, 0.4618271239730D+01, 0.1831953657923D+02,  0.1709711119545D-06, 0.5300003455669D+01, 0.4933208510675D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #18236 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J= 91,100) /  0.2107159351716D-06, 0.2229819815115D+01, 0.7477522907414D+01,  0.1750333080295D-06, 0.6161485880008D+01, 0.1044738781244D+02,  0.2000598210339D-06, 0.2967357299999D+01, 0.8031092209206D+01,  0.1380920248681D-06, 0.3027007923917D+01, 0.8635942003952D+01,  0.1412460470299D-06, 0.6037597163798D+01, 0.2942463415728D+01,  0.1888459803001D-06, 0.8561476243374D+00, 0.1561374759853D+03,  0.1788370542585D-06, 0.4869736290209D+01, 0.1592596075957D+01,  0.1360893296167D-06, 0.3626411886436D+01, 0.1309584267300D+02,  0.1506846530160D-06, 0.1550975377427D+01, 0.1649636139783D+02,  0.1800913376176D-06, 0.2075826033190D+01, 0.1729818233119D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j= 91,100)" is not supported. Skipping.
Line #18247 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=101,110) /  0.1436261390649D-06, 0.6148876420255D+01, 0.2042657109477D+02,  0.1220227114151D-06, 0.4382583879906D+01, 0.7632943190217D+01,  0.1337883603592D-06, 0.2036644327361D+01, 0.1213955354133D+02,  0.1159326650738D-06, 0.3892276994687D+01, 0.5331357529664D+01,  0.1352853128569D-06, 0.1447950649744D+01, 0.1673046366289D+02,  0.1433408296083D-06, 0.4457854692961D+01, 0.7342457794669D+01,  0.1234701666518D-06, 0.1538818147151D+01, 0.6279485555400D+01,  0.1234027192007D-06, 0.1968523220760D+01, 0.6286666145492D+01,  0.1244024091797D-06, 0.5779803499985D+01, 0.1511046609763D+02,  0.1097934945516D-06, 0.6210975221388D+00, 0.1098880815746D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=101,110)" is not supported. Skipping.
Line #18258 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=111,120) /  0.1254611329856D-06, 0.2591963807998D+01, 0.1572083878776D+02,  0.1158247286784D-06, 0.2483612812670D+01, 0.5729506548653D+01,  0.9039078252960D-07, 0.3857554579796D+01, 0.9623688285163D+01,  0.9108024978836D-07, 0.5826368512984D+01, 0.7234794171227D+01,  0.8887068108436D-07, 0.3475694573987D+01, 0.6148010737701D+01,  0.8632374035438D-07, 0.3059070488983D-01, 0.6418140963190D+01,  0.7893186992967D-07, 0.1583194837728D+01, 0.2118763888447D+01,  0.8297650201172D-07, 0.8519770534637D+00, 0.1471231707864D+02,  0.1019759578988D-06, 0.1319598738732D+00, 0.1349867339771D+01,  0.1010037696236D-06, 0.9937860115618D+00, 0.6836645152238D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=111,120)" is not supported. Skipping.
Line #18269 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=121,130) /  0.1047727548266D-06, 0.1382138405399D+01, 0.5999216516294D+01,  0.7351993881086D-07, 0.3833397851735D+01, 0.6040347114260D+01,  0.9868771092341D-07, 0.2124913814390D+01, 0.6566935184597D+01,  0.7007321959390D-07, 0.5946305343763D+01, 0.6525804586632D+01,  0.6861411679709D-07, 0.4574654977089D+01, 0.7238675589263D+01,  0.7554519809614D-07, 0.5949232686844D+01, 0.1253985337760D+02,  0.9541880448335D-07, 0.3495242990564D+01, 0.2122839202813D+02,  0.7185606722155D-07, 0.4310113471661D+01, 0.6245048154254D+01,  0.7131360871710D-07, 0.5480309323650D+01, 0.6321103546637D+01,  0.6651142021039D-07, 0.5411097713654D+01, 0.5327476111629D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=121,130)" is not supported. Skipping.
Line #18280 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=131,140) /  0.8538618213667D-07, 0.1827849973951D+01, 0.1101510648075D+02,  0.8634954288044D-07, 0.5443584943349D+01, 0.5643178611111D+01,  0.7449415051484D-07, 0.2011535459060D+01, 0.5368044267797D+00,  0.7421047599169D-07, 0.3464562529249D+01, 0.2354323048545D+02,  0.6140694354424D-07, 0.5657556228815D+01, 0.1296430071988D+02,  0.6353525143033D-07, 0.3463816593821D+01, 0.1990745094947D+01,  0.6221964013447D-07, 0.1532259498697D+01, 0.9517183207817D+00,  0.5852480257244D-07, 0.1375396598875D+01, 0.9555997388169D+00,  0.6398637498911D-07, 0.2405645801972D+01, 0.2407292145756D+02,  0.7039744069878D-07, 0.5397541799027D+01, 0.5225775174439D+00 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=131,140)" is not supported. Skipping.
Line #18291 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=141,150) /  0.6977997694382D-07, 0.4762347105419D+01, 0.1097355562493D+02,  0.7460629558396D-07, 0.2711944692164D+01, 0.2200391463820D+02,  0.5376577536101D-07, 0.2352980430239D+01, 0.1431416805965D+02,  0.7530607893556D-07, 0.1943940180699D+01, 0.1842262939178D+02,  0.6822928971605D-07, 0.4337651846959D+01, 0.1554202828031D+00,  0.6220772380094D-07, 0.6716871369278D+00, 0.1845107853235D+02,  0.6586950799043D-07, 0.2229714460505D+01, 0.5216580451554D+01,  0.5873800565771D-07, 0.7627013920580D+00, 0.6398972393349D+00,  0.6264346929745D-07, 0.6202785478961D+00, 0.6277552955062D+01,  0.6257929115669D-07, 0.2886775596668D+01, 0.6288598745829D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=141,150)" is not supported. Skipping.
Line #18302 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=151,160) /  0.5343536033409D-07, 0.1977241012051D+01, 0.4690479774488D+01,  0.5587849781714D-07, 0.1922923484825D+01, 0.1551045220144D+01,  0.6905100845603D-07, 0.3570757164631D+01, 0.1030928125552D+00,  0.6178957066649D-07, 0.5197558947765D+01, 0.5230807360890D+01,  0.6187270224331D-07, 0.8193497368922D+00, 0.5650292065779D+01,  0.5385664291426D-07, 0.5406336665586D+01, 0.7771377146812D+02,  0.6329363917926D-07, 0.2837760654536D+01, 0.2608790314060D+02,  0.4546018761604D-07, 0.2933580297050D+01, 0.5535693017924D+00,  0.6196091049375D-07, 0.4157871494377D+01, 0.8467247584405D+02,  0.6159555108218D-07, 0.3211703561703D+01, 0.2394243902548D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=151,160)" is not supported. Skipping.
Line #18313 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=161,170) /  0.4995340539317D-07, 0.1459098102922D+01, 0.4732030630302D+01,  0.5457031243572D-07, 0.1430457676136D+01, 0.6179983037890D+01,  0.4863461418397D-07, 0.2196425916730D+01, 0.9027992316901D+02,  0.5342947626870D-07, 0.2086612890268D+01, 0.6386168663001D+01,  0.5674296648439D-07, 0.2760204966535D+01, 0.6915859635113D+01,  0.4745783120161D-07, 0.4245368971862D+01, 0.6282970628506D+01,  0.4745676961198D-07, 0.5544725787016D+01, 0.6283181072386D+01,  0.4049796869973D-07, 0.2213984363586D+01, 0.6254626709878D+01,  0.4248333596940D-07, 0.8075781952896D+00, 0.7875671926403D+01,  0.4027178070205D-07, 0.1293268540378D+01, 0.6311524991013D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=161,170)" is not supported. Skipping.
Line #18324 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=171,180) /  0.4066543943476D-07, 0.3986141175804D+01, 0.3634620989887D+01,  0.4858863787880D-07, 0.1276112738231D+01, 0.5760498333002D+01,  0.5277398263530D-07, 0.4916111741527D+01, 0.2515860172507D+02,  0.4105635656559D-07, 0.1725805864426D+01, 0.6709674010002D+01,  0.4376781925772D-07, 0.2243642442106D+01, 0.6805653367890D+01,  0.3235827894693D-07, 0.3614135118271D+01, 0.1066495398892D+01,  0.3073244740308D-07, 0.2460873393460D+01, 0.5863591145557D+01,  0.3088609271373D-07, 0.5678431771790D+01, 0.9917696840332D+01,  0.3393022279836D-07, 0.3814017477291D+01, 0.1391601904066D+02,  0.3038686508802D-07, 0.4660216229171D+01, 0.1256621883632D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=171,180)" is not supported. Skipping.
Line #18335 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=181,190) /  0.4019677752497D-07, 0.5906906243735D+01, 0.1334167431096D+02,  0.3288834998232D-07, 0.9536146445882D+00, 0.1620077269078D+02,  0.3889973794631D-07, 0.3942205097644D+01, 0.7478166569050D-01,  0.3050438987141D-07, 0.1624810271286D+01, 0.1805292951336D+02,  0.3601142564638D-07, 0.4030467142575D+01, 0.6208294184755D+01,  0.3689015557141D-07, 0.3648878818694D+01, 0.5966683958112D+01,  0.3563471893565D-07, 0.5749584017096D+01, 0.6357857516136D+01,  0.2776183170667D-07, 0.2630124187070D+01, 0.3523159621801D-02,  0.2922350530341D-07, 0.1790346403629D+01, 0.1272157198369D+02,  0.3511076917302D-07, 0.6142198301611D+01, 0.6599467742779D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=181,190)" is not supported. Skipping.
Line #18346 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=191,200) /  0.3619351007632D-07, 0.1432421386492D+01, 0.6019991944201D+01,  0.2561254711098D-07, 0.2302822475792D+01, 0.1259245002418D+02,  0.2626903942920D-07, 0.8660470994571D+00, 0.6702560555334D+01,  0.2550187397083D-07, 0.6069721995383D+01, 0.1057540660594D+02,  0.2535873526138D-07, 0.1079020331795D-01, 0.3141537925223D+02,  0.3519786153847D-07, 0.3809066902283D+01, 0.2505706758577D+03,  0.3424651492873D-07, 0.2075435114417D+01, 0.6546159756691D+01,  0.2372676630861D-07, 0.2057803120154D+01, 0.2388894113936D+01,  0.2710980779541D-07, 0.1510068488010D+01, 0.1202934727411D+02,  0.3038710889704D-07, 0.5043617528901D+01, 0.1256608456547D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=191,200)" is not supported. Skipping.
Line #18357 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=201,210) /  0.2220364130585D-07, 0.3694793218205D+01, 0.1336244973887D+02,  0.3025880825460D-07, 0.5450618999049D-01, 0.2908881142201D+02,  0.2784493486864D-07, 0.3381164084502D+01, 0.1494531617769D+02,  0.2294414142438D-07, 0.4382309025210D+01, 0.6076890225335D+01,  0.2012723294724D-07, 0.9142212256518D+00, 0.6262720680387D+01,  0.2036357831958D-07, 0.5676172293154D+01, 0.4701116388778D+01,  0.2003474823288D-07, 0.2592767977625D+01, 0.6303431020504D+01,  0.2207144900109D-07, 0.5404976271180D+01, 0.6489261475556D+01,  0.2481664905135D-07, 0.4373284587027D+01, 0.1204357418345D+02,  0.2674949182295D-07, 0.5859182188482D+01, 0.4590910121555D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=201,210)" is not supported. Skipping.
Line #18368 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=211,220) /  0.2450554720322D-07, 0.4555381557451D+01, 0.1495633313810D+00,  0.2601975986457D-07, 0.3933165584959D+01, 0.1965104848470D+02,  0.2199860022848D-07, 0.5227977189087D+01, 0.1351787002167D+02,  0.2448121172316D-07, 0.4858060353949D+01, 0.1162474756779D+01,  0.1876014864049D-07, 0.5690546553605D+01, 0.6279194432410D+01,  0.1874513219396D-07, 0.4099539297446D+01, 0.6286957268481D+01,  0.2156380842559D-07, 0.4382594769913D+00, 0.1813929450232D+02,  0.1981691240061D-07, 0.1829784152444D+01, 0.4686889479442D+01,  0.2329992648539D-07, 0.2836254278973D+01, 0.1002183730415D+02,  0.1765184135302D-07, 0.2803494925833D+01, 0.4292330755499D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=211,220)" is not supported. Skipping.
Line #18379 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=221,230) /  0.2436368366085D-07, 0.2836897959677D+01, 0.9514313292143D+02,  0.2164089203889D-07, 0.6127522446024D+01, 0.6037244212485D+01,  0.1847755034221D-07, 0.3683163635008D+01, 0.2427287361862D+00,  0.1674798769966D-07, 0.3316993867246D+00, 0.1311972100268D+02,  0.2222542124356D-07, 0.8294097805480D+00, 0.1266924451345D+02,  0.2071074505925D-07, 0.3659492220261D+01, 0.6528907488406D+01,  0.1608224471835D-07, 0.4774492067182D+01, 0.1352175143971D+02,  0.1857583439071D-07, 0.2873120597682D+01, 0.8662240327241D+01,  0.1793018836159D-07, 0.5282441177929D+00, 0.6819880277225D+01,  0.1575391221692D-07, 0.1320789654258D+01, 0.1102062672231D+00 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=221,230)" is not supported. Skipping.
Line #18390 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=231,240) /  0.1840132009557D-07, 0.1917110916256D+01, 0.6514761976723D+02,  0.1760917288281D-07, 0.2972635937132D+01, 0.5746271423666D+01,  0.1561779518516D-07, 0.4372569261981D+01, 0.6272439236156D+01,  0.1558687885205D-07, 0.5416424926425D+01, 0.6293712464735D+01,  0.1951359382579D-07, 0.3094448898752D+01, 0.2301353951334D+02,  0.1569144275614D-07, 0.2802103689808D+01, 0.1765478049437D+02,  0.1479130389462D-07, 0.2136435020467D+01, 0.2077542790660D-01,  0.1467828510764D-07, 0.7072627435674D+00, 0.1052268489556D+01,  0.1627627337440D-07, 0.3947607143237D+01, 0.6327837846670D+00,  0.1503498479758D-07, 0.4079248909190D+01, 0.7626583626240D-01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=231,240)" is not supported. Skipping.
Line #18401 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=241,250) /  0.1297967708237D-07, 0.6269637122840D+01, 0.1149965630200D+02,  0.1374416896634D-07, 0.4175657970702D+01, 0.6016468784579D+01,  0.1783812325219D-07, 0.1476540547560D+01, 0.3301902111895D+02,  0.1525884228756D-07, 0.4653477715241D+01, 0.9411464614024D+01,  0.1451067396763D-07, 0.2573001128225D+01, 0.1277945078067D+02,  0.1297713111950D-07, 0.5612799618771D+01, 0.6549682916313D+01,  0.1462784012820D-07, 0.4189661623870D+01, 0.1863592847156D+02,  0.1384185980007D-07, 0.2656915472196D+01, 0.2379164476796D+01,  0.1221497599801D-07, 0.5612515760138D+01, 0.1257326515556D+02,  0.1560574525896D-07, 0.4783414317919D+01, 0.1887552587463D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=241,250)" is not supported. Skipping.
Line #18412 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=251,260) /  0.1544598372036D-07, 0.2694431138063D+01, 0.1820933031200D+02,  0.1531678928696D-07, 0.4105103489666D+01, 0.2593412433514D+02,  0.1349321503795D-07, 0.3082437194015D+00, 0.5120601093667D+01,  0.1252030290917D-07, 0.6124072334087D+01, 0.6993008899458D+01,  0.1459243816687D-07, 0.3733103981697D+01, 0.3813291813120D-01,  0.1226103625262D-07, 0.1267127706817D+01, 0.2435678079171D+02,  0.1019449641504D-07, 0.4367790112269D+01, 0.1725663147538D+02,  0.1380789433607D-07, 0.3387201768700D+01, 0.2458316379602D+00,  0.1019453421658D-07, 0.9204143073737D+00, 0.6112403035119D+01,  0.1297929434405D-07, 0.5786874896426D+01, 0.1249137003520D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=251,260)" is not supported. Skipping.
Line #18423 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=261,270) /  0.9912677786097D-08, 0.3164232870746D+01, 0.6247047890016D+01,  0.9829386098599D-08, 0.2586762413351D+01, 0.6453748665772D+01,  0.1226807746104D-07, 0.6239068436607D+01, 0.5429879531333D+01,  0.1192691755997D-07, 0.1867380051424D+01, 0.6290122169689D+01,  0.9836499227081D-08, 0.3424716293727D+00, 0.6319103810876D+01,  0.9642862564285D-08, 0.5661372990657D+01, 0.8273820945392D+01,  0.1165184404862D-07, 0.5768367239093D+01, 0.1778273215245D+02,  0.1175794418818D-07, 0.1657351222943D+01, 0.6276029531202D+01,  0.1018948635601D-07, 0.6458292350865D+00, 0.1254537627298D+02,  0.9500383606676D-08, 0.1054306140741D+01, 0.1256517118505D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=261,270)" is not supported. Skipping.
Line #18434 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=271,280) /  0.1227512202906D-07, 0.2505278379114D+01, 0.2248384854122D+02,  0.9664792009993D-08, 0.4289737277000D+01, 0.6259197520765D+01,  0.9613285666331D-08, 0.5500597673141D+01, 0.6306954180126D+01,  0.1117906736211D-07, 0.2361405953468D+01, 0.1779695906178D+02,  0.9611378640782D-08, 0.2851310576269D+01, 0.2061856251104D+00,  0.8845354852370D-08, 0.6208777705343D+01, 0.1692165728891D+01,  0.1054046966600D-07, 0.5413091423934D+01, 0.2204125344462D+00,  0.1215539124483D-07, 0.5613969479755D+01, 0.8257698122054D+02,  0.9932460955209D-08, 0.1106124877015D+01, 0.1017725758696D+02,  0.8785804715043D-08, 0.2869224476477D+01, 0.9491756770005D+00 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=271,280)" is not supported. Skipping.
Line #18445 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=281,290) /  0.8538084097562D-08, 0.6159640899344D+01, 0.6393282117669D+01,  0.8648994369529D-08, 0.1374901198784D+01, 0.4804209201333D+01,  0.1039063219067D-07, 0.5171080641327D+01, 0.1550861511662D+02,  0.8867983926439D-08, 0.8317320304902D+00, 0.3903911373650D+01,  0.8327495955244D-08, 0.3605591969180D+01, 0.6172869583223D+01,  0.9243088356133D-08, 0.6114299196843D+01, 0.6267823317922D+01,  0.9205657357835D-08, 0.3675153683737D+01, 0.6298328382969D+01,  0.1033269714606D-07, 0.3313328813024D+01, 0.5573142801433D+01,  0.8001706275552D-08, 0.2019980960053D+01, 0.2648454860559D+01,  0.9171858254191D-08, 0.8992015524177D+00, 0.1498544001348D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=281,290)" is not supported. Skipping.
Line #18456 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=291,300) /  0.1075327150242D-07, 0.2898669963648D+01, 0.3694923081589D+02,  0.9884866689828D-08, 0.4946715904478D+01, 0.1140367694411D+02,  0.9541835576677D-08, 0.2371787888469D+01, 0.1256713221673D+02,  0.7739903376237D-08, 0.2213775190612D+01, 0.7834121070590D+01,  0.7311962684106D-08, 0.3429378787739D+01, 0.1192625446156D+02,  0.9724904869624D-08, 0.6195878564404D+01, 0.2280573557157D+02,  0.9251628983612D-08, 0.6511509527390D+00, 0.2787043132925D+01,  0.7320763787842D-08, 0.6001083639421D+01, 0.6282655592598D+01,  0.7320296650962D-08, 0.3789073265087D+01, 0.6283496108294D+01,  0.7947032271039D-08, 0.1059659582204D+01, 0.1241073141809D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=291,300)" is not supported. Skipping.
Line #18467 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=301,310) /  0.9005277053115D-08, 0.1280315624361D+01, 0.6281591679874D+01,  0.8995601652048D-08, 0.2224439106766D+01, 0.6284560021018D+01,  0.8288040568796D-08, 0.5234914433867D+01, 0.1241658836951D+02,  0.6359381347255D-08, 0.4137989441490D+01, 0.1596186371003D+01,  0.8699572228626D-08, 0.1758411009497D+01, 0.6133512519065D+01,  0.6456797542736D-08, 0.5919285089994D+01, 0.1685848245639D+02,  0.7424573475452D-08, 0.5414616938827D+01, 0.4061219149443D+01,  0.7235671196168D-08, 0.1496516557134D+01, 0.1610006857377D+03,  0.8104015182733D-08, 0.1919918242764D+01, 0.8460828644453D+00,  0.8098576535937D-08, 0.3819615855458D+01, 0.3894181736510D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=301,310)" is not supported. Skipping.
Line #18478 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=311,320) /  0.6275292346625D-08, 0.6244264115141D+01, 0.8531963191132D+00,  0.6052432989112D-08, 0.5037731872610D+00, 0.1567108171867D+02,  0.5705651535817D-08, 0.2984557271995D+01, 0.1258692712880D+02,  0.5789650115138D-08, 0.6087038140697D+01, 0.1193336791622D+02,  0.5512132153377D-08, 0.5855668994076D+01, 0.1232342296471D+02,  0.7388890819102D-08, 0.2443128574740D+01, 0.4907302013889D+01,  0.5467593991798D-08, 0.3017561234194D+01, 0.1884211409667D+02,  0.6388519802999D-08, 0.5887386712935D+01, 0.5217580628120D+02,  0.6106777149944D-08, 0.3483461059895D+00, 0.1422690933580D-01,  0.7383420275489D-08, 0.5417387056707D+01, 0.2358125818164D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=311,320)" is not supported. Skipping.
Line #18489 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=321,330) /  0.5505208141738D-08, 0.2848193644783D+01, 0.1151388321134D+02,  0.6310757462877D-08, 0.2349882520828D+01, 0.1041998632314D+02,  0.6166904929691D-08, 0.5728575944077D+00, 0.6151533897323D+01,  0.5263442042754D-08, 0.4495796125937D+01, 0.1885275071096D+02,  0.5591828082629D-08, 0.1355441967677D+01, 0.4337116142245D+00,  0.5397051680497D-08, 0.1673422864307D+01, 0.6286362197481D+01,  0.5396992745159D-08, 0.1833502206373D+01, 0.6279789503410D+01,  0.6572913000726D-08, 0.3331122065824D+01, 0.1176433076753D+02,  0.5123421866413D-08, 0.2165327142679D+01, 0.1245594543367D+02,  0.5930495725999D-08, 0.2931146089284D+01, 0.6414617803568D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=321,330)" is not supported. Skipping.
Line #18500 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=331,340) /  0.6431797403933D-08, 0.4134407994088D+01, 0.1350651127443D+00,  0.5003182207604D-08, 0.3805420303749D+01, 0.1096996532989D+02,  0.5587731032504D-08, 0.1082469260599D+01, 0.6062663316000D+01,  0.5935263407816D-08, 0.8384333678401D+00, 0.5326786718777D+01,  0.4756019827760D-08, 0.3552588749309D+01, 0.3104930017775D+01,  0.6599951172637D-08, 0.4320826409528D+01, 0.4087944051283D+02,  0.5902606868464D-08, 0.4811879454445D+01, 0.5849364236221D+01,  0.5921147809031D-08, 0.9942628922396D-01, 0.1581959461667D+01,  0.5505382581266D-08, 0.2466557607764D+01, 0.6503488384892D+01,  0.5353771071862D-08, 0.4551978748683D+01, 0.1735668374386D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=331,340)" is not supported. Skipping.
Line #18511 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=341,350) /  0.5063282210946D-08, 0.5710812312425D+01, 0.1248988586463D+02,  0.5926120403383D-08, 0.1333998428358D+01, 0.2673594526851D+02,  0.5211016176149D-08, 0.4649315360760D+01, 0.2460261242967D+02,  0.5347075084894D-08, 0.5512754081205D+01, 0.4171425416666D+01,  0.4872609773574D-08, 0.1308025299938D+01, 0.5333900173445D+01,  0.4727711321420D-08, 0.2144908368062D+01, 0.7232251527446D+01,  0.6029426018652D-08, 0.5567259412084D+01, 0.3227113045244D+03,  0.4321485284369D-08, 0.5230667156451D+01, 0.9388005868221D+01,  0.4476406760553D-08, 0.6134081115303D+01, 0.5547199253223D+01,  0.5835268277420D-08, 0.4783808492071D+01, 0.7285056171570D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=341,350)" is not supported. Skipping.
Line #18522 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=351,360) /  0.5172183602748D-08, 0.5161817911099D+01, 0.1884570439172D+02,  0.5693571465184D-08, 0.1381646203111D+01, 0.9723862754494D+02,  0.4060634965349D-08, 0.3876705259495D+00, 0.4274518229222D+01,  0.3967398770473D-08, 0.5029491776223D+01, 0.3496032717521D+01,  0.3943754005255D-08, 0.1923162955490D+01, 0.6244942932314D+01,  0.4781323427824D-08, 0.4633332586423D+01, 0.2929661536378D+02,  0.3871483781204D-08, 0.1616650009743D+01, 0.6321208768577D+01,  0.5141741733997D-08, 0.9817316704659D-01, 0.1232032006293D+02,  0.4002385978497D-08, 0.3656161212139D+01, 0.7018952447668D+01,  0.4901092604097D-08, 0.4404098713092D+01, 0.1478866649112D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=351,360)" is not supported. Skipping.
Line #18533 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=361,370) /  0.3740932630345D-08, 0.5181188732639D+00, 0.6922973089781D+01,  0.4387283718538D-08, 0.3254859566869D+01, 0.2331413144044D+03,  0.5019197802033D-08, 0.3086773224677D+01, 0.1715706182245D+02,  0.3834931695175D-08, 0.2797882673542D+01, 0.1491901785440D+02,  0.3760413942497D-08, 0.2892676280217D+01, 0.1726726808967D+02,  0.3719717204628D-08, 0.5861046025739D+01, 0.6297302759782D+01,  0.4145623530149D-08, 0.2168239627033D+01, 0.1376059875786D+02,  0.3932788425380D-08, 0.6271811124181D+01, 0.7872148766781D+01,  0.3686377476857D-08, 0.3936853151404D+01, 0.6268848941110D+01,  0.3779077950339D-08, 0.1404148734043D+01, 0.4157198507331D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=361,370)" is not supported. Skipping.
Line #18544 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=371,380) /  0.4091334550598D-08, 0.2452436180854D+01, 0.9779108567966D+01,  0.3926694536146D-08, 0.6102292739040D+01, 0.1098419223922D+02,  0.4841000253289D-08, 0.6072760457276D+01, 0.1252801878276D+02,  0.4949340130240D-08, 0.1154832815171D+01, 0.1617106187867D+03,  0.3761557737360D-08, 0.5527545321897D+01, 0.3185192151914D+01,  0.3647396268188D-08, 0.1525035688629D+01, 0.6271346477544D+01,  0.3932405074189D-08, 0.5570681040569D+01, 0.2139354194808D+02,  0.3631322501141D-08, 0.1981240601160D+01, 0.6294805223347D+01,  0.4130007425139D-08, 0.2050060880201D+01, 0.2195415756911D+02,  0.4433905965176D-08, 0.3277477970321D+01, 0.7445550607224D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=371,380)" is not supported. Skipping.
Line #18555 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=381,390) /  0.3851814176947D-08, 0.5210690074886D+01, 0.9562891316684D+00,  0.3485807052785D-08, 0.6653274904611D+00, 0.1161697602389D+02,  0.3979772816991D-08, 0.1767941436148D+01, 0.2277943724828D+02,  0.3402607460500D-08, 0.3421746306465D+01, 0.1087398597200D+02,  0.4049993000926D-08, 0.1127144787547D+01, 0.3163918923335D+00,  0.3420511182382D-08, 0.4214794779161D+01, 0.1362553364512D+02,  0.3640772365012D-08, 0.5324905497687D+01, 0.1725304118033D+02,  0.3323037987501D-08, 0.6135761838271D+01, 0.6279143387820D+01,  0.4503141663637D-08, 0.1802305450666D+01, 0.1385561574497D+01,  0.4314560055588D-08, 0.4812299731574D+01, 0.4176041334900D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=381,390)" is not supported. Skipping.
Line #18566 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=391,400) /  0.3294226949110D-08, 0.3657547059723D+01, 0.6287008313071D+01,  0.3215657197281D-08, 0.4866676894425D+01, 0.5749861718712D+01,  0.4129362656266D-08, 0.3809342558906D+01, 0.5905702259363D+01,  0.3137762976388D-08, 0.2494635174443D+01, 0.2099539292909D+02,  0.3514010952384D-08, 0.2699961831678D+01, 0.7335344340001D+01,  0.3327607571530D-08, 0.3318457714816D+01, 0.5436992986000D+01,  0.3541066946675D-08, 0.4382703582466D+01, 0.1234573916645D+02,  0.3216179847052D-08, 0.5271066317054D+01, 0.3802769619140D-01,  0.2959045059570D-08, 0.5819591585302D+01, 0.2670964694522D+02,  0.3884040326665D-08, 0.5980934960428D+01, 0.6660449441528D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=391,400)" is not supported. Skipping.
Line #18577 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=401,410) /  0.2922027539886D-08, 0.3337290282483D+01, 0.1375773836557D+01,  0.4110846382042D-08, 0.5742978187327D+01, 0.4480965020977D+02,  0.2934508411032D-08, 0.2278075804200D+01, 0.6408777551755D+00,  0.3966896193000D-08, 0.5835747858477D+01, 0.3773735910827D+00,  0.3286695827610D-08, 0.5838898193902D+01, 0.3932462625300D-02,  0.3720643094196D-08, 0.1122212337858D+01, 0.1646033343740D+02,  0.3285508906174D-08, 0.9182250996416D+00, 0.1081813534213D+02,  0.3753880575973D-08, 0.5174761973266D+01, 0.5642198095270D+01,  0.3022129385587D-08, 0.3381611020639D+01, 0.2982630633589D+02,  0.2798569205621D-08, 0.3546193723922D+01, 0.1937891852345D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=401,410)" is not supported. Skipping.
Line #18588 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=411,420) /  0.3397872070505D-08, 0.4533203197934D+01, 0.6923953605621D+01,  0.3708099772977D-08, 0.2756168198616D+01, 0.3066615496545D+02,  0.3599283541510D-08, 0.1934395469918D+01, 0.6147450479709D+01,  0.3688702753059D-08, 0.7149920971109D+00, 0.2636725487657D+01,  0.2681084724003D-08, 0.4899819493154D+01, 0.6816289982179D+01,  0.3495993460759D-08, 0.1572418915115D+01, 0.6418701221183D+01,  0.3130770324995D-08, 0.8912190180489D+00, 0.1235996607578D+02,  0.2744353821941D-08, 0.3800821940055D+01, 0.2059724391010D+02,  0.2842732906341D-08, 0.2644717440029D+01, 0.2828699048865D+02,  0.3046882682154D-08, 0.3987793020179D+01, 0.6055599646783D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=411,420)" is not supported. Skipping.
Line #18599 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=421,430) /  0.2399072455143D-08, 0.9908826440764D+00, 0.6255674361143D+01,  0.2384306274204D-08, 0.2516149752220D+01, 0.6310477339748D+01,  0.2977324500559D-08, 0.5849195642118D+01, 0.1652265972112D+02,  0.3062835258972D-08, 0.1681660100162D+01, 0.1172006883645D+02,  0.3109682589231D-08, 0.5804143987737D+00, 0.2751146787858D+02,  0.2903920355299D-08, 0.5800768280123D+01, 0.6510552054109D+01,  0.2823221989212D-08, 0.9241118370216D+00, 0.5469525544182D+01,  0.3187949696649D-08, 0.3139776445735D+01, 0.1693792562116D+03,  0.2922559771655D-08, 0.3549440782984D+01, 0.2630839062450D+00,  0.2436302066603D-08, 0.4735540696319D+01, 0.3946258593675D+00 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=421,430)" is not supported. Skipping.
Line #18610 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=431,440) /  0.3049473043606D-08, 0.4998289124561D+01, 0.8390110365991D+01,  0.2863682575784D-08, 0.6709515671102D+00, 0.2243449970715D+00,  0.2641750517966D-08, 0.5410978257284D+01, 0.2986433403208D+02,  0.2704093466243D-08, 0.4778317207821D+01, 0.6129297044991D+01,  0.2445522177011D-08, 0.6009020662222D+01, 0.1171295538178D+02,  0.2623608810230D-08, 0.5010449777147D+01, 0.6436854655901D+01,  0.2079259704053D-08, 0.5980943768809D+01, 0.2019909489111D+02,  0.2820225596771D-08, 0.2679965110468D+01, 0.5934151399930D+01,  0.2365221950927D-08, 0.1894231148810D+01, 0.2470570524223D+02,  0.2359682077149D-08, 0.4220752950780D+01, 0.8671969964381D+01 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=431,440)" is not supported. Skipping.
Line #18621 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=441,450) /  0.2387577137206D-08, 0.2571783940617D+01, 0.7096626156709D+01,  0.1982102089816D-08, 0.5169765997119D+00, 0.1727188400790D+02,  0.2687502389925D-08, 0.6239078264579D+01, 0.7075506709219D+02,  0.2207751669135D-08, 0.2031184412677D+01, 0.4377611041777D+01,  0.2618370214274D-08, 0.8266079985979D+00, 0.6632000300961D+01,  0.2591951887361D-08, 0.8819350522008D+00, 0.4873985990671D+02,  0.2375055656248D-08, 0.3520944177789D+01, 0.1590676413561D+02,  0.2472019978911D-08, 0.1551431908671D+01, 0.6612329252343D+00,  0.2368157127199D-08, 0.4178610147412D+01, 0.3459636466239D+02,  0.1764846605693D-08, 0.1506764000157D+01, 0.1980094587212D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=441,450)" is not supported. Skipping.
Line #18632 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=451,460) /  0.2291769608798D-08, 0.2118250611782D+01, 0.2844914056730D-01,  0.2209997316943D-08, 0.3363255261678D+01, 0.2666070658668D+00,  0.2292699097923D-08, 0.4200423956460D+00, 0.1484170571900D-02,  0.1629683015329D-08, 0.2331362582487D+01, 0.3035599730800D+02,  0.2206492862426D-08, 0.3400274026992D+01, 0.6281667977667D+01,  0.2205746568257D-08, 0.1066051230724D+00, 0.6284483723224D+01,  0.2026310767991D-08, 0.2779066487979D+01, 0.2449240616245D+02,  0.1762977622163D-08, 0.9951450691840D+00, 0.2045286941806D+02,  0.1368535049606D-08, 0.6402447365817D+00, 0.2473415438279D+02,  0.1720598775450D-08, 0.2303524214705D+00, 0.1679593901136D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=451,460)" is not supported. Skipping.
Line #18643 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=461,470) /  0.1702429015449D-08, 0.6164622655048D+01, 0.3338575901272D+03,  0.1414033197685D-08, 0.3954561185580D+01, 0.1624205518357D+03,  0.1573768958043D-08, 0.2028286308984D+01, 0.3144167757552D+02,  0.1650705184447D-08, 0.2304040666128D+01, 0.5267006960365D+02,  0.1651087618855D-08, 0.2538461057280D+01, 0.8956999012000D+02,  0.1616409518983D-08, 0.5111054348152D+01, 0.3332657872986D+02,  0.1537175173581D-08, 0.5601130666603D+01, 0.3852657435933D+02,  0.1593191980553D-08, 0.2614340453411D+01, 0.2282781046519D+03,  0.1499480170643D-08, 0.3624721577264D+01, 0.2823723341956D+02,  0.1493807843235D-08, 0.4214569879008D+01, 0.2876692439167D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=461,470)" is not supported. Skipping.
Line #18654 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=471,480) /  0.1074571199328D-08, 0.1496911744704D+00, 0.8397383534231D+02,  0.1074406983417D-08, 0.1187817671922D+01, 0.8401985929482D+02,  0.9757576855851D-09, 0.2655703035858D+01, 0.7826370942180D+02,  0.1258432887565D-08, 0.4969896184844D+01, 0.3115650189215D+03,  0.1240336343282D-08, 0.5192460776926D+01, 0.1784300471910D+03,  0.9016107005164D-09, 0.1960356923057D+01, 0.5886454391678D+02,  0.1135392360918D-08, 0.5082427809068D+01, 0.7842370451713D+02,  0.9216046089565D-09, 0.2793775037273D+01, 0.1014262087719D+03,  0.1061276615030D-08, 0.3726144311409D+01, 0.5660027930059D+02,  0.1010110596263D-08, 0.7404080708937D+00, 0.4245678405627D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=471,480)" is not supported. Skipping.
Line #18665 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=481,490) /  0.7217424756199D-09, 0.2697449980577D-01, 0.2457074661053D+03,  0.6912003846756D-09, 0.4253296276335D+01, 0.1679936946371D+03,  0.6871814664847D-09, 0.5148072412354D+01, 0.6053048899753D+02,  0.4887158016343D-09, 0.2153581148294D+01, 0.9656299901946D+02,  0.5161802866314D-09, 0.3852750634351D+01, 0.2442876000072D+03,  0.5652599559057D-09, 0.1233233356270D+01, 0.8365903305582D+02,  0.4710812608586D-09, 0.5610486976767D+01, 0.3164282286739D+03,  0.4909977500324D-09, 0.1639629524123D+01, 0.4059982187939D+03,  0.4772641839378D-09, 0.3737100368583D+01, 0.1805255418145D+03,  0.4487562567153D-09, 0.1158417054478D+00, 0.8433466158131D+02 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=481,490)" is not supported. Skipping.
Line #18676 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=491,500) /  0.3943441230497D-09, 0.6243502862796D+00, 0.2568537517081D+03,  0.3952236913598D-09, 0.3510377382385D+01, 0.2449975330562D+03,  0.3788898363417D-09, 0.5916128302299D+01, 0.1568131045107D+03,  0.3738329328831D-09, 0.1042266763456D+01, 0.3948519331910D+03,  0.2451199165151D-09, 0.1166788435700D+01, 0.1435713242844D+03,  0.2436734402904D-09, 0.3254726114901D+01, 0.2268582385539D+03,  0.2213605274325D-09, 0.1687210598530D+01, 0.1658638954901D+03,  0.1491521204829D-09, 0.2657541786794D+01, 0.2219950288015D+03,  0.1474995329744D-09, 0.5013089805819D+01, 0.3052819430710D+03,  0.1661939475656D-09, 0.5495315428418D+01, 0.2526661704812D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=491,500)" is not supported. Skipping.
Line #18680 in sofapy.f:"      DATA ((E0(I,J,2),I=1,3),J=501,NE0Y) /  0.9015946748003D-10, 0.2236989966505D+01, 0.4171445043968D+03 /"
	analyzeline: implied-DO list "((e0(i,j,2),i=1,3),j=501,ne0y)" is not supported. Skipping.
Line #18691 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J=  1, 10) /  0.9304690546528D-06, 0.0000000000000D+00, 0.0000000000000D+00,  0.5150715570663D-06, 0.4431807116294D+01, 0.1256615170089D+02,  0.1290825411056D-07, 0.4388610039678D+01, 0.1884922755134D+02,  0.4645466665386D-08, 0.5827263376034D+01, 0.6283075850446D+01,  0.2079625310718D-08, 0.1621698662282D+00, 0.6279552690824D+01,  0.2078189850907D-08, 0.3344713435140D+01, 0.6286599010068D+01,  0.6207190138027D-09, 0.5074049319576D+01, 0.4705732307012D+01,  0.5989826532569D-09, 0.2231842216620D+01, 0.6256777527156D+01,  0.5961360812618D-09, 0.1274975769045D+01, 0.6309374173736D+01,  0.4874165471016D-09, 0.3642277426779D+01, 0.7755226100720D+00 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18702 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 11, 20) /  0.4283834034360D-09, 0.5148765510106D+01, 0.1059381944224D+01,  0.4652389287529D-09, 0.4715794792175D+01, 0.7860419393880D+01,  0.3751707476401D-09, 0.6617207370325D+00, 0.5753384878334D+01,  0.3559998806198D-09, 0.6155548875404D+01, 0.5884926831456D+01,  0.3558447558857D-09, 0.2898827297664D+01, 0.6812766822558D+01,  0.3211116927106D-09, 0.3625813502509D+01, 0.6681224869435D+01,  0.2875609914672D-09, 0.4345435813134D+01, 0.2513230340178D+02,  0.2843109704069D-09, 0.5862263940038D+01, 0.6127655567643D+01,  0.2744676468427D-09, 0.3926419475089D+01, 0.6438496133249D+01,  0.2481285237789D-09, 0.1351976572828D+01, 0.5486777812467D+01 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #18713 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 21, 30) /  0.2060338481033D-09, 0.2147556998591D+01, 0.7079373888424D+01,  0.2015822358331D-09, 0.4408358972216D+01, 0.6290189305114D+01,  0.2001195944195D-09, 0.5385829822531D+01, 0.6275962395778D+01,  0.1953667642377D-09, 0.1304933746120D+01, 0.5507553240374D+01,  0.1839744078713D-09, 0.6173567228835D+01, 0.1179062909082D+02,  0.1643334294845D-09, 0.4635942997523D+01, 0.1150676975667D+02,  0.1768051018652D-09, 0.5086283558874D+01, 0.7113454667900D-02,  0.1674874205489D-09, 0.2243332137241D+01, 0.7058598460518D+01,  0.1421445397609D-09, 0.6186899771515D+01, 0.7962980379786D+00,  0.1255163958267D-09, 0.5730238465658D+01, 0.4694002934110D+01 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #18724 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 31, 40) /  0.1013945281961D-09, 0.1726055228402D+01, 0.3738761453707D+01,  0.1047294335852D-09, 0.2658801228129D+01, 0.6282095334605D+01,  0.1047103879392D-09, 0.8481047835035D+00, 0.6284056366286D+01,  0.9530343962826D-10, 0.3079267149859D+01, 0.6069776770667D+01,  0.9604637611690D-10, 0.3258679792918D+00, 0.4136910472696D+01,  0.9153518537177D-10, 0.4398599886584D+00, 0.6496374930224D+01,  0.8562458214922D-10, 0.4772686794145D+01, 0.1194447056968D+01,  0.8232525360654D-10, 0.5966220721679D+01, 0.1589072916335D+01,  0.6150223411438D-10, 0.1780985591923D+01, 0.8827390247185D+01,  0.6272087858000D-10, 0.3184305429012D+01, 0.8429241228195D+01 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #18735 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 41, 50) /  0.5540476311040D-10, 0.3801260595433D+01, 0.4933208510675D+01,  0.7331901699361D-10, 0.5205948591865D+01, 0.4535059491685D+01,  0.6018528702791D-10, 0.4770139083623D+01, 0.1255903824622D+02,  0.5150530724804D-10, 0.3574796899585D+01, 0.1176985366291D+02,  0.6471933741811D-10, 0.2679787266521D+01, 0.5088628793478D+01,  0.5317460644174D-10, 0.9528763345494D+00, 0.3154687086868D+01,  0.4832187748783D-10, 0.5329322498232D+01, 0.6040347114260D+01,  0.4716763555110D-10, 0.2395235316466D+01, 0.5331357529664D+01,  0.4871509139861D-10, 0.3056663648823D+01, 0.1256967486051D+02,  0.4598417696768D-10, 0.4452762609019D+01, 0.6525804586632D+01 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #18746 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 51, 60) /  0.5674189533175D-10, 0.9879680872193D+00, 0.5729506548653D+01,  0.4073560328195D-10, 0.5939127696986D+01, 0.7632943190217D+01,  0.5040994945359D-10, 0.4549875824510D+01, 0.8031092209206D+01,  0.5078185134679D-10, 0.7346659893982D+00, 0.7477522907414D+01,  0.3769343537061D-10, 0.1071317188367D+01, 0.7234794171227D+01,  0.4980331365299D-10, 0.2500345341784D+01, 0.6836645152238D+01,  0.3458236594757D-10, 0.3825159450711D+01, 0.1097707878456D+02,  0.3578859493602D-10, 0.5299664791549D+01, 0.4164311961999D+01,  0.3370504646419D-10, 0.5002316301593D+01, 0.1137170464392D+02,  0.3299873338428D-10, 0.2526123275282D+01, 0.3930209696940D+01 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #18757 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 61, 70) /  0.4304917318409D-10, 0.3368078557132D+01, 0.1592596075957D+01,  0.3402418753455D-10, 0.8385495425800D+00, 0.3128388763578D+01,  0.2778460572146D-10, 0.3669905203240D+01, 0.7342457794669D+01,  0.2782710128902D-10, 0.2691664812170D+00, 0.1748016358760D+01,  0.2711725179646D-10, 0.4707487217718D+01, 0.5296909721118D+00,  0.2981760946340D-10, 0.3190260867816D+00, 0.5368044267797D+00,  0.2811672977772D-10, 0.3196532315372D+01, 0.7084896783808D+01,  0.2863454474467D-10, 0.2263240324780D+00, 0.5223693906222D+01,  0.3333464634051D-10, 0.3498451685065D+01, 0.8018209333619D+00,  0.3312991747609D-10, 0.5839154477412D+01, 0.1554202828031D+00 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #18770 in sofapy.f:"      DATA ((E1(I,J,2),I=1,3),J= 71,NE1Y) /  0.2813255564006D-10, 0.8268044346621D+00, 0.5225775174439D+00,  0.2665098083966D-10, 0.3934021725360D+01, 0.5216580451554D+01,  0.2349795705216D-10, 0.5197620913779D+01, 0.2146165377750D+01,  0.2330352293961D-10, 0.2984999231807D+01, 0.1726015463500D+02,  0.2728001683419D-10, 0.6521679638544D+00, 0.8635942003952D+01,  0.2484061007669D-10, 0.3468955561097D+01, 0.5230807360890D+01,  0.2646328768427D-10, 0.1013724533516D+01, 0.2629832328990D-01,  0.2518630264831D-10, 0.6108081057122D+01, 0.5481254917084D+01,  0.2421901455384D-10, 0.1651097776260D+01, 0.1349867339771D+01,  0.6348533267831D-11, 0.3220226560321D+01, 0.8433466158131D+02 /"
	analyzeline: implied-DO list "((e1(i,j,2),i=1,3),j= 71,ne1y)" is not supported. Skipping.
Line #18778 in sofapy.f:"      DATA ((E2(I,J,2),I=1,3),J=  1,NE2Y) /  0.5063375872532D-10, 0.0000000000000D+00, 0.0000000000000D+00,  0.2173815785980D-10, 0.2827805833053D+01, 0.1256615170089D+02,  0.1010231999920D-10, 0.4634612377133D+01, 0.6283075850446D+01,  0.9259745317636D-12, 0.2620612076189D+01, 0.1884922755134D+02,  0.1022202095812D-12, 0.3809562326066D+01, 0.8399684731857D+02 /"
	analyzeline: implied-DO list "((e2(i,j,2),i=1,3),j=  1,ne2y)" is not supported. Skipping.
Line #18789 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J=  1, 10) /  0.2796207639075D-05, 0.3198701560209D+01, 0.8433466158131D+02,  0.1016042198142D-05, 0.5422360395913D+01, 0.5507553240374D+01,  0.8044305033647D-06, 0.3880222866652D+01, 0.5223693906222D+01,  0.4385347909274D-06, 0.3704369937468D+01, 0.2352866153506D+01,  0.3186156414906D-06, 0.3999639363235D+01, 0.1577343543434D+01,  0.2272412285792D-06, 0.3984738315952D+01, 0.1047747311755D+01,  0.1645620103007D-06, 0.3565412516841D+01, 0.5856477690889D+01,  0.1815836921166D-06, 0.4984507059020D+01, 0.6283075850446D+01,  0.1447461676364D-06, 0.3702753570108D+01, 0.9437762937313D+01,  0.1430760876382D-06, 0.3409658712357D+01, 0.1021328554739D+02 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18800 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 11, 20) /  0.1120445753226D-06, 0.4829561570246D+01, 0.1414349524433D+02,  0.1090232840797D-06, 0.2080729178066D+01, 0.6812766822558D+01,  0.9715727346551D-07, 0.3476295881948D+01, 0.4694002934110D+01,  0.1036267136217D-06, 0.4056639536648D+01, 0.7109288135493D+02,  0.8752665271340D-07, 0.4448159519911D+01, 0.5753384878334D+01,  0.8331864956004D-07, 0.4991704044208D+01, 0.7084896783808D+01,  0.6901658670245D-07, 0.4325358994219D+01, 0.6275962395778D+01,  0.9144536848998D-07, 0.1141826375363D+01, 0.6620890113188D+01,  0.7205085037435D-07, 0.3624344170143D+01, 0.5296909721118D+00,  0.7697874654176D-07, 0.5554257458998D+01, 0.1676215758509D+03 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #18811 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 21, 30) /  0.5197545738384D-07, 0.6251760961735D+01, 0.1807370494127D+02,  0.5031345378608D-07, 0.2497341091913D+01, 0.4705732307012D+01,  0.4527110205840D-07, 0.2335079920992D+01, 0.6309374173736D+01,  0.4753355798089D-07, 0.7094148987474D+00, 0.5884926831456D+01,  0.4296951977516D-07, 0.1101916352091D+01, 0.6681224869435D+01,  0.3855341568387D-07, 0.1825495405486D+01, 0.5486777812467D+01,  0.5253930970990D-07, 0.4424740687208D+01, 0.7860419393880D+01,  0.4024630496471D-07, 0.5120498157053D+01, 0.1336797263425D+02,  0.4061069791453D-07, 0.6029771435451D+01, 0.3930209696940D+01,  0.3797883804205D-07, 0.4435193600836D+00, 0.3154687086868D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #18822 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 31, 40) /  0.2933033225587D-07, 0.5124157356507D+01, 0.1059381944224D+01,  0.3503000930426D-07, 0.5421830162065D+01, 0.6069776770667D+01,  0.3670096214050D-07, 0.4582101667297D+01, 0.1219403291462D+02,  0.2905609437008D-07, 0.1926566420072D+01, 0.1097707878456D+02,  0.2466827821713D-07, 0.6090174539834D+00, 0.6496374930224D+01,  0.2691647295332D-07, 0.1393432595077D+01, 0.2200391463820D+02,  0.2150554667946D-07, 0.4308671715951D+01, 0.5643178611111D+01,  0.2237481922680D-07, 0.8133968269414D+00, 0.8635942003952D+01,  0.1817741038157D-07, 0.3755205127454D+01, 0.3340612434717D+01,  0.2227820762132D-07, 0.2759558596664D+01, 0.1203646072878D+02 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #18833 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 41, 50) /  0.1944713772307D-07, 0.5699645869121D+01, 0.1179062909082D+02,  0.1527340520662D-07, 0.1986749091746D+01, 0.3981490189893D+00,  0.1577282574914D-07, 0.3205017217983D+01, 0.5088628793478D+01,  0.1424738825424D-07, 0.6256747903666D+01, 0.2544314396739D+01,  0.1616563121701D-07, 0.2601671259394D+00, 0.1729818233119D+02,  0.1401210391692D-07, 0.4686939173506D+01, 0.7058598460518D+01,  0.1488726974214D-07, 0.2815862451372D+01, 0.2593412433514D+02,  0.1692626442388D-07, 0.4956894109797D+01, 0.1564752902480D+03,  0.1123571582910D-07, 0.2381192697696D+01, 0.3738761453707D+01,  0.9903308606317D-08, 0.4294851657684D+01, 0.9225539266174D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #18844 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 51, 60) /  0.9174533187191D-08, 0.3075171510642D+01, 0.4164311961999D+01,  0.8645985631457D-08, 0.5477534821633D+00, 0.8429241228195D+01, -0.1085876492688D-07, 0.0000000000000D+00, 0.0000000000000D+00,  0.9264309077815D-08, 0.5968571670097D+01, 0.7079373888424D+01,  0.8243116984954D-08, 0.1489098777643D+01, 0.1044738781244D+02,  0.8268102113708D-08, 0.3512977691983D+01, 0.1150676975667D+02,  0.9043613988227D-08, 0.1290704408221D+00, 0.1101510648075D+02,  0.7432912038789D-08, 0.1991086893337D+01, 0.2608790314060D+02,  0.8586233727285D-08, 0.4238357924414D+01, 0.2986433403208D+02,  0.7612230060131D-08, 0.2911090150166D+01, 0.4732030630302D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #18855 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 61, 70) /  0.7097787751408D-08, 0.1908938392390D+01, 0.8031092209206D+01,  0.7640237040175D-08, 0.6129219000168D+00, 0.7962980379786D+00,  0.7070445688081D-08, 0.1380417036651D+01, 0.2146165377750D+01,  0.7690770957702D-08, 0.1680504249084D+01, 0.2122839202813D+02,  0.8051292542594D-08, 0.5127423484511D+01, 0.2942463415728D+01,  0.5902709104515D-08, 0.2020274190917D+01, 0.7755226100720D+00,  0.5134567496462D-08, 0.2606778676418D+01, 0.1256615170089D+02,  0.5525802046102D-08, 0.1613011769663D+01, 0.8018209333619D+00,  0.5880724784221D-08, 0.4604483417236D+01, 0.4690479774488D+01,  0.5211699081370D-08, 0.5718964114193D+01, 0.8827390247185D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #18866 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 71, 80) /  0.4891849573562D-08, 0.3689658932196D+01, 0.2132990797783D+00,  0.5150246069997D-08, 0.4099769855122D+01, 0.6480980550449D+02,  0.5102434319633D-08, 0.5660834602509D+01, 0.3379454372902D+02,  0.5083405254252D-08, 0.9842221218974D+00, 0.4136910472696D+01,  0.4206562585682D-08, 0.1341363634163D+00, 0.3128388763578D+01,  0.4663249683579D-08, 0.8130132735866D+00, 0.5216580451554D+01,  0.4099474416530D-08, 0.5791497770644D+01, 0.4265981595566D+00,  0.4628251220767D-08, 0.1249802769331D+01, 0.1572083878776D+02,  0.5024068728142D-08, 0.4795684802743D+01, 0.6290189305114D+01,  0.5120234327758D-08, 0.3810420387208D+01, 0.5230807360890D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #18877 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 81, 90) /  0.5524029815280D-08, 0.1029264714351D+01, 0.2397622045175D+03,  0.4757415718860D-08, 0.3528044781779D+01, 0.1649636139783D+02,  0.3915786131127D-08, 0.5593889282646D+01, 0.1589072916335D+01,  0.4869053149991D-08, 0.3299636454433D+01, 0.7632943190217D+01,  0.3649365703729D-08, 0.1286049002584D+01, 0.6206810014183D+01,  0.3992493949002D-08, 0.3100307589464D+01, 0.2515860172507D+02,  0.3320247477418D-08, 0.6212683940807D+01, 0.1216800268190D+02,  0.3287123739696D-08, 0.4699118445928D+01, 0.7234794171227D+01,  0.3472776811103D-08, 0.2630507142004D+01, 0.7342457794669D+01,  0.3423253294767D-08, 0.2946432844305D+01, 0.9623688285163D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #18888 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J= 91,100) /  0.3896173898244D-08, 0.1224834179264D+01, 0.6438496133249D+01,  0.3388455337924D-08, 0.1543807616351D+01, 0.1494531617769D+02,  0.3062704716523D-08, 0.1191777572310D+01, 0.8662240327241D+01,  0.3270075600400D-08, 0.5483498767737D+01, 0.1194447056968D+01,  0.3101209215259D-08, 0.8000833804348D+00, 0.3772475342596D+02,  0.2780883347311D-08, 0.4077980721888D+00, 0.5863591145557D+01,  0.2903605931824D-08, 0.2617490302147D+01, 0.1965104848470D+02,  0.2682014743119D-08, 0.2634703158290D+01, 0.7238675589263D+01,  0.2534360108492D-08, 0.6102446114873D+01, 0.6836645152238D+01,  0.2392564882509D-08, 0.3681820208691D+01, 0.5849364236221D+01 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j= 91,100)" is not supported. Skipping.
Line #18899 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J=101,110) /  0.2656667254856D-08, 0.6216045388886D+01, 0.6133512519065D+01,  0.2331242096773D-08, 0.5864949777744D+01, 0.4535059491685D+01,  0.2287898363668D-08, 0.4566628532802D+01, 0.7477522907414D+01,  0.2336944521306D-08, 0.2442722126930D+01, 0.1137170464392D+02,  0.3156632236269D-08, 0.1626628050682D+01, 0.2509084901204D+03,  0.2982612402766D-08, 0.2803604512609D+01, 0.1748016358760D+01,  0.2774031674807D-08, 0.4654002897158D+01, 0.8223916695780D+02,  0.2295236548638D-08, 0.4326518333253D+01, 0.3378142627421D+00,  0.2190714699873D-08, 0.4519614578328D+01, 0.2908881142201D+02,  0.2191495845045D-08, 0.3012626912549D+01, 0.1673046366289D+02 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j=101,110)" is not supported. Skipping.
Line #18910 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J=111,120) /  0.2492901628386D-08, 0.1290101424052D+00, 0.1543797956245D+03,  0.1993778064319D-08, 0.3864046799414D+01, 0.1778984560711D+02,  0.1898146479022D-08, 0.5053777235891D+01, 0.2042657109477D+02,  0.1918280127634D-08, 0.2222470192548D+01, 0.4165496312290D+02,  0.1916351061607D-08, 0.8719067257774D+00, 0.7737595720538D+02,  0.1834720181466D-08, 0.4031491098040D+01, 0.2358125818164D+02,  0.1249201523806D-08, 0.5938379466835D+01, 0.3301902111895D+02,  0.1477304050539D-08, 0.6544722606797D+00, 0.9548094718417D+02,  0.1264316431249D-08, 0.2059072853236D+01, 0.8399684731857D+02,  0.1203526495039D-08, 0.3644813532605D+01, 0.4558517281984D+02 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j=111,120)" is not supported. Skipping.
Line #18921 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J=121,130) /  0.9221681059831D-09, 0.3241815055602D+01, 0.7805158573086D+02,  0.7849278367646D-09, 0.5043812342457D+01, 0.5217580628120D+02,  0.7983392077387D-09, 0.5000024502753D+01, 0.1501922143975D+03,  0.7925395431654D-09, 0.1398734871821D-01, 0.9061773743175D+02,  0.7640473285886D-09, 0.5067111723130D+01, 0.4951538251678D+02,  0.5398937754482D-09, 0.5597382200075D+01, 0.1613385000004D+03,  0.5626247550193D-09, 0.2601338209422D+01, 0.7318837597844D+02,  0.5525197197855D-09, 0.5814832109256D+01, 0.1432335100216D+03,  0.5407629837898D-09, 0.3384820609076D+01, 0.3230491187871D+03,  0.3856739119801D-09, 0.1072391840473D+01, 0.2334791286671D+03 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j=121,130)" is not supported. Skipping.
Line #18931 in sofapy.f:"      DATA ((E0(I,J,3),I=1,3),J=131,NE0Z) /  0.3856425239987D-09, 0.2369540393327D+01, 0.1739046517013D+03,  0.4350867755983D-09, 0.5255575751082D+01, 0.1620484330494D+03,  0.3844113924996D-09, 0.5482356246182D+01, 0.9757644180768D+02,  0.2854869155431D-09, 0.9573634763143D+00, 0.1697170704744D+03,  0.1719227671416D-09, 0.1887203025202D+01, 0.2265204242912D+03,  0.1527846879755D-09, 0.3982183931157D+01, 0.3341954043900D+03,  0.1128229264847D-09, 0.2787457156298D+01, 0.3119028331842D+03 /"
	analyzeline: implied-DO list "((e0(i,j,3),i=1,3),j=131,ne0z)" is not supported. Skipping.
Line #18942 in sofapy.f:"      DATA ((E1(I,J,3),I=1,3),J=  1, 10) /  0.2278290449966D-05, 0.3413716033863D+01, 0.6283075850446D+01,  0.5429458209830D-07, 0.0000000000000D+00, 0.0000000000000D+00,  0.1903240492525D-07, 0.3370592358297D+01, 0.1256615170089D+02,  0.2385409276743D-09, 0.3327914718416D+01, 0.1884922755134D+02,  0.8676928342573D-10, 0.1824006811264D+01, 0.5223693906222D+01,  0.7765442593544D-10, 0.3888564279247D+01, 0.5507553240374D+01,  0.7066158332715D-10, 0.5194267231944D+01, 0.2352866153506D+01,  0.7092175288657D-10, 0.2333246960021D+01, 0.8399684731857D+02,  0.5357582213535D-10, 0.2224031176619D+01, 0.5296909721118D+00,  0.3828035865021D-10, 0.2156710933584D+01, 0.6279552690824D+01 /"
	analyzeline: implied-DO list "((e1(i,j,3),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18947 in sofapy.f:"      DATA ((E1(I,J,3),I=1,3),J= 11,NE1Z) /  0.3824857220427D-10, 0.1529755219915D+01, 0.6286599010068D+01,  0.3286995181628D-10, 0.4879512900483D+01, 0.1021328554739D+02 /"
	analyzeline: implied-DO list "((e1(i,j,3),i=1,3),j= 11,ne1z)" is not supported. Skipping.
Line #18953 in sofapy.f:"      DATA ((E2(I,J,3),I=1,3),J=  1,NE2Z) /  0.9722666114891D-10, 0.5152219582658D+01, 0.6283075850446D+01, -0.3494819171909D-11, 0.0000000000000D+00, 0.0000000000000D+00,  0.6713034376076D-12, 0.6440188750495D+00, 0.1256615170089D+02 /"
	analyzeline: implied-DO list "((e2(i,j,3),i=1,3),j=  1,ne2z)" is not supported. Skipping.
Line #18964 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=  1, 10) /  0.4956757536410D-02, 0.3741073751789D+01, 0.5296909721118D+00,  0.2718490072522D-02, 0.4016011511425D+01, 0.2132990797783D+00,  0.1546493974344D-02, 0.2170528330642D+01, 0.3813291813120D-01,  0.8366855276341D-03, 0.2339614075294D+01, 0.7478166569050D-01,  0.2936777942117D-03, 0.0000000000000D+00, 0.0000000000000D+00,  0.1201317439469D-03, 0.4090736353305D+01, 0.1059381944224D+01,  0.7578550887230D-04, 0.3241518088140D+01, 0.4265981595566D+00,  0.1941787367773D-04, 0.1012202064330D+01, 0.2061856251104D+00,  0.1889227765991D-04, 0.3892520416440D+01, 0.2204125344462D+00,  0.1937896968613D-04, 0.4797779441161D+01, 0.1495633313810D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #18975 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 11, 20) /  0.1434506110873D-04, 0.3868960697933D+01, 0.5225775174439D+00,  0.1406659911580D-04, 0.4759766557397D+00, 0.5368044267797D+00,  0.1179022300202D-04, 0.7774961520598D+00, 0.7626583626240D-01,  0.8085864460959D-05, 0.3254654471465D+01, 0.3664874755930D-01,  0.7622752967615D-05, 0.4227633103489D+01, 0.3961708870310D-01,  0.6209171139066D-05, 0.2791828325711D+00, 0.7329749511860D-01,  0.4366435633970D-05, 0.4440454875925D+01, 0.1589072916335D+01,  0.3792124889348D-05, 0.5156393842356D+01, 0.7113454667900D-02,  0.3154548963402D-05, 0.6157005730093D+01, 0.4194847048887D+00,  0.3088359882942D-05, 0.2494567553163D+01, 0.6398972393349D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #18986 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 21, 30) /  0.2788440902136D-05, 0.4934318747989D+01, 0.1102062672231D+00,  0.3039928456376D-05, 0.4895077702640D+01, 0.6283075850446D+01,  0.2272258457679D-05, 0.5278394064764D+01, 0.1030928125552D+00,  0.2162007057957D-05, 0.5802978019099D+01, 0.3163918923335D+00,  0.1767632855737D-05, 0.3415346595193D-01, 0.1021328554739D+02,  0.1349413459362D-05, 0.2001643230755D+01, 0.1484170571900D-02,  0.1170141900476D-05, 0.2424750491620D+01, 0.6327837846670D+00,  0.1054355266820D-05, 0.3123311487576D+01, 0.4337116142245D+00,  0.9800822461610D-06, 0.3026258088130D+01, 0.1052268489556D+01,  0.1091203749931D-05, 0.3157811670347D+01, 0.1162474756779D+01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #18997 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 31, 40) /  0.6960236715913D-06, 0.8219570542313D+00, 0.1066495398892D+01,  0.5689257296909D-06, 0.1323052375236D+01, 0.9491756770005D+00,  0.6613172135802D-06, 0.2765348881598D+00, 0.8460828644453D+00,  0.6277702517571D-06, 0.5794064466382D+01, 0.1480791608091D+00,  0.6304884066699D-06, 0.7323555380787D+00, 0.2243449970715D+00,  0.4897850467382D-06, 0.3062464235399D+01, 0.3340612434717D+01,  0.3759148598786D-06, 0.4588290469664D+01, 0.3516457698740D-01,  0.3110520548195D-06, 0.1374299536572D+01, 0.6373574839730D-01,  0.3064708359780D-06, 0.4222267485047D+01, 0.1104591729320D-01,  0.2856347168241D-06, 0.3714202944973D+01, 0.1510475019529D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #19008 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 41, 50) /  0.2840945514288D-06, 0.2847972875882D+01, 0.4110125927500D-01,  0.2378951599405D-06, 0.3762072563388D+01, 0.2275259891141D+00,  0.2714229481417D-06, 0.1036049980031D+01, 0.2535050500000D-01,  0.2323551717307D-06, 0.4682388599076D+00, 0.8582758298370D-01,  0.1881790512219D-06, 0.4790565425418D+01, 0.2118763888447D+01,  0.2261353968371D-06, 0.1669144912212D+01, 0.7181332454670D-01,  0.2214546389848D-06, 0.3937717281614D+01, 0.2968341143800D-02,  0.2184915594933D-06, 0.1129169845099D+00, 0.7775000683430D-01,  0.2000164937936D-06, 0.4030009638488D+01, 0.2093666171530D+00,  0.1966105136719D-06, 0.8745955786834D+00, 0.2172315424036D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #19019 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 51, 60) /  0.1904742332624D-06, 0.5919743598964D+01, 0.2022531624851D+00,  0.1657399705031D-06, 0.2549141484884D+01, 0.7358765972222D+00,  0.1574070533987D-06, 0.5277533020230D+01, 0.7429900518901D+00,  0.1832261651039D-06, 0.3064688127777D+01, 0.3235053470014D+00,  0.1733615346569D-06, 0.3011432799094D+01, 0.1385174140878D+00,  0.1549124014496D-06, 0.4005569132359D+01, 0.5154640627760D+00,  0.1637044713838D-06, 0.1831375966632D+01, 0.8531963191132D+00,  0.1123420082383D-06, 0.1180270407578D+01, 0.1990721704425D+00,  0.1083754165740D-06, 0.3414101320863D+00, 0.5439178814476D+00,  0.1156638012655D-06, 0.6130479452594D+00, 0.5257585094865D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #19030 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 61, 70) /  0.1142548785134D-06, 0.3724761948846D+01, 0.5336234347371D+00,  0.7921463895965D-07, 0.2435425589361D+01, 0.1478866649112D+01,  0.7428600285231D-07, 0.3542144398753D+01, 0.2164800718209D+00,  0.8323211246747D-07, 0.3525058072354D+01, 0.1692165728891D+01,  0.7257595116312D-07, 0.1364299431982D+01, 0.2101180877357D+00,  0.7111185833236D-07, 0.2460478875808D+01, 0.4155522422634D+00,  0.6868090383716D-07, 0.4397327670704D+01, 0.1173197218910D+00,  0.7226419974175D-07, 0.4042647308905D+01, 0.1265567569334D+01,  0.6955642383177D-07, 0.2865047906085D+01, 0.9562891316684D+00,  0.7492139296331D-07, 0.5014278994215D+01, 0.1422690933580D-01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #19041 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 71, 80) /  0.6598363128857D-07, 0.2376730020492D+01, 0.6470106940028D+00,  0.7381147293385D-07, 0.3272990384244D+01, 0.1581959461667D+01,  0.6402909624032D-07, 0.5302290955138D+01, 0.9597935788730D-01,  0.6237454263857D-07, 0.5444144425332D+01, 0.7084920306520D-01,  0.5241198544016D-07, 0.4215359579205D+01, 0.5265099800692D+00,  0.5144463853918D-07, 0.1218916689916D+00, 0.5328719641544D+00,  0.5868164772299D-07, 0.2369402002213D+01, 0.7871412831580D-01,  0.6233195669151D-07, 0.1254922242403D+01, 0.2608790314060D+02,  0.6068463791422D-07, 0.5679713760431D+01, 0.1114304132498D+00,  0.4359361135065D-07, 0.6097219641646D+00, 0.1375773836557D+01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #19052 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 81, 90) /  0.4686510366826D-07, 0.4786231041431D+01, 0.1143987543936D+00,  0.3758977287225D-07, 0.1167368068139D+01, 0.1596186371003D+01,  0.4282051974778D-07, 0.1519471064319D+01, 0.2770348281756D+00,  0.5153765386113D-07, 0.1860532322984D+01, 0.2228608264996D+00,  0.4575129387188D-07, 0.7632857887158D+00, 0.1465949902372D+00,  0.3326844933286D-07, 0.1298219485285D+01, 0.5070101000000D-01,  0.3748617450984D-07, 0.1046510321062D+01, 0.4903339079539D+00,  0.2816756661499D-07, 0.3434522346190D+01, 0.2991266627620D+00,  0.3412750405039D-07, 0.2523766270318D+01, 0.3518164938661D+00,  0.2655796761776D-07, 0.2904422260194D+01, 0.6256703299991D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #19063 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J= 91,100) /  0.2963597929458D-07, 0.5923900431149D+00, 0.1099462426779D+00,  0.2539523734781D-07, 0.4851947722567D+01, 0.1256615170089D+02,  0.2283087914139D-07, 0.3400498595496D+01, 0.6681224869435D+01,  0.2321309799331D-07, 0.5789099148673D+01, 0.3368040641550D-01,  0.2549657649750D-07, 0.3991856479792D-01, 0.1169588211447D+01,  0.2290462303977D-07, 0.2788567577052D+01, 0.1045155034888D+01,  0.1945398522914D-07, 0.3290896998176D+01, 0.1155361302111D+01,  0.1849171512638D-07, 0.2698060129367D+01, 0.4452511715700D-02,  0.1647199834254D-07, 0.3016735644085D+01, 0.4408250688924D+00,  0.1529530765273D-07, 0.5573043116178D+01, 0.6521991896920D-01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j= 91,100)" is not supported. Skipping.
Line #19074 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=101,110) /  0.1433199339978D-07, 0.1481192356147D+01, 0.9420622223326D+00,  0.1729134193602D-07, 0.1422817538933D+01, 0.2108507877249D+00,  0.1716463931346D-07, 0.3469468901855D+01, 0.2157473718317D+00,  0.1391206061378D-07, 0.6122436220547D+01, 0.4123712502208D+00,  0.1404746661924D-07, 0.1647765641936D+01, 0.4258542984690D-01,  0.1410452399455D-07, 0.5989729161964D+01, 0.2258291676434D+00,  0.1089828772168D-07, 0.2833705509371D+01, 0.4226656969313D+00,  0.1047374564948D-07, 0.5090690007331D+00, 0.3092784376656D+00,  0.1358279126532D-07, 0.5128990262836D+01, 0.7923417740620D-01,  0.1020456476148D-07, 0.9632772880808D+00, 0.1456308687557D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=101,110)" is not supported. Skipping.
Line #19085 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=111,120) /  0.1033428735328D-07, 0.3223779318418D+01, 0.1795258541446D+01,  0.1412435841540D-07, 0.2410271572721D+01, 0.1525316725248D+00,  0.9722759371574D-08, 0.2333531395690D+01, 0.8434341241180D-01,  0.9657334084704D-08, 0.6199270974168D+01, 0.1272681024002D+01,  0.1083641148690D-07, 0.2864222292929D+01, 0.7032915397480D-01,  0.1067318403838D-07, 0.5833458866568D+00, 0.2123349582968D+00,  0.1062366201976D-07, 0.4307753989494D+01, 0.2142632012598D+00,  0.1236364149266D-07, 0.2873917870593D+01, 0.1847279083684D+00,  0.1092759489593D-07, 0.2959887266733D+01, 0.1370332435159D+00,  0.8912069362899D-08, 0.5141213702562D+01, 0.2648454860559D+01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=111,120)" is not supported. Skipping.
Line #19096 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=121,130) /  0.9656467707970D-08, 0.4532182462323D+01, 0.4376440768498D+00,  0.8098386150135D-08, 0.2268906338379D+01, 0.2880807454688D+00,  0.7857714675000D-08, 0.4055544260745D+01, 0.2037373330570D+00,  0.7288455940646D-08, 0.5357901655142D+01, 0.1129145838217D+00,  0.9450595950552D-08, 0.4264926963939D+01, 0.5272426800584D+00,  0.9381718247537D-08, 0.7489366976576D-01, 0.5321392641652D+00,  0.7079052646038D-08, 0.1923311052874D+01, 0.6288513220417D+00,  0.9259004415344D-08, 0.2970256853438D+01, 0.1606092486742D+00,  0.8259801499742D-08, 0.3327056314697D+01, 0.8389694097774D+00,  0.6476334355779D-08, 0.2954925505727D+01, 0.2008557621224D+01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=121,130)" is not supported. Skipping.
Line #19107 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=131,140) /  0.5984021492007D-08, 0.9138753105829D+00, 0.2042657109477D+02,  0.5989546863181D-08, 0.3244464082031D+01, 0.2111650433779D+01,  0.6233108606023D-08, 0.4995232638403D+00, 0.4305306221819D+00,  0.6877299149965D-08, 0.2834987233449D+01, 0.9561746721300D-02,  0.8311234227190D-08, 0.2202951835758D+01, 0.3801276407308D+00,  0.6599472832414D-08, 0.4478581462618D+01, 0.1063314406849D+01,  0.6160491096549D-08, 0.5145858696411D+01, 0.1368660381889D+01,  0.6164772043891D-08, 0.3762976697911D+00, 0.4234171675140D+00,  0.6363248684450D-08, 0.3162246718685D+01, 0.1253008786510D-01,  0.6448587520999D-08, 0.3442693302119D+01, 0.5287268506303D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=131,140)" is not supported. Skipping.
Line #19118 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=141,150) /  0.6431662283977D-08, 0.8977549136606D+00, 0.5306550935933D+00,  0.6351223158474D-08, 0.4306447410369D+01, 0.5217580628120D+02,  0.5476721393451D-08, 0.3888529177855D+01, 0.2221856701002D+01,  0.5341772572619D-08, 0.2655560662512D+01, 0.7466759693650D-01,  0.5337055758302D-08, 0.5164990735946D+01, 0.7489573444450D-01,  0.5373120816787D-08, 0.6041214553456D+01, 0.1274714967946D+00,  0.5392351705426D-08, 0.9177763485932D+00, 0.1055449481598D+01,  0.6688495850205D-08, 0.3089608126937D+01, 0.2213766559277D+00,  0.5072003660362D-08, 0.4311316541553D+01, 0.2132517061319D+00,  0.5070726650455D-08, 0.5790675464444D+00, 0.2133464534247D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=141,150)" is not supported. Skipping.
Line #19129 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=151,160) /  0.5658012950032D-08, 0.2703945510675D+01, 0.7287631425543D+00,  0.4835509924854D-08, 0.2975422976065D+01, 0.7160067364790D-01,  0.6479821978012D-08, 0.1324168733114D+01, 0.2209183458640D-01,  0.6230636494980D-08, 0.2860103632836D+01, 0.3306188016693D+00,  0.4649239516213D-08, 0.4832259763403D+01, 0.7796265773310D-01,  0.6487325792700D-08, 0.2726165825042D+01, 0.3884652414254D+00,  0.4682823682770D-08, 0.6966602455408D+00, 0.1073608853559D+01,  0.5704230804976D-08, 0.5669634104606D+01, 0.8731175355560D-01,  0.6125413585489D-08, 0.1513386538915D+01, 0.7605151500000D-01,  0.6035825038187D-08, 0.1983509168227D+01, 0.9846002785331D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=151,160)" is not supported. Skipping.
Line #19140 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=161,170) /  0.4331123462303D-08, 0.2782892992807D+01, 0.4297791515992D+00,  0.4681107685143D-08, 0.5337232886836D+01, 0.2127790306879D+00,  0.4669105829655D-08, 0.5837133792160D+01, 0.2138191288687D+00,  0.5138823602365D-08, 0.3080560200507D+01, 0.7233337363710D-01,  0.4615856664534D-08, 0.1661747897471D+01, 0.8603097737811D+00,  0.4496916702197D-08, 0.2112508027068D+01, 0.7381754420900D-01,  0.4278479042945D-08, 0.5716528462627D+01, 0.7574578717200D-01,  0.3840525503932D-08, 0.6424172726492D+00, 0.3407705765729D+00,  0.4866636509685D-08, 0.4919244697715D+01, 0.7722995774390D-01,  0.3526100639296D-08, 0.2550821052734D+01, 0.6225157782540D-01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=161,170)" is not supported. Skipping.
Line #19151 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=171,180) /  0.3939558488075D-08, 0.3939331491710D+01, 0.5268983110410D-01,  0.4041268772576D-08, 0.2275337571218D+01, 0.3503323232942D+00,  0.3948761842853D-08, 0.1999324200790D+01, 0.1451108196653D+00,  0.3258394550029D-08, 0.9121001378200D+00, 0.5296435984654D+00,  0.3257897048761D-08, 0.3428428660869D+01, 0.5297383457582D+00,  0.3842559031298D-08, 0.6132927720035D+01, 0.9098186128426D+00,  0.3109920095448D-08, 0.7693650193003D+00, 0.3932462625300D-02,  0.3132237775119D-08, 0.3621293854908D+01, 0.2346394437820D+00,  0.3942189421510D-08, 0.4841863659733D+01, 0.3180992042600D-02,  0.3796972285340D-08, 0.1814174994268D+01, 0.1862120789403D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=171,180)" is not supported. Skipping.
Line #19162 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=181,190) /  0.3995640233688D-08, 0.1386990406091D+01, 0.4549093064213D+00,  0.2875013727414D-08, 0.9178318587177D+00, 0.1905464808669D+01,  0.3073719932844D-08, 0.2688923811835D+01, 0.3628624111593D+00,  0.2731016580075D-08, 0.1188259127584D+01, 0.2131850110243D+00,  0.2729549896546D-08, 0.3702160634273D+01, 0.2134131485323D+00,  0.3339372892449D-08, 0.7199163960331D+00, 0.2007689919132D+00,  0.2898833764204D-08, 0.1916709364999D+01, 0.5291709230214D+00,  0.2894536549362D-08, 0.2424043195547D+01, 0.5302110212022D+00,  0.3096872473843D-08, 0.4445894977497D+01, 0.2976424921901D+00,  0.2635672326810D-08, 0.3814366984117D+01, 0.1485980103780D+01 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=181,190)" is not supported. Skipping.
Line #19173 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=191,200) /  0.3649302697001D-08, 0.2924200596084D+01, 0.6044726378023D+00,  0.3127954585895D-08, 0.1842251648327D+01, 0.1084620721060D+00,  0.2616040173947D-08, 0.4155841921984D+01, 0.1258454114666D+01,  0.2597395859860D-08, 0.1158045978874D+00, 0.2103781122809D+00,  0.2593286172210D-08, 0.4771850408691D+01, 0.2162200472757D+00,  0.2481823585747D-08, 0.4608842558889D+00, 0.1062562936266D+01,  0.2742219550725D-08, 0.1538781127028D+01, 0.5651155736444D+00,  0.3199558469610D-08, 0.3226647822878D+00, 0.7036329877322D+00,  0.2666088542957D-08, 0.1967991731219D+00, 0.1400015846597D+00,  0.2397067430580D-08, 0.3707036669873D+01, 0.2125476091956D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=191,200)" is not supported. Skipping.
Line #19184 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=201,210) /  0.2376570772738D-08, 0.1182086628042D+01, 0.2140505503610D+00,  0.2547228007887D-08, 0.4906256820629D+01, 0.1534957940063D+00,  0.2265575594114D-08, 0.3414949866857D+01, 0.2235935264888D+00,  0.2464381430585D-08, 0.4599122275378D+01, 0.2091065926078D+00,  0.2433408527044D-08, 0.2830751145445D+00, 0.2174915669488D+00,  0.2443605509076D-08, 0.4212046432538D+01, 0.1739420156204D+00,  0.2319779262465D-08, 0.9881978408630D+00, 0.7530171478090D-01,  0.2284622835465D-08, 0.5565347331588D+00, 0.7426161660010D-01,  0.2467268750783D-08, 0.5655708150766D+00, 0.2526561439362D+00,  0.2808513492782D-08, 0.1418405053408D+01, 0.5636314030725D+00 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=201,210)" is not supported. Skipping.
Line #19189 in sofapy.f:"      DATA ((S0(I,J,1),I=1,3),J=211,NS0X) /  0.2329528932532D-08, 0.4069557545675D+01, 0.1056200952181D+01,  0.9698639532817D-09, 0.1074134313634D+01, 0.7826370942180D+02 /"
	analyzeline: implied-DO list "((s0(i,j,1),i=1,3),j=211,ns0x)" is not supported. Skipping.
Line #19200 in sofapy.f:"      DATA ((S1(I,J,1),I=1,3),J=  1, 10) / -0.1296310361520D-07, 0.0000000000000D+00, 0.0000000000000D+00,  0.8975769009438D-08, 0.1128891609250D+01, 0.4265981595566D+00,  0.7771113441307D-08, 0.2706039877077D+01, 0.2061856251104D+00,  0.7538303866642D-08, 0.2191281289498D+01, 0.2204125344462D+00,  0.6061384579336D-08, 0.3248167319958D+01, 0.1059381944224D+01,  0.5726994235594D-08, 0.5569981398610D+01, 0.5225775174439D+00,  0.5616492836424D-08, 0.5057386614909D+01, 0.5368044267797D+00,  0.1010881584769D-08, 0.3473577116095D+01, 0.7113454667900D-02,  0.7259606157626D-09, 0.3651858593665D+00, 0.6398972393349D+00,  0.8755095026935D-09, 0.1662835408338D+01, 0.4194847048887D+00 /"
	analyzeline: implied-DO list "((s1(i,j,1),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #19211 in sofapy.f:"      DATA ((S1(I,J,1),I=1,3),J= 11, 20) /  0.5370491182812D-09, 0.1327673878077D+01, 0.4337116142245D+00,  0.5743773887665D-09, 0.4250200846687D+01, 0.2132990797783D+00,  0.4408103140300D-09, 0.3598752574277D+01, 0.1589072916335D+01,  0.3101892374445D-09, 0.4887822983319D+01, 0.1052268489556D+01,  0.3209453713578D-09, 0.9702272295114D+00, 0.5296909721118D+00,  0.3017228286064D-09, 0.5484462275949D+01, 0.1066495398892D+01,  0.3200700038601D-09, 0.2846613338643D+01, 0.1495633313810D+00,  0.2137637279911D-09, 0.5692163292729D+00, 0.3163918923335D+00,  0.1899686386727D-09, 0.2061077157189D+01, 0.2275259891141D+00,  0.1401994545308D-09, 0.4177771136967D+01, 0.1102062672231D+00 /"
	analyzeline: implied-DO list "((s1(i,j,1),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #19222 in sofapy.f:"      DATA ((S1(I,J,1),I=1,3),J= 21, 30) /  0.1578057810499D-09, 0.5782460597335D+01, 0.7626583626240D-01,  0.1237713253351D-09, 0.5705900866881D+01, 0.5154640627760D+00,  0.1313076837395D-09, 0.5163438179576D+01, 0.3664874755930D-01,  0.1184963304860D-09, 0.3054804427242D+01, 0.6327837846670D+00,  0.1238130878565D-09, 0.2317292575962D+01, 0.3961708870310D-01,  0.1015959527736D-09, 0.2194643645526D+01, 0.7329749511860D-01,  0.9017954423714D-10, 0.2868603545435D+01, 0.1990721704425D+00,  0.8668024955603D-10, 0.4923849675082D+01, 0.5439178814476D+00,  0.7756083930103D-10, 0.3014334135200D+01, 0.9491756770005D+00,  0.7536503401741D-10, 0.2704886279769D+01, 0.1030928125552D+00 /"
	analyzeline: implied-DO list "((s1(i,j,1),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #19233 in sofapy.f:"      DATA ((S1(I,J,1),I=1,3),J= 31, 40) /  0.5483308679332D-10, 0.6010983673799D+01, 0.8531963191132D+00,  0.5184339620428D-10, 0.1952704573291D+01, 0.2093666171530D+00,  0.5108658712030D-10, 0.2958575786649D+01, 0.2172315424036D+00,  0.5019424524650D-10, 0.1736317621318D+01, 0.2164800718209D+00,  0.4909312625978D-10, 0.3167216416257D+01, 0.2101180877357D+00,  0.4456638901107D-10, 0.7697579923471D+00, 0.3235053470014D+00,  0.4227030350925D-10, 0.3490910137928D+01, 0.6373574839730D-01,  0.4095456040093D-10, 0.5178888984491D+00, 0.6470106940028D+00,  0.4990537041422D-10, 0.3323887668974D+01, 0.1422690933580D-01,  0.4321170010845D-10, 0.4288484987118D+01, 0.7358765972222D+00 /"
	analyzeline: implied-DO list "((s1(i,j,1),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #19246 in sofapy.f:"      DATA ((S1(I,J,1),I=1,3),J= 41,NS1X) /  0.3544072091802D-10, 0.6021051579251D+01, 0.5265099800692D+00,  0.3480198638687D-10, 0.4600027054714D+01, 0.5328719641544D+00,  0.3440287244435D-10, 0.4349525970742D+01, 0.8582758298370D-01,  0.3330628322713D-10, 0.2347391505082D+01, 0.1104591729320D-01,  0.2973060707184D-10, 0.4789409286400D+01, 0.5257585094865D+00,  0.2932606766089D-10, 0.5831693799927D+01, 0.5336234347371D+00,  0.2876972310953D-10, 0.2692638514771D+01, 0.1173197218910D+00,  0.2827488278556D-10, 0.2056052487960D+01, 0.2022531624851D+00,  0.2515028239756D-10, 0.7411863262449D+00, 0.9597935788730D-01,  0.2853033744415D-10, 0.3948481024894D+01, 0.2118763888447D+01 /"
	analyzeline: implied-DO list "((s1(i,j,1),i=1,3),j= 41,ns1x)" is not supported. Skipping.
Line #19258 in sofapy.f:"      DATA ((S2(I,J,1),I=1,3),J=  1,NS2X) /  0.1603551636587D-11, 0.4404109410481D+01, 0.2061856251104D+00,  0.1556935889384D-11, 0.4818040873603D+00, 0.2204125344462D+00,  0.1182594414915D-11, 0.9935762734472D+00, 0.5225775174439D+00,  0.1158794583180D-11, 0.3353180966450D+01, 0.5368044267797D+00,  0.9597358943932D-12, 0.5567045358298D+01, 0.2132990797783D+00,  0.6511516579605D-12, 0.5630872420788D+01, 0.4265981595566D+00,  0.7419792747688D-12, 0.2156188581957D+01, 0.5296909721118D+00,  0.3951972655848D-12, 0.1981022541805D+01, 0.1059381944224D+01,  0.4478223877045D-12, 0.0000000000000D+00, 0.0000000000000D+00 /"
	analyzeline: implied-DO list "((s2(i,j,1),i=1,3),j=  1,ns2x)" is not supported. Skipping.
Line #19269 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=  1, 10) /  0.4955392320126D-02, 0.2170467313679D+01, 0.5296909721118D+00,  0.2722325167392D-02, 0.2444433682196D+01, 0.2132990797783D+00,  0.1546579925346D-02, 0.5992779281546D+00, 0.3813291813120D-01,  0.8363140252966D-03, 0.7687356310801D+00, 0.7478166569050D-01,  0.3385792683603D-03, 0.0000000000000D+00, 0.0000000000000D+00,  0.1201192221613D-03, 0.2520035601514D+01, 0.1059381944224D+01,  0.7587125720554D-04, 0.1669954006449D+01, 0.4265981595566D+00,  0.1964155361250D-04, 0.5707743963343D+01, 0.2061856251104D+00,  0.1891900364909D-04, 0.2320960679937D+01, 0.2204125344462D+00,  0.1937373433356D-04, 0.3226940689555D+01, 0.1495633313810D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #19280 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 11, 20) /  0.1437139941351D-04, 0.2301626908096D+01, 0.5225775174439D+00,  0.1406267683099D-04, 0.5188579265542D+01, 0.5368044267797D+00,  0.1178703080346D-04, 0.5489483248476D+01, 0.7626583626240D-01,  0.8079835186041D-05, 0.1683751835264D+01, 0.3664874755930D-01,  0.7623253594652D-05, 0.2656400462961D+01, 0.3961708870310D-01,  0.6248667483971D-05, 0.4992775362055D+01, 0.7329749511860D-01,  0.4366353695038D-05, 0.2869706279678D+01, 0.1589072916335D+01,  0.3829101568895D-05, 0.3572131359950D+01, 0.7113454667900D-02,  0.3175733773908D-05, 0.4535372530045D+01, 0.4194847048887D+00,  0.3092437902159D-05, 0.9230153317909D+00, 0.6398972393349D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #19291 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 21, 30) /  0.2874168812154D-05, 0.3363143761101D+01, 0.1102062672231D+00,  0.3040119321826D-05, 0.3324250895675D+01, 0.6283075850446D+01,  0.2699723308006D-05, 0.2917882441928D+00, 0.1030928125552D+00,  0.2134832683534D-05, 0.4220997202487D+01, 0.3163918923335D+00,  0.1770412139433D-05, 0.4747318496462D+01, 0.1021328554739D+02,  0.1377264209373D-05, 0.4305058462401D+00, 0.1484170571900D-02,  0.1127814538960D-05, 0.8538177240740D+00, 0.6327837846670D+00,  0.1055608090130D-05, 0.1551800742580D+01, 0.4337116142245D+00,  0.9802673861420D-06, 0.1459646735377D+01, 0.1052268489556D+01,  0.1090329461951D-05, 0.1587351228711D+01, 0.1162474756779D+01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #19302 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 31, 40) /  0.6959590025090D-06, 0.5534442628766D+01, 0.1066495398892D+01,  0.5664914529542D-06, 0.6030673003297D+01, 0.9491756770005D+00,  0.6607787763599D-06, 0.4989507233927D+01, 0.8460828644453D+00,  0.6269725742838D-06, 0.4222951804572D+01, 0.1480791608091D+00,  0.6301889697863D-06, 0.5444316669126D+01, 0.2243449970715D+00,  0.4891042662861D-06, 0.1490552839784D+01, 0.3340612434717D+01,  0.3457083123290D-06, 0.3030475486049D+01, 0.3516457698740D-01,  0.3032559967314D-06, 0.2652038793632D+01, 0.1104591729320D-01,  0.2841133988903D-06, 0.1276744786829D+01, 0.4110125927500D-01,  0.2855564444432D-06, 0.2143368674733D+01, 0.1510475019529D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #19313 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 41, 50) /  0.2765157135038D-06, 0.5444186109077D+01, 0.6373574839730D-01,  0.2382312465034D-06, 0.2190521137593D+01, 0.2275259891141D+00,  0.2808060365077D-06, 0.5735195064841D+01, 0.2535050500000D-01,  0.2332175234405D-06, 0.9481985524859D-01, 0.7181332454670D-01,  0.2322488199659D-06, 0.5180499361533D+01, 0.8582758298370D-01,  0.1881850258423D-06, 0.3219788273885D+01, 0.2118763888447D+01,  0.2196111392808D-06, 0.2366941159761D+01, 0.2968341143800D-02,  0.2183810335519D-06, 0.4825445110915D+01, 0.7775000683430D-01,  0.2002733093326D-06, 0.2457148995307D+01, 0.2093666171530D+00,  0.1967111767229D-06, 0.5586291545459D+01, 0.2172315424036D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #19324 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 51, 60) /  0.1568473250543D-06, 0.3708003123320D+01, 0.7429900518901D+00,  0.1852528314300D-06, 0.4310638151560D+01, 0.2022531624851D+00,  0.1832111226447D-06, 0.1494665322656D+01, 0.3235053470014D+00,  0.1746805502310D-06, 0.1451378500784D+01, 0.1385174140878D+00,  0.1555730966650D-06, 0.1068040418198D+01, 0.7358765972222D+00,  0.1554883462559D-06, 0.2442579035461D+01, 0.5154640627760D+00,  0.1638380568746D-06, 0.2597913420625D+00, 0.8531963191132D+00,  0.1159938593640D-06, 0.5834512021280D+01, 0.1990721704425D+00,  0.1083427965695D-06, 0.5054033177950D+01, 0.5439178814476D+00,  0.1156480369431D-06, 0.5325677432457D+01, 0.5257585094865D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #19335 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 61, 70) /  0.1141308860095D-06, 0.2153403923857D+01, 0.5336234347371D+00,  0.7913146470946D-07, 0.8642846847027D+00, 0.1478866649112D+01,  0.7439752463733D-07, 0.1970628496213D+01, 0.2164800718209D+00,  0.7280277104079D-07, 0.6073307250609D+01, 0.2101180877357D+00,  0.8319567719136D-07, 0.1954371928334D+01, 0.1692165728891D+01,  0.7137705549290D-07, 0.8904989440909D+00, 0.4155522422634D+00,  0.6900825396225D-07, 0.2825717714977D+01, 0.1173197218910D+00,  0.7245757216635D-07, 0.2481677513331D+01, 0.1265567569334D+01,  0.6961165696255D-07, 0.1292955312978D+01, 0.9562891316684D+00,  0.7571804456890D-07, 0.3427517575069D+01, 0.1422690933580D-01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 61, 70)" is not supported. Skipping.
Line #19346 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 71, 80) /  0.6605425721904D-07, 0.8052192701492D+00, 0.6470106940028D+00,  0.7375477357248D-07, 0.1705076390088D+01, 0.1581959461667D+01,  0.7041664951470D-07, 0.4848356967891D+00, 0.9597935788730D-01,  0.6322199535763D-07, 0.3878069473909D+01, 0.7084920306520D-01,  0.5244380279191D-07, 0.2645560544125D+01, 0.5265099800692D+00,  0.5143125704988D-07, 0.4834486101370D+01, 0.5328719641544D+00,  0.5871866319373D-07, 0.7981472548900D+00, 0.7871412831580D-01,  0.6300822573871D-07, 0.5979398788281D+01, 0.2608790314060D+02,  0.6062154271548D-07, 0.4108655402756D+01, 0.1114304132498D+00,  0.4361912339976D-07, 0.5322624319280D+01, 0.1375773836557D+01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 71, 80)" is not supported. Skipping.
Line #19357 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 81, 90) /  0.4417005920067D-07, 0.6240817359284D+01, 0.2770348281756D+00,  0.4686806749936D-07, 0.3214977301156D+01, 0.1143987543936D+00,  0.3758892132305D-07, 0.5879809634765D+01, 0.1596186371003D+01,  0.5151351332319D-07, 0.2893377688007D+00, 0.2228608264996D+00,  0.4554683578572D-07, 0.5475427144122D+01, 0.1465949902372D+00,  0.3442381385338D-07, 0.5992034796640D+01, 0.5070101000000D-01,  0.2831093954933D-07, 0.5367350273914D+01, 0.3092784376656D+00,  0.3756267090084D-07, 0.5758171285420D+01, 0.4903339079539D+00,  0.2816374679892D-07, 0.1863718700923D+01, 0.2991266627620D+00,  0.3419307025569D-07, 0.9524347534130D+00, 0.3518164938661D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 81, 90)" is not supported. Skipping.
Line #19368 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J= 91,100) /  0.2904250494239D-07, 0.5304471615602D+01, 0.1099462426779D+00,  0.2471734511206D-07, 0.1297069793530D+01, 0.6256703299991D+00,  0.2539620831872D-07, 0.3281126083375D+01, 0.1256615170089D+02,  0.2281017868007D-07, 0.1829122133165D+01, 0.6681224869435D+01,  0.2275319473335D-07, 0.5797198160181D+01, 0.3932462625300D-02,  0.2547755368442D-07, 0.4752697708330D+01, 0.1169588211447D+01,  0.2285979669317D-07, 0.1223205292886D+01, 0.1045155034888D+01,  0.1913386560994D-07, 0.1757532993389D+01, 0.1155361302111D+01,  0.1809020525147D-07, 0.4246116108791D+01, 0.3368040641550D-01,  0.1649213300201D-07, 0.1445162890627D+01, 0.4408250688924D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j= 91,100)" is not supported. Skipping.
Line #19379 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=101,110) /  0.1834972793932D-07, 0.1126917567225D+01, 0.4452511715700D-02,  0.1439550648138D-07, 0.6160756834764D+01, 0.9420622223326D+00,  0.1487645457041D-07, 0.4358761931792D+01, 0.4123712502208D+00,  0.1731729516660D-07, 0.6134456753344D+01, 0.2108507877249D+00,  0.1717747163567D-07, 0.1898186084455D+01, 0.2157473718317D+00,  0.1418190430374D-07, 0.4180286741266D+01, 0.6521991896920D-01,  0.1404844134873D-07, 0.7654053565412D-01, 0.4258542984690D-01,  0.1409842846538D-07, 0.4418612420312D+01, 0.2258291676434D+00,  0.1090948346291D-07, 0.1260615686131D+01, 0.4226656969313D+00,  0.1357577323612D-07, 0.3558248818690D+01, 0.7923417740620D-01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=101,110)" is not supported. Skipping.
Line #19390 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=111,120) /  0.1018154061960D-07, 0.5676087241256D+01, 0.1456308687557D+00,  0.1412073972109D-07, 0.8394392632422D+00, 0.1525316725248D+00,  0.1030938326496D-07, 0.1653593274064D+01, 0.1795258541446D+01,  0.1180081567104D-07, 0.1285802592036D+01, 0.7032915397480D-01,  0.9708510575650D-08, 0.7631889488106D+00, 0.8434341241180D-01,  0.9637689663447D-08, 0.4630642649176D+01, 0.1272681024002D+01,  0.1068910429389D-07, 0.5294934032165D+01, 0.2123349582968D+00,  0.1063716179336D-07, 0.2736266800832D+01, 0.2142632012598D+00,  0.1234858713814D-07, 0.1302891146570D+01, 0.1847279083684D+00,  0.8912631189738D-08, 0.3570415993621D+01, 0.2648454860559D+01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=111,120)" is not supported. Skipping.
Line #19401 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=121,130) /  0.1036378285534D-07, 0.4236693440949D+01, 0.1370332435159D+00,  0.9667798501561D-08, 0.2960768892398D+01, 0.4376440768498D+00,  0.8108314201902D-08, 0.6987781646841D+00, 0.2880807454688D+00,  0.7648364324628D-08, 0.2499017863863D+01, 0.2037373330570D+00,  0.7286136828406D-08, 0.3787426951665D+01, 0.1129145838217D+00,  0.9448237743913D-08, 0.2694354332983D+01, 0.5272426800584D+00,  0.9374276106428D-08, 0.4787121277064D+01, 0.5321392641652D+00,  0.7100226287462D-08, 0.3530238792101D+00, 0.6288513220417D+00,  0.9253056659571D-08, 0.1399478925664D+01, 0.1606092486742D+00,  0.6636432145504D-08, 0.3479575438447D+01, 0.1368660381889D+01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=121,130)" is not supported. Skipping.
Line #19412 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=131,140) /  0.6469975312932D-08, 0.1383669964800D+01, 0.2008557621224D+01,  0.7335849729765D-08, 0.1243698166898D+01, 0.9561746721300D-02,  0.8743421205855D-08, 0.3776164289301D+01, 0.3801276407308D+00,  0.5993635744494D-08, 0.5627122113596D+01, 0.2042657109477D+02,  0.5981008479693D-08, 0.1674336636752D+01, 0.2111650433779D+01,  0.6188535145838D-08, 0.5214925208672D+01, 0.4305306221819D+00,  0.6596074017566D-08, 0.2907653268124D+01, 0.1063314406849D+01,  0.6630815126226D-08, 0.2127643669658D+01, 0.8389694097774D+00,  0.6156772830040D-08, 0.5082160803295D+01, 0.4234171675140D+00,  0.6446960563014D-08, 0.1872100916905D+01, 0.5287268506303D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=131,140)" is not supported. Skipping.
Line #19423 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=141,150) /  0.6429324424668D-08, 0.5610276103577D+01, 0.5306550935933D+00,  0.6302232396465D-08, 0.1592152049607D+01, 0.1253008786510D-01,  0.6399244436159D-08, 0.2746214421532D+01, 0.5217580628120D+02,  0.5474965172558D-08, 0.2317666374383D+01, 0.2221856701002D+01,  0.5339293190692D-08, 0.1084724961156D+01, 0.7466759693650D-01,  0.5334733683389D-08, 0.3594106067745D+01, 0.7489573444450D-01,  0.5392665782110D-08, 0.5630254365606D+01, 0.1055449481598D+01,  0.6682075673789D-08, 0.1518480041732D+01, 0.2213766559277D+00,  0.5079130495960D-08, 0.2739765115711D+01, 0.2132517061319D+00,  0.5077759793261D-08, 0.5290711290094D+01, 0.2133464534247D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=141,150)" is not supported. Skipping.
Line #19434 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=151,160) /  0.4832037368310D-08, 0.1404473217200D+01, 0.7160067364790D-01,  0.6463279674802D-08, 0.6038381695210D+01, 0.2209183458640D-01,  0.6240592771560D-08, 0.1290170653666D+01, 0.3306188016693D+00,  0.4672013521493D-08, 0.3261895939677D+01, 0.7796265773310D-01,  0.6500650750348D-08, 0.1154522312095D+01, 0.3884652414254D+00,  0.6344161389053D-08, 0.6206111545062D+01, 0.7605151500000D-01,  0.4682518370646D-08, 0.5409118796685D+01, 0.1073608853559D+01,  0.5329460015591D-08, 0.1202985784864D+01, 0.7287631425543D+00,  0.5701588675898D-08, 0.4098715257064D+01, 0.8731175355560D-01,  0.6030690867211D-08, 0.4132033218460D+00, 0.9846002785331D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=151,160)" is not supported. Skipping.
Line #19445 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=161,170) /  0.4336256312655D-08, 0.1211415991827D+01, 0.4297791515992D+00,  0.4688498808975D-08, 0.3765479072409D+01, 0.2127790306879D+00,  0.4675578609335D-08, 0.4265540037226D+01, 0.2138191288687D+00,  0.4225578112158D-08, 0.5237566010676D+01, 0.3407705765729D+00,  0.5139422230028D-08, 0.1507173079513D+01, 0.7233337363710D-01,  0.4619995093571D-08, 0.9023957449848D-01, 0.8603097737811D+00,  0.4494776255461D-08, 0.5414930552139D+00, 0.7381754420900D-01,  0.4274026276788D-08, 0.4145735303659D+01, 0.7574578717200D-01,  0.5018141789353D-08, 0.3344408829055D+01, 0.3180992042600D-02,  0.4866163952181D-08, 0.3348534657607D+01, 0.7722995774390D-01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=161,170)" is not supported. Skipping.
Line #19456 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=171,180) /  0.4111986020501D-08, 0.4198823597220D+00, 0.1451108196653D+00,  0.3356142784950D-08, 0.5609144747180D+01, 0.1274714967946D+00,  0.4070575554551D-08, 0.7028411059224D+00, 0.3503323232942D+00,  0.3257451857278D-08, 0.5624697983086D+01, 0.5296435984654D+00,  0.3256973703026D-08, 0.1857842076707D+01, 0.5297383457582D+00,  0.3830771508640D-08, 0.4562887279931D+01, 0.9098186128426D+00,  0.3725024005962D-08, 0.2358058692652D+00, 0.1084620721060D+00,  0.3136763921756D-08, 0.2049731526845D+01, 0.2346394437820D+00,  0.3795147256194D-08, 0.2432356296933D+00, 0.1862120789403D+00,  0.2877342229911D-08, 0.5631101279387D+01, 0.1905464808669D+01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=171,180)" is not supported. Skipping.
Line #19467 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=181,190) /  0.3076931798805D-08, 0.1117615737392D+01, 0.3628624111593D+00,  0.2734765945273D-08, 0.5899826516955D+01, 0.2131850110243D+00,  0.2733405296885D-08, 0.2130562964070D+01, 0.2134131485323D+00,  0.2898552353410D-08, 0.3462387048225D+00, 0.5291709230214D+00,  0.2893736103681D-08, 0.8534352781543D+00, 0.5302110212022D+00,  0.3095717734137D-08, 0.2875061429041D+01, 0.2976424921901D+00,  0.2636190425832D-08, 0.2242512846659D+01, 0.1485980103780D+01,  0.3645512095537D-08, 0.1354016903958D+01, 0.6044726378023D+00,  0.2808173547723D-08, 0.6705114365631D-01, 0.6225157782540D-01,  0.2625012866888D-08, 0.4775705748482D+01, 0.5268983110410D-01 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=181,190)" is not supported. Skipping.
Line #19478 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=191,200) /  0.2572233995651D-08, 0.2638924216139D+01, 0.1258454114666D+01,  0.2604238824792D-08, 0.4826358927373D+01, 0.2103781122809D+00,  0.2596886385239D-08, 0.3200388483118D+01, 0.2162200472757D+00,  0.3228057304264D-08, 0.5384848409563D+01, 0.2007689919132D+00,  0.2481601798252D-08, 0.5173373487744D+01, 0.1062562936266D+01,  0.2745977498864D-08, 0.6250966149853D+01, 0.5651155736444D+00,  0.2669878833811D-08, 0.4906001352499D+01, 0.1400015846597D+00,  0.3203986611711D-08, 0.5034333010005D+01, 0.7036329877322D+00,  0.3354961227212D-08, 0.6108262423137D+01, 0.4549093064213D+00,  0.2400407324558D-08, 0.2135399294955D+01, 0.2125476091956D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=191,200)" is not supported. Skipping.
Line #19489 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=201,210) /  0.2379905859802D-08, 0.5893721933961D+01, 0.2140505503610D+00,  0.2550844302187D-08, 0.3331940762063D+01, 0.1534957940063D+00,  0.2268824211001D-08, 0.1843418461035D+01, 0.2235935264888D+00,  0.2464700891204D-08, 0.3029548547230D+01, 0.2091065926078D+00,  0.2436814726024D-08, 0.4994717970364D+01, 0.2174915669488D+00,  0.2443623894745D-08, 0.2645102591375D+01, 0.1739420156204D+00,  0.2318701783838D-08, 0.5700547397897D+01, 0.7530171478090D-01,  0.2284448700256D-08, 0.5268898905872D+01, 0.7426161660010D-01,  0.2468848123510D-08, 0.5276280575078D+01, 0.2526561439362D+00,  0.2814052350303D-08, 0.6130168623475D+01, 0.5636314030725D+00 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=201,210)" is not supported. Skipping.
Line #19495 in sofapy.f:"      DATA ((S0(I,J,2),I=1,3),J=211,NS0Y) /  0.2243662755220D-08, 0.6631692457995D+00, 0.8886590321940D-01,  0.2330795855941D-08, 0.2499435487702D+01, 0.1056200952181D+01,  0.9757679038404D-09, 0.5796846023126D+01, 0.7826370942180D+02 /"
	analyzeline: implied-DO list "((s0(i,j,2),i=1,3),j=211,ns0y)" is not supported. Skipping.
Line #19506 in sofapy.f:"      DATA ((S1(I,J,2),I=1,3),J=  1, 10) /  0.8989047573576D-08, 0.5840593672122D+01, 0.4265981595566D+00,  0.7815938401048D-08, 0.1129664707133D+01, 0.2061856251104D+00,  0.7550926713280D-08, 0.6196589104845D+00, 0.2204125344462D+00,  0.6056556925895D-08, 0.1677494667846D+01, 0.1059381944224D+01,  0.5734142698204D-08, 0.4000920852962D+01, 0.5225775174439D+00,  0.5614341822459D-08, 0.3486722577328D+01, 0.5368044267797D+00,  0.1028678147656D-08, 0.1877141024787D+01, 0.7113454667900D-02,  0.7270792075266D-09, 0.5077167301739D+01, 0.6398972393349D+00,  0.8734141726040D-09, 0.9069550282609D-01, 0.4194847048887D+00,  0.5377371402113D-09, 0.6039381844671D+01, 0.4337116142245D+00 /"
	analyzeline: implied-DO list "((s1(i,j,2),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #19517 in sofapy.f:"      DATA ((S1(I,J,2),I=1,3),J= 11, 20) /  0.4729719431571D-09, 0.2153086311760D+01, 0.2132990797783D+00,  0.4458052820973D-09, 0.5059830025565D+01, 0.5296909721118D+00,  0.4406855467908D-09, 0.2027971692630D+01, 0.1589072916335D+01,  0.3101659310977D-09, 0.3317677981860D+01, 0.1052268489556D+01,  0.3016749232545D-09, 0.3913703482532D+01, 0.1066495398892D+01,  0.3198541352656D-09, 0.1275513098525D+01, 0.1495633313810D+00,  0.2142065389871D-09, 0.5301351614597D+01, 0.3163918923335D+00,  0.1902615247592D-09, 0.4894943352736D+00, 0.2275259891141D+00,  0.1613410990871D-09, 0.2449891130437D+01, 0.1102062672231D+00,  0.1576992165097D-09, 0.4211421447633D+01, 0.7626583626240D-01 /"
	analyzeline: implied-DO list "((s1(i,j,2),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #19528 in sofapy.f:"      DATA ((S1(I,J,2),I=1,3),J= 21, 30) /  0.1241637259894D-09, 0.4140803368133D+01, 0.5154640627760D+00,  0.1313974830355D-09, 0.3591920305503D+01, 0.3664874755930D-01,  0.1181697118258D-09, 0.1506314382788D+01, 0.6327837846670D+00,  0.1238239742779D-09, 0.7461405378404D+00, 0.3961708870310D-01,  0.1010107068241D-09, 0.6271010795475D+00, 0.7329749511860D-01,  0.9226316616509D-10, 0.1259158839583D+01, 0.1990721704425D+00,  0.8664946419555D-10, 0.3353244696934D+01, 0.5439178814476D+00,  0.7757230468978D-10, 0.1447677295196D+01, 0.9491756770005D+00,  0.7693168628139D-10, 0.1120509896721D+01, 0.1030928125552D+00,  0.5487897454612D-10, 0.4439380426795D+01, 0.8531963191132D+00 /"
	analyzeline: implied-DO list "((s1(i,j,2),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #19539 in sofapy.f:"      DATA ((S1(I,J,2),I=1,3),J= 31, 40) /  0.5196118677218D-10, 0.3788856619137D+00, 0.2093666171530D+00,  0.5110853339935D-10, 0.1386879372016D+01, 0.2172315424036D+00,  0.5027804534813D-10, 0.1647881805466D+00, 0.2164800718209D+00,  0.4922485922674D-10, 0.1594315079862D+01, 0.2101180877357D+00,  0.6155599524400D-10, 0.0000000000000D+00, 0.0000000000000D+00,  0.4447147832161D-10, 0.5480720918976D+01, 0.3235053470014D+00,  0.4144691276422D-10, 0.1931371033660D+01, 0.6373574839730D-01,  0.4099950625452D-10, 0.5229611294335D+01, 0.6470106940028D+00,  0.5060541682953D-10, 0.1731112486298D+01, 0.1422690933580D-01,  0.4293615946300D-10, 0.2714571038925D+01, 0.7358765972222D+00 /"
	analyzeline: implied-DO list "((s1(i,j,2),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #19552 in sofapy.f:"      DATA ((S1(I,J,2),I=1,3),J= 41,NS1Y) /  0.3545659845763D-10, 0.4451041444634D+01, 0.5265099800692D+00,  0.3479112041196D-10, 0.3029385448081D+01, 0.5328719641544D+00,  0.3438516493570D-10, 0.2778507143731D+01, 0.8582758298370D-01,  0.3297341285033D-10, 0.7898709807584D+00, 0.1104591729320D-01,  0.2972585818015D-10, 0.3218785316973D+01, 0.5257585094865D+00,  0.2931707295017D-10, 0.4260731012098D+01, 0.5336234347371D+00,  0.2897198149403D-10, 0.1120753978101D+01, 0.1173197218910D+00,  0.2832293240878D-10, 0.4597682717827D+00, 0.2022531624851D+00,  0.2864348326612D-10, 0.2169939928448D+01, 0.9597935788730D-01,  0.2852714675471D-10, 0.2377659870578D+01, 0.2118763888447D+01 /"
	analyzeline: implied-DO list "((s1(i,j,2),i=1,3),j= 41,ns1y)" is not supported. Skipping.
Line #19564 in sofapy.f:"      DATA ((S2(I,J,2),I=1,3),J=  1,NS2Y) /  0.1609114495091D-11, 0.2831096993481D+01, 0.2061856251104D+00,  0.1560330784946D-11, 0.5193058213906D+01, 0.2204125344462D+00,  0.1183535479202D-11, 0.5707003443890D+01, 0.5225775174439D+00,  0.1158183066182D-11, 0.1782400404928D+01, 0.5368044267797D+00,  0.1032868027407D-11, 0.4036925452011D+01, 0.2132990797783D+00,  0.6540142847741D-12, 0.4058241056717D+01, 0.4265981595566D+00,  0.7305236491596D-12, 0.6175401942957D+00, 0.5296909721118D+00, -0.5580725052968D-12, 0.0000000000000D+00, 0.0000000000000D+00,  0.3946122651015D-12, 0.4108265279171D+00, 0.1059381944224D+01 /"
	analyzeline: implied-DO list "((s2(i,j,2),i=1,3),j=  1,ns2y)" is not supported. Skipping.
Line #19575 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J=  1, 10) /  0.1181255122986D-03, 0.4607918989164D+00, 0.2132990797783D+00,  0.1127777651095D-03, 0.4169146331296D+00, 0.5296909721118D+00,  0.4777754401806D-04, 0.4582657007130D+01, 0.3813291813120D-01,  0.1129354285772D-04, 0.5758735142480D+01, 0.7478166569050D-01, -0.1149543637123D-04, 0.0000000000000D+00, 0.0000000000000D+00,  0.3298730512306D-05, 0.5978801994625D+01, 0.4265981595566D+00,  0.2733376706079D-05, 0.7665413691040D+00, 0.1059381944224D+01,  0.9426389657270D-06, 0.3710201265838D+01, 0.2061856251104D+00,  0.8187517749552D-06, 0.3390675605802D+00, 0.2204125344462D+00,  0.4080447871819D-06, 0.4552296640088D+00, 0.5225775174439D+00 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #19586 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 11, 20) /  0.3169973017028D-06, 0.3445455899321D+01, 0.5368044267797D+00,  0.2438098615549D-06, 0.5664675150648D+01, 0.3664874755930D-01,  0.2601897517235D-06, 0.1931894095697D+01, 0.1495633313810D+00,  0.2314558080079D-06, 0.3666319115574D+00, 0.3961708870310D-01,  0.1962549548002D-06, 0.3167411699020D+01, 0.7626583626240D-01,  0.2180518287925D-06, 0.1544420746580D+01, 0.7113454667900D-02,  0.1451382442868D-06, 0.1583756740070D+01, 0.1102062672231D+00,  0.1358439007389D-06, 0.5239941758280D+01, 0.6398972393349D+00,  0.1050585898028D-06, 0.2266958352859D+01, 0.3163918923335D+00,  0.1050029870186D-06, 0.2711495250354D+01, 0.4194847048887D+00 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 11, 20)" is not supported. Skipping.
Line #19597 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 21, 30) /  0.9934920679800D-07, 0.1116208151396D+01, 0.1589072916335D+01,  0.1048395331560D-06, 0.3408619600206D+01, 0.1021328554739D+02,  0.8370147196668D-07, 0.3810459401087D+01, 0.2535050500000D-01,  0.7989856510998D-07, 0.3769910473647D+01, 0.7329749511860D-01,  0.5441221655233D-07, 0.2416994903374D+01, 0.1030928125552D+00,  0.4610812906784D-07, 0.5858503336994D+01, 0.4337116142245D+00,  0.3923022803444D-07, 0.3354170010125D+00, 0.1484170571900D-02,  0.2610725582128D-07, 0.5410600646324D+01, 0.6327837846670D+00,  0.2455279767721D-07, 0.6120216681403D+01, 0.1162474756779D+01,  0.2375530706525D-07, 0.6055443426143D+01, 0.1052268489556D+01 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 21, 30)" is not supported. Skipping.
Line #19608 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 31, 40) /  0.1782967577553D-07, 0.3146108708004D+01, 0.8460828644453D+00,  0.1581687095238D-07, 0.6255496089819D+00, 0.3340612434717D+01,  0.1594657672461D-07, 0.3782604300261D+01, 0.1066495398892D+01,  0.1563448615040D-07, 0.1997775733196D+01, 0.2022531624851D+00,  0.1463624258525D-07, 0.1736316792088D+00, 0.3516457698740D-01,  0.1331585056673D-07, 0.4331941830747D+01, 0.9491756770005D+00,  0.1130634557637D-07, 0.6152017751825D+01, 0.2968341143800D-02,  0.1028949607145D-07, 0.2101792614637D+00, 0.2275259891141D+00,  0.1024074971618D-07, 0.4071833211074D+01, 0.5070101000000D-01,  0.8826956060303D-08, 0.4861633688145D+00, 0.2093666171530D+00 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 31, 40)" is not supported. Skipping.
Line #19619 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 41, 50) /  0.8572230171541D-08, 0.5268190724302D+01, 0.4110125927500D-01,  0.7649332643544D-08, 0.5134543417106D+01, 0.2608790314060D+02,  0.8581673291033D-08, 0.2920218146681D+01, 0.1480791608091D+00,  0.8430589300938D-08, 0.3604576619108D+01, 0.2172315424036D+00,  0.7776165501012D-08, 0.3772942249792D+01, 0.6373574839730D-01,  0.8311070234408D-08, 0.6200412329888D+01, 0.3235053470014D+00,  0.6927365212582D-08, 0.4543353113437D+01, 0.8531963191132D+00,  0.6791574208598D-08, 0.2882188406238D+01, 0.7181332454670D-01,  0.5593100811839D-08, 0.1776646892780D+01, 0.7429900518901D+00,  0.4553381853021D-08, 0.3949617611240D+01, 0.7775000683430D-01 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 41, 50)" is not supported. Skipping.
Line #19630 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 51, 60) /  0.5758000450068D-08, 0.3859251775075D+01, 0.1990721704425D+00,  0.4281283457133D-08, 0.1466294631206D+01, 0.2118763888447D+01,  0.4206935661097D-08, 0.5421776011706D+01, 0.1104591729320D-01,  0.4213751641837D-08, 0.3412048993322D+01, 0.2243449970715D+00,  0.5310506239878D-08, 0.5421641370995D+00, 0.5154640627760D+00,  0.3827450341320D-08, 0.8887314524995D+00, 0.1510475019529D+00,  0.4292435241187D-08, 0.1405043757194D+01, 0.1422690933580D-01,  0.3189780702289D-08, 0.1060049293445D+01, 0.1173197218910D+00,  0.3226611928069D-08, 0.6270858897442D+01, 0.2164800718209D+00,  0.2893897608830D-08, 0.5117563223301D+01, 0.6470106940028D+00 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 51, 60)" is not supported. Skipping.
Line #19642 in sofapy.f:"      DATA ((S0(I,J,3),I=1,3),J= 61,NS0Z) /  0.3239852024578D-08, 0.4079092237983D+01, 0.2101180877357D+00,  0.2956892222200D-08, 0.1594917021704D+01, 0.3092784376656D+00,  0.2980177912437D-08, 0.5258787667564D+01, 0.4155522422634D+00,  0.3163725690776D-08, 0.3854589225479D+01, 0.8582758298370D-01,  0.2662262399118D-08, 0.3561326430187D+01, 0.5257585094865D+00,  0.2766689135729D-08, 0.3180732086830D+00, 0.1385174140878D+00,  0.2411600278464D-08, 0.3324798335058D+01, 0.5439178814476D+00,  0.2483527695131D-08, 0.4169069291947D+00, 0.5336234347371D+00,  0.7788777276590D-09, 0.1900569908215D+01, 0.5217580628120D+02 /"
	analyzeline: implied-DO list "((s0(i,j,3),i=1,3),j= 61,ns0z)" is not supported. Skipping.
Line #19653 in sofapy.f:"      DATA ((S1(I,J,3),I=1,3),J=  1, 10) /  0.5444220475678D-08, 0.1803825509310D+01, 0.2132990797783D+00,  0.3883412695596D-08, 0.4668616389392D+01, 0.5296909721118D+00,  0.1334341434551D-08, 0.0000000000000D+00, 0.0000000000000D+00,  0.3730001266883D-09, 0.5401405918943D+01, 0.2061856251104D+00,  0.2894929197956D-09, 0.4932415609852D+01, 0.2204125344462D+00,  0.2857950357701D-09, 0.3154625362131D+01, 0.7478166569050D-01,  0.2499226432292D-09, 0.3657486128988D+01, 0.4265981595566D+00,  0.1937705443593D-09, 0.5740434679002D+01, 0.1059381944224D+01,  0.1374894396320D-09, 0.1712857366891D+01, 0.5368044267797D+00,  0.1217248678408D-09, 0.2312090870932D+01, 0.5225775174439D+00 /"
	analyzeline: implied-DO list "((s1(i,j,3),i=1,3),j=  1, 10)" is not supported. Skipping.
Line #19660 in sofapy.f:"      DATA ((S1(I,J,3),I=1,3),J= 11,NS1Z) /  0.7961052740870D-10, 0.5283368554163D+01, 0.3813291813120D-01,  0.4979225949689D-10, 0.4298290471860D+01, 0.4194847048887D+00,  0.4388552286597D-10, 0.6145515047406D+01, 0.7113454667900D-02,  0.2586835212560D-10, 0.3019448001809D+01, 0.6398972393349D+00 /"
	analyzeline: implied-DO list "((s1(i,j,3),i=1,3),j= 11,ns1z)" is not supported. Skipping.
Line #19664 in sofapy.f:"      DATA ((S2(I,J,3),I=1,3),J=  1,NS2Z) /  0.3749920358054D-12, 0.3230285558668D+01, 0.2132990797783D+00,  0.2735037220939D-12, 0.6154322683046D+01, 0.5296909721118D+00 /"
	analyzeline: implied-DO list "((s2(i,j,3),i=1,3),j=  1,ns2z)" is not supported. Skipping.
Line #26591 in sofapy.f:"      PARAMETER ( A = 24110.54841D0 - D2S/2D0,            B = 8640184.812866D0,            C = 0.093104D0,            D = -6.2D-6 )"
	determineexprtype: could not determine expressions ('24110.54841d0 - d2s/2d0') type.
analyzeline: Failed to evaluate '24110.54841d0 - d2s/2d0'. Ignoring: invalid syntax (<string>, line 1)
{'before': '', 'this': 'intent', 'after': '(in) rh, dh, drh, ddh, pxh, rvh,'}
Line #27766 in sofapy.f:"        intent(in) RH, DH, DRH, DDH, PXH, RVH,"
	analyzeline: no name pattern found in intent statement for ''. Skipping.
Line #31080 in sofapy.f:"      DATA ((PQPOL(I,J),I=1,NPOL),J=1,2) /       +5851.607687    D0,          -0.1189000   D0,          -0.00028913  D0,          +0.000000101 D0,       -1600.886300    D0,          +1.1689818   D0,          -0.00000020  D0,          -0.000000437 D0 /"
	analyzeline: implied-DO list "((pqpol(i,j),i=1,npol),j=1,2)" is not supported. Skipping.
Line #31100 in sofapy.f:"       DATA ((PQPER(I,J),I=1,5),J=1,NPER) /   708.15D0,  -5486.751211D0,   -684.661560D0,                667.666730D0,  -5523.863691D0,  2309.00D0,    -17.127623D0,   2446.283880D0,              -2354.886252D0,   -549.747450D0,  1620.00D0,   -617.517403D0,    399.671049D0,               -428.152441D0,   -310.998056D0,   492.20D0,    413.442940D0,   -356.652376D0,                376.202861D0,    421.535876D0,  1183.00D0,     78.614193D0,   -186.387003D0,                184.778874D0,    -36.776172D0,   622.00D0,   -180.732815D0,   -316.800070D0,                335.321713D0,   -145.278396D0,   882.00D0,    -87.676083D0,    198.296701D0,               -185.138669D0,    -34.744450D0,   547.00D0,     46.140315D0,    101.135679D0,               -120.972830D0,     22.885731D0 /"
	analyzeline: implied-DO list "((pqper(i,j),i=1,5),j=1,nper)" is not supported. Skipping.
Line #31331 in sofapy.f:"      DATA ((XYPOL(I,J),I=1,NPOL),J=1,2) /       +5453.282155    D0,          +0.4252841   D0,          -0.00037173  D0,          -0.000000152 D0,      -73750.930350    D0,          -0.7675452   D0,          -0.00018725  D0,          +0.000000231 D0 /"
	analyzeline: implied-DO list "((xypol(i,j),i=1,npol),j=1,2)" is not supported. Skipping.
Line #31363 in sofapy.f:"       DATA ((XYPER(I,J),I=1,5),J=1,NPER) /   256.75D0,   -819.940624D0,  75004.344875D0,              81491.287984D0,   1558.515853D0,   708.15D0,  -8444.676815D0,    624.033993D0,                787.163481D0,   7774.939698D0,   274.20D0,   2600.009459D0,   1251.136893D0,               1251.296102D0,  -2219.534038D0,   241.45D0,   2755.175630D0,  -1102.212834D0,              -1257.950837D0,  -2523.969396D0,  2309.00D0,   -167.659835D0,  -2660.664980D0,              -2966.799730D0,    247.850422D0,   492.20D0,    871.855056D0,    699.291817D0,                639.744522D0,   -846.485643D0,   396.10D0,     44.769698D0,    153.167220D0,                131.600209D0,  -1393.124055D0,   288.90D0,   -512.313065D0,   -950.865637D0,               -445.040117D0,    368.526116D0,   231.10D0,   -819.415595D0,    499.754645D0,                584.522874D0,    749.045012D0,  1610.00D0,   -538.071099D0,   -145.188210D0,                -89.756563D0,    444.704518D0,   620.00D0,   -189.793622D0,    558.116553D0,                524.429630D0,    235.934465D0,   157.87D0,   -402.922932D0,    -23.923029D0,                -13.549067D0,    374.049623D0,   220.30D0,    179.516345D0,   -165.405086D0,               -210.157124D0,   -171.330180D0,  1200.00D0,     -9.814756D0,      9.344131D0,                -44.919798D0,    -22.899655D0 /"
	analyzeline: implied-DO list "((xyper(i,j),i=1,5),j=1,nper)" is not supported. Skipping.
Line #32465 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=  1, 10 ) /          0,    0,    0,    0,    1,          0,    0,    2,   -2,    2,          0,    0,    2,    0,    2,          0,    0,    0,    0,    2,          0,    1,    0,    0,    0,          0,    1,    2,   -2,    2,          1,    0,    0,    0,    0,          0,    0,    2,    0,    1,          1,    0,    2,    0,    2,          0,   -1,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=  1, 10 )" is not supported. Skipping.
Line #32476 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 11, 20 ) /          0,    0,    2,   -2,    1,         -1,    0,    2,    0,    2,         -1,    0,    0,    2,    0,          1,    0,    0,    0,    1,         -1,    0,    0,    0,    1,         -1,    0,    2,    2,    2,          1,    0,    2,    0,    1,         -2,    0,    2,    0,    1,          0,    0,    0,    2,    0,          0,    0,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 11, 20 )" is not supported. Skipping.
Line #32487 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 21, 30 ) /          0,   -2,    2,   -2,    2,         -2,    0,    0,    2,    0,          2,    0,    2,    0,    2,          1,    0,    2,   -2,    2,         -1,    0,    2,    0,    1,          2,    0,    0,    0,    0,          0,    0,    2,    0,    0,          0,    1,    0,    0,    1,         -1,    0,    0,    2,    1,          0,    2,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 21, 30 )" is not supported. Skipping.
Line #32498 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 31, 40 ) /          0,    0,   -2,    2,    0,          1,    0,    0,   -2,    1,          0,   -1,    0,    0,    1,         -1,    0,    2,    2,    1,          0,    2,    0,    0,    0,          1,    0,    2,    2,    2,         -2,    0,    2,    0,    0,          0,    1,    2,    0,    2,          0,    0,    2,    2,    1,          0,   -1,    2,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 31, 40 )" is not supported. Skipping.
Line #32509 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 41, 50 ) /          0,    0,    0,    2,    1,          1,    0,    2,   -2,    1,          2,    0,    2,   -2,    2,         -2,    0,    0,    2,    1,          2,    0,    2,    0,    1,          0,   -1,    2,   -2,    1,          0,    0,    0,   -2,    1,         -1,   -1,    0,    2,    0,          2,    0,    0,   -2,    1,          1,    0,    0,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 41, 50 )" is not supported. Skipping.
Line #32520 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 51, 60 ) /          0,    1,    2,   -2,    1,          1,   -1,    0,    0,    0,         -2,    0,    2,    0,    2,          3,    0,    2,    0,    2,          0,   -1,    0,    2,    0,          1,   -1,    2,    0,    2,          0,    0,    0,    1,    0,         -1,   -1,    2,    2,    2,         -1,    0,    2,    0,    0,          0,   -1,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 51, 60 )" is not supported. Skipping.
Line #32531 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 61, 70 ) /         -2,    0,    0,    0,    1,          1,    1,    2,    0,    2,          2,    0,    0,    0,    1,         -1,    1,    0,    1,    0,          1,    1,    0,    0,    0,          1,    0,    2,    0,    0,         -1,    0,    2,   -2,    1,          1,    0,    0,    0,    2,         -1,    0,    0,    1,    0,          0,    0,    2,    1,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 61, 70 )" is not supported. Skipping.
Line #32542 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 71, 80 ) /         -1,    0,    2,    4,    2,         -1,    1,    0,    1,    1,          0,   -2,    2,   -2,    1,          1,    0,    2,    2,    1,         -2,    0,    2,    2,    2,         -1,    0,    0,    0,    2,          1,    1,    2,   -2,    2,         -2,    0,    2,    4,    2,         -1,    0,    4,    0,    2,          2,    0,    2,   -2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 71, 80 )" is not supported. Skipping.
Line #32553 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 81, 90 ) /          2,    0,    2,    2,    2,          1,    0,    0,    2,    1,          3,    0,    0,    0,    0,          3,    0,    2,   -2,    2,          0,    0,    4,   -2,    2,          0,    1,    2,    0,    1,          0,    0,   -2,    2,    1,          0,    0,    2,   -2,    3,         -1,    0,    0,    4,    0,          2,    0,   -2,    0,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 81, 90 )" is not supported. Skipping.
Line #32564 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 91,100 ) /         -2,    0,    0,    4,    0,         -1,   -1,    0,    2,    1,         -1,    0,    0,    1,    1,          0,    1,    0,    0,    2,          0,    0,   -2,    0,    1,          0,   -1,    2,    0,    1,          0,    0,    2,   -1,    2,          0,    0,    2,    4,    2,         -2,   -1,    0,    2,    0,          1,    1,    0,   -2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 91,100 )" is not supported. Skipping.
Line #32575 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=101,110 ) /         -1,    1,    0,    2,    0,         -1,    1,    0,    1,    2,          1,   -1,    0,    0,    1,          1,   -1,    2,    2,    2,         -1,    1,    2,    2,    2,          3,    0,    2,    0,    1,          0,    1,   -2,    2,    0,         -1,    0,    0,   -2,    1,          0,    1,    2,    2,    2,         -1,   -1,    2,    2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=101,110 )" is not supported. Skipping.
Line #32586 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=111,120 ) /          0,   -1,    0,    0,    2,          1,    0,    2,   -4,    1,         -1,    0,   -2,    2,    0,          0,   -1,    2,    2,    1,          2,   -1,    2,    0,    2,          0,    0,    0,    2,    2,          1,   -1,    2,    0,    1,         -1,    1,    2,    0,    2,          0,    1,    0,    2,    0,          0,   -1,   -2,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=111,120 )" is not supported. Skipping.
Line #32597 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=121,130 ) /          0,    3,    2,   -2,    2,          0,    0,    0,    1,    1,         -1,    0,    2,    2,    0,          2,    1,    2,    0,    2,          1,    1,    0,    0,    1,          1,    1,    2,    0,    1,          2,    0,    0,    2,    0,          1,    0,   -2,    2,    0,         -1,    0,    0,    2,    2,          0,    1,    0,    1,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=121,130 )" is not supported. Skipping.
Line #32608 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=131,140 ) /          0,    1,    0,   -2,    1,         -1,    0,    2,   -2,    2,          0,    0,    0,   -1,    1,         -1,    1,    0,    0,    1,          1,    0,    2,   -1,    2,          1,   -1,    0,    2,    0,          0,    0,    0,    4,    0,          1,    0,    2,    1,    2,          0,    0,    2,    1,    1,          1,    0,    0,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=131,140 )" is not supported. Skipping.
Line #32619 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=141,150 ) /         -1,    0,    2,    4,    1,          1,    0,   -2,    0,    1,          1,    1,    2,   -2,    1,          0,    0,    2,    2,    0,         -1,    0,    2,   -1,    1,         -2,    0,    2,    2,    1,          4,    0,    2,    0,    2,          2,   -1,    0,    0,    0,          2,    1,    2,   -2,    2,          0,    1,    2,    1,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=141,150 )" is not supported. Skipping.
Line #32630 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=151,160 ) /          1,    0,    4,   -2,    2,         -1,   -1,    0,    0,    1,          0,    1,    0,    2,    1,         -2,    0,    2,    4,    1,          2,    0,    2,    0,    0,          1,    0,    0,    1,    0,         -1,    0,    0,    4,    1,         -1,    0,    4,    0,    1,          2,    0,    2,    2,    1,          0,    0,    2,   -3,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=151,160 )" is not supported. Skipping.
Line #32641 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=161,170 ) /         -1,   -2,    0,    2,    0,          2,    1,    0,    0,    0,          0,    0,    4,    0,    2,          0,    0,    0,    0,    3,          0,    3,    0,    0,    0,          0,    0,    2,   -4,    1,          0,   -1,    0,    2,    1,          0,    0,    0,    4,    1,         -1,   -1,    2,    4,    2,          1,    0,    2,    4,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=161,170 )" is not supported. Skipping.
Line #32652 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=171,180 ) /         -2,    2,    0,    2,    0,         -2,   -1,    2,    0,    1,         -2,    0,    0,    2,    2,         -1,   -1,    2,    0,    2,          0,    0,    4,   -2,    1,          3,    0,    2,   -2,    1,         -2,   -1,    0,    2,    1,          1,    0,    0,   -1,    1,          0,   -2,    0,    2,    0,         -2,    0,    0,    4,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=171,180 )" is not supported. Skipping.
Line #32663 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=181,190 ) /         -3,    0,    0,    0,    1,          1,    1,    2,    2,    2,          0,    0,    2,    4,    1,          3,    0,    2,    2,    2,         -1,    1,    2,   -2,    1,          2,    0,    0,   -4,    1,          0,    0,    0,   -2,    2,          2,    0,    2,   -4,    1,         -1,    1,    0,    2,    1,          0,    0,    2,   -1,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=181,190 )" is not supported. Skipping.
Line #32674 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=191,200 ) /          0,   -2,    2,    2,    2,          2,    0,    0,    2,    1,          4,    0,    2,   -2,    2,          2,    0,    0,   -2,    2,          0,    2,    0,    0,    1,          1,    0,    0,   -4,    1,          0,    2,    2,   -2,    1,         -3,    0,    0,    4,    0,         -1,    1,    2,    0,    1,         -1,   -1,    0,    4,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=191,200 )" is not supported. Skipping.
Line #32685 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=201,210 ) /         -1,   -2,    2,    2,    2,         -2,   -1,    2,    4,    2,          1,   -1,    2,    2,    1,         -2,    1,    0,    2,    0,         -2,    1,    2,    0,    1,          2,    1,    0,   -2,    1,         -3,    0,    2,    0,    1,         -2,    0,    2,   -2,    1,         -1,    1,    0,    2,    2,          0,   -1,    2,   -1,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=201,210 )" is not supported. Skipping.
Line #32696 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=211,220 ) /         -1,    0,    4,   -2,    2,          0,   -2,    2,    0,    2,         -1,    0,    2,    1,    2,          2,    0,    0,    0,    2,          0,    0,    2,    0,    3,         -2,    0,    4,    0,    2,         -1,    0,   -2,    0,    1,         -1,    1,    2,    2,    1,          3,    0,    0,    0,    1,         -1,    0,    2,    3,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=211,220 )" is not supported. Skipping.
Line #32707 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=221,230 ) /          2,   -1,    2,    0,    1,          0,    1,    2,    2,    1,          0,   -1,    2,    4,    2,          2,   -1,    2,    2,    2,          0,    2,   -2,    2,    0,         -1,   -1,    2,   -1,    1,          0,   -2,    0,    0,    1,          1,    0,    2,   -4,    2,          1,   -1,    0,   -2,    1,         -1,   -1,    2,    0,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=221,230 )" is not supported. Skipping.
Line #32718 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=231,240 ) /          1,   -1,    2,   -2,    2,         -2,   -1,    0,    4,    0,         -1,    0,    0,    3,    0,         -2,   -1,    2,    2,    2,          0,    2,    2,    0,    2,          1,    1,    0,    2,    0,          2,    0,    2,   -1,    2,          1,    0,    2,    1,    1,          4,    0,    0,    0,    0,          2,    1,    2,    0,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=231,240 )" is not supported. Skipping.
Line #32729 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=241,250 ) /          3,   -1,    2,    0,    2,         -2,    2,    0,    2,    1,          1,    0,    2,   -3,    1,          1,    1,    2,   -4,    1,         -1,   -1,    2,   -2,    1,          0,   -1,    0,   -1,    1,          0,   -1,    0,   -2,    1,         -2,    0,    0,    0,    2,         -2,    0,   -2,    2,    0,         -1,    0,   -2,    4,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=241,250 )" is not supported. Skipping.
Line #32740 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=251,260 ) /          1,   -2,    0,    0,    0,          0,    1,    0,    1,    1,         -1,    2,    0,    2,    0,          1,   -1,    2,   -2,    1,          1,    2,    2,   -2,    2,          2,   -1,    2,   -2,    2,          1,    0,    2,   -1,    1,          2,    1,    2,   -2,    1,         -2,    0,    0,   -2,    1,          1,   -2,    2,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=251,260 )" is not supported. Skipping.
Line #32751 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=261,270 ) /          0,    1,    2,    1,    1,          1,    0,    4,   -2,    1,         -2,    0,    4,    2,    2,          1,    1,    2,    1,    2,          1,    0,    0,    4,    0,          1,    0,    2,    2,    0,          2,    0,    2,    1,    2,          3,    1,    2,    0,    2,          4,    0,    2,    0,    1,         -2,   -1,    2,    0,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=261,270 )" is not supported. Skipping.
Line #32762 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=271,280 ) /          0,    1,   -2,    2,    1,          1,    0,   -2,    1,    0,          0,   -1,   -2,    2,    1,          2,   -1,    0,   -2,    1,         -1,    0,    2,   -1,    2,          1,    0,    2,   -3,    2,          0,    1,    2,   -2,    3,          0,    0,    2,   -3,    1,         -1,    0,   -2,    2,    1,          0,    0,    2,   -4,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=271,280 )" is not supported. Skipping.
Line #32773 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=281,290 ) /         -2,    1,    0,    0,    1,         -1,    0,    0,   -1,    1,          2,    0,    2,   -4,    2,          0,    0,    4,   -4,    4,          0,    0,    4,   -4,    2,         -1,   -2,    0,    2,    1,         -2,    0,    0,    3,    0,          1,    0,   -2,    2,    1,         -3,    0,    2,    2,    2,         -3,    0,    2,    2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=281,290 )" is not supported. Skipping.
Line #32784 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=291,300 ) /         -2,    0,    2,    2,    0,          2,   -1,    0,    0,    1,         -2,    1,    2,    2,    2,          1,    1,    0,    1,    0,          0,    1,    4,   -2,    2,         -1,    1,    0,   -2,    1,          0,    0,    0,   -4,    1,          1,   -1,    0,    2,    1,          1,    1,    0,    2,    1,         -1,    2,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=291,300 )" is not supported. Skipping.
Line #32795 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=301,310 ) /          3,    1,    2,   -2,    2,          0,   -1,    0,    4,    0,          2,   -1,    0,    2,    0,          0,    0,    4,    0,    1,          2,    0,    4,   -2,    2,         -1,   -1,    2,    4,    1,          1,    0,    0,    4,    1,          1,   -2,    2,    2,    2,          0,    0,    2,    3,    2,         -1,    1,    2,    4,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=301,310 )" is not supported. Skipping.
Line #32806 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=311,320 ) /          3,    0,    0,    2,    0,         -1,    0,    4,    2,    2,          1,    1,    2,    2,    1,         -2,    0,    2,    6,    2,          2,    1,    2,    2,    2,         -1,    0,    2,    6,    2,          1,    0,    2,    4,    1,          2,    0,    2,    4,    2,          1,    1,   -2,    1,    0,         -3,    1,    2,    1,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=311,320 )" is not supported. Skipping.
Line #32817 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=321,330 ) /          2,    0,   -2,    0,    2,         -1,    0,    0,    1,    2,         -4,    0,    2,    2,    1,         -1,   -1,    0,    1,    0,          0,    0,   -2,    2,    2,          1,    0,    0,   -1,    2,          0,   -1,    2,   -2,    3,         -2,    1,    2,    0,    0,          0,    0,    2,   -2,    4,         -2,   -2,    0,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=321,330 )" is not supported. Skipping.
Line #32828 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=331,340 ) /         -2,    0,   -2,    4,    0,          0,   -2,   -2,    2,    0,          1,    2,    0,   -2,    1,          3,    0,    0,   -4,    1,         -1,    1,    2,   -2,    2,          1,   -1,    2,   -4,    1,          1,    1,    0,   -2,    2,         -3,    0,    2,    0,    0,         -3,    0,    2,    0,    2,         -2,    0,    0,    1,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=331,340 )" is not supported. Skipping.
Line #32839 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=341,350 ) /          0,    0,   -2,    1,    0,         -3,    0,    0,    2,    1,         -1,   -1,   -2,    2,    0,          0,    1,    2,   -4,    1,          2,    1,    0,   -4,    1,          0,    2,    0,   -2,    1,          1,    0,    0,   -3,    1,         -2,    0,    2,   -2,    2,         -2,   -1,    0,    0,    1,         -4,    0,    0,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=341,350 )" is not supported. Skipping.
Line #32850 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=351,360 ) /          1,    1,    0,   -4,    1,         -1,    0,    2,   -4,    1,          0,    0,    4,   -4,    1,          0,    3,    2,   -2,    2,         -3,   -1,    0,    4,    0,         -3,    0,    0,    4,    1,          1,   -1,   -2,    2,    0,         -1,   -1,    0,    2,    2,          1,   -2,    0,    0,    1,          1,   -1,    0,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=351,360 )" is not supported. Skipping.
Line #32861 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=361,370 ) /          0,    0,    0,    1,    2,         -1,   -1,    2,    0,    0,          1,   -2,    2,   -2,    2,          0,   -1,    2,   -1,    1,         -1,    0,    2,    0,    3,          1,    1,    0,    0,    2,         -1,    1,    2,    0,    0,          1,    2,    0,    0,    0,         -1,    2,    2,    0,    2,         -1,    0,    4,   -2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=361,370 )" is not supported. Skipping.
Line #32872 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=371,380 ) /          3,    0,    2,   -4,    2,          1,    2,    2,   -2,    1,          1,    0,    4,   -4,    2,         -2,   -1,    0,    4,    1,          0,   -1,    0,    2,    2,         -2,    1,    0,    4,    0,         -2,   -1,    2,    2,    1,          2,    0,   -2,    2,    0,          1,    0,    0,    1,    1,          0,    1,    0,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=371,380 )" is not supported. Skipping.
Line #32883 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=381,390 ) /          1,   -1,    2,   -1,    2,         -2,    0,    4,    0,    1,          2,    1,    0,    0,    1,          0,    1,    2,    0,    0,          0,   -1,    4,   -2,    2,          0,    0,    4,   -2,    4,          0,    2,    2,    0,    1,         -3,    0,    0,    6,    0,         -1,   -1,    0,    4,    1,          1,   -2,    0,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=381,390 )" is not supported. Skipping.
Line #32894 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=391,400 ) /         -1,    0,    0,    4,    2,         -1,   -2,    2,    2,    1,         -1,    0,    0,   -2,    2,          1,    0,   -2,   -2,    1,          0,    0,   -2,   -2,    1,         -2,    0,   -2,    0,    1,          0,    0,    0,    3,    1,          0,    0,    0,    3,    0,         -1,    1,    0,    4,    0,         -1,   -1,    2,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=391,400 )" is not supported. Skipping.
Line #32905 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=401,410 ) /         -2,    0,    2,    3,    2,          1,    0,    0,    2,    2,          0,   -1,    2,    1,    2,          3,   -1,    0,    0,    0,          2,    0,    0,    1,    0,          1,   -1,    2,    0,    0,          0,    0,    2,    1,    0,          1,    0,    2,    0,    3,          3,    1,    0,    0,    0,          3,   -1,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=401,410 )" is not supported. Skipping.
Line #32916 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=411,420 ) /          2,    0,    2,   -1,    1,          1,    1,    2,    0,    0,          0,    0,    4,   -1,    2,          1,    2,    2,    0,    2,         -2,    0,    0,    6,    0,          0,   -1,    0,    4,    1,         -2,   -1,    2,    4,    1,          0,   -2,    2,    2,    1,          0,   -1,    2,    2,    0,         -1,    0,    2,    3,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=411,420 )" is not supported. Skipping.
Line #32927 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=421,430 ) /         -2,    1,    2,    4,    2,          2,    0,    0,    2,    2,          2,   -2,    2,    0,    2,         -1,    1,    2,    3,    2,          3,    0,    2,   -1,    2,          4,    0,    2,   -2,    1,         -1,    0,    0,    6,    0,         -1,   -2,    2,    4,    2,         -3,    0,    2,    6,    2,         -1,    0,    2,    4,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=421,430 )" is not supported. Skipping.
Line #32938 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=431,440 ) /          3,    0,    0,    2,    1,          3,   -1,    2,    0,    1,          3,    0,    2,    0,    0,          1,    0,    4,    0,    2,          5,    0,    2,   -2,    2,          0,   -1,    2,    4,    1,          2,   -1,    2,    2,    1,          0,    1,    2,    4,    2,          1,   -1,    2,    4,    2,          3,   -1,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=431,440 )" is not supported. Skipping.
Line #32949 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=441,450 ) /          3,    0,    2,    2,    1,          5,    0,    2,    0,    2,          0,    0,    2,    6,    2,          4,    0,    2,    2,    2,          0,   -1,    1,   -1,    1,         -1,    0,    1,    0,    3,          0,   -2,    2,   -2,    3,          1,    0,   -1,    0,    1,          2,   -2,    0,   -2,    1,         -1,    0,    1,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=441,450 )" is not supported. Skipping.
Line #32960 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=451,460 ) /         -1,    0,    1,    0,    1,         -1,   -1,    2,   -1,    2,         -2,    2,    0,    2,    2,         -1,    0,    1,    0,    0,         -4,    1,    2,    2,    2,         -3,    0,    2,    1,    1,         -2,   -1,    2,    0,    2,          1,    0,   -2,    1,    1,          2,   -1,   -2,    0,    1,         -4,    0,    2,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=451,460 )" is not supported. Skipping.
Line #32971 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=461,470 ) /         -3,    1,    0,    3,    0,         -1,    0,   -1,    2,    0,          0,   -2,    0,    0,    2,          0,   -2,    0,    0,    2,         -3,    0,    0,    3,    0,         -2,   -1,    0,    2,    2,         -1,    0,   -2,    3,    0,         -4,    0,    0,    4,    0,          2,    1,   -2,    0,    1,          2,   -1,    0,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=461,470 )" is not supported. Skipping.
Line #32982 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=471,480 ) /          0,    0,    1,   -1,    0,         -1,    2,    0,    1,    0,         -2,    1,    2,    0,    2,          1,    1,    0,   -1,    1,          1,    0,    1,   -2,    1,          0,    2,    0,    0,    2,          1,   -1,    2,   -3,    1,         -1,    1,    2,   -1,    1,         -2,    0,    4,   -2,    2,         -2,    0,    4,   -2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=471,480 )" is not supported. Skipping.
Line #32993 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=481,490 ) /         -2,   -2,    0,    2,    1,         -2,    0,   -2,    4,    0,          1,    2,    2,   -4,    1,          1,    1,    2,   -4,    2,         -1,    2,    2,   -2,    1,          2,    0,    0,   -3,    1,         -1,    2,    0,    0,    1,          0,    0,    0,   -2,    0,         -1,   -1,    2,   -2,    2,         -1,    1,    0,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=481,490 )" is not supported. Skipping.
Line #33004 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=491,500 ) /          0,    0,    0,   -1,    2,         -2,    1,    0,    1,    0,          1,   -2,    0,   -2,    1,          1,    0,   -2,    0,    2,         -3,    1,    0,    2,    0,         -1,    1,   -2,    2,    0,         -1,   -1,    0,    0,    2,         -3,    0,    0,    2,    0,         -3,   -1,    0,    2,    0,          2,    0,    2,   -6,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=491,500 )" is not supported. Skipping.
Line #33015 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=501,510 ) /          0,    1,    2,   -4,    2,          2,    0,    0,   -4,    2,         -2,    1,    2,   -2,    1,          0,   -1,    2,   -4,    1,          0,    1,    0,   -2,    2,         -1,    0,    0,   -2,    0,          2,    0,   -2,   -2,    1,         -4,    0,    2,    0,    1,         -1,   -1,    0,   -1,    1,          0,    0,   -2,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=501,510 )" is not supported. Skipping.
Line #33026 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=511,520 ) /         -3,    0,    0,    1,    0,         -1,    0,   -2,    1,    0,         -2,    0,   -2,    2,    1,          0,    0,   -4,    2,    0,         -2,   -1,   -2,    2,    0,          1,    0,    2,   -6,    1,         -1,    0,    2,   -4,    2,          1,    0,    0,   -4,    2,          2,    1,    2,   -4,    2,          2,    1,    2,   -4,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=511,520 )" is not supported. Skipping.
Line #33037 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=521,530 ) /          0,    1,    4,   -4,    4,          0,    1,    4,   -4,    2,         -1,   -1,   -2,    4,    0,         -1,   -3,    0,    2,    0,         -1,    0,   -2,    4,    1,         -2,   -1,    0,    3,    0,          0,    0,   -2,    3,    0,         -2,    0,    0,    3,    1,          0,   -1,    0,    1,    0,         -3,    0,    2,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=521,530 )" is not supported. Skipping.
Line #33048 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=531,540 ) /          1,    1,   -2,    2,    0,         -1,    1,    0,    2,    2,          1,   -2,    2,   -2,    1,          0,    0,    1,    0,    2,          0,    0,    1,    0,    1,          0,    0,    1,    0,    0,         -1,    2,    0,    2,    1,          0,    0,    2,    0,    2,         -2,    0,    2,    0,    2,          2,    0,    0,   -1,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=531,540 )" is not supported. Skipping.
Line #33059 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=541,550 ) /          3,    0,    0,   -2,    1,          1,    0,    2,   -2,    3,          1,    2,    0,    0,    1,          2,    0,    2,   -3,    2,         -1,    1,    4,   -2,    2,         -2,   -2,    0,    4,    0,          0,   -3,    0,    2,    0,          0,    0,   -2,    4,    0,         -1,   -1,    0,    3,    0,         -2,    0,    0,    4,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=541,550 )" is not supported. Skipping.
Line #33070 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=551,560 ) /         -1,    0,    0,    3,    1,          2,   -2,    0,    0,    0,          1,   -1,    0,    1,    0,         -1,    0,    0,    2,    0,          0,   -2,    2,    0,    1,         -1,    0,    1,    2,    1,         -1,    1,    0,    3,    0,         -1,   -1,    2,    1,    2,          0,   -1,    2,    0,    0,         -2,    1,    2,    2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=551,560 )" is not supported. Skipping.
Line #33081 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=561,570 ) /          2,   -2,    2,   -2,    2,          1,    1,    0,    1,    1,          1,    0,    1,    0,    1,          1,    0,    1,    0,    0,          0,    2,    0,    2,    0,          2,   -1,    2,   -2,    1,          0,   -1,    4,   -2,    1,          0,    0,    4,   -2,    3,          0,    1,    4,   -2,    1,          4,    0,    2,   -4,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=561,570 )" is not supported. Skipping.
Line #33092 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=571,580 ) /          2,    2,    2,   -2,    2,          2,    0,    4,   -4,    2,         -1,   -2,    0,    4,    0,         -1,   -3,    2,    2,    2,         -3,    0,    2,    4,    2,         -3,    0,    2,   -2,    1,         -1,   -1,    0,   -2,    1,         -3,    0,    0,    0,    2,         -3,    0,   -2,    2,    0,          0,    1,    0,   -4,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=571,580 )" is not supported. Skipping.
Line #33103 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=581,590 ) /         -2,    1,    0,   -2,    1,         -4,    0,    0,    0,    1,         -1,    0,    0,   -4,    1,         -3,    0,    0,   -2,    1,          0,    0,    0,    3,    2,         -1,    1,    0,    4,    1,          1,   -2,    2,    0,    1,          0,    1,    0,    3,    0,         -1,    0,    2,    2,    3,          0,    0,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=581,590 )" is not supported. Skipping.
Line #33114 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=591,600 ) /         -2,    0,    2,    2,    2,         -1,    1,    2,    2,    0,          3,    0,    0,    0,    2,          2,    1,    0,    1,    0,          2,   -1,    2,   -1,    2,          0,    0,    2,    0,    1,          0,    0,    3,    0,    3,          0,    0,    3,    0,    2,         -1,    2,    2,    2,    1,         -1,    0,    4,    0,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=591,600 )" is not supported. Skipping.
Line #33125 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=601,610 ) /          1,    2,    2,    0,    1,          3,    1,    2,   -2,    1,          1,    1,    4,   -2,    2,         -2,   -1,    0,    6,    0,          0,   -2,    0,    4,    0,         -2,    0,    0,    6,    1,         -2,   -2,    2,    4,    2,          0,   -3,    2,    2,    2,          0,    0,    0,    4,    2,         -1,   -1,    2,    3,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=601,610 )" is not supported. Skipping.
Line #33136 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=611,620 ) /         -2,    0,    2,    4,    0,          2,   -1,    0,    2,    1,          1,    0,    0,    3,    0,          0,    1,    0,    4,    1,          0,    1,    0,    4,    0,          1,   -1,    2,    1,    2,          0,    0,    2,    2,    3,          1,    0,    2,    2,    2,         -1,    0,    2,    2,    2,         -2,    0,    4,    2,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=611,620 )" is not supported. Skipping.
Line #33147 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=621,630 ) /          2,    1,    0,    2,    1,          2,    1,    0,    2,    0,          2,   -1,    2,    0,    0,          1,    0,    2,    1,    0,          0,    1,    2,    2,    0,          2,    0,    2,    0,    3,          3,    0,    2,    0,    2,          1,    0,    2,    0,    2,          1,    0,    3,    0,    3,          1,    1,    2,    1,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=621,630 )" is not supported. Skipping.
Line #33158 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=631,640 ) /          0,    2,    2,    2,    2,          2,    1,    2,    0,    0,          2,    0,    4,   -2,    1,          4,    1,    2,   -2,    2,         -1,   -1,    0,    6,    0,         -3,   -1,    2,    6,    2,         -1,    0,    0,    6,    1,         -3,    0,    2,    6,    1,          1,   -1,    0,    4,    1,          1,   -1,    0,    4,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=631,640 )" is not supported. Skipping.
Line #33169 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=641,650 ) /         -2,    0,    2,    5,    2,          1,   -2,    2,    2,    1,          3,   -1,    0,    2,    0,          1,   -1,    2,    2,    0,          0,    0,    2,    3,    1,         -1,    1,    2,    4,    1,          0,    1,    2,    3,    2,         -1,    0,    4,    2,    1,          2,    0,    2,    1,    1,          5,    0,    0,    0,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=641,650 )" is not supported. Skipping.
Line #33180 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=651,660 ) /          2,    1,    2,    1,    2,          1,    0,    4,    0,    1,          3,    1,    2,    0,    1,          3,    0,    4,   -2,    2,         -2,   -1,    2,    6,    2,          0,    0,    0,    6,    0,          0,   -2,    2,    4,    2,         -2,    0,    2,    6,    1,          2,    0,    0,    4,    1,          2,    0,    0,    4,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=651,660 )" is not supported. Skipping.
Line #33191 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=661,670 ) /          2,   -2,    2,    2,    2,          0,    0,    2,    4,    0,          1,    0,    2,    3,    2,          4,    0,    0,    2,    0,          2,    0,    2,    2,    0,          0,    0,    4,    2,    2,          4,   -1,    2,    0,    2,          3,    0,    2,    1,    2,          2,    1,    2,    2,    1,          4,    1,    2,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=661,670 )" is not supported. Skipping.
Line #33206 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=671,678 ) /         -1,   -1,    2,    6,    2,         -1,    0,    2,    6,    1,          1,   -1,    2,    4,    1,          1,    1,    2,    4,    2,          3,    1,    2,    2,    2,          5,    0,    2,    0,    1,          2,   -1,    2,    4,    2,          2,    0,    2,    4,    1 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=671,678 )" is not supported. Skipping.
Line #33217 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=  1, 10 ) / -172064161D0, -174666D0,  33386D0, 92052331D0,  9086D0, 15377D0,  -13170906D0,   -1675D0, -13696D0,  5730336D0, -3015D0, -4587D0,   -2276413D0,    -234D0,   2796D0,   978459D0,  -485D0,  1374D0,    2074554D0,     207D0,   -698D0,  -897492D0,   470D0,  -291D0,    1475877D0,   -3633D0,  11817D0,    73871D0,  -184D0, -1924D0,    -516821D0,    1226D0,   -524D0,   224386D0,  -677D0,  -174D0,     711159D0,      73D0,   -872D0,    -6750D0,     0D0,   358D0,    -387298D0,    -367D0,    380D0,   200728D0,    18D0,   318D0,    -301461D0,     -36D0,    816D0,   129025D0,   -63D0,   367D0,     215829D0,    -494D0,    111D0,   -95929D0,   299D0,   132D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=  1, 10 )" is not supported. Skipping.
Line #33228 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 11, 20 ) /     128227D0,     137D0,    181D0,   -68982D0,    -9D0,    39D0,     123457D0,      11D0,     19D0,   -53311D0,    32D0,    -4D0,     156994D0,      10D0,   -168D0,    -1235D0,     0D0,    82D0,      63110D0,      63D0,     27D0,   -33228D0,     0D0,    -9D0,     -57976D0,     -63D0,   -189D0,    31429D0,     0D0,   -75D0,     -59641D0,     -11D0,    149D0,    25543D0,   -11D0,    66D0,     -51613D0,     -42D0,    129D0,    26366D0,     0D0,    78D0,      45893D0,      50D0,     31D0,   -24236D0,   -10D0,    20D0,      63384D0,      11D0,   -150D0,    -1220D0,     0D0,    29D0,     -38571D0,      -1D0,    158D0,    16452D0,   -11D0,    68D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 11, 20 )" is not supported. Skipping.
Line #33239 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 21, 30 ) /      32481D0,       0D0,      0D0,   -13870D0,     0D0,     0D0,     -47722D0,       0D0,    -18D0,      477D0,     0D0,   -25D0,     -31046D0,      -1D0,    131D0,    13238D0,   -11D0,    59D0,      28593D0,       0D0,     -1D0,   -12338D0,    10D0,    -3D0,      20441D0,      21D0,     10D0,   -10758D0,     0D0,    -3D0,      29243D0,       0D0,    -74D0,     -609D0,     0D0,    13D0,      25887D0,       0D0,    -66D0,     -550D0,     0D0,    11D0,     -14053D0,     -25D0,     79D0,     8551D0,    -2D0,   -45D0,      15164D0,      10D0,     11D0,    -8001D0,     0D0,    -1D0,     -15794D0,      72D0,    -16D0,     6850D0,   -42D0,    -5D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 21, 30 )" is not supported. Skipping.
Line #33250 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 31, 40 ) /      21783D0,       0D0,     13D0,     -167D0,     0D0,    13D0,     -12873D0,     -10D0,    -37D0,     6953D0,     0D0,   -14D0,     -12654D0,      11D0,     63D0,     6415D0,     0D0,    26D0,     -10204D0,       0D0,     25D0,     5222D0,     0D0,    15D0,      16707D0,     -85D0,    -10D0,      168D0,    -1D0,    10D0,      -7691D0,       0D0,     44D0,     3268D0,     0D0,    19D0,     -11024D0,       0D0,    -14D0,      104D0,     0D0,     2D0,       7566D0,     -21D0,    -11D0,    -3250D0,     0D0,    -5D0,      -6637D0,     -11D0,     25D0,     3353D0,     0D0,    14D0,      -7141D0,      21D0,      8D0,     3070D0,     0D0,     4D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 31, 40 )" is not supported. Skipping.
Line #33261 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 41, 50 ) /      -6302D0,     -11D0,      2D0,     3272D0,     0D0,     4D0,       5800D0,      10D0,      2D0,    -3045D0,     0D0,    -1D0,       6443D0,       0D0,     -7D0,    -2768D0,     0D0,    -4D0,      -5774D0,     -11D0,    -15D0,     3041D0,     0D0,    -5D0,      -5350D0,       0D0,     21D0,     2695D0,     0D0,    12D0,      -4752D0,     -11D0,     -3D0,     2719D0,     0D0,    -3D0,      -4940D0,     -11D0,    -21D0,     2720D0,     0D0,    -9D0,       7350D0,       0D0,     -8D0,      -51D0,     0D0,     4D0,       4065D0,       0D0,      6D0,    -2206D0,     0D0,     1D0,       6579D0,       0D0,    -24D0,     -199D0,     0D0,     2D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 41, 50 )" is not supported. Skipping.
Line #33272 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 51, 60 ) /       3579D0,       0D0,      5D0,    -1900D0,     0D0,     1D0,       4725D0,       0D0,     -6D0,      -41D0,     0D0,     3D0,      -3075D0,       0D0,     -2D0,     1313D0,     0D0,    -1D0,      -2904D0,       0D0,     15D0,     1233D0,     0D0,     7D0,       4348D0,       0D0,    -10D0,      -81D0,     0D0,     2D0,      -2878D0,       0D0,      8D0,     1232D0,     0D0,     4D0,      -4230D0,       0D0,      5D0,      -20D0,     0D0,    -2D0,      -2819D0,       0D0,      7D0,     1207D0,     0D0,     3D0,      -4056D0,       0D0,      5D0,       40D0,     0D0,    -2D0,      -2647D0,       0D0,     11D0,     1129D0,     0D0,     5D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 51, 60 )" is not supported. Skipping.
Line #33283 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 61, 70 ) /      -2294D0,       0D0,    -10D0,     1266D0,     0D0,    -4D0,       2481D0,       0D0,     -7D0,    -1062D0,     0D0,    -3D0,       2179D0,       0D0,     -2D0,    -1129D0,     0D0,    -2D0,       3276D0,       0D0,      1D0,       -9D0,     0D0,     0D0,      -3389D0,       0D0,      5D0,       35D0,     0D0,    -2D0,       3339D0,       0D0,    -13D0,     -107D0,     0D0,     1D0,      -1987D0,       0D0,     -6D0,     1073D0,     0D0,    -2D0,      -1981D0,       0D0,      0D0,      854D0,     0D0,     0D0,       4026D0,       0D0,   -353D0,     -553D0,     0D0,  -139D0,       1660D0,       0D0,     -5D0,     -710D0,     0D0,    -2D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 61, 70 )" is not supported. Skipping.
Line #33294 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 71, 80 ) /      -1521D0,       0D0,      9D0,      647D0,     0D0,     4D0,       1314D0,       0D0,      0D0,     -700D0,     0D0,     0D0,      -1283D0,       0D0,      0D0,      672D0,     0D0,     0D0,      -1331D0,       0D0,      8D0,      663D0,     0D0,     4D0,       1383D0,       0D0,     -2D0,     -594D0,     0D0,    -2D0,       1405D0,       0D0,      4D0,     -610D0,     0D0,     2D0,       1290D0,       0D0,      0D0,     -556D0,     0D0,     0D0,      -1214D0,       0D0,      5D0,      518D0,     0D0,     2D0,       1146D0,       0D0,     -3D0,     -490D0,     0D0,    -1D0,       1019D0,       0D0,     -1D0,     -527D0,     0D0,    -1D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 71, 80 )" is not supported. Skipping.
Line #33305 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 81, 90 ) /      -1100D0,       0D0,      9D0,      465D0,     0D0,     4D0,       -970D0,       0D0,      2D0,      496D0,     0D0,     1D0,       1575D0,       0D0,     -6D0,      -50D0,     0D0,     0D0,        934D0,       0D0,     -3D0,     -399D0,     0D0,    -1D0,        922D0,       0D0,     -1D0,     -395D0,     0D0,    -1D0,        815D0,       0D0,     -1D0,     -422D0,     0D0,    -1D0,        834D0,       0D0,      2D0,     -440D0,     0D0,     1D0,       1248D0,       0D0,      0D0,     -170D0,     0D0,     1D0,       1338D0,       0D0,     -5D0,      -39D0,     0D0,     0D0,        716D0,       0D0,     -2D0,     -389D0,     0D0,    -1D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 81, 90 )" is not supported. Skipping.
Line #33316 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 91,100 ) /       1282D0,       0D0,     -3D0,      -23D0,     0D0,     1D0,        742D0,       0D0,      1D0,     -391D0,     0D0,     0D0,       1020D0,       0D0,    -25D0,     -495D0,     0D0,   -10D0,        715D0,       0D0,     -4D0,     -326D0,     0D0,     2D0,       -666D0,       0D0,     -3D0,      369D0,     0D0,    -1D0,       -667D0,       0D0,      1D0,      346D0,     0D0,     1D0,       -704D0,       0D0,      0D0,      304D0,     0D0,     0D0,       -694D0,       0D0,      5D0,      294D0,     0D0,     2D0,      -1014D0,       0D0,     -1D0,        4D0,     0D0,    -1D0,       -585D0,       0D0,     -2D0,      316D0,     0D0,    -1D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 91,100 )" is not supported. Skipping.
Line #33327 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=101,110 ) /       -949D0,       0D0,      1D0,        8D0,     0D0,    -1D0,       -595D0,       0D0,      0D0,      258D0,     0D0,     0D0,        528D0,       0D0,      0D0,     -279D0,     0D0,     0D0,       -590D0,       0D0,      4D0,      252D0,     0D0,     2D0,        570D0,       0D0,     -2D0,     -244D0,     0D0,    -1D0,       -502D0,       0D0,      3D0,      250D0,     0D0,     2D0,       -875D0,       0D0,      1D0,       29D0,     0D0,     0D0,       -492D0,       0D0,     -3D0,      275D0,     0D0,    -1D0,        535D0,       0D0,     -2D0,     -228D0,     0D0,    -1D0,       -467D0,       0D0,      1D0,      240D0,     0D0,     1D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=101,110 )" is not supported. Skipping.
Line #33338 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=111,120 ) /        591D0,       0D0,      0D0,     -253D0,     0D0,     0D0,       -453D0,       0D0,     -1D0,      244D0,     0D0,    -1D0,        766D0,       0D0,      1D0,        9D0,     0D0,     0D0,       -446D0,       0D0,      2D0,      225D0,     0D0,     1D0,       -488D0,       0D0,      2D0,      207D0,     0D0,     1D0,       -468D0,       0D0,      0D0,      201D0,     0D0,     0D0,       -421D0,       0D0,      1D0,      216D0,     0D0,     1D0,        463D0,       0D0,      0D0,     -200D0,     0D0,     0D0,       -673D0,       0D0,      2D0,       14D0,     0D0,     0D0,        658D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=111,120 )" is not supported. Skipping.
Line #33349 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=121,130 ) /       -438D0,       0D0,      0D0,      188D0,     0D0,     0D0,       -390D0,       0D0,      0D0,      205D0,     0D0,     0D0,        639D0,     -11D0,     -2D0,      -19D0,     0D0,     0D0,        412D0,       0D0,     -2D0,     -176D0,     0D0,    -1D0,       -361D0,       0D0,      0D0,      189D0,     0D0,     0D0,        360D0,       0D0,     -1D0,     -185D0,     0D0,    -1D0,        588D0,       0D0,     -3D0,      -24D0,     0D0,     0D0,       -578D0,       0D0,      1D0,        5D0,     0D0,     0D0,       -396D0,       0D0,      0D0,      171D0,     0D0,     0D0,        565D0,       0D0,     -1D0,       -6D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=121,130 )" is not supported. Skipping.
Line #33360 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=131,140 ) /       -335D0,       0D0,     -1D0,      184D0,     0D0,    -1D0,        357D0,       0D0,      1D0,     -154D0,     0D0,     0D0,        321D0,       0D0,      1D0,     -174D0,     0D0,     0D0,       -301D0,       0D0,     -1D0,      162D0,     0D0,     0D0,       -334D0,       0D0,      0D0,      144D0,     0D0,     0D0,        493D0,       0D0,     -2D0,      -15D0,     0D0,     0D0,        494D0,       0D0,     -2D0,      -19D0,     0D0,     0D0,        337D0,       0D0,     -1D0,     -143D0,     0D0,    -1D0,        280D0,       0D0,     -1D0,     -144D0,     0D0,     0D0,        309D0,       0D0,      1D0,     -134D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=131,140 )" is not supported. Skipping.
Line #33371 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=141,150 ) /       -263D0,       0D0,      2D0,      131D0,     0D0,     1D0,        253D0,       0D0,      1D0,     -138D0,     0D0,     0D0,        245D0,       0D0,      0D0,     -128D0,     0D0,     0D0,        416D0,       0D0,     -2D0,      -17D0,     0D0,     0D0,       -229D0,       0D0,      0D0,      128D0,     0D0,     0D0,        231D0,       0D0,      0D0,     -120D0,     0D0,     0D0,       -259D0,       0D0,      2D0,      109D0,     0D0,     1D0,        375D0,       0D0,     -1D0,       -8D0,     0D0,     0D0,        252D0,       0D0,      0D0,     -108D0,     0D0,     0D0,       -245D0,       0D0,      1D0,      104D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=141,150 )" is not supported. Skipping.
Line #33382 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=151,160 ) /        243D0,       0D0,     -1D0,     -104D0,     0D0,     0D0,        208D0,       0D0,      1D0,     -112D0,     0D0,     0D0,        199D0,       0D0,      0D0,     -102D0,     0D0,     0D0,       -208D0,       0D0,      1D0,      105D0,     0D0,     0D0,        335D0,       0D0,     -2D0,      -14D0,     0D0,     0D0,       -325D0,       0D0,      1D0,        7D0,     0D0,     0D0,       -187D0,       0D0,      0D0,       96D0,     0D0,     0D0,        197D0,       0D0,     -1D0,     -100D0,     0D0,     0D0,       -192D0,       0D0,      2D0,       94D0,     0D0,     1D0,       -188D0,       0D0,      0D0,       83D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=151,160 )" is not supported. Skipping.
Line #33393 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=161,170 ) /        276D0,       0D0,      0D0,       -2D0,     0D0,     0D0,       -286D0,       0D0,      1D0,        6D0,     0D0,     0D0,        186D0,       0D0,     -1D0,      -79D0,     0D0,     0D0,       -219D0,       0D0,      0D0,       43D0,     0D0,     0D0,        276D0,       0D0,      0D0,        2D0,     0D0,     0D0,       -153D0,       0D0,     -1D0,       84D0,     0D0,     0D0,       -156D0,       0D0,      0D0,       81D0,     0D0,     0D0,       -154D0,       0D0,      1D0,       78D0,     0D0,     0D0,       -174D0,       0D0,      1D0,       75D0,     0D0,     0D0,       -163D0,       0D0,      2D0,       69D0,     0D0,     1D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=161,170 )" is not supported. Skipping.
Line #33404 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=171,180 ) /       -228D0,       0D0,      0D0,        1D0,     0D0,     0D0,         91D0,       0D0,     -4D0,      -54D0,     0D0,    -2D0,        175D0,       0D0,      0D0,      -75D0,     0D0,     0D0,       -159D0,       0D0,      0D0,       69D0,     0D0,     0D0,        141D0,       0D0,      0D0,      -72D0,     0D0,     0D0,        147D0,       0D0,      0D0,      -75D0,     0D0,     0D0,       -132D0,       0D0,      0D0,       69D0,     0D0,     0D0,        159D0,       0D0,    -28D0,      -54D0,     0D0,    11D0,        213D0,       0D0,      0D0,       -4D0,     0D0,     0D0,        123D0,       0D0,      0D0,      -64D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=171,180 )" is not supported. Skipping.
Line #33415 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=181,190 ) /       -118D0,       0D0,     -1D0,       66D0,     0D0,     0D0,        144D0,       0D0,     -1D0,      -61D0,     0D0,     0D0,       -121D0,       0D0,      1D0,       60D0,     0D0,     0D0,       -134D0,       0D0,      1D0,       56D0,     0D0,     1D0,       -105D0,       0D0,      0D0,       57D0,     0D0,     0D0,       -102D0,       0D0,      0D0,       56D0,     0D0,     0D0,        120D0,       0D0,      0D0,      -52D0,     0D0,     0D0,        101D0,       0D0,      0D0,      -54D0,     0D0,     0D0,       -113D0,       0D0,      0D0,       59D0,     0D0,     0D0,       -106D0,       0D0,      0D0,       61D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=181,190 )" is not supported. Skipping.
Line #33426 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=191,200 ) /       -129D0,       0D0,      1D0,       55D0,     0D0,     0D0,       -114D0,       0D0,      0D0,       57D0,     0D0,     0D0,        113D0,       0D0,     -1D0,      -49D0,     0D0,     0D0,       -102D0,       0D0,      0D0,       44D0,     0D0,     0D0,        -94D0,       0D0,      0D0,       51D0,     0D0,     0D0,       -100D0,       0D0,     -1D0,       56D0,     0D0,     0D0,         87D0,       0D0,      0D0,      -47D0,     0D0,     0D0,        161D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         96D0,       0D0,      0D0,      -50D0,     0D0,     0D0,        151D0,       0D0,     -1D0,       -5D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=191,200 )" is not supported. Skipping.
Line #33437 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=201,210 ) /       -104D0,       0D0,      0D0,       44D0,     0D0,     0D0,       -110D0,       0D0,      0D0,       48D0,     0D0,     0D0,       -100D0,       0D0,      1D0,       50D0,     0D0,     0D0,         92D0,       0D0,     -5D0,       12D0,     0D0,    -2D0,         82D0,       0D0,      0D0,      -45D0,     0D0,     0D0,         82D0,       0D0,      0D0,      -45D0,     0D0,     0D0,        -78D0,       0D0,      0D0,       41D0,     0D0,     0D0,        -77D0,       0D0,      0D0,       43D0,     0D0,     0D0,          2D0,       0D0,      0D0,       54D0,     0D0,     0D0,         94D0,       0D0,      0D0,      -40D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=201,210 )" is not supported. Skipping.
Line #33448 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=211,220 ) /        -93D0,       0D0,      0D0,       40D0,     0D0,     0D0,        -83D0,       0D0,     10D0,       40D0,     0D0,    -2D0,         83D0,       0D0,      0D0,      -36D0,     0D0,     0D0,        -91D0,       0D0,      0D0,       39D0,     0D0,     0D0,        128D0,       0D0,      0D0,       -1D0,     0D0,     0D0,        -79D0,       0D0,      0D0,       34D0,     0D0,     0D0,        -83D0,       0D0,      0D0,       47D0,     0D0,     0D0,         84D0,       0D0,      0D0,      -44D0,     0D0,     0D0,         83D0,       0D0,      0D0,      -43D0,     0D0,     0D0,         91D0,       0D0,      0D0,      -39D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=211,220 )" is not supported. Skipping.
Line #33459 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=221,230 ) /        -77D0,       0D0,      0D0,       39D0,     0D0,     0D0,         84D0,       0D0,      0D0,      -43D0,     0D0,     0D0,        -92D0,       0D0,      1D0,       39D0,     0D0,     0D0,        -92D0,       0D0,      1D0,       39D0,     0D0,     0D0,        -94D0,       0D0,      0D0,        0D0,     0D0,     0D0,         68D0,       0D0,      0D0,      -36D0,     0D0,     0D0,        -61D0,       0D0,      0D0,       32D0,     0D0,     0D0,         71D0,       0D0,      0D0,      -31D0,     0D0,     0D0,         62D0,       0D0,      0D0,      -34D0,     0D0,     0D0,        -63D0,       0D0,      0D0,       33D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=221,230 )" is not supported. Skipping.
Line #33470 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=231,240 ) /        -73D0,       0D0,      0D0,       32D0,     0D0,     0D0,        115D0,       0D0,      0D0,       -2D0,     0D0,     0D0,       -103D0,       0D0,      0D0,        2D0,     0D0,     0D0,         63D0,       0D0,      0D0,      -28D0,     0D0,     0D0,         74D0,       0D0,      0D0,      -32D0,     0D0,     0D0,       -103D0,       0D0,     -3D0,        3D0,     0D0,    -1D0,        -69D0,       0D0,      0D0,       30D0,     0D0,     0D0,         57D0,       0D0,      0D0,      -29D0,     0D0,     0D0,         94D0,       0D0,      0D0,       -4D0,     0D0,     0D0,         64D0,       0D0,      0D0,      -33D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=231,240 )" is not supported. Skipping.
Line #33481 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=241,250 ) /        -63D0,       0D0,      0D0,       26D0,     0D0,     0D0,        -38D0,       0D0,      0D0,       20D0,     0D0,     0D0,        -43D0,       0D0,      0D0,       24D0,     0D0,     0D0,        -45D0,       0D0,      0D0,       23D0,     0D0,     0D0,         47D0,       0D0,      0D0,      -24D0,     0D0,     0D0,        -48D0,       0D0,      0D0,       25D0,     0D0,     0D0,         45D0,       0D0,      0D0,      -26D0,     0D0,     0D0,         56D0,       0D0,      0D0,      -25D0,     0D0,     0D0,         88D0,       0D0,      0D0,        2D0,     0D0,     0D0,        -75D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=241,250 )" is not supported. Skipping.
Line #33492 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=251,260 ) /         85D0,       0D0,      0D0,        0D0,     0D0,     0D0,         49D0,       0D0,      0D0,      -26D0,     0D0,     0D0,        -74D0,       0D0,     -3D0,       -1D0,     0D0,    -1D0,        -39D0,       0D0,      0D0,       21D0,     0D0,     0D0,         45D0,       0D0,      0D0,      -20D0,     0D0,     0D0,         51D0,       0D0,      0D0,      -22D0,     0D0,     0D0,        -40D0,       0D0,      0D0,       21D0,     0D0,     0D0,         41D0,       0D0,      0D0,      -21D0,     0D0,     0D0,        -42D0,       0D0,      0D0,       24D0,     0D0,     0D0,        -51D0,       0D0,      0D0,       22D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=251,260 )" is not supported. Skipping.
Line #33503 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=261,270 ) /        -42D0,       0D0,      0D0,       22D0,     0D0,     0D0,         39D0,       0D0,      0D0,      -21D0,     0D0,     0D0,         46D0,       0D0,      0D0,      -18D0,     0D0,     0D0,        -53D0,       0D0,      0D0,       22D0,     0D0,     0D0,         82D0,       0D0,      0D0,       -4D0,     0D0,     0D0,         81D0,       0D0,     -1D0,       -4D0,     0D0,     0D0,         47D0,       0D0,      0D0,      -19D0,     0D0,     0D0,         53D0,       0D0,      0D0,      -23D0,     0D0,     0D0,        -45D0,       0D0,      0D0,       22D0,     0D0,     0D0,        -44D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=261,270 )" is not supported. Skipping.
Line #33514 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=271,280 ) /        -33D0,       0D0,      0D0,       16D0,     0D0,     0D0,        -61D0,       0D0,      0D0,        1D0,     0D0,     0D0,         28D0,       0D0,      0D0,      -15D0,     0D0,     0D0,        -38D0,       0D0,      0D0,       19D0,     0D0,     0D0,        -33D0,       0D0,      0D0,       21D0,     0D0,     0D0,        -60D0,       0D0,      0D0,        0D0,     0D0,     0D0,         48D0,       0D0,      0D0,      -10D0,     0D0,     0D0,         27D0,       0D0,      0D0,      -14D0,     0D0,     0D0,         38D0,       0D0,      0D0,      -20D0,     0D0,     0D0,         31D0,       0D0,      0D0,      -13D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=271,280 )" is not supported. Skipping.
Line #33525 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=281,290 ) /        -29D0,       0D0,      0D0,       15D0,     0D0,     0D0,         28D0,       0D0,      0D0,      -15D0,     0D0,     0D0,        -32D0,       0D0,      0D0,       15D0,     0D0,     0D0,         45D0,       0D0,      0D0,       -8D0,     0D0,     0D0,        -44D0,       0D0,      0D0,       19D0,     0D0,     0D0,         28D0,       0D0,      0D0,      -15D0,     0D0,     0D0,        -51D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -36D0,       0D0,      0D0,       20D0,     0D0,     0D0,         44D0,       0D0,      0D0,      -19D0,     0D0,     0D0,         26D0,       0D0,      0D0,      -14D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=281,290 )" is not supported. Skipping.
Line #33536 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=291,300 ) /        -60D0,       0D0,      0D0,        2D0,     0D0,     0D0,         35D0,       0D0,      0D0,      -18D0,     0D0,     0D0,        -27D0,       0D0,      0D0,       11D0,     0D0,     0D0,         47D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         36D0,       0D0,      0D0,      -15D0,     0D0,     0D0,        -36D0,       0D0,      0D0,       20D0,     0D0,     0D0,        -35D0,       0D0,      0D0,       19D0,     0D0,     0D0,        -37D0,       0D0,      0D0,       19D0,     0D0,     0D0,         32D0,       0D0,      0D0,      -16D0,     0D0,     0D0,         35D0,       0D0,      0D0,      -14D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=291,300 )" is not supported. Skipping.
Line #33547 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=301,310 ) /         32D0,       0D0,      0D0,      -13D0,     0D0,     0D0,         65D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         47D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         32D0,       0D0,      0D0,      -16D0,     0D0,     0D0,         37D0,       0D0,      0D0,      -16D0,     0D0,     0D0,        -30D0,       0D0,      0D0,       15D0,     0D0,     0D0,        -32D0,       0D0,      0D0,       16D0,     0D0,     0D0,        -31D0,       0D0,      0D0,       13D0,     0D0,     0D0,         37D0,       0D0,      0D0,      -16D0,     0D0,     0D0,         31D0,       0D0,      0D0,      -13D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=301,310 )" is not supported. Skipping.
Line #33558 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=311,320 ) /         49D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         32D0,       0D0,      0D0,      -13D0,     0D0,     0D0,         23D0,       0D0,      0D0,      -12D0,     0D0,     0D0,        -43D0,       0D0,      0D0,       18D0,     0D0,     0D0,         26D0,       0D0,      0D0,      -11D0,     0D0,     0D0,        -32D0,       0D0,      0D0,       14D0,     0D0,     0D0,        -29D0,       0D0,      0D0,       14D0,     0D0,     0D0,        -27D0,       0D0,      0D0,       12D0,     0D0,     0D0,         30D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -11D0,       0D0,      0D0,        5D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=311,320 )" is not supported. Skipping.
Line #33569 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=321,330 ) /        -21D0,       0D0,      0D0,       10D0,     0D0,     0D0,        -34D0,       0D0,      0D0,       15D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        6D0,     0D0,     0D0,        -36D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -9D0,       0D0,      0D0,        4D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        5D0,     0D0,     0D0,        -21D0,       0D0,      0D0,        5D0,     0D0,     0D0,        -29D0,       0D0,      0D0,       -1D0,     0D0,     0D0,        -15D0,       0D0,      0D0,        3D0,     0D0,     0D0,        -20D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=321,330 )" is not supported. Skipping.
Line #33580 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=331,340 ) /         28D0,       0D0,      0D0,        0D0,     0D0,    -2D0,         17D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -22D0,       0D0,      0D0,       12D0,     0D0,     0D0,        -14D0,       0D0,      0D0,        7D0,     0D0,     0D0,         24D0,       0D0,      0D0,      -11D0,     0D0,     0D0,         11D0,       0D0,      0D0,       -6D0,     0D0,     0D0,         14D0,       0D0,      0D0,       -6D0,     0D0,     0D0,         24D0,       0D0,      0D0,        0D0,     0D0,     0D0,         18D0,       0D0,      0D0,       -8D0,     0D0,     0D0,        -38D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=331,340 )" is not supported. Skipping.
Line #33591 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=341,350 ) /        -31D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -16D0,       0D0,      0D0,        8D0,     0D0,     0D0,         29D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -18D0,       0D0,      0D0,       10D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        5D0,     0D0,     0D0,        -17D0,       0D0,      0D0,       10D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -4D0,     0D0,     0D0,         16D0,       0D0,      0D0,       -6D0,     0D0,     0D0,         22D0,       0D0,      0D0,      -12D0,     0D0,     0D0,         20D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=341,350 )" is not supported. Skipping.
Line #33602 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=351,360 ) /        -13D0,       0D0,      0D0,        6D0,     0D0,     0D0,        -17D0,       0D0,      0D0,        9D0,     0D0,     0D0,        -14D0,       0D0,      0D0,        8D0,     0D0,     0D0,          0D0,       0D0,      0D0,       -7D0,     0D0,     0D0,         14D0,       0D0,      0D0,        0D0,     0D0,     0D0,         19D0,       0D0,      0D0,      -10D0,     0D0,     0D0,        -34D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -20D0,       0D0,      0D0,        8D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -5D0,     0D0,     0D0,        -18D0,       0D0,      0D0,        7D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=351,360 )" is not supported. Skipping.
Line #33613 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=361,370 ) /         13D0,       0D0,      0D0,       -6D0,     0D0,     0D0,         17D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        5D0,     0D0,     0D0,         15D0,       0D0,      0D0,       -8D0,     0D0,     0D0,        -11D0,       0D0,      0D0,        3D0,     0D0,     0D0,         13D0,       0D0,      0D0,       -5D0,     0D0,     0D0,        -18D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -35D0,       0D0,      0D0,        0D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -4D0,     0D0,     0D0,        -19D0,       0D0,      0D0,       10D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=361,370 )" is not supported. Skipping.
Line #33624 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=371,380 ) /        -26D0,       0D0,      0D0,       11D0,     0D0,     0D0,          8D0,       0D0,      0D0,       -4D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        4D0,     0D0,     0D0,         10D0,       0D0,      0D0,       -6D0,     0D0,     0D0,        -21D0,       0D0,      0D0,        9D0,     0D0,     0D0,        -15D0,       0D0,      0D0,        0D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -5D0,     0D0,     0D0,        -29D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -19D0,       0D0,      0D0,       10D0,     0D0,     0D0,         12D0,       0D0,      0D0,       -5D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=371,380 )" is not supported. Skipping.
Line #33635 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=381,390 ) /         22D0,       0D0,      0D0,       -9D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        5D0,     0D0,     0D0,        -20D0,       0D0,      0D0,       11D0,     0D0,     0D0,        -20D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -17D0,       0D0,      0D0,        7D0,     0D0,     0D0,         15D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          8D0,       0D0,      0D0,       -4D0,     0D0,     0D0,         14D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        6D0,     0D0,     0D0,         25D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=381,390 )" is not supported. Skipping.
Line #33646 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=391,400 ) /        -13D0,       0D0,      0D0,        6D0,     0D0,     0D0,        -14D0,       0D0,      0D0,        8D0,     0D0,     0D0,         13D0,       0D0,      0D0,       -5D0,     0D0,     0D0,        -17D0,       0D0,      0D0,        9D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        6D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        5D0,     0D0,     0D0,         10D0,       0D0,      0D0,       -6D0,     0D0,     0D0,        -15D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -22D0,       0D0,      0D0,        0D0,     0D0,     0D0,         28D0,       0D0,      0D0,       -1D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=391,400 )" is not supported. Skipping.
Line #33657 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=401,410 ) /         15D0,       0D0,      0D0,       -7D0,     0D0,     0D0,         23D0,       0D0,      0D0,      -10D0,     0D0,     0D0,         12D0,       0D0,      0D0,       -5D0,     0D0,     0D0,         29D0,       0D0,      0D0,       -1D0,     0D0,     0D0,        -25D0,       0D0,      0D0,        1D0,     0D0,     0D0,         22D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -18D0,       0D0,      0D0,        0D0,     0D0,     0D0,         15D0,       0D0,      0D0,        3D0,     0D0,     0D0,        -23D0,       0D0,      0D0,        0D0,     0D0,     0D0,         12D0,       0D0,      0D0,       -5D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=401,410 )" is not supported. Skipping.
Line #33668 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=411,420 ) /         -8D0,       0D0,      0D0,        4D0,     0D0,     0D0,        -19D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        4D0,     0D0,     0D0,         21D0,       0D0,      0D0,       -9D0,     0D0,     0D0,         23D0,       0D0,      0D0,       -1D0,     0D0,     0D0,        -16D0,       0D0,      0D0,        8D0,     0D0,     0D0,        -19D0,       0D0,      0D0,        9D0,     0D0,     0D0,        -22D0,       0D0,      0D0,       10D0,     0D0,     0D0,         27D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         16D0,       0D0,      0D0,       -8D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=411,420 )" is not supported. Skipping.
Line #33679 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=421,430 ) /         19D0,       0D0,      0D0,       -8D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -4D0,     0D0,     0D0,         -9D0,       0D0,      0D0,        4D0,     0D0,     0D0,         -9D0,       0D0,      0D0,        4D0,     0D0,     0D0,         -8D0,       0D0,      0D0,        4D0,     0D0,     0D0,         18D0,       0D0,      0D0,       -9D0,     0D0,     0D0,         16D0,       0D0,      0D0,       -1D0,     0D0,     0D0,        -10D0,       0D0,      0D0,        4D0,     0D0,     0D0,        -23D0,       0D0,      0D0,        9D0,     0D0,     0D0,         16D0,       0D0,      0D0,       -1D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=421,430 )" is not supported. Skipping.
Line #33690 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=431,440 ) /        -12D0,       0D0,      0D0,        6D0,     0D0,     0D0,         -8D0,       0D0,      0D0,        4D0,     0D0,     0D0,         30D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         24D0,       0D0,      0D0,      -10D0,     0D0,     0D0,         10D0,       0D0,      0D0,       -4D0,     0D0,     0D0,        -16D0,       0D0,      0D0,        7D0,     0D0,     0D0,        -16D0,       0D0,      0D0,        7D0,     0D0,     0D0,         17D0,       0D0,      0D0,       -7D0,     0D0,     0D0,        -24D0,       0D0,      0D0,       10D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        5D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=431,440 )" is not supported. Skipping.
Line #33701 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=441,450 ) /        -24D0,       0D0,      0D0,       11D0,     0D0,     0D0,        -23D0,       0D0,      0D0,        9D0,     0D0,     0D0,        -13D0,       0D0,      0D0,        5D0,     0D0,     0D0,        -15D0,       0D0,      0D0,        7D0,     0D0,     0D0,          0D0,       0D0,  -1988D0,        0D0,     0D0, -1679D0,          0D0,       0D0,    -63D0,        0D0,     0D0,   -27D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          0D0,       0D0,      5D0,        0D0,     0D0,     4D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          0D0,       0D0,    364D0,        0D0,     0D0,   176D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=441,450 )" is not supported. Skipping.
Line #33712 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=451,460 ) /          0D0,       0D0,  -1044D0,        0D0,     0D0,  -891D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          0D0,       0D0,    330D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=451,460 )" is not supported. Skipping.
Line #33723 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=461,470 ) /          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,          0D0,       0D0,      5D0,        0D0,     0D0,     0D0,          0D0,       0D0,      0D0,        1D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          6D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=461,470 )" is not supported. Skipping.
Line #33734 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=471,480 ) /         -5D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        3D0,     0D0,     0D0,          7D0,       0D0,      0D0,       -4D0,     0D0,     0D0,          0D0,       0D0,    -12D0,        0D0,     0D0,   -10D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=471,480 )" is not supported. Skipping.
Line #33745 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=481,490 ) /         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          0D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          7D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        3D0,     0D0,     0D0,          5D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=481,490 )" is not supported. Skipping.
Line #33756 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=491,500 ) /         -8D0,       0D0,      0D0,        3D0,     0D0,     0D0,          9D0,       0D0,      0D0,        0D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          5D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=491,500 )" is not supported. Skipping.
Line #33767 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=501,510 ) /          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          9D0,       0D0,      0D0,       -3D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=501,510 )" is not supported. Skipping.
Line #33778 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=511,520 ) /         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          8D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=511,520 )" is not supported. Skipping.
Line #33789 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=521,530 ) /          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0,          9D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        3D0,     0D0,     0D0,        -13D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=521,530 )" is not supported. Skipping.
Line #33800 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=531,540 ) /         10D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         10D0,       0D0,     13D0,        6D0,     0D0,    -5D0,          0D0,       0D0,     30D0,        0D0,     0D0,    14D0,          0D0,       0D0,   -162D0,        0D0,     0D0,  -138D0,          0D0,       0D0,     75D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        4D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=531,540 )" is not supported. Skipping.
Line #33811 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=541,550 ) /          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          6D0,       0D0,      0D0,        0D0,     0D0,     0D0,          9D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=541,550 )" is not supported. Skipping.
Line #33822 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=551,560 ) /         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          7D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -6D0,       0D0,     -3D0,        3D0,     0D0,     1D0,          0D0,       0D0,     -3D0,        0D0,     0D0,    -2D0,         11D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         11D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=551,560 )" is not supported. Skipping.
Line #33833 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=561,570 ) /         -1D0,       0D0,      3D0,        3D0,     0D0,    -1D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          0D0,       0D0,    -13D0,        0D0,     0D0,   -11D0,          3D0,       0D0,      6D0,        0D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        3D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=561,570 )" is not supported. Skipping.
Line #33844 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=571,580 ) /          8D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         11D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          8D0,       0D0,      0D0,       -4D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         11D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=571,580 )" is not supported. Skipping.
Line #33855 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=581,590 ) /         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -8D0,       0D0,      0D0,        4D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0,          6D0,       0D0,      0D0,        0D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -1D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=581,590 )" is not supported. Skipping.
Line #33866 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=591,600 ) /         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          0D0,       0D0,    -26D0,        0D0,     0D0,   -11D0,          0D0,       0D0,    -10D0,        0D0,     0D0,    -5D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,        -13D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=591,600 )" is not supported. Skipping.
Line #33877 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=601,610 ) /          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          7D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -7D0,       0D0,      0D0,        3D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=601,610 )" is not supported. Skipping.
Line #33888 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=611,620 ) /         13D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0,        -11D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=611,620 )" is not supported. Skipping.
Line #33899 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=621,630 ) /          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,        -12D0,       0D0,      0D0,        0D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,          0D0,       0D0,     -5D0,        0D0,     0D0,    -2D0,         -7D0,       0D0,      0D0,        4D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=621,630 )" is not supported. Skipping.
Line #33910 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=631,640 ) /          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,          3D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        3D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,         12D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=631,640 )" is not supported. Skipping.
Line #33921 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=641,650 ) /          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,          6D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          6D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          6D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=641,650 )" is not supported. Skipping.
Line #33932 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=651,660 ) /         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          7D0,       0D0,      0D0,       -4D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -5D0,       0D0,      0D0,        2D0,     0D0,     0D0,          5D0,       0D0,      0D0,        0D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        3D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         10D0,       0D0,      0D0,        0D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=651,660 )" is not supported. Skipping.
Line #33943 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=661,670 ) /         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,          7D0,       0D0,      0D0,        0D0,     0D0,     0D0,          7D0,       0D0,      0D0,       -3D0,     0D0,     0D0,          4D0,       0D0,      0D0,        0D0,     0D0,     0D0,         11D0,       0D0,      0D0,        0D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0,         -6D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          5D0,       0D0,      0D0,       -2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=661,670 )" is not supported. Skipping.
Line #33957 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=671,678 ) /         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -4D0,       0D0,      0D0,        2D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0,          4D0,       0D0,      0D0,       -2D0,     0D0,     0D0,          3D0,       0D0,      0D0,       -1D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        1D0,     0D0,     0D0,         -3D0,       0D0,      0D0,        2D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=671,678 )" is not supported. Skipping.
Line #33968 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=  1, 10 ) /         0,  0,  0,  0,  0,  0,  0,  8,-16,  4,  5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -8, 16, -4, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  8,-16,  4,  5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  2,  2,         0,  0,  0,  0,  0,  0,  0, -4,  8, -1, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0,  3, -8,  3,  0,  0,  0,  0,        -1,  0,  0,  0,  0,  0, 10, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0, -2,  6, -3,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=  1, 10 )" is not supported. Skipping.
Line #33979 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 11, 20 ) /         0,  0,  1, -1,  1,  0,  0, -5,  8, -3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -4,  8, -3,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  4, -8,  1,  5,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  6,  4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -1,  0,  2, -5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0, -2,  5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0, -2,  5,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 11, 20 )" is not supported. Skipping.
Line #33990 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 21, 30 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0, -2,  5,  0,  0,  2,         2,  0, -1, -1,  0,  0,  0,  3, -7,  0,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0, 19,-21,  3,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  2, -4,  0, -3,  0,  0,  0,  0,         1,  0,  0, -1,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0, -4, 10,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  0,  2,  0,  0, -5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -7,  4,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  1, -1,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  0,  2,  0, -2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 21, 30 )" is not supported. Skipping.
Line #34001 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 31, 40 ) /        -1,  0,  0,  0,  0,  0, 18,-16,  0,  0,  0,  0,  0,  0,        -2,  0,  1,  1,  2,  0,  0,  1,  0, -2,  0,  0,  0,  0,        -1,  0,  1, -1,  1,  0, 18,-17,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  1,  1,  0,  0,  2, -2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -8, 13,  0,  0,  0,  0,  0,  2,         0,  0,  2, -2,  2,  0, -8, 11,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -8, 13,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -8, 12,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  8,-14,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 31, 40 )" is not supported. Skipping.
Line #34012 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 41, 50 ) /         0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0,  1,        -2,  0,  0,  2,  1,  0,  0,  2,  0, -4,  5,  0,  0,  0,        -2,  0,  0,  2,  2,  0,  3, -3,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -3,  1,  0,  0,  0,         0,  0,  0,  0,  1,  0,  3, -5,  0,  2,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -4,  3,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -1,  2,  0,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -2,  2,  0,  0,  0,  0,  0,        -1,  0,  1,  0,  1,  0,  3, -5,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 41, 50 )" is not supported. Skipping.
Line #34023 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 51, 60 ) /        -1,  0,  0,  1,  0,  0,  3, -4,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -2, -2,  0,  0,  0,        -2,  0,  2,  0,  2,  0,  0, -5,  9,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0, -1,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  0,  2,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  2,        -1,  0,  0,  1,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  0,  2,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 51, 60 )" is not supported. Skipping.
Line #34034 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 61, 70 ) /         0,  0,  1, -1,  2,  0,  0, -1,  0,  0,  2,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -9, 17,  0,  0,  0,  0,  0,         0,  0,  0,  0,  2,  0, -3,  5,  0,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  2,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,         1,  0,  0, -2,  0,  0, 17,-16,  0, -2,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  1, -3,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  0,  5, -6,  0,  0,  0,  0,  0,         0,  0, -2,  2,  0,  0,  0,  9,-13,  0,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -1,  0,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 61, 70 )" is not supported. Skipping.
Line #34045 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 71, 80 ) /         0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  1,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  0,  1,  0,  0,  0,         0,  0, -2,  2,  0,  0,  5, -6,  0,  0,  0,  0,  0,  0,         0,  0, -1,  1,  1,  0,  5, -7,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  6, -8,  0,  0,  0,  0,  0,  0,         2,  0,  1, -3,  1,  0, -6,  7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  0,         0,  0, -1,  1,  1,  0,  0,  1,  0,  1,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  2,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 71, 80 )" is not supported. Skipping.
Line #34056 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 81, 90 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  2,         0,  0,  0,  0,  0,  0,  0, -8, 15,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -8, 15,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -9, 15,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  8,-15,  0,  0,  0,  0,  0,         1,  0, -1, -1,  0,  0,  0,  8,-15,  0,  0,  0,  0,  0,         2,  0,  0, -2,  0,  0,  2, -5,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -5,  5,  0,  0,  0,         2,  0,  0, -2,  1,  0,  0, -6,  8,  0,  0,  0,  0,  0,         2,  0,  0, -2,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 81, 90 )" is not supported. Skipping.
Line #34067 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J= 91,100 ) /        -2,  0,  1,  1,  0,  0,  0,  1,  0, -3,  0,  0,  0,  0,        -2,  0,  1,  1,  1,  0,  0,  1,  0, -3,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  6, -8,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -1, -5,  0,  0,  0,        -1,  0,  0,  1,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,        -1,  0,  1,  1,  1,  0,-20, 20,  0,  0,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0, 20,-21,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  8,-15,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0,-10, 15,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j= 91,100 )" is not supported. Skipping.
Line #34078 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=101,110 ) /         0,  0, -1,  1,  0,  0,  0,  1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  0,  0,  1,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0, -2,  4,  0,  0,  0,         2,  0,  0, -2,  1,  0, -6,  8,  0,  0,  0,  0,  0,  0,         0,  0, -2,  2,  1,  0,  5, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0, -1,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=101,110 )" is not supported. Skipping.
Line #34089 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=111,120 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  2,         0,  0,  2, -2,  1,  0,  0, -9, 13,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  7,-13,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  9,-17,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -9, 17,  0,  0,  0,  0,  2,         1,  0,  0, -1,  1,  0,  0, -3,  4,  0,  0,  0,  0,  0,         1,  0,  0, -1,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  2,  0,  0, -1,  2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=111,120 )" is not supported. Skipping.
Line #34100 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=121,130 ) /         0,  0, -1,  1,  1,  0,  0,  0,  2,  0,  0,  0,  0,  0,         0,  0, -2,  2,  0,  1,  0, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -5,  0,  2,  0,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  0,  2,  0, -3,  1,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  3, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  8,-13,  0,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  8,-12,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0, -8, 11,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  1,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,        -1,  0,  0,  0,  1,  0, 18,-16,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=121,130 )" is not supported. Skipping.
Line #34111 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=131,140 ) /         0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  1,  0,  0,  0,         0,  0,  0,  0,  1,  0,  3, -7,  4,  0,  0,  0,  0,  0,        -2,  0,  1,  1,  1,  0,  0, -3,  7,  0,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -1,  0, -2,  5,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  0,  0, -2,  5,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -4,  8, -3,  0,  0,  0,  0,         1,  0,  0,  0,  1,  0,-10,  3,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -2,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  0,  1,  0, 10, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  4, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=131,140 )" is not supported. Skipping.
Line #34122 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=141,150 ) /         0,  0,  0,  0,  1,  0,  0,  0,  0,  2, -5,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  2, -5,  0,  0,  0,         2,  0, -1, -1,  1,  0,  0,  3, -7,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0,  0, -5,  0,  0,  0,         0,  0,  0,  0,  1,  0, -3,  7, -4,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,         1,  0,  0,  0,  1,  0,-18, 16,  0,  0,  0,  0,  0,  0,        -2,  0,  1,  1,  1,  0,  0,  1,  0, -2,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0, -8, 12,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0, -8, 13,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=141,150 )" is not supported. Skipping.
Line #34133 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=151,160 ) /         0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0,  0, -2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -2,  2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  2,  0,  0,  0,  0,  1,        -1,  0,  0,  1,  1,  0,  3, -4,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  1,  1,  0,  0,  3, -4,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0, -2,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  2,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=151,160 )" is not supported. Skipping.
Line #34144 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=161,170 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  2,         0,  0,  1, -1,  0,  0,  3, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0, -3,  5,  0,  0,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0, -3,  4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -2,  4,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0, -5,  6,  0,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  5, -7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  5, -8,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  6, -8,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -8, 15,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=161,170 )" is not supported. Skipping.
Line #34155 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=171,180 ) /        -2,  0,  0,  2,  1,  0,  0,  2,  0, -3,  0,  0,  0,  0,        -2,  0,  0,  2,  1,  0,  0,  6, -8,  0,  0,  0,  0,  0,         1,  0,  0, -1,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=171,180 )" is not supported. Skipping.
Line #34166 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=181,190 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  2,         0,  0,  1, -1,  2,  0,  0, -1,  0,  0, -1,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  0,  0,  0, -1,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -7, 13,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  7,-13,  0,  0,  0,  0,  0,         2,  0,  0, -2,  1,  0,  0, -5,  6,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -8, 11,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1, -1,  0,  2,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=181,190 )" is not supported. Skipping.
Line #34177 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=191,200 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,         0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  3,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  2,        -2,  0,  0,  2,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,         0,  0,  0,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0,         2,  0,  0, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -1,  0,  2,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0,  0, -2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=191,200 )" is not supported. Skipping.
Line #34188 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=201,210 ) /         0,  0,  0,  0,  1,  0,  0,  1, -2,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0,  0, -2,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -2,  0,  0,  2,  0,  0,  0,         0,  0,  1, -1,  1,  0,  3, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0,  0,         0,  0,  1, -1,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -3,  5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -3,  5,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=201,210 )" is not supported. Skipping.
Line #34199 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=211,220 ) /         0,  0,  2, -2,  2,  0, -3,  3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -3,  5,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0,  1, -4,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -2,  4,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -3,  4,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -2,  4,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0, -2,  4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  8,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=211,220 )" is not supported. Skipping.
Line #34210 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=221,230 ) /         0,  0,  2, -2,  2,  0, -5,  6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -5,  8,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  8,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -5,  7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -5,  8,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0,  0,         0,  0,  1, -1,  2,  0,  0, -1,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  0,  0, -1,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -2,  0,  1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=221,230 )" is not supported. Skipping.
Line #34221 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=231,240 ) /         0,  0,  0,  0,  0,  0,  0, -6, 11,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6,-11,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0, -1,  0,  4,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0,  0,  0,  0,         2,  0,  0, -2,  1,  0, -3,  3,  0,  0,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  2,  0,  0, -2,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -7,  9,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=231,240 )" is not supported. Skipping.
Line #34232 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=241,250 ) /         0,  0,  1, -1,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  2,         0,  0,  2, -2,  2,  0,  0, -2,  0,  2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  5,  0,  0,  2,         0,  0,  0,  0,  1,  0,  3, -5,  0,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  3, -4,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0, -3,  3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  2, -4,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -4,  4,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=241,250 )" is not supported. Skipping.
Line #34243 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=251,260 ) /         0,  0,  1, -1,  2,  0, -5,  7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -3,  6,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -4,  6,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -3,  6,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0, -3,  6,  0,  0,  0,  0,  2,         0,  0, -1,  1,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  2, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -5,  9,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -5,  9,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=251,260 )" is not supported. Skipping.
Line #34254 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=261,270 ) /         0,  0,  0,  0,  0,  0,  0,  5, -9,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  0,  1,  0, -2,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,        -2,  0,  1,  1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0, -2,  2,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -6, 10,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -6, 10,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -2,  3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -2,  3,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=261,270 )" is not supported. Skipping.
Line #34265 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=271,280 ) /         0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0, -1,  0,  3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -8,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -4,  8,  0,  0,  0,  0,  2,         0,  0, -2,  2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -4,  7,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=271,280 )" is not supported. Skipping.
Line #34276 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=281,290 ) /         0,  0,  0,  0,  0,  0,  0, -4,  7,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0, -2,  3,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -5, 10,  0,  0,  0,  0,  2,         0,  0,  0,  0,  1,  0, -1,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -3,  5,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -3,  5,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=281,290 )" is not supported. Skipping.
Line #34287 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=291,300 ) /         0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  1, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -1,  2,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -1,  2,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7, 11,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7, 11,  0,  0,  0,  0,  0,  1,         0,  0, -2,  2,  0,  0,  4, -4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0, -4,  4,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=291,300 )" is not supported. Skipping.
Line #34298 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=301,310 ) /         0,  0, -1,  1,  0,  0,  4, -5,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -4,  7,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -4,  6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -4,  7,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -4,  6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -4,  6,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -4,  5,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -4,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=301,310 )" is not supported. Skipping.
Line #34309 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=311,320 ) /        -2,  0,  0,  2,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,         0,  0, -1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  1, -1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  0,  5,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  3,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -7, 12,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -1,  1,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -1,  1,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=311,320 )" is not supported. Skipping.
Line #34320 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=321,330 ) /         0,  0,  1, -1,  1,  0, -1,  0,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  1, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -2,  5,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  0,  4,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0, -1,  1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -6, 10,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -6, 10,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=321,330 )" is not supported. Skipping.
Line #34331 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=331,340 ) /         0,  0,  2, -2,  1,  0,  0, -3,  0,  3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -3,  7,  0,  0,  0,  0,  2,        -2,  0,  0,  2,  0,  0,  4, -4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -5,  8,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  0,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  0,  3,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -2,  4,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=331,340 )" is not supported. Skipping.
Line #34342 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=341,350 ) /         0,  0,  1, -1,  1,  0, -2,  3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -2,  4,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  9,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  9,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  1,  0, -2,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -4,  6,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  3, -4,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=341,350 )" is not supported. Skipping.
Line #34353 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=351,360 ) /         0,  0,  0,  0,  0,  0,  0, -1,  0,  2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0, -2,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -5,  9,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -3,  4,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -3,  4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  1,  0,  0,  2, -2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=351,360 )" is not supported. Skipping.
Line #34364 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=361,370 ) /         0,  0,  0,  0,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -3,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  1, -5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  0,  1,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  5,  0,  0,  0,         0,  0,  0,  0,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -2,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=361,370 )" is not supported. Skipping.
Line #34375 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=371,380 ) /         0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0, -2,  2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -8, 14,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0,  2, -5,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  5, -8,  3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  5, -8,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  3, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=371,380 )" is not supported. Skipping.
Line #34386 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=381,390 ) /         0,  0,  0,  0,  0,  0,  0, -3,  8, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0, -2,  5,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 12,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 12,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  1, -2,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  1,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  2,  0,  0,  2,         0,  0,  2, -2,  1,  0, -5,  5,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=381,390 )" is not supported. Skipping.
Line #34397 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=391,400 ) /         0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -3,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -3,  6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  7,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  7,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0, -5,  6,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=391,400 )" is not supported. Skipping.
Line #34408 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=401,410 ) /         0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  0,  0,  0, -1,  0,  3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  1,  0,  2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -2,  6,  0,  0,  0,  0,  2,         0,  0,  0,  0,  1,  0,  2, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -6,  9,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -2,  2,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=401,410 )" is not supported. Skipping.
Line #34419 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=411,420 ) /         0,  0,  1, -1,  1,  0, -2,  1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  1,  0,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -5,  7,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -1,  3,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=411,420 )" is not supported. Skipping.
Line #34430 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=421,430 ) /         0,  0,  1, -1,  1,  0, -1,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -1,  3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7, 10,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7, 10,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -4,  8,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -4,  5,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -4,  5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=421,430 )" is not supported. Skipping.
Line #34441 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=431,440 ) /         0,  0,  0,  0,  0,  0,  0, -2,  0,  5,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -9, 13,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  5,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -2,  0,  4,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0, -4,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -2,  7,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=431,440 )" is not supported. Skipping.
Line #34452 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=441,450 ) /         0,  0,  0,  0,  0,  0, -2,  5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -2,  5,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  8,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  8,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  6, -8,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  1,  0,  0,  2,  0, -2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0, -3,  9,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=441,450 )" is not supported. Skipping.
Line #34463 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=451,460 ) /         0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5, 10,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -3,  3,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -3,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=451,460 )" is not supported. Skipping.
Line #34474 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=461,470 ) /         0,  0,  0,  0,  0,  0,  0, -5, 13,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0, -1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -2,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -2,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -1,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -6, 15,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 15,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=461,470 )" is not supported. Skipping.
Line #34485 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=471,480 ) /         0,  0,  0,  0,  0,  0, -3,  9, -4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  2, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -2,  8, -1, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6, -8,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  1,         0,  0,  1, -1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=471,480 )" is not supported. Skipping.
Line #34496 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=481,490 ) /         0,  0,  0,  0,  0,  0,  0, -6, 16, -4, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -2,  8, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -2,  8, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6, -8,  1,  5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3, -5,  4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 11,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 11,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -8, 11,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, 11,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=481,490 )" is not supported. Skipping.
Line #34507 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=491,500 ) /         0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  1,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3, -3,  0,  2,  0,  0,  0,  2,         0,  0,  2, -2,  1,  0,  0,  4, -8,  3,  0,  0,  0,  0,         0,  0,  1, -1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  0, -4,  8, -3,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  1,  2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -3,  7,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  6,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=491,500 )" is not supported. Skipping.
Line #34518 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=501,510 ) /         0,  0,  0,  0,  0,  0, -5,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  6,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  7, -9,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  2, -1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2, -1,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6, -7,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=501,510 )" is not supported. Skipping.
Line #34529 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=511,520 ) /         0,  0,  0,  0,  0,  0, -1,  4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -1,  4,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7,  9,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -7,  9,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  4, -3,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -4,  4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=511,520 )" is not supported. Skipping.
Line #34540 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=521,530 ) /         0,  0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -3,  0,  5,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -9, 12,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0, -4,  0,  0,  0,  0,         0,  0,  2, -2,  1,  0,  1, -1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  7, -8,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0, -3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=521,530 )" is not supported. Skipping.
Line #34551 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=531,540 ) /         0,  0,  0,  0,  0,  0,  0,  3,  0, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -2,  6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  7,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  6, -7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0, -2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  3,  0, -2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=531,540 )" is not supported. Skipping.
Line #34562 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=541,550 ) /         0,  0,  0,  0,  0,  0,  0,  3,  0, -1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0, -1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0,  0, -2,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0,  0, -1,  0,  0,  2,         0,  0,  2, -2,  1,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0, -8, 16,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0,  2, -5,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  7, -8,  3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -5, 16, -4, -5,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=541,550 )" is not supported. Skipping.
Line #34573 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=551,560 ) /         0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0, -1,  8, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 10,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8, 10,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -8, 10,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  2,  2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  3,  0,  1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -3,  8,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -5,  5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=551,560 )" is not supported. Skipping.
Line #34584 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=561,570 ) /         0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6, -5,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  7, -8,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=561,570 )" is not supported. Skipping.
Line #34595 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=571,580 ) /         0,  0,  0,  0,  0,  0,  4, -3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  1,  2,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -9, 11,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -9, 11,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  4,  0, -4,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4,  0, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -6,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  4,  0, -2,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=571,580 )" is not supported. Skipping.
Line #34606 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=581,590 ) /         0,  0,  0,  0,  0,  0,  0,  6, -4,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4,  0, -1,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4,  0,  0, -2,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5, -2,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  8, -9,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  5, -4,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=581,590 )" is not supported. Skipping.
Line #34617 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=591,600 ) /         0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -7,  7,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  5,  0, -4,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=591,600 )" is not supported. Skipping.
Line #34628 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=601,610 ) /         0,  0,  0,  0,  0,  0,  0,  5,  0, -3,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  5,  0, -2,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -8,  8,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  8, -8,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0, -9,  9,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -9,  9,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0, -9,  9,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=601,610 )" is not supported. Skipping.
Line #34639 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=611,620 ) /         0,  0,  0,  0,  0,  0,  9, -9,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  6, -4,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  2,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  1,         0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=611,620 )" is not supported. Skipping.
Line #34650 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=621,630 ) /         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,         1,  0,  0, -2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,        -1,  0,  0,  2,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,         1,  0,  0, -2,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,        -2,  0,  0,  2,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=621,630 )" is not supported. Skipping.
Line #34661 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=631,640 ) /        -1,  0,  0,  0,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0,        -1,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,        -1,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  2,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         1,  0, -1,  1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,        -1,  0,  0,  2,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0,        -2,  0,  0,  0,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0,         1,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,        -1,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  0,  0,  0,         1,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=631,640 )" is not supported. Skipping.
Line #34672 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=641,650 ) /        -1,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,        -1,  0,  0,  2,  1,  0,  0,  2,  0, -2,  0,  0,  0,  0,         0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,        -1,  0,  0,  2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,        -1,  0,  0,  2,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,         1,  0,  0, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,         1,  0,  2, -2,  2,  0, -3,  3,  0,  0,  0,  0,  0,  0,         1,  0,  2, -2,  2,  0,  0, -2,  0,  2,  0,  0,  0,  0,         1,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,         1,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=641,650 )" is not supported. Skipping.
Line #34683 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=651,660 ) /         0,  0,  0, -2,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,         0,  0,  0, -2,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0, -2,  2,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  0, -1,  0,  1,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0, -1,  1,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0, -2,  3,  0,  0,  0,  0,  0,  0,         0,  0,  0,  2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,         0,  0,  1,  1,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,        -1,  0,  2,  0,  2,  0, 10, -3,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=651,660 )" is not supported. Skipping.
Line #34694 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=661,670 ) /         0,  0,  1,  1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,        -1,  0,  2,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,         2,  0,  2, -2,  2,  0,  0, -2,  0,  3,  0,  0,  0,  0,         1,  0,  2,  0,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0,         0,  0,  1,  1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,        -1,  0,  2,  0,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,        -2,  0,  2,  2,  2,  0,  0,  2,  0, -2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=661,670 )" is not supported. Skipping.
Line #34705 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=671,680 ) /         0,  0,  2,  0,  2,  0,  2, -3,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  1, -1,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  0,  1,  0, -1,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  2, -2,  0,  0,  0,  0,  0,  0,        -1,  0,  2,  2,  2,  0,  0, -1,  0,  1,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0, -1,  1,  0,  0,  0,  0,  0,  0,        -1,  0,  2,  2,  2,  0,  0,  2,  0, -3,  0,  0,  0,  0,         2,  0,  2,  0,  2,  0,  0,  2,  0, -3,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=671,680 )" is not supported. Skipping.
Line #34719 in sofapy.f:"      DATA ( ( NAPL(I,J), I=1,14 ), J=681,687 ) /         1,  0,  1,  1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,         0,  0,  2,  0,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,         2,  0,  2,  0,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,        -1,  0,  2,  2,  2,  0,  0,  2,  0, -2,  0,  0,  0,  0,        -1,  0,  2,  2,  2,  0,  3, -3,  0,  0,  0,  0,  0,  0,         1,  0,  2,  0,  2,  0,  1, -1,  0,  0,  0,  0,  0,  0,         0,  0,  2,  2,  2,  0,  0,  2,  0, -2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( napl(i,j), i=1,14 ), j=681,687 )" is not supported. Skipping.
Line #34730 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=  1, 10 ) /       1440,          0,          0,          0,         56,       -117,        -42,        -40,        125,        -43,          0,        -54,          0,          5,          0,          0,          3,         -7,         -3,          0,          3,          0,          0,         -2,       -114,          0,          0,         61,       -219,         89,          0,          0,         -3,          0,          0,          0,       -462,       1604,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=  1, 10 )" is not supported. Skipping.
Line #34741 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 11, 20 ) /         99,          0,          0,        -53,         -3,          0,          0,          2,          0,          6,          2,          0,          3,          0,          0,          0,        -12,          0,          0,          0,         14,       -218,        117,          8,         31,       -481,       -257,        -17,       -491,        128,          0,          0,      -3084,       5123,       2735,       1647,      -1444,       2409,      -1286,       -771 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 11, 20 )" is not supported. Skipping.
Line #34752 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 21, 30 ) /         11,        -24,        -11,         -9,         26,         -9,          0,          0,        103,        -60,          0,          0,          0,        -13,         -7,          0,        -26,        -29,        -16,         14,          9,        -27,        -14,         -5,         12,          0,          0,         -6,         -7,          0,          0,          0,          0,         24,          0,          0,        284,          0,          0,       -151 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 21, 30 )" is not supported. Skipping.
Line #34763 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 31, 40 ) /        226,        101,          0,          0,          0,         -8,         -2,          0,          0,         -6,         -3,          0,          5,          0,          0,         -3,        -41,        175,         76,         17,          0,         15,          6,          0,        425,        212,       -133,        269,       1200,        598,        319,       -641,        235,        334,          0,          0,         11,        -12,         -7,         -6 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 31, 40 )" is not supported. Skipping.
Line #34774 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 41, 50 ) /          5,         -6,          3,          3,         -5,          0,          0,          3,          6,          0,          0,         -3,         15,          0,          0,          0,         13,          0,          0,         -7,         -6,         -9,          0,          0,        266,        -78,          0,          0,       -460,       -435,       -232,        246,          0,         15,          7,          0,         -3,          0,          0,          2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 41, 50 )" is not supported. Skipping.
Line #34785 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 51, 60 ) /          0,        131,          0,          0,          4,          0,          0,          0,          0,          3,          0,          0,          0,          4,          2,          0,          0,          3,          0,          0,        -17,        -19,        -10,          9,         -9,        -11,          6,         -5,         -6,          0,          0,          3,        -16,          8,          0,          0,          0,          3,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 51, 60 )" is not supported. Skipping.
Line #34796 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 61, 70 ) /         11,         24,         11,         -5,         -3,         -4,         -2,          1,          3,          0,          0,         -1,          0,         -8,         -4,          0,          0,          3,          0,          0,          0,          5,          0,          0,          0,          3,          2,          0,         -6,          4,          2,          3,         -3,         -5,          0,          0,         -5,          0,          0,          2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 61, 70 )" is not supported. Skipping.
Line #34807 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 71, 80 ) /          4,         24,         13,         -2,        -42,         20,          0,          0,        -10,        233,          0,          0,         -3,          0,          0,          1,         78,        -18,          0,          0,          0,          3,          1,          0,          0,         -3,         -1,          0,          0,         -4,         -2,          1,          0,         -8,         -4,         -1,          0,         -5,          3,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 71, 80 )" is not supported. Skipping.
Line #34818 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 81, 90 ) /         -7,          0,          0,          3,        -14,          8,          3,          6,          0,          8,         -4,          0,          0,         19,         10,          0,         45,        -22,          0,          0,         -3,          0,          0,          0,          0,         -3,          0,          0,          0,          3,          0,          0,          3,          5,          3,         -2,         89,        -16,         -9,        -48 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 81, 90 )" is not supported. Skipping.
Line #34829 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J= 91,100 ) /          0,          3,          0,          0,         -3,          7,          4,          2,       -349,        -62,          0,          0,        -15,         22,          0,          0,         -3,          0,          0,          0,        -53,          0,          0,          0,          5,          0,          0,         -3,          0,         -8,          0,          0,         15,         -7,         -4,         -8,         -3,          0,          0,          1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j= 91,100 )" is not supported. Skipping.
Line #34840 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=101,110 ) /        -21,        -78,          0,          0,         20,        -70,        -37,        -11,          0,          6,          3,          0,          5,          3,          2,         -2,        -17,         -4,         -2,          9,          0,          6,          3,          0,         32,         15,         -8,         17,        174,         84,         45,        -93,         11,         56,          0,          0,        -66,        -12,         -6,         35 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=101,110 )" is not supported. Skipping.
Line #34851 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=111,120 ) /         47,          8,          4,        -25,          0,          8,          4,          0,         10,        -22,        -12,         -5,         -3,          0,          0,          2,        -24,         12,          0,          0,          5,         -6,          0,          0,          3,          0,          0,         -2,          4,          3,          1,         -2,          0,         29,         15,          0,         -5,         -4,         -2,          2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=111,120 )" is not supported. Skipping.
Line #34862 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=121,130 ) /          8,         -3,         -1,         -5,          0,         -3,          0,          0,         10,          0,          0,          0,          3,          0,          0,         -2,         -5,          0,          0,          3,         46,         66,         35,        -25,        -14,          7,          0,          0,          0,          3,          2,          0,         -5,          0,          0,          0,        -68,        -34,        -18,         36 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=121,130 )" is not supported. Skipping.
Line #34873 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=131,140 ) /          0,         14,          7,          0,         10,         -6,         -3,         -5,         -5,         -4,         -2,          3,         -3,          5,          2,          1,         76,         17,          9,        -41,         84,        298,        159,        -45,          3,          0,          0,         -1,         -3,          0,          0,          2,         -3,          0,          0,          1,        -82,        292,        156,         44 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=131,140 )" is not supported. Skipping.
Line #34884 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=141,150 ) /        -73,         17,          9,         39,         -9,        -16,          0,          0,          3,          0,         -1,         -2,         -3,          0,          0,          0,         -9,         -5,         -3,          5,       -439,          0,          0,          0,         57,        -28,        -15,        -30,          0,         -6,         -3,          0,         -4,          0,          0,          2,        -40,         57,         30,         21 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=141,150 )" is not supported. Skipping.
Line #34895 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=151,160 ) /         23,          7,          3,        -13,        273,         80,         43,       -146,       -449,        430,          0,          0,         -8,        -47,        -25,          4,          6,         47,         25,         -3,          0,         23,         13,          0,         -3,          0,          0,          2,          3,         -4,         -2,         -2,        -48,       -110,        -59,         26,         51,        114,         61,        -27 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=151,160 )" is not supported. Skipping.
Line #34906 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=161,170 ) /       -133,          0,          0,         57,          0,          4,          0,          0,        -21,         -6,         -3,         11,          0,         -3,         -1,          0,        -11,        -21,        -11,          6,        -18,       -436,       -233,          9,         35,         -7,          0,          0,          0,          5,          3,          0,         11,         -3,         -1,         -6,         -5,         -3,         -1,          3 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=161,170 )" is not supported. Skipping.
Line #34917 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=171,180 ) /        -53,         -9,         -5,         28,          0,          3,          2,          1,          4,          0,          0,         -2,          0,         -4,          0,          0,        -50,        194,        103,         27,        -13,         52,         28,          7,        -91,        248,          0,          0,          6,         49,         26,         -3,         -6,        -47,        -25,          3,          0,          5,          3,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=171,180 )" is not supported. Skipping.
Line #34928 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=181,190 ) /         52,         23,         10,        -23,         -3,          0,          0,          1,          0,          5,          3,          0,         -4,          0,          0,          0,         -4,          8,          3,          2,         10,          0,          0,          0,          3,          0,          0,         -2,          0,          8,          4,          0,          0,          8,          4,          1,         -4,          0,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=181,190 )" is not supported. Skipping.
Line #34939 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=191,200 ) /         -4,          0,          0,          0,         -8,          4,          2,          4,          8,         -4,         -2,         -4,          0,         15,          7,          0,       -138,          0,          0,          0,          0,         -7,         -3,          0,          0,         -7,         -3,          0,         54,          0,          0,        -29,          0,         10,          4,          0,         -7,          0,          0,          3 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=191,200 )" is not supported. Skipping.
Line #34950 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=201,210 ) /        -37,         35,         19,         20,          0,          4,          0,          0,         -4,          9,          0,          0,          8,          0,          0,         -4,         -9,        -14,         -8,          5,         -3,         -9,         -5,          3,       -145,         47,          0,          0,        -10,         40,         21,          5,         11,        -49,        -26,         -7,      -2150,          0,          0,        932 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=201,210 )" is not supported. Skipping.
Line #34961 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=211,220 ) /        -12,          0,          0,          5,         85,          0,          0,        -37,          4,          0,          0,         -2,          3,          0,          0,         -2,        -86,        153,          0,          0,         -6,          9,          5,          3,          9,        -13,         -7,         -5,         -8,         12,          6,          4,        -51,          0,          0,         22,        -11,       -268,       -116,          5 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=211,220 )" is not supported. Skipping.
Line #34972 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=221,230 ) /          0,         12,          5,          0,          0,          7,          3,          0,         31,          6,          3,        -17,        140,         27,         14,        -75,         57,         11,          6,        -30,        -14,        -39,          0,          0,          0,         -6,         -2,          0,          4,         15,          8,         -2,          0,          4,          0,          0,         -3,          0,          0,          1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=221,230 )" is not supported. Skipping.
Line #34983 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=231,240 ) /          0,         11,          5,          0,          9,          6,          0,          0,         -4,         10,          4,          2,          5,          3,          0,          0,         16,          0,          0,         -9,         -3,          0,          0,          0,          0,          3,          2,         -1,          7,          0,          0,         -3,        -25,         22,          0,          0,         42,        223,        119,        -22 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=231,240 )" is not supported. Skipping.
Line #34994 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=241,250 ) /        -27,       -143,        -77,         14,          9,         49,         26,         -5,      -1166,          0,          0,        505,         -5,          0,          0,          2,         -6,          0,          0,          3,         -8,          0,          1,          4,          0,         -4,          0,          0,        117,          0,          0,        -63,         -4,          8,          4,          2,          3,          0,          0,         -2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=241,250 )" is not supported. Skipping.
Line #35005 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=251,260 ) /         -5,          0,          0,          2,          0,         31,          0,          0,         -5,          0,          1,          3,          4,          0,          0,         -2,         -4,          0,          0,          2,        -24,        -13,         -6,         10,          3,          0,          0,          0,          0,        -32,        -17,          0,          8,         12,          5,         -3,          3,          0,          0,         -1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=251,260 )" is not supported. Skipping.
Line #35016 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=261,270 ) /          7,         13,          0,          0,         -3,         16,          0,          0,         50,          0,          0,        -27,          0,         -5,         -3,          0,         13,          0,          0,          0,          0,          5,          3,          1,         24,          5,          2,        -11,          5,        -11,         -5,         -2,         30,         -3,         -2,        -16,         18,          0,          0,         -9 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=261,270 )" is not supported. Skipping.
Line #35027 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=271,280 ) /          8,        614,          0,          0,          3,         -3,         -1,         -2,          6,         17,          9,         -3,         -3,         -9,         -5,          2,          0,          6,          3,         -1,       -127,         21,          9,         55,          3,          5,          0,          0,         -6,        -10,         -4,          3,          5,          0,          0,          0,         16,          9,          4,         -7 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=271,280 )" is not supported. Skipping.
Line #35038 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=281,290 ) /          3,          0,          0,         -2,          0,         22,          0,          0,          0,         19,         10,          0,          7,          0,          0,         -4,          0,         -5,         -2,          0,          0,          3,          1,          0,         -9,          3,          1,          4,         17,          0,          0,         -7,          0,         -3,         -2,         -1,        -20,         34,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=281,290 )" is not supported. Skipping.
Line #35049 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=291,300 ) /        -10,          0,          1,          5,         -4,          0,          0,          2,         22,        -87,          0,          0,         -4,          0,          0,          2,         -3,         -6,         -2,          1,        -16,         -3,         -1,          7,          0,         -3,         -2,          0,          4,          0,          0,          0,        -68,         39,          0,          0,         27,          0,          0,        -14 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=291,300 )" is not supported. Skipping.
Line #35060 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=301,310 ) /          0,         -4,          0,          0,        -25,          0,          0,          0,        -12,         -3,         -2,          6,          3,          0,          0,         -1,          3,         66,         29,         -1,        490,          0,          0,       -213,        -22,         93,         49,         12,         -7,         28,         15,          4,         -3,         13,          7,          2,        -46,         14,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=301,310 )" is not supported. Skipping.
Line #35071 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=311,320 ) /         -5,          0,          0,          0,          2,          1,          0,          0,          0,         -3,          0,          0,        -28,          0,          0,         15,          5,          0,          0,         -2,          0,          3,          0,          0,        -11,          0,          0,          5,          0,          3,          1,          0,         -3,          0,          0,          1,         25,        106,         57,        -13 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=311,320 )" is not supported. Skipping.
Line #35082 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=321,330 ) /          5,         21,         11,         -3,       1485,          0,          0,          0,         -7,        -32,        -17,          4,          0,          5,          3,          0,         -6,         -3,         -2,          3,         30,         -6,         -2,        -13,         -4,          4,          0,          0,        -19,          0,          0,         10,          0,          4,          2,         -1,          0,          3,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=321,330 )" is not supported. Skipping.
Line #35093 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=331,340 ) /          4,          0,          0,         -2,          0,         -3,         -1,          0,         -3,          0,          0,          0,          5,          3,          1,         -2,          0,         11,          0,          0,        118,          0,          0,        -52,          0,         -5,         -3,          0,        -28,         36,          0,          0,          5,         -5,          0,          0,         14,        -59,        -31,         -8 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=331,340 )" is not supported. Skipping.
Line #35104 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=341,350 ) /          0,          9,          5,          1,       -458,          0,          0,        198,          0,        -45,        -20,          0,          9,          0,          0,         -5,          0,         -3,          0,          0,          0,         -4,         -2,         -1,         11,          0,          0,         -6,          6,          0,          0,         -2,        -16,         23,          0,          0,          0,         -4,         -2,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=341,350 )" is not supported. Skipping.
Line #35115 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=351,360 ) /         -5,          0,          0,          2,       -166,        269,          0,          0,         15,          0,          0,         -8,         10,          0,          0,         -4,        -78,         45,          0,          0,          0,         -5,         -2,          0,          7,          0,          0,         -4,         -5,        328,          0,          0,          3,          0,          0,         -2,          5,          0,          0,         -2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=351,360 )" is not supported. Skipping.
Line #35126 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=361,370 ) /          0,          3,          1,          0,         -3,          0,          0,          0,         -3,          0,          0,          0,          0,         -4,         -2,          0,      -1223,        -26,          0,          0,          0,          7,          3,          0,          3,          0,          0,          0,          0,          3,          2,          0,         -6,         20,          0,          0,       -368,          0,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=361,370 )" is not supported. Skipping.
Line #35137 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=371,380 ) /        -75,          0,          0,          0,         11,          0,          0,         -6,          3,          0,          0,         -2,         -3,          0,          0,          1,        -13,        -30,          0,          0,         21,          3,          0,          0,         -3,          0,          0,          1,         -4,          0,          0,          2,          8,        -27,          0,          0,        -19,        -11,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=371,380 )" is not supported. Skipping.
Line #35148 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=381,390 ) /         -4,          0,          0,          2,          0,          5,          2,          0,         -6,          0,          0,          2,         -8,          0,          0,          0,         -1,          0,          0,          0,        -14,          0,          0,          6,          6,          0,          0,          0,        -74,          0,          0,         32,          0,         -3,         -1,          0,          4,          0,          0,         -2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=381,390 )" is not supported. Skipping.
Line #35159 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=391,400 ) /          8,         11,          0,          0,          0,          3,          2,          0,       -262,          0,          0,        114,          0,         -4,          0,          0,         -7,          0,          0,          4,          0,        -27,        -12,          0,        -19,         -8,         -4,          8,        202,          0,          0,        -87,         -8,         35,         19,          5,          0,          4,          2,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=391,400 )" is not supported. Skipping.
Line #35170 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=401,410 ) /         16,         -5,          0,          0,          5,          0,          0,         -3,          0,         -3,          0,          0,          1,          0,          0,          0,        -35,        -48,        -21,         15,         -3,         -5,         -2,          1,          6,          0,          0,         -3,          3,          0,          0,         -1,          0,         -5,          0,          0,         12,         55,         29,         -6 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=401,410 )" is not supported. Skipping.
Line #35181 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=411,420 ) /          0,          5,          3,          0,       -598,          0,          0,          0,         -3,        -13,         -7,          1,         -5,         -7,         -3,          2,          3,          0,          0,         -1,          5,         -7,          0,          0,          4,          0,          0,         -2,         16,         -6,          0,          0,          8,         -3,          0,          0,          8,        -31,        -16,         -4 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=411,420 )" is not supported. Skipping.
Line #35192 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=421,430 ) /          0,          3,          1,          0,        113,          0,          0,        -49,          0,        -24,        -10,          0,          4,          0,          0,         -2,         27,          0,          0,          0,         -3,          0,          0,          1,          0,         -4,         -2,          0,          5,          0,          0,         -2,          0,         -3,          0,          0,        -13,          0,          0,          6 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=421,430 )" is not supported. Skipping.
Line #35203 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=431,440 ) /          5,          0,          0,         -2,        -18,        -10,         -4,          8,         -4,        -28,          0,          0,         -5,          6,          3,          2,         -3,          0,          0,          1,         -5,         -9,         -4,          2,         17,          0,          0,         -7,         11,          4,          0,          0,          0,         -6,         -2,          0,         83,         15,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=431,440 )" is not supported. Skipping.
Line #35214 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=441,450 ) /         -4,          0,          0,          2,          0,       -114,        -49,          0,        117,          0,          0,        -51,         -5,         19,         10,          2,         -3,          0,          0,          0,         -3,          0,          0,          2,          0,         -3,         -1,          0,          3,          0,          0,          0,          0,         -6,         -2,          0,        393,          3,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=441,450 )" is not supported. Skipping.
Line #35225 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=451,460 ) /         -4,         21,         11,          2,         -6,          0,         -1,          3,         -3,          8,          4,          1,          8,          0,          0,          0,         18,        -29,        -13,         -8,          8,         34,         18,         -4,         89,          0,          0,          0,          3,         12,          6,         -1,         54,        -15,         -7,        -24,          0,          3,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=451,460 )" is not supported. Skipping.
Line #35236 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=461,470 ) /          3,          0,          0,         -1,          0,         35,          0,          0,       -154,        -30,        -13,         67,         15,          0,          0,          0,          0,          4,          2,          0,          0,          9,          0,          0,         80,        -71,        -31,        -35,          0,        -20,         -9,          0,         11,          5,          2,         -5,         61,        -96,        -42,        -27 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=461,470 )" is not supported. Skipping.
Line #35247 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=471,480 ) /         14,          9,          4,         -6,        -11,         -6,         -3,          5,          0,         -3,         -1,          0,        123,       -415,       -180,        -53,          0,          0,          0,        -35,         -5,          0,          0,          0,          7,        -32,        -17,         -4,          0,         -9,         -5,          0,          0,         -4,          2,          0,        -89,          0,          0,         38 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=471,480 )" is not supported. Skipping.
Line #35258 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=481,490 ) /          0,        -86,        -19,         -6,          0,          0,        -19,          6,       -123,       -416,       -180,         53,          0,         -3,         -1,          0,         12,         -6,         -3,         -5,        -13,          9,          4,          6,          0,        -15,         -7,          0,          3,          0,          0,         -1,        -62,        -97,        -42,         27,        -11,          5,          2,          5 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=481,490 )" is not supported. Skipping.
Line #35269 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=491,500 ) /          0,        -19,         -8,          0,         -3,          0,          0,          1,          0,          4,          2,          0,          0,          3,          0,          0,          0,          4,          2,          0,        -85,        -70,        -31,         37,        163,        -12,         -5,        -72,        -63,        -16,         -7,         28,        -21,        -32,        -14,          9,          0,         -3,         -1,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=491,500 )" is not supported. Skipping.
Line #35280 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=501,510 ) /          3,          0,          0,         -2,          0,          8,          0,          0,          3,         10,          4,         -1,          3,          0,          0,         -1,          0,         -7,         -3,          0,          0,         -4,         -2,          0,          6,         19,          0,          0,          5,       -173,        -75,         -2,          0,         -7,         -3,          0,          7,        -12,         -5,         -3 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=501,510 )" is not supported. Skipping.
Line #35291 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=511,520 ) /         -3,          0,          0,          2,          3,         -4,         -2,         -1,         74,          0,          0,        -32,         -3,         12,          6,          2,         26,        -14,         -6,        -11,         19,          0,          0,         -8,          6,         24,         13,         -3,         83,          0,          0,          0,          0,        -10,         -5,          0,         11,         -3,         -1,         -5 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=511,520 )" is not supported. Skipping.
Line #35302 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=521,530 ) /          3,          0,          1,         -1,          3,          0,          0,         -1,         -4,          0,          0,          0,          5,        -23,        -12,         -3,       -339,          0,          0,        147,          0,        -10,         -5,          0,          5,          0,          0,          0,          3,          0,          0,         -1,          0,         -4,         -2,          0,         18,         -3,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=521,530 )" is not supported. Skipping.
Line #35313 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=531,540 ) /          9,        -11,         -5,         -4,         -8,          0,          0,          4,          3,          0,          0,         -1,          0,          9,          0,          0,          6,         -9,         -4,         -2,         -4,        -12,          0,          0,         67,        -91,        -39,        -29,         30,        -18,         -8,        -13,          0,          0,          0,          0,          0,       -114,        -50,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=531,540 )" is not supported. Skipping.
Line #35324 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=541,550 ) /          0,          0,          0,         23,        517,         16,          7,       -224,          0,         -7,         -3,          0,        143,         -3,         -1,        -62,         29,          0,          0,        -13,         -4,          0,          0,          2,         -6,          0,          0,          3,          5,         12,          5,         -2,        -25,          0,          0,         11,         -3,          0,          0,          1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=541,550 )" is not supported. Skipping.
Line #35335 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=551,560 ) /          0,          4,          2,          0,        -22,         12,          5,         10,         50,          0,          0,        -22,          0,          7,          4,          0,          0,          3,          1,          0,         -4,          4,          2,          2,         -5,        -11,         -5,          2,          0,          4,          2,          0,          4,         17,          9,         -2,         59,          0,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=551,560 )" is not supported. Skipping.
Line #35346 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=561,570 ) /          0,         -4,         -2,          0,         -8,          0,          0,          4,         -3,          0,          0,          0,          4,        -15,         -8,         -2,        370,         -8,          0,       -160,          0,          0,         -3,          0,          0,          3,          1,          0,         -6,          3,          1,          3,          0,          6,          0,          0,        -10,          0,          0,          4 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=561,570 )" is not supported. Skipping.
Line #35357 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=571,580 ) /          0,          9,          4,          0,          4,         17,          7,         -2,         34,          0,          0,        -15,          0,          5,          3,          0,         -5,          0,          0,          2,        -37,         -7,         -3,         16,          3,         13,          7,         -2,         40,          0,          0,          0,          0,         -3,         -2,          0,       -184,         -3,         -1,         80 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=571,580 )" is not supported. Skipping.
Line #35368 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=581,590 ) /         -3,          0,          0,          1,         -3,          0,          0,          0,          0,        -10,         -6,         -1,         31,         -6,          0,        -13,         -3,        -32,        -14,          1,         -7,          0,          0,          3,          0,         -8,         -4,          0,          3,         -4,          0,          0,          0,          4,          0,          0,          0,          3,          1,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=581,590 )" is not supported. Skipping.
Line #35379 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=591,600 ) /         19,        -23,        -10,          2,          0,          0,          0,        -10,          0,          3,          2,          0,          0,          9,          5,         -1,         28,          0,          0,          0,          0,         -7,         -4,          0,          8,         -4,          0,         -4,          0,          0,         -2,          0,          0,          3,          0,          0,         -3,          0,          0,          1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=591,600 )" is not supported. Skipping.
Line #35390 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=601,610 ) /         -9,          0,          1,          4,          3,         12,          5,         -1,         17,         -3,         -1,          0,          0,          7,          4,          0,         19,          0,          0,          0,          0,         -5,         -3,          0,         14,         -3,          0,         -1,          0,          0,         -1,          0,          0,          0,          0,         -5,          0,          5,          3,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=601,610 )" is not supported. Skipping.
Line #35401 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=611,620 ) /         13,          0,          0,          0,          0,         -3,         -2,          0,          2,          9,          4,          3,          0,          0,          0,         -4,          8,          0,          0,          0,          0,          4,          2,          0,          6,          0,          0,         -3,          6,          0,          0,          0,          0,          3,          1,          0,          5,          0,          0,         -2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=611,620 )" is not supported. Skipping.
Line #35412 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=621,630 ) /          3,          0,          0,         -1,         -3,          0,          0,          0,          6,          0,          0,          0,          7,          0,          0,          0,         -4,          0,          0,          0,          4,          0,          0,          0,          6,          0,          0,          0,          0,         -4,          0,          0,          0,         -4,          0,          0,          5,          0,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=621,630 )" is not supported. Skipping.
Line #35423 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=631,640 ) /         -3,          0,          0,          0,          4,          0,          0,          0,         -5,          0,          0,          0,          4,          0,          0,          0,          0,          3,          0,          0,         13,          0,          0,          0,         21,         11,          0,          0,          0,         -5,          0,          0,          0,         -5,         -2,          0,          0,          5,          3,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=631,640 )" is not supported. Skipping.
Line #35434 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=641,650 ) /          0,         -5,          0,          0,         -3,          0,          0,          2,         20,         10,          0,          0,        -34,          0,          0,          0,        -19,          0,          0,          0,          3,          0,          0,         -2,         -3,          0,          0,          1,         -6,          0,          0,          3,         -4,          0,          0,          0,          3,          0,          0,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=641,650 )" is not supported. Skipping.
Line #35445 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=651,660 ) /          3,          0,          0,          0,          4,          0,          0,          0,          3,          0,          0,         -1,          6,          0,          0,         -3,         -8,          0,          0,          3,          0,          3,          1,          0,         -3,          0,          0,          0,          0,         -3,         -2,          0,        126,        -63,        -27,        -55,         -5,          0,          1,          2 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=651,660 )" is not supported. Skipping.
Line #35456 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=661,670 ) /         -3,         28,         15,          2,          5,          0,          1,         -2,          0,          9,          4,          1,          0,          9,          4,         -1,       -126,        -63,        -27,         55,          3,          0,          0,         -1,         21,        -11,         -6,        -11,          0,         -4,          0,          0,        -21,        -11,         -6,         11,         -3,          0,          0,          1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=661,670 )" is not supported. Skipping.
Line #35467 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=671,680 ) /          0,          3,          1,          0,          8,          0,          0,         -4,         -6,          0,          0,          3,         -3,          0,          0,          1,          3,          0,          0,         -1,         -3,          0,          0,          1,         -5,          0,          0,          2,         24,        -12,         -5,        -11,          0,          3,          1,          0,          0,          3,          1,          0 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=671,680 )" is not supported. Skipping.
Line #35477 in sofapy.f:"      DATA ( ( ICPL(I,J), I=1,4 ), J=681,687 ) /          0,          3,          2,          0,        -24,        -12,         -5,         10,          4,          0,         -1,         -2,         13,          0,          0,         -6,          7,          0,          0,         -3,          3,          0,          0,         -1,          3,          0,          0,         -1 /"
	analyzeline: implied-DO list "( ( icpl(i,j), i=1,4 ), j=681,687 )" is not supported. Skipping.
Line #35936 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J= 1,10 ) /          0,    0,    0,    0,    1,          0,    0,    2,   -2,    2,          0,    0,    2,    0,    2,          0,    0,    0,    0,    2,          0,    1,    0,    0,    0,          0,    1,    2,   -2,    2,          1,    0,    0,    0,    0,          0,    0,    2,    0,    1,          1,    0,    2,    0,    2,          0,   -1,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j= 1,10 )" is not supported. Skipping.
Line #35947 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=11,20 ) /          0,    0,    2,   -2,    1,         -1,    0,    2,    0,    2,         -1,    0,    0,    2,    0,          1,    0,    0,    0,    1,         -1,    0,    0,    0,    1,         -1,    0,    2,    2,    2,          1,    0,    2,    0,    1,         -2,    0,    2,    0,    1,          0,    0,    0,    2,    0,          0,    0,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=11,20 )" is not supported. Skipping.
Line #35958 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=21,30 ) /          0,   -2,    2,   -2,    2,         -2,    0,    0,    2,    0,          2,    0,    2,    0,    2,          1,    0,    2,   -2,    2,         -1,    0,    2,    0,    1,          2,    0,    0,    0,    0,          0,    0,    2,    0,    0,          0,    1,    0,    0,    1,         -1,    0,    0,    2,    1,          0,    2,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=21,30 )" is not supported. Skipping.
Line #35969 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=31,40 ) /          0,    0,   -2,    2,    0,          1,    0,    0,   -2,    1,          0,   -1,    0,    0,    1,         -1,    0,    2,    2,    1,          0,    2,    0,    0,    0,          1,    0,    2,    2,    2,         -2,    0,    2,    0,    0,          0,    1,    2,    0,    2,          0,    0,    2,    2,    1,          0,   -1,    2,    0,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=31,40 )" is not supported. Skipping.
Line #35980 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=41,50 ) /          0,    0,    0,    2,    1,          1,    0,    2,   -2,    1,          2,    0,    2,   -2,    2,         -2,    0,    0,    2,    1,          2,    0,    2,    0,    1,          0,   -1,    2,   -2,    1,          0,    0,    0,   -2,    1,         -1,   -1,    0,    2,    0,          2,    0,    0,   -2,    1,          1,    0,    0,    2,    0 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=41,50 )" is not supported. Skipping.
Line #35991 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=51,60 ) /          0,    1,    2,   -2,    1,          1,   -1,    0,    0,    0,         -2,    0,    2,    0,    2,          3,    0,    2,    0,    2,          0,   -1,    0,    2,    0,          1,   -1,    2,    0,    2,          0,    0,    0,    1,    0,         -1,   -1,    2,    2,    2,         -1,    0,    2,    0,    0,          0,   -1,    2,    2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=51,60 )" is not supported. Skipping.
Line #36002 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=61,70 ) /         -2,    0,    0,    0,    1,          1,    1,    2,    0,    2,          2,    0,    0,    0,    1,         -1,    1,    0,    1,    0,          1,    1,    0,    0,    0,          1,    0,    2,    0,    0,         -1,    0,    2,   -2,    1,          1,    0,    0,    0,    2,         -1,    0,    0,    1,    0,          0,    0,    2,    1,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=61,70 )" is not supported. Skipping.
Line #36016 in sofapy.f:"      DATA ( ( NALS(I,J), I=1,5 ), J=71,77 ) /         -1,    0,    2,    4,    2,         -1,    1,    0,    1,    1,          0,   -2,    2,   -2,    1,          1,    0,    2,    2,    1,         -2,    0,    2,    2,    2,         -1,    0,    0,    0,    2,          1,    1,    2,   -2,    2 /"
	analyzeline: implied-DO list "( ( nals(i,j), i=1,5 ), j=71,77 )" is not supported. Skipping.
Line #36027 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J= 1,10 ) / -172064161D0, -174666D0,  33386D0, 92052331D0,  9086D0, 15377D0,  -13170906D0,   -1675D0, -13696D0,  5730336D0, -3015D0, -4587D0,   -2276413D0,    -234D0,   2796D0,   978459D0,  -485D0,  1374D0,    2074554D0,     207D0,   -698D0,  -897492D0,   470D0,  -291D0,    1475877D0,   -3633D0,  11817D0,    73871D0,  -184D0, -1924D0,    -516821D0,    1226D0,   -524D0,   224386D0,  -677D0,  -174D0,     711159D0,      73D0,   -872D0,    -6750D0,     0D0,   358D0,    -387298D0,    -367D0,    380D0,   200728D0,    18D0,   318D0,    -301461D0,     -36D0,    816D0,   129025D0,   -63D0,   367D0,     215829D0,    -494D0,    111D0,   -95929D0,   299D0,   132D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j= 1,10 )" is not supported. Skipping.
Line #36038 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=11,20 ) /     128227D0,     137D0,    181D0,   -68982D0,    -9D0,    39D0,     123457D0,      11D0,     19D0,   -53311D0,    32D0,    -4D0,     156994D0,      10D0,   -168D0,    -1235D0,     0D0,    82D0,      63110D0,      63D0,     27D0,   -33228D0,     0D0,    -9D0,     -57976D0,     -63D0,   -189D0,    31429D0,     0D0,   -75D0,     -59641D0,     -11D0,    149D0,    25543D0,   -11D0,    66D0,     -51613D0,     -42D0,    129D0,    26366D0,     0D0,    78D0,      45893D0,      50D0,     31D0,   -24236D0,   -10D0,    20D0,      63384D0,      11D0,   -150D0,    -1220D0,     0D0,    29D0,     -38571D0,      -1D0,    158D0,    16452D0,   -11D0,    68D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=11,20 )" is not supported. Skipping.
Line #36049 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=21,30 ) /      32481D0,       0D0,      0D0,   -13870D0,     0D0,     0D0,     -47722D0,       0D0,    -18D0,      477D0,     0D0,   -25D0,     -31046D0,      -1D0,    131D0,    13238D0,   -11D0,    59D0,      28593D0,       0D0,     -1D0,   -12338D0,    10D0,    -3D0,      20441D0,      21D0,     10D0,   -10758D0,     0D0,    -3D0,      29243D0,       0D0,    -74D0,     -609D0,     0D0,    13D0,      25887D0,       0D0,    -66D0,     -550D0,     0D0,    11D0,     -14053D0,     -25D0,     79D0,     8551D0,    -2D0,   -45D0,      15164D0,      10D0,     11D0,    -8001D0,     0D0,    -1D0,     -15794D0,      72D0,    -16D0,     6850D0,   -42D0,    -5D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=21,30 )" is not supported. Skipping.
Line #36060 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=31,40 ) /      21783D0,       0D0,     13D0,     -167D0,     0D0,    13D0,     -12873D0,     -10D0,    -37D0,     6953D0,     0D0,   -14D0,     -12654D0,      11D0,     63D0,     6415D0,     0D0,    26D0,     -10204D0,       0D0,     25D0,     5222D0,     0D0,    15D0,      16707D0,     -85D0,    -10D0,      168D0,    -1D0,    10D0,      -7691D0,       0D0,     44D0,     3268D0,     0D0,    19D0,     -11024D0,       0D0,    -14D0,      104D0,     0D0,     2D0,       7566D0,     -21D0,    -11D0,    -3250D0,     0D0,    -5D0,      -6637D0,     -11D0,     25D0,     3353D0,     0D0,    14D0,      -7141D0,      21D0,      8D0,     3070D0,     0D0,     4D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=31,40 )" is not supported. Skipping.
Line #36071 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=41,50 ) /      -6302D0,     -11D0,      2D0,     3272D0,     0D0,     4D0,       5800D0,      10D0,      2D0,    -3045D0,     0D0,    -1D0,       6443D0,       0D0,     -7D0,    -2768D0,     0D0,    -4D0,      -5774D0,     -11D0,    -15D0,     3041D0,     0D0,    -5D0,      -5350D0,       0D0,     21D0,     2695D0,     0D0,    12D0,      -4752D0,     -11D0,     -3D0,     2719D0,     0D0,    -3D0,      -4940D0,     -11D0,    -21D0,     2720D0,     0D0,    -9D0,       7350D0,       0D0,     -8D0,      -51D0,     0D0,     4D0,       4065D0,       0D0,      6D0,    -2206D0,     0D0,     1D0,       6579D0,       0D0,    -24D0,     -199D0,     0D0,     2D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=41,50 )" is not supported. Skipping.
Line #36082 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=51,60 ) /       3579D0,       0D0,      5D0,    -1900D0,     0D0,     1D0,       4725D0,       0D0,     -6D0,      -41D0,     0D0,     3D0,      -3075D0,       0D0,     -2D0,     1313D0,     0D0,    -1D0,      -2904D0,       0D0,     15D0,     1233D0,     0D0,     7D0,       4348D0,       0D0,    -10D0,      -81D0,     0D0,     2D0,      -2878D0,       0D0,      8D0,     1232D0,     0D0,     4D0,      -4230D0,       0D0,      5D0,      -20D0,     0D0,    -2D0,      -2819D0,       0D0,      7D0,     1207D0,     0D0,     3D0,      -4056D0,       0D0,      5D0,       40D0,     0D0,    -2D0,      -2647D0,       0D0,     11D0,     1129D0,     0D0,     5D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=51,60 )" is not supported. Skipping.
Line #36093 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=61,70 ) /      -2294D0,       0D0,    -10D0,     1266D0,     0D0,    -4D0,       2481D0,       0D0,     -7D0,    -1062D0,     0D0,    -3D0,       2179D0,       0D0,     -2D0,    -1129D0,     0D0,    -2D0,       3276D0,       0D0,      1D0,       -9D0,     0D0,     0D0,      -3389D0,       0D0,      5D0,       35D0,     0D0,    -2D0,       3339D0,       0D0,    -13D0,     -107D0,     0D0,     1D0,      -1987D0,       0D0,     -6D0,     1073D0,     0D0,    -2D0,      -1981D0,       0D0,      0D0,      854D0,     0D0,     0D0,       4026D0,       0D0,   -353D0,     -553D0,     0D0,  -139D0,       1660D0,       0D0,     -5D0,     -710D0,     0D0,    -2D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=61,70 )" is not supported. Skipping.
Line #36103 in sofapy.f:"      DATA ( ( CLS(I,J), I=1,6 ), J=71,77 ) /      -1521D0,       0D0,      9D0,      647D0,     0D0,     4D0,       1314D0,       0D0,      0D0,     -700D0,     0D0,     0D0,      -1283D0,       0D0,      0D0,      672D0,     0D0,     0D0,      -1331D0,       0D0,      8D0,      663D0,     0D0,     4D0,       1383D0,       0D0,     -2D0,     -594D0,     0D0,    -2D0,       1405D0,       0D0,      4D0,     -610D0,     0D0,     2D0,       1290D0,       0D0,      0D0,     -556D0,     0D0,     0D0 /"
	analyzeline: implied-DO list "( ( cls(i,j), i=1,6 ), j=71,77 )" is not supported. Skipping.
Line #36601 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=1,10) /      0.,  0.,  0.,  0.,  1., -171996., -1742.,  92025.,  89.,      0.,  0.,  0.,  0.,  2.,    2062.,     2.,   -895.,   5.,     -2.,  0.,  2.,  0.,  1.,      46.,     0.,    -24.,   0.,      2.,  0., -2.,  0.,  0.,      11.,     0.,      0.,   0.,     -2.,  0.,  2.,  0.,  2.,      -3.,     0.,      1.,   0.,      1., -1.,  0., -1.,  0.,      -3.,     0.,      0.,   0.,      0., -2.,  2., -2.,  1.,      -2.,     0.,      1.,   0.,      2.,  0., -2.,  0.,  1.,       1.,     0.,      0.,   0.,      0.,  0.,  2., -2.,  2.,  -13187.,   -16.,   5736., -31.,      0.,  1.,  0.,  0.,  0.,    1426.,   -34.,     54.,  -1. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=1,10)" is not supported. Skipping.
Line #36612 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=11,20) /      0.,  1.,  2., -2.,  2.,    -517.,    12.,    224.,  -6.,      0., -1.,  2., -2.,  2.,     217.,    -5.,    -95.,   3.,      0.,  0.,  2., -2.,  1.,     129.,     1.,    -70.,   0.,      2.,  0.,  0., -2.,  0.,      48.,     0.,      1.,   0.,      0.,  0.,  2., -2.,  0.,     -22.,     0.,      0.,   0.,      0.,  2.,  0.,  0.,  0.,      17.,    -1.,      0.,   0.,      0.,  1.,  0.,  0.,  1.,     -15.,     0.,      9.,   0.,      0.,  2.,  2., -2.,  2.,     -16.,     1.,      7.,   0.,      0., -1.,  0.,  0.,  1.,     -12.,     0.,      6.,   0.,     -2.,  0.,  0.,  2.,  1.,      -6.,     0.,      3.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=11,20)" is not supported. Skipping.
Line #36623 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=21,30) /      0., -1.,  2., -2.,  1.,      -5.,     0.,      3.,   0.,      2.,  0.,  0., -2.,  1.,       4.,     0.,     -2.,   0.,      0.,  1.,  2., -2.,  1.,       4.,     0.,     -2.,   0.,      1.,  0.,  0., -1.,  0.,      -4.,     0.,      0.,   0.,      2.,  1.,  0., -2.,  0.,       1.,     0.,      0.,   0.,      0.,  0., -2.,  2.,  1.,       1.,     0.,      0.,   0.,      0.,  1., -2.,  2.,  0.,      -1.,     0.,      0.,   0.,      0.,  1.,  0.,  0.,  2.,       1.,     0.,      0.,   0.,     -1.,  0.,  0.,  1.,  1.,       1.,     0.,      0.,   0.,      0.,  1.,  2., -2.,  0.,      -1.,     0.,      0.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=21,30)" is not supported. Skipping.
Line #36634 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=31,40) /      0.,  0.,  2.,  0.,  2.,   -2274.,    -2.,    977.,  -5.,      1.,  0.,  0.,  0.,  0.,     712.,     1.,     -7.,   0.,      0.,  0.,  2.,  0.,  1.,    -386.,    -4.,    200.,   0.,      1.,  0.,  2.,  0.,  2.,    -301.,     0.,    129.,  -1.,      1.,  0.,  0., -2.,  0.,    -158.,     0.,     -1.,   0.,     -1.,  0.,  2.,  0.,  2.,     123.,     0.,    -53.,   0.,      0.,  0.,  0.,  2.,  0.,      63.,     0.,     -2.,   0.,      1.,  0.,  0.,  0.,  1.,      63.,     1.,    -33.,   0.,     -1.,  0.,  0.,  0.,  1.,     -58.,    -1.,     32.,   0.,     -1.,  0.,  2.,  2.,  2.,     -59.,     0.,     26.,   0./"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=31,40)" is not supported. Skipping.
Line #36645 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=41,50) /      1.,  0.,  2.,  0.,  1.,     -51.,     0.,     27.,   0.,      0.,  0.,  2.,  2.,  2.,     -38.,     0.,     16.,   0.,      2.,  0.,  0.,  0.,  0.,      29.,     0.,     -1.,   0.,      1.,  0.,  2., -2.,  2.,      29.,     0.,    -12.,   0.,      2.,  0.,  2.,  0.,  2.,     -31.,     0.,     13.,   0.,      0.,  0.,  2.,  0.,  0.,      26.,     0.,     -1.,   0.,     -1.,  0.,  2.,  0.,  1.,      21.,     0.,    -10.,   0.,     -1.,  0.,  0.,  2.,  1.,      16.,     0.,     -8.,   0.,      1.,  0.,  0., -2.,  1.,     -13.,     0.,      7.,   0.,     -1.,  0.,  2.,  2.,  1.,     -10.,     0.,      5.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=41,50)" is not supported. Skipping.
Line #36656 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=51,60) /      1.,  1.,  0., -2.,  0.,      -7.,     0.,      0.,   0.,      0.,  1.,  2.,  0.,  2.,       7.,     0.,     -3.,   0.,      0., -1.,  2.,  0.,  2.,      -7.,     0.,      3.,   0.,      1.,  0.,  2.,  2.,  2.,      -8.,     0.,      3.,   0.,      1.,  0.,  0.,  2.,  0.,       6.,     0.,      0.,   0.,      2.,  0.,  2., -2.,  2.,       6.,     0.,     -3.,   0.,      0.,  0.,  0.,  2.,  1.,      -6.,     0.,      3.,   0.,      0.,  0.,  2.,  2.,  1.,      -7.,     0.,      3.,   0.,      1.,  0.,  2., -2.,  1.,       6.,     0.,     -3.,   0.,      0.,  0.,  0., -2.,  1.,      -5.,     0.,      3.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=51,60)" is not supported. Skipping.
Line #36667 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=61,70) /      1., -1.,  0.,  0.,  0.,       5.,     0.,      0.,   0.,      2.,  0.,  2.,  0.,  1.,      -5.,     0.,      3.,   0.,      0.,  1.,  0., -2.,  0.,      -4.,     0.,      0.,   0.,      1.,  0., -2.,  0.,  0.,       4.,     0.,      0.,   0.,      0.,  0.,  0.,  1.,  0.,      -4.,     0.,      0.,   0.,      1.,  1.,  0.,  0.,  0.,      -3.,     0.,      0.,   0.,      1.,  0.,  2.,  0.,  0.,       3.,     0.,      0.,   0.,      1., -1.,  2.,  0.,  2.,      -3.,     0.,      1.,   0.,     -1., -1.,  2.,  2.,  2.,      -3.,     0.,      1.,   0.,     -2.,  0.,  0.,  0.,  1.,      -2.,     0.,      1.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=61,70)" is not supported. Skipping.
Line #36678 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=71,80) /      3.,  0.,  2.,  0.,  2.,      -3.,     0.,      1.,   0.,      0., -1.,  2.,  2.,  2.,      -3.,     0.,      1.,   0.,      1.,  1.,  2.,  0.,  2.,       2.,     0.,     -1.,   0.,     -1.,  0.,  2., -2.,  1.,      -2.,     0.,      1.,   0.,      2.,  0.,  0.,  0.,  1.,       2.,     0.,     -1.,   0.,      1.,  0.,  0.,  0.,  2.,      -2.,     0.,      1.,   0.,      3.,  0.,  0.,  0.,  0.,       2.,     0.,      0.,   0.,      0.,  0.,  2.,  1.,  2.,       2.,     0.,     -1.,   0.,     -1.,  0.,  0.,  0.,  2.,       1.,     0.,     -1.,   0.,      1.,  0.,  0., -4.,  0.,      -1.,     0.,      0.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=71,80)" is not supported. Skipping.
Line #36689 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=81,90) /     -2.,  0.,  2.,  2.,  2.,       1.,     0.,     -1.,   0.,     -1.,  0.,  2.,  4.,  2.,      -2.,     0.,      1.,   0.,      2.,  0.,  0., -4.,  0.,      -1.,     0.,      0.,   0.,      1.,  1.,  2., -2.,  2.,       1.,     0.,     -1.,   0.,      1.,  0.,  2.,  2.,  1.,      -1.,     0.,      1.,   0.,     -2.,  0.,  2.,  4.,  2.,      -1.,     0.,      1.,   0.,     -1.,  0.,  4.,  0.,  2.,       1.,     0.,      0.,   0.,      1., -1.,  0., -2.,  0.,       1.,     0.,      0.,   0.,      2.,  0.,  2., -2.,  1.,       1.,     0.,     -1.,   0.,      2.,  0.,  2.,  2.,  2.,      -1.,     0.,      0.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=81,90)" is not supported. Skipping.
Line #36700 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=91,100) /      1.,  0.,  0.,  2.,  1.,      -1.,     0.,      0.,   0.,      0.,  0.,  4., -2.,  2.,       1.,     0.,      0.,   0.,      3.,  0.,  2., -2.,  2.,       1.,     0.,      0.,   0.,      1.,  0.,  2., -2.,  0.,      -1.,     0.,      0.,   0.,      0.,  1.,  2.,  0.,  1.,       1.,     0.,      0.,   0.,     -1., -1.,  0.,  2.,  1.,       1.,     0.,      0.,   0.,      0.,  0., -2.,  0.,  1.,      -1.,     0.,      0.,   0.,      0.,  0.,  2., -1.,  2.,      -1.,     0.,      0.,   0.,      0.,  1.,  0.,  2.,  0.,      -1.,     0.,      0.,   0.,      1.,  0., -2., -2.,  0.,      -1.,     0.,      0.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=91,100)" is not supported. Skipping.
Line #36711 in sofapy.f:"      DATA ((X(I,J),I=1,9),J=101,106) /      0., -1.,  2.,  0.,  1.,      -1.,     0.,      0.,   0.,      1.,  1.,  0., -2.,  1.,      -1.,     0.,      0.,   0.,      1.,  0., -2.,  2.,  0.,      -1.,     0.,      0.,   0.,      2.,  0.,  0.,  2.,  0.,       1.,     0.,      0.,   0.,      0.,  0.,  2.,  4.,  2.,      -1.,     0.,      0.,   0.,      0.,  1.,  0.,  1.,  0.,       1.,     0.,      0.,   0. /"
	analyzeline: implied-DO list "((x(i,j),i=1,9),j=101,106)" is not supported. Skipping.
Line #47796 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=1,10 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  2, -2,  3,  0,  0,  0,  0,  0,  2, -2,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  3,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  1,  0,  0,  1,  0,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=1,10 )" is not supported. Skipping.
Line #47807 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=11,20 ) /  1,  0,  0,  0, -1,  0,  0,  0,  1,  0,  0,  0,  1,  0,  0,  0,  0,  1,  2, -2,  3,  0,  0,  0,  0,  1,  2, -2,  1,  0,  0,  0,  0,  0,  4, -4,  4,  0,  0,  0,  0,  0,  1, -1,  1, -8, 12,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  1,  0,  2,  0,  3,  0,  0,  0,  1,  0,  2,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=11,20 )" is not supported. Skipping.
Line #47818 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=21,30 ) /  0,  0,  2, -2,  0,  0,  0,  0,  0,  1, -2,  2, -3,  0,  0,  0,  0,  1, -2,  2, -1,  0,  0,  0,  0,  0,  0,  0,  0,  8,-13, -1,  0,  0,  0,  2,  0,  0,  0,  0,  2,  0, -2,  0, -1,  0,  0,  0,  0,  1,  2, -2,  2,  0,  0,  0,  1,  0,  0, -2,  1,  0,  0,  0,  1,  0,  0, -2, -1,  0,  0,  0,  0,  0,  4, -2,  4,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=21,30 )" is not supported. Skipping.
Line #47824 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=31,NS0 ) /  0,  0,  2, -2,  4,  0,  0,  0,  1,  0, -2,  0, -3,  0,  0,  0,  1,  0, -2,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=31,ns0 )" is not supported. Skipping.
Line #47830 in sofapy.f:"      DATA ( ( KS1(I,J), I=1,8), J=1,NS1 ) /  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  3,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks1(i,j), i=1,8), j=1,ns1 )" is not supported. Skipping.
Line #47841 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=1,10 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,  0,  1,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  1,  0,  2,  0,  2,  0,  0,  0,  0,  1, -2,  2, -2,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=1,10 )" is not supported. Skipping.
Line #47852 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=11,20 ) /  1,  0,  0, -2,  0,  0,  0,  0,  0,  0,  2, -2,  1,  0,  0,  0,  1,  0, -2,  0, -2,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  1,  0,  0,  0,  1,  0, -2, -2, -2,  0,  0,  0,  1,  0,  0,  0, -1,  0,  0,  0,  1,  0,  2,  0,  1,  0,  0,  0,  2,  0,  0, -2,  0,  0,  0,  0,  2,  0, -2,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=11,20 )" is not supported. Skipping.
Line #47860 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=21,NS2 ) /  0,  0,  2,  2,  2,  0,  0,  0,  2,  0,  2,  0,  2,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  1,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=21,ns2 )" is not supported. Skipping.
Line #47867 in sofapy.f:"      DATA ( ( KS3(I,J), I=1,8), J=1,NS3 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks3(i,j), i=1,8), j=1,ns3 )" is not supported. Skipping.
Line #47871 in sofapy.f:"      DATA ( ( KS4(I,J), I=1,8), J=1,NS4 ) /  0,  0,  0,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks4(i,j), i=1,8), j=1,ns4 )" is not supported. Skipping.
Line #47882 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=1,10 ) /            -2640.73D-6,          +0.39D-6,              -63.53D-6,          +0.02D-6,              -11.75D-6,          -0.01D-6,              -11.21D-6,          -0.01D-6,               +4.57D-6,           0.00D-6,               -2.02D-6,           0.00D-6,               -1.98D-6,           0.00D-6,               +1.72D-6,           0.00D-6,               +1.41D-6,          +0.01D-6,               +1.26D-6,          +0.01D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=1,10 )" is not supported. Skipping.
Line #47893 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=11,20 ) /               +0.63D-6,           0.00D-6,               +0.63D-6,           0.00D-6,               -0.46D-6,           0.00D-6,               -0.45D-6,           0.00D-6,               -0.36D-6,           0.00D-6,               +0.24D-6,          +0.12D-6,               -0.32D-6,           0.00D-6,               -0.28D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.26D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=11,20 )" is not supported. Skipping.
Line #47904 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=21,30 ) /               +0.21D-6,           0.00D-6,               -0.19D-6,           0.00D-6,               -0.18D-6,           0.00D-6,               +0.10D-6,          -0.05D-6,               -0.15D-6,           0.00D-6,               +0.14D-6,           0.00D-6,               +0.14D-6,           0.00D-6,               -0.14D-6,           0.00D-6,               -0.14D-6,           0.00D-6,               -0.13D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=21,30 )" is not supported. Skipping.
Line #47910 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=31,NS0 ) /               +0.11D-6,           0.00D-6,               -0.11D-6,           0.00D-6,               -0.11D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=31,ns0 )" is not supported. Skipping.
Line #47916 in sofapy.f:"      DATA ( ( SS1(I,J), I=1,2), J=1,NS1 ) /               -0.07D-6,          +3.57D-6,               +1.71D-6,          -0.03D-6,                0.00D-6,          +0.48D-6 /"
	analyzeline: implied-DO list "( ( ss1(i,j), i=1,2), j=1,ns1 )" is not supported. Skipping.
Line #47927 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=1,10 ) /             +743.53D-6,          -0.17D-6,              +56.91D-6,          +0.06D-6,               +9.84D-6,          -0.01D-6,               -8.85D-6,          +0.01D-6,               -6.38D-6,          -0.05D-6,               -3.07D-6,           0.00D-6,               +2.23D-6,           0.00D-6,               +1.67D-6,           0.00D-6,               +1.30D-6,           0.00D-6,               +0.93D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=1,10 )" is not supported. Skipping.
Line #47938 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=11,20 ) /               +0.68D-6,           0.00D-6,               -0.55D-6,           0.00D-6,               +0.53D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.26D-6,           0.00D-6,               -0.25D-6,           0.00D-6,               +0.22D-6,           0.00D-6,               -0.21D-6,           0.00D-6,               +0.20D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=11,20 )" is not supported. Skipping.
Line #47946 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=21,NS2 ) /               +0.17D-6,           0.00D-6,               +0.13D-6,           0.00D-6,               -0.13D-6,           0.00D-6,               -0.12D-6,           0.00D-6,               -0.11D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=21,ns2 )" is not supported. Skipping.
Line #47953 in sofapy.f:"      DATA ( ( SS3(I,J), I=1,2), J=1,NS3 ) /               +0.30D-6,         -23.51D-6,               -0.03D-6,          -1.39D-6,               -0.01D-6,          -0.24D-6,                0.00D-6,          +0.22D-6 /"
	analyzeline: implied-DO list "( ( ss3(i,j), i=1,2), j=1,ns3 )" is not supported. Skipping.
Line #47959 in sofapy.f:"      DATA ( ( SS4(I,J), I=1,2), J=1,NS4 ) /               -0.26D-6,          -0.01D-6 /"
	analyzeline: implied-DO list "( ( ss4(i,j), i=1,2), j=1,ns4 )" is not supported. Skipping.
Line #48710 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=1,10 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  2, -2,  3,  0,  0,  0,  0,  0,  2, -2,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  3,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  1,  0,  0,  1,  0,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=1,10 )" is not supported. Skipping.
Line #48721 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=11,20 ) /  1,  0,  0,  0, -1,  0,  0,  0,  1,  0,  0,  0,  1,  0,  0,  0,  0,  1,  2, -2,  3,  0,  0,  0,  0,  1,  2, -2,  1,  0,  0,  0,  0,  0,  4, -4,  4,  0,  0,  0,  0,  0,  1, -1,  1, -8, 12,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  1,  0,  2,  0,  3,  0,  0,  0,  1,  0,  2,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=11,20 )" is not supported. Skipping.
Line #48732 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=21,30 ) /  0,  0,  2, -2,  0,  0,  0,  0,  0,  1, -2,  2, -3,  0,  0,  0,  0,  1, -2,  2, -1,  0,  0,  0,  0,  0,  0,  0,  0,  8,-13, -1,  0,  0,  0,  2,  0,  0,  0,  0,  2,  0, -2,  0, -1,  0,  0,  0,  0,  1,  2, -2,  2,  0,  0,  0,  1,  0,  0, -2,  1,  0,  0,  0,  1,  0,  0, -2, -1,  0,  0,  0,  0,  0,  4, -2,  4,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=21,30 )" is not supported. Skipping.
Line #48738 in sofapy.f:"      DATA ( ( KS0(I,J), I=1,8), J=31,NS0 ) /  0,  0,  2, -2,  4,  0,  0,  0,  1,  0, -2,  0, -3,  0,  0,  0,  1,  0, -2,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks0(i,j), i=1,8), j=31,ns0 )" is not supported. Skipping.
Line #48744 in sofapy.f:"      DATA ( ( KS1(I,J), I=1,8), J=1,NS1 ) /  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  3,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks1(i,j), i=1,8), j=1,ns1 )" is not supported. Skipping.
Line #48755 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=1,10 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,  0,  1,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  1,  0,  2,  0,  2,  0,  0,  0,  0,  1, -2,  2, -2,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=1,10 )" is not supported. Skipping.
Line #48766 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=11,20 ) /  1,  0,  0, -2,  0,  0,  0,  0,  0,  0,  2, -2,  1,  0,  0,  0,  1,  0, -2,  0, -2,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  1,  0,  0,  0,  1,  0, -2, -2, -2,  0,  0,  0,  1,  0,  0,  0, -1,  0,  0,  0,  1,  0,  2,  0,  1,  0,  0,  0,  2,  0,  0, -2,  0,  0,  0,  0,  2,  0, -2,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=11,20 )" is not supported. Skipping.
Line #48774 in sofapy.f:"      DATA ( ( KS2(I,J), I=1,8), J=21,NS2 ) /  0,  0,  2,  2,  2,  0,  0,  0,  2,  0,  2,  0,  2,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,  1,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks2(i,j), i=1,8), j=21,ns2 )" is not supported. Skipping.
Line #48781 in sofapy.f:"      DATA ( ( KS3(I,J), I=1,8), J=1,NS3 ) /  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  2, -2,  2,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks3(i,j), i=1,8), j=1,ns3 )" is not supported. Skipping.
Line #48785 in sofapy.f:"      DATA ( ( KS4(I,J), I=1,8), J=1,NS4 ) /  0,  0,  0,  0,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "( ( ks4(i,j), i=1,8), j=1,ns4 )" is not supported. Skipping.
Line #48796 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=1,10 ) /            -2640.73D-6,          +0.39D-6,              -63.53D-6,          +0.02D-6,              -11.75D-6,          -0.01D-6,              -11.21D-6,          -0.01D-6,               +4.57D-6,           0.00D-6,               -2.02D-6,           0.00D-6,               -1.98D-6,           0.00D-6,               +1.72D-6,           0.00D-6,               +1.41D-6,          +0.01D-6,               +1.26D-6,          +0.01D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=1,10 )" is not supported. Skipping.
Line #48807 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=11,20 ) /               +0.63D-6,           0.00D-6,               +0.63D-6,           0.00D-6,               -0.46D-6,           0.00D-6,               -0.45D-6,           0.00D-6,               -0.36D-6,           0.00D-6,               +0.24D-6,          +0.12D-6,               -0.32D-6,           0.00D-6,               -0.28D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.26D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=11,20 )" is not supported. Skipping.
Line #48818 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=21,30 ) /               +0.21D-6,           0.00D-6,               -0.19D-6,           0.00D-6,               -0.18D-6,           0.00D-6,               +0.10D-6,          -0.05D-6,               -0.15D-6,           0.00D-6,               +0.14D-6,           0.00D-6,               +0.14D-6,           0.00D-6,               -0.14D-6,           0.00D-6,               -0.14D-6,           0.00D-6,               -0.13D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=21,30 )" is not supported. Skipping.
Line #48824 in sofapy.f:"      DATA ( ( SS0(I,J), I=1,2), J=31,NS0 ) /               +0.11D-6,           0.00D-6,               -0.11D-6,           0.00D-6,               -0.11D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss0(i,j), i=1,2), j=31,ns0 )" is not supported. Skipping.
Line #48830 in sofapy.f:"      DATA ( ( SS1(I,J), I=1,2), J=1,NS1 ) /               -0.07D-6,          +3.57D-6,               +1.73D-6,          -0.03D-6,                0.00D-6,          +0.48D-6 /"
	analyzeline: implied-DO list "( ( ss1(i,j), i=1,2), j=1,ns1 )" is not supported. Skipping.
Line #48841 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=1,10 ) /             +743.52D-6,          -0.17D-6,              +56.91D-6,          +0.06D-6,               +9.84D-6,          -0.01D-6,               -8.85D-6,          +0.01D-6,               -6.38D-6,          -0.05D-6,               -3.07D-6,           0.00D-6,               +2.23D-6,           0.00D-6,               +1.67D-6,           0.00D-6,               +1.30D-6,           0.00D-6,               +0.93D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=1,10 )" is not supported. Skipping.
Line #48852 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=11,20 ) /               +0.68D-6,           0.00D-6,               -0.55D-6,           0.00D-6,               +0.53D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.27D-6,           0.00D-6,               -0.26D-6,           0.00D-6,               -0.25D-6,           0.00D-6,               +0.22D-6,           0.00D-6,               -0.21D-6,           0.00D-6,               +0.20D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=11,20 )" is not supported. Skipping.
Line #48860 in sofapy.f:"      DATA ( ( SS2(I,J), I=1,2), J=21,NS2 ) /               +0.17D-6,           0.00D-6,               +0.13D-6,           0.00D-6,               -0.13D-6,           0.00D-6,               -0.12D-6,           0.00D-6,               -0.11D-6,           0.00D-6 /"
	analyzeline: implied-DO list "( ( ss2(i,j), i=1,2), j=21,ns2 )" is not supported. Skipping.
Line #48867 in sofapy.f:"      DATA ( ( SS3(I,J), I=1,2), J=1,NS3 ) /               +0.30D-6,         -23.42D-6,               -0.03D-6,          -1.46D-6,               -0.01D-6,          -0.25D-6,                0.00D-6,          +0.23D-6 /"
	analyzeline: implied-DO list "( ( ss3(i,j), i=1,2), j=1,ns3 )" is not supported. Skipping.
Line #48871 in sofapy.f:"      DATA ( ( SS4(I,J), I=1,2), J=1,NS4 ) /               -0.26D-6,          -0.01D-6 /"
	analyzeline: implied-DO list "( ( ss4(i,j), i=1,2), j=1,ns4 )" is not supported. Skipping.
Line #51358 in sofapy.f:"      PARAMETER ( DTAT = 32.184D0/86400D0 )"
	determineexprtype: could not determine expressions ('32.184d0/86400d0') type.
analyzeline: Failed to evaluate '32.184d0/86400d0'. Ignoring: invalid syntax (<string>, line 1)
Line #51940 in sofapy.f:"      PARAMETER ( ELB = 1.550519768D-8,            TDB0 = -6.55D-5/86400D0 )"
	determineexprtype: could not determine expressions ('-6.55d-5/86400d0') type.
analyzeline: Failed to evaluate '-6.55d-5/86400d0'. Ignoring: invalid syntax (<string>, line 1)
Line #52311 in sofapy.f:"      PARAMETER ( ELB = 1.550519768D-8,            TDB0 = -6.55D-5/86400D0 )"
	determineexprtype: could not determine expressions ('-6.55d-5/86400d0') type.
analyzeline: Failed to evaluate '-6.55d-5/86400d0'. Ignoring: invalid syntax (<string>, line 1)
Line #54773 in sofapy.f:"      PARAMETER ( DTAT = 32.184D0/86400D0 )"
	determineexprtype: could not determine expressions ('32.184d0/86400d0') type.
analyzeline: Failed to evaluate '32.184d0/86400d0'. Ignoring: invalid syntax (<string>, line 1)
Line #56656 in sofapy.f:"      DATA ((XYP(I,JXY),I=0,MAXPT),JXY=0,1) /             -0.016617     D0,          +2004.191898     D0,             -0.4297829    D0,             -0.19861834   D0,             +0.000007578  D0,             +0.0000059285 D0,             -0.006951     D0,             -0.025896     D0,            -22.4072747    D0,             +0.00190059   D0,             +0.001112526  D0,             +0.0000001358 D0 /"
	analyzeline: implied-DO list "((xyp(i,jxy),i=0,maxpt),jxy=0,1)" is not supported. Skipping.
Line #56667 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=1,10) /   0,  0,  0,  0,  1,   0,  0,  2, -2,  2,   0,  0,  2,  0,  2,   0,  0,  0,  0,  2,   0,  1,  0,  0,  0,   0,  1,  2, -2,  2,   1,  0,  0,  0,  0,   0,  0,  2,  0,  1,   1,  0,  2,  0,  2,   0,  1, -2,  2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=1,10)" is not supported. Skipping.
Line #56678 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=11,20) /   0,  0,  2, -2,  1,   1,  0, -2,  0, -2,   1,  0,  0, -2,  0,   1,  0,  0,  0,  1,   1,  0,  0,  0, -1,   1,  0, -2, -2, -2,   1,  0,  2,  0,  1,   2,  0, -2,  0, -1,   0,  0,  0,  2,  0,   0,  0,  2,  2,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=11,20)" is not supported. Skipping.
Line #56689 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=21,30) /   2,  0,  0, -2,  0,   0,  2, -2,  2, -2,   2,  0,  2,  0,  2,   1,  0,  2, -2,  2,   1,  0, -2,  0, -1,   2,  0,  0,  0,  0,   0,  0,  2,  0,  0,   0,  1,  0,  0,  1,   1,  0,  0, -2, -1,   0,  2,  2, -2,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=21,30)" is not supported. Skipping.
Line #56700 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=31,40) /   0,  0,  2, -2,  0,   1,  0,  0, -2,  1,   0,  1,  0,  0, -1,   0,  2,  0,  0,  0,   1,  0, -2, -2, -1,   1,  0,  2,  2,  2,   0,  1,  2,  0,  2,   2,  0, -2,  0,  0,   0,  0,  2,  2,  1,   0,  1, -2,  0, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=31,40)" is not supported. Skipping.
Line #56711 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=41,50) /   0,  0,  0,  2,  1,   1,  0,  2, -2,  1,   2,  0,  0, -2, -1,   2,  0,  2, -2,  2,   2,  0,  2,  0,  1,   0,  0,  0,  2, -1,   0,  1, -2,  2, -1,   1,  1,  0, -2,  0,   2,  0,  0, -2,  1,   1,  0,  0,  2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=41,50)" is not supported. Skipping.
Line #56722 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=51,60) /   0,  1,  2, -2,  1,   1, -1,  0,  0,  0,   0,  1, -1,  1, -1,   2,  0, -2,  0, -2,   0,  1,  0, -2,  0,   1,  0,  0, -1,  0,   3,  0,  2,  0,  2,   0,  0,  0,  1,  0,   1, -1,  2,  0,  2,   1,  1, -2, -2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=51,60)" is not supported. Skipping.
Line #56733 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=61,70) /   1,  0, -2,  0,  0,   2,  0,  0,  0, -1,   0,  1, -2, -2, -2,   1,  1,  2,  0,  2,   2,  0,  0,  0,  1,   1,  1,  0,  0,  0,   1,  0, -2,  2, -1,   1,  0,  2,  0,  0,   1, -1,  0, -1,  0,   1,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=61,70)" is not supported. Skipping.
Line #56744 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=71,80) /   1,  0, -1,  0, -1,   0,  0,  2,  1,  2,   1,  0, -2, -4, -2,   1, -1,  0, -1, -1,   1,  0,  2,  2,  1,   0,  2, -2,  2, -1,   1,  0,  0,  0, -2,   2,  0, -2, -2, -2,   1,  1,  2, -2,  2,   2,  0, -2, -4, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=71,80)" is not supported. Skipping.
Line #56755 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=81,90) /   1,  0, -4,  0, -2,   2,  0,  2, -2,  1,   1,  0,  0, -1, -1,   2,  0,  2,  2,  2,   3,  0,  0,  0,  0,   1,  0,  0,  2,  1,   0,  0,  2, -2, -1,   3,  0,  2, -2,  2,   0,  0,  4, -2,  2,   1,  0,  0, -4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=81,90)" is not supported. Skipping.
Line #56766 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=91,100) /   0,  1,  2,  0,  1,   2,  0,  0, -4,  0,   1,  1,  0, -2, -1,   2,  0, -2,  0,  1,   0,  0,  2,  0, -1,   0,  1, -2,  0, -1,   0,  1,  0,  0,  2,   0,  0,  2, -1,  2,   0,  0,  2,  4,  2,   2,  1,  0, -2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=91,100)" is not supported. Skipping.
Line #56777 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=101,110) /   1,  1,  0, -2,  1,   1, -1,  0, -2,  0,   1, -1,  0, -1, -2,   1, -1,  0,  0,  1,   0,  1, -2,  2,  0,   0,  1,  0,  0, -2,   1, -1,  2,  2,  2,   1,  0,  0,  2, -1,   1, -1, -2, -2, -2,   3,  0,  2,  0,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=101,110)" is not supported. Skipping.
Line #56788 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=111,120) /   0,  1,  2,  2,  2,   1,  0,  2, -2,  0,   1,  1, -2, -2, -1,   1,  0,  2, -4,  1,   0,  1, -2, -2, -1,   2, -1,  2,  0,  2,   0,  0,  0,  2,  2,   1, -1,  2,  0,  1,   1, -1, -2,  0, -2,   0,  1,  0,  2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=111,120)" is not supported. Skipping.
Line #56799 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=121,130) /   0,  1,  2, -2,  0,   0,  0,  0,  1,  1,   1,  0, -2, -2,  0,   0,  3,  2, -2,  2,   2,  1,  2,  0,  2,   1,  1,  0,  0,  1,   2,  0,  0,  2,  0,   1,  1,  2,  0,  1,   1,  0,  0, -2, -2,   1,  0, -2,  2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=121,130)" is not supported. Skipping.
Line #56810 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=131,140) /   1,  0, -1,  0, -2,   0,  1,  0, -2,  1,   0,  1,  0,  1,  0,   0,  0,  0,  1, -1,   1,  0, -2,  2, -2,   1, -1,  0,  0, -1,   0,  0,  0,  4,  0,   1, -1,  0,  2,  0,   1,  0,  2,  1,  2,   1,  0,  2, -1,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=131,140)" is not supported. Skipping.
Line #56821 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=141,150) /   0,  0,  2,  1,  1,   1,  0,  0, -2,  2,   1,  0, -2,  0,  1,   1,  0, -2, -4, -1,   0,  0,  2,  2,  0,   1,  1,  2, -2,  1,   1,  0, -2,  1, -1,   0,  0,  1,  0,  1,   2,  0, -2, -2, -1,   4,  0,  2,  0,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=141,150)" is not supported. Skipping.
Line #56832 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=151,160) /   2, -1,  0,  0,  0,   2,  1,  2, -2,  2,   0,  1,  2,  1,  2,   1,  0,  4, -2,  2,   1,  1,  0,  0, -1,   2,  0,  2,  0,  0,   2,  0, -2, -4, -1,   1,  0, -1,  0,  0,   1,  0,  0,  1,  0,   0,  1,  0,  2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=151,160)" is not supported. Skipping.
Line #56843 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=161,170) /   1,  0, -4,  0, -1,   1,  0,  0, -4, -1,   2,  0,  2,  2,  1,   2,  1,  0,  0,  0,   0,  0,  2, -3,  2,   1,  2,  0, -2,  0,   0,  3,  0,  0,  0,   0,  0,  4,  0,  2,   0,  0,  2, -4,  1,   2,  0,  0, -2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=161,170)" is not supported. Skipping.
Line #56854 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=171,180) /   1,  1, -2, -4, -2,   0,  1,  0, -2, -1,   0,  0,  0,  4,  1,   3,  0,  2, -2,  1,   1,  0,  2,  4,  2,   1,  1, -2,  0, -2,   0,  0,  4, -2,  1,   2, -2,  0, -2,  0,   2,  1,  0, -2, -1,   0,  2,  0, -2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=171,180)" is not supported. Skipping.
Line #56865 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=181,190) /   1,  0,  0, -1,  1,   1,  1,  2,  2,  2,   3,  0,  0,  0, -1,   2,  0,  0, -4, -1,   3,  0,  2,  2,  2,   0,  0,  2,  4,  1,   0,  2, -2, -2, -2,   1, -1,  0, -2, -1,   0,  0,  2, -1,  1,   2,  0,  0,  2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=181,190)" is not supported. Skipping.
Line #56876 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=191,200) /   1, -1, -2,  2, -1,   0,  0,  0,  2, -2,   2,  0,  0, -4,  1,   1,  0,  0, -4,  1,   2,  0,  2, -4,  1,   4,  0,  2, -2,  2,   2,  1, -2,  0, -1,   2,  1, -2, -4, -2,   3,  0,  0, -4,  0,   1, -1,  2,  2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=191,200)" is not supported. Skipping.
Line #56887 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=201,210) /   1, -1, -2,  0, -1,   0,  2,  0,  0,  1,   1,  2, -2, -2, -2,   1,  1,  0, -4,  0,   2,  0,  0, -2,  2,   0,  2,  2, -2,  1,   1,  0,  2,  0, -1,   2,  1,  0, -2,  1,   2, -1, -2,  0, -1,   1, -1, -2, -2, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=201,210)" is not supported. Skipping.
Line #56898 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=211,220) /   0,  1, -2,  1, -2,   1,  0, -4,  2, -2,   0,  1,  2,  2,  1,   3,  0,  0,  0,  1,   2, -1,  2,  2,  2,   0,  1, -2, -4, -2,   1,  0, -2, -3, -2,   2,  0,  0,  0,  2,   1, -1,  0, -2, -2,   2,  0, -2,  2, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=211,220)" is not supported. Skipping.
Line #56909 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=221,230) /   0,  2, -2,  0, -2,   3,  0, -2,  0, -1,   2, -1,  2,  0,  1,   1,  0, -2, -1, -2,   0,  0,  2,  0,  3,   2,  0, -4,  0, -2,   2,  1,  0, -4,  0,   1,  1, -2,  1, -1,   0,  2,  2,  0,  2,   1, -1,  2, -2,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=221,230)" is not supported. Skipping.
Line #56920 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=231,240) /   1, -1,  0, -2,  1,   2,  1,  2,  0,  1,   1,  0,  2, -4,  2,   1,  1, -2,  0, -1,   1,  1,  0,  2,  0,   1,  0,  0, -3,  0,   2,  0,  2, -1,  2,   0,  2,  0,  0, -1,   2, -1,  0, -2,  0,   4,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=231,240)" is not supported. Skipping.
Line #56931 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=241,250) /   2,  1, -2, -2, -2,   0,  2, -2,  2,  0,   1,  0,  2,  1,  1,   1,  0, -1,  0, -3,   3, -1,  2,  0,  2,   2,  0,  2, -2,  0,   1, -2,  0,  0,  0,   2,  0,  0,  0, -2,   1,  0,  0,  4,  0,   0,  1,  0,  1,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=241,250)" is not supported. Skipping.
Line #56942 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=251,260) /   1,  0,  2,  2,  0,   0,  1,  0,  2, -1,   0,  1,  0,  1, -1,   0,  0,  2, -2,  3,   3,  1,  2,  0,  2,   1,  1,  2,  1,  2,   1,  1, -2,  2, -1,   2, -1,  2, -2,  2,   1, -2,  2,  0,  2,   1,  0,  2, -4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=251,260)" is not supported. Skipping.
Line #56953 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=261,270) /   0,  0,  1,  0,  0,   1,  0,  2, -3,  1,   1, -2,  0, -2,  0,   2,  0,  0,  2, -1,   1,  1,  2, -4,  1,   4,  0,  2,  0,  1,   0,  1,  2,  1,  1,   1,  2,  2, -2,  2,   2,  0,  2,  1,  2,   2,  1,  2, -2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=261,270)" is not supported. Skipping.
Line #56964 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=271,280) /   1,  0,  2, -1,  1,   1,  0,  4, -2,  1,   1, -1,  2, -2,  1,   0,  1,  0, -4,  0,   3,  0, -2, -2, -2,   0,  0,  4, -4,  2,   2,  0, -4, -2, -2,   2, -2,  0, -2, -1,   1,  0,  2, -2, -1,   2,  0, -2, -6, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=271,280)" is not supported. Skipping.
Line #56975 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=281,290) /   1,  0, -2,  1, -2,   1,  0, -2,  2,  1,   1, -1,  0,  2, -1,   1,  0, -2,  1,  0,   2, -1,  0, -2,  1,   1, -1,  0,  2,  1,   2,  0, -2, -2,  0,   1,  0,  2, -3,  2,   0,  0,  0,  4, -1,   2, -1,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=281,290)" is not supported. Skipping.
Line #56986 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=291,300) /   2,  0,  4, -2,  2,   0,  0,  2,  3,  2,   0,  1,  4, -2,  2,   0,  1, -2,  2,  1,   1,  1,  0,  2,  1,   1,  0,  0,  4,  1,   0,  0,  4,  0,  1,   2,  0,  0, -3,  0,   1,  0,  0, -1, -2,   1, -2, -2, -2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=291,300)" is not supported. Skipping.
Line #56997 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=301,310) /   3,  0,  0,  2,  0,   2,  0,  2, -4,  2,   1,  1, -2, -4, -1,   1,  0, -2, -6, -2,   2, -1,  0,  0, -1,   2, -1,  0,  2,  0,   0,  1,  2, -2, -1,   1,  1,  0,  1,  0,   1,  2,  0, -2, -1,   1,  0,  0,  1, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=301,310)" is not supported. Skipping.
Line #57008 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=311,320) /   0,  0,  1,  0,  2,   3,  1,  2, -2,  2,   1,  0, -4, -2, -2,   1,  0,  2,  4,  1,   1, -2,  2,  2,  2,   1, -1, -2, -4, -2,   0,  0,  2, -4,  2,   0,  0,  2, -3,  1,   2,  1, -2,  0,  0,   3,  0, -2, -2, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=311,320)" is not supported. Skipping.
Line #57019 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=321,330) /   2,  0,  2,  4,  2,   0,  0,  0,  0,  3,   2, -1, -2, -2, -2,   2,  0,  0, -1,  0,   3,  0,  2, -4,  2,   2,  1,  2,  2,  2,   0,  0,  3,  0,  3,   1,  1,  2,  2,  1,   2,  1,  0,  0, -1,   1,  2,  0, -2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=321,330)" is not supported. Skipping.
Line #57030 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=331,340) /   3,  0,  2,  2,  1,   1, -1, -2,  2, -2,   1,  1,  0, -1,  0,   1,  2,  0,  0,  0,   1,  0,  4,  0,  2,   1, -1,  2,  4,  2,   2,  1,  0,  0,  1,   1,  0,  0,  2,  2,   1, -1, -2,  2,  0,   0,  2, -2, -2, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=331,340)" is not supported. Skipping.
Line #57041 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=341,350) /   2,  0, -2,  0,  2,   5,  0,  2,  0,  2,   3,  0, -2, -6, -2,   1, -1,  2, -1,  2,   3,  0,  0, -4, -1,   1,  0,  0,  1,  1,   1,  0, -4,  2, -1,   0,  1,  2, -4,  1,   1,  2,  2,  0,  2,   0,  1,  0, -2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=341,350)" is not supported. Skipping.
Line #57052 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=351,360) /   0,  0,  2, -1,  0,   1,  0,  1,  0,  1,   0,  2,  0, -2,  1,   3,  0,  2,  0,  0,   1,  1, -2,  1,  0,   2,  1, -2, -4, -1,   3, -1,  0,  0,  0,   2, -1, -2,  0,  0,   4,  0,  2, -2,  1,   2,  0, -2,  2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=351,360)" is not supported. Skipping.
Line #57063 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=361,370) /   1,  1,  2, -2,  0,   1,  0, -2,  4, -1,   1,  0, -2, -2,  1,   2,  0,  2, -4,  0,   1,  1,  0, -2, -2,   1,  1, -2, -2,  0,   1,  0,  1, -2,  1,   2, -1, -2, -4, -2,   3,  0, -2,  0, -2,   0,  1, -2, -2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=361,370)" is not supported. Skipping.
Line #57074 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=371,380) /   3,  0,  0, -2, -1,   1,  0, -2, -3, -1,   0,  1,  0, -4, -1,   1, -2,  2, -2,  1,   0,  1, -2,  1, -1,   1, -1,  0,  0,  2,   2,  0,  0,  1,  0,   1, -2,  0,  2,  0,   1,  2, -2, -2, -1,   0,  0,  4, -4,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=371,380)" is not supported. Skipping.
Line #57085 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=381,390) /   0,  1,  2,  4,  2,   0,  1, -4,  2, -2,   3,  0, -2,  0,  0,   2, -1,  2,  2,  1,   0,  1, -2, -4, -1,   4,  0,  2,  2,  2,   2,  0, -2, -3, -2,   2,  0,  0, -6,  0,   1,  0,  2,  0,  3,   3,  1,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=381,390)" is not supported. Skipping.
Line #57096 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=391,400) /   3,  0,  0, -4,  1,   1, -1,  2,  0,  0,   1, -1,  0, -4,  0,   2,  0, -2,  2, -2,   1,  1,  0, -2,  2,   4,  0,  0, -2,  0,   2,  2,  0, -2,  0,   0,  1,  2,  0,  0,   1,  1,  0, -4,  1,   1,  0,  0, -4, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=391,400)" is not supported. Skipping.
Line #57107 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=401,410) /   0,  0,  0,  1,  2,   3,  0,  0,  2,  1,   1,  1,  0, -4, -1,   0,  0,  2,  2, -1,   1,  1,  2,  0,  0,   1, -1,  2, -4,  1,   1,  1,  0,  0,  2,   0,  0,  2,  6,  2,   4,  0, -2, -2, -1,   2,  1,  0, -4, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=401,410)" is not supported. Skipping.
Line #57118 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=411,420) /   0,  0,  0,  3,  1,   1, -1, -2,  0,  0,   0,  0,  2,  1,  0,   1,  0,  0,  2, -2,   3, -1,  2,  2,  2,   3, -1,  2, -2,  2,   1,  0,  0, -1,  2,   1, -2,  2, -2,  2,   0,  1,  0,  2,  2,   0,  1, -2, -1, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=411,420)" is not supported. Skipping.
Line #57129 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=421,430) /   1,  1, -2,  0,  0,   0,  2,  2, -2,  0,   3, -1, -2, -1, -2,   1,  0,  0, -6,  0,   1,  0, -2, -4,  0,   2,  1,  0, -4,  1,   2,  0,  2,  0, -1,   2,  0, -4,  0, -1,   0,  0,  3,  0,  2,   2,  1, -2, -2, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=421,430)" is not supported. Skipping.
Line #57140 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=431,440) /   1, -2,  0,  0,  1,   2, -1,  0, -4,  0,   0,  0,  0,  3,  0,   5,  0,  2, -2,  2,   1,  2, -2, -4, -2,   1,  0,  4, -4,  2,   0,  0,  4, -1,  2,   3,  1,  0, -4,  0,   3,  0,  0, -6,  0,   2,  0,  0,  2,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=431,440)" is not supported. Skipping.
Line #57151 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=441,450) /   2, -2,  2,  0,  2,   1,  0,  0, -3,  1,   1, -2, -2,  0, -2,   1, -1, -2, -3, -2,   0,  0,  2, -2, -2,   2,  0, -2, -4,  0,   1,  0, -4,  0,  0,   0,  1,  0, -1,  0,   4,  0,  0,  0, -1,   3,  0,  2, -1,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=441,450)" is not supported. Skipping.
Line #57162 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=451,460) /   3, -1,  2,  0,  1,   2,  0,  2, -1,  1,   1,  2,  2, -2,  1,   1,  1,  0,  2, -1,   0,  2,  2,  0,  1,   3,  1,  2,  0,  1,   1,  1,  2,  1,  1,   1,  1,  0, -1,  1,   1, -2,  0, -2, -1,   4,  0,  0, -4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=451,460)" is not supported. Skipping.
Line #57173 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=461,470) /   2,  1,  0,  2,  0,   1, -1,  0,  4,  0,   0,  1,  0, -2,  2,   0,  0,  2,  0, -2,   1,  0, -1,  0,  1,   3,  0,  2, -2,  0,   2,  0,  2,  2,  0,   1,  2,  0, -4,  0,   1, -1,  0, -3,  0,   0,  1,  0,  4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=461,470)" is not supported. Skipping.
Line #57184 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=471,480) /   0,  1, -2,  0,  0,   2,  2,  2, -2,  2,   0,  0,  0,  1, -2,   0,  2, -2,  0, -1,   4,  0,  2, -4,  2,   2,  0, -4,  2, -2,   2, -1, -2,  0, -2,   1,  1,  4, -2,  2,   1,  1,  2, -4,  2,   1,  0,  2,  3,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=471,480)" is not supported. Skipping.
Line #57195 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=481,490) /   1,  0,  0,  4, -1,   0,  0,  0,  4,  2,   2,  0,  0,  4,  0,   1,  1, -2,  2,  0,   2,  1,  2,  1,  2,   2,  1,  2, -4,  1,   2,  0,  2,  1,  1,   2,  0, -4, -2, -1,   2,  0, -2, -6, -1,   2, -1,  2, -1,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=481,490)" is not supported. Skipping.
Line #57206 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=491,500) /   1, -2,  2,  0,  1,   1, -2,  0, -2,  1,   1, -1,  0, -4, -1,   0,  2,  2,  2,  2,   0,  2, -2, -4, -2,   0,  1,  2,  3,  2,   0,  1,  0, -4,  1,   3,  0,  0, -2,  1,   2,  1, -2,  0,  1,   2,  0,  4, -2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=491,500)" is not supported. Skipping.
Line #57217 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=501,510) /   2,  0,  0, -3, -1,   2, -2,  0, -2,  1,   2, -1,  2, -2,  1,   1,  0,  0, -6, -1,   1, -2,  0,  0, -1,   1, -2, -2, -2, -1,   0,  1,  4, -2,  1,   0,  0,  2,  3,  1,   2, -1,  0, -1,  0,   1,  3,  0, -2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=501,510)" is not supported. Skipping.
Line #57228 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=511,520) /   0,  3,  0, -2,  0,   2, -2,  2, -2,  2,   0,  0,  4, -2,  0,   4, -1,  2,  0,  2,   2,  2, -2, -4, -2,   4,  1,  2,  0,  2,   4, -1, -2, -2, -2,   2,  1,  0, -2, -2,   2,  1, -2, -6, -2,   2,  0,  0, -1,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=511,520)" is not supported. Skipping.
Line #57239 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=521,530) /   2, -1, -2,  2, -1,   1,  1, -2,  2, -2,   1,  1, -2, -3, -2,   1,  0,  3,  0,  3,   1,  0, -2,  1,  1,   1,  0, -2,  0,  2,   1, -1,  2,  1,  2,   1, -1,  0,  0, -2,   1, -1, -4,  2, -2,   0,  3, -2, -2, -2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=521,530)" is not supported. Skipping.
Line #57250 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=531,540) /   0,  1,  0,  4,  1,   0,  0,  4,  2,  2,   3,  0, -2, -2,  0,   2, -2,  0,  0,  0,   1,  1,  2, -4,  0,   1,  1,  0, -3,  0,   1,  0,  2, -3,  0,   1, -1,  2, -2,  0,   0,  2,  0,  2,  0,   0,  0,  2,  4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=531,540)" is not supported. Skipping.
Line #57261 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=541,550) /   1,  0,  1,  0,  0,   3,  1,  2, -2,  1,   3,  0,  4, -2,  2,   3,  0,  2,  1,  2,   3,  0,  0,  2, -1,   3,  0,  0,  0,  2,   3,  0, -2,  2, -1,   2,  0,  4, -4,  2,   2,  0,  2, -3,  2,   2,  0,  0,  4,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=541,550)" is not supported. Skipping.
Line #57272 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=551,560) /   2,  0,  0, -3,  1,   2,  0, -4,  2, -1,   2,  0, -2, -2,  1,   2, -2,  2,  2,  2,   2, -2,  0, -2, -2,   2, -1,  0,  2,  1,   2, -1,  0,  2, -1,   1,  1,  2,  4,  2,   1,  1,  0,  1,  1,   1,  1,  0,  1, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=551,560)" is not supported. Skipping.
Line #57283 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=561,570) /   1,  1, -2, -6, -2,   1,  0,  0, -3, -1,   1,  0, -4, -2, -1,   1,  0, -2, -6, -1,   1, -2,  2,  2,  1,   1, -2, -2,  2, -1,   1, -1, -2, -4, -1,   0,  2,  0,  0,  2,   0,  1,  2, -4,  2,   0,  1, -2,  4, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=561,570)" is not supported. Skipping.
Line #57294 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=571,580) /   5,  0,  0,  0,  0,   3,  0,  0, -3,  0,   2,  2,  0, -4,  0,   1, -1,  2,  2,  0,   0,  1,  0,  3,  0,   4,  0, -2,  0, -1,   3,  0, -2, -6, -1,   3,  0, -2, -1, -1,   2,  1,  2,  2,  1,   2,  1,  0,  2,  1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=571,580)" is not supported. Skipping.
Line #57305 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=581,590) /   2,  0,  2,  4,  1,   2,  0,  2, -6,  1,   2,  0,  2, -2, -1,   2,  0,  0, -6, -1,   2, -1, -2, -2, -1,   1,  2,  2,  0,  1,   1,  2,  0,  0,  1,   1,  0,  4,  0,  1,   1,  0,  2, -6,  1,   1,  0,  2, -4, -1 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=581,590)" is not supported. Skipping.
Line #57316 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=591,600) /   1,  0, -1, -2, -1,   1, -1,  2,  4,  1,   1, -1,  2, -3,  1,   1, -1,  0,  4,  1,   1, -1, -2,  1, -1,   0,  1,  2, -2,  3,   3,  0,  0, -2,  0,   1,  0,  1, -2,  0,   0,  2,  0, -4,  0,   0,  0,  2, -4,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=591,600)" is not supported. Skipping.
Line #57327 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=601,610) /   0,  0,  1, -1,  0,   0,  0,  0,  6,  0,   0,  2,  0,  0, -2,   0,  1, -2,  2, -3,   4,  0,  0,  2,  0,   3,  0,  0, -1,  0,   3, -1,  0,  2,  0,   2,  1,  0,  1,  0,   2,  1,  0, -6,  0,   2, -1,  2,  0,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=601,610)" is not supported. Skipping.
Line #57338 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=611,620) /   1,  0,  2, -1,  0,   1, -1,  0,  1,  0,   1, -1, -2, -2,  0,   0,  1,  2,  2,  0,   0,  0,  2, -3,  0,   2,  2,  0, -2, -1,   2, -1, -2,  0,  1,   1,  2,  2, -4,  1,   0,  1,  4, -4,  2,   0,  0,  0,  3,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=611,620)" is not supported. Skipping.
Line #57349 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=621,630) /   5,  0,  2,  0,  1,   4,  1,  2, -2,  2,   4,  0, -2, -2,  0,   3,  1,  2,  2,  2,   3,  1,  0, -2,  0,   3,  1, -2, -6, -2,   3,  0,  0,  0, -2,   3,  0, -2, -4, -2,   3, -1,  0, -3,  0,   3, -1,  0, -2,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=621,630)" is not supported. Skipping.
Line #57360 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=631,640) /   2,  1,  2,  0,  0,   2,  1,  2, -4,  2,   2,  1,  2, -2,  0,   2,  1,  0, -3,  0,   2,  1, -2,  0, -2,   2,  0,  0, -4,  2,   2,  0,  0, -4, -2,   2,  0, -2, -5, -2,   2, -1,  2,  4,  2,   2, -1,  0, -2,  2 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=631,640)" is not supported. Skipping.
Line #57371 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=641,650) /   1,  3, -2, -2, -2,   1,  1,  0,  0, -2,   1,  1,  0, -6,  0,   1,  1, -2,  1, -2,   1,  1, -2, -1, -2,   1,  0,  2,  1,  0,   1,  0,  0,  3,  0,   1,  0,  0, -4,  2,   1,  0, -2,  4, -2,   1, -2,  0, -1,  0 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=641,650)" is not supported. Skipping.
Line #57377 in sofapy.f:"      DATA ((MFALS(I,J),I=1,5),J=651,NFLS) /   0,  1, -4,  2, -1,   1,  0, -2,  0, -3,   0,  0,  4, -4,  4 /"
	analyzeline: implied-DO list "((mfals(i,j),i=1,5),j=651,nfls)" is not supported. Skipping.
Line #57388 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=1,10) /   0,  0,  1, -1,  1,  0,  0, -1,  0, -2,  5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0, -1,   0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  1,  0, -8, 12,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  8,-16,  4,  5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -1,  2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=1,10)" is not supported. Skipping.
Line #57399 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=11,20) /   0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1,  1,  0,  0, -1,  0,  2, -5,  0,  0,  0,   0,  0,  2, -2,  1,  0, -5,  6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3,  0, -1,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2, -8,  3,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  6, -8,  3,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=11,20)" is not supported. Skipping.
Line #57410 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=21,30) /   0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  1,  0,  0, -4,  8, -3,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  4, -8,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  2,   0,  0,  1, -1,  1,  0,  0,  0, -2,  0,  0,  0,  0,  0,   2,  0,  0, -2, -1,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  1,   2,  0,  0, -2,  0,  0,  0, -2,  0,  2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=21,30)" is not supported. Skipping.
Line #57421 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=31,40) /   0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  1,   2,  0,  0, -2,  0,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=31,40)" is not supported. Skipping.
Line #57432 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=41,50) /   0,  0,  0,  0,  0,  0,  0,  1,  0, -2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  0,  0,  0,  0, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4,  0, -2,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2, -1,  0,  0,  0,  0,  0,  2,   1,  0,  0,  0,  0,  0,-18, 16,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0,  1,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=41,50)" is not supported. Skipping.
Line #57443 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=51,60) /   0,  0,  1, -1,  1,  0, -5,  7,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,-10,  3,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  0,  0, -5,  6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0, -1,  0,  0,  0,  2,   1,  0,  2,  0,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  1,   1,  0, -2,  0, -2,  0,  0,  4, -8,  3,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  2,  0,  0,  0,   0,  0,  2, -2,  1,  0, -3,  3,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=51,60)" is not supported. Skipping.
Line #57454 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=61,70) /   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  8,-16,  4,  5,  0,  0, -2,   0,  0,  1, -1,  1,  0,  0,  3, -8,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-11,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  8,-16,  4,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=61,70)" is not supported. Skipping.
Line #57465 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=71,80) /   0,  0,  0,  0,  0,  0,  6, -8,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  8,-15,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3,  0, -2,  0,  0,  0,  2,   0,  0,  1, -1,  1,  0,  0, -5,  8, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  2,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=71,80)" is not supported. Skipping.
Line #57476 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=81,90) /   2,  0,  0, -2,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0, -1,   2,  0,  0, -2,  0,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  8,-13,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  0,  0, -2,  5,  0,  0,  0,   1,  0,  0, -1,  0,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  2,   1,  0,  0,  0, -1,  0,-18, 16,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  0,  0,  2, -5,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  0,  0,  1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=81,90)" is not supported. Skipping.
Line #57487 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=91,100) /   1,  0,  0, -2,  0,  0, 19,-21,  3,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -8, 13,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7, -9,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  2,   1,  0,  0,  0,  1,  0,-18, 16,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  6,-16,  4,  5,  0,  0, -2,   0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  3, -7,  0,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=91,100)" is not supported. Skipping.
Line #57498 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=101,110) /   0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  1,   2,  0,  0, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,  0,   2,  0,  0, -2, -1,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  2,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=101,110)" is not supported. Skipping.
Line #57509 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=111,120) /   0,  0,  0,  0,  1,  0,  0,  1, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  2,   0,  0,  2, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0, -1,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0, -6,  8,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -2,  2,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=111,120)" is not supported. Skipping.
Line #57520 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=121,130) /   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  1,   0,  0,  1, -1,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-10,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0, -2,   1,  0,  0, -1,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=121,130)" is not supported. Skipping.
Line #57531 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=131,140) /   0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -1,   0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4,  0, -3,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  1,  0,  2, -3,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=131,140)" is not supported. Skipping.
Line #57542 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=141,150) /   1,  0,  0, -1,  0,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  5, -4,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  9,-11,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  8,-15,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -4,  5,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4,  0, -1,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=141,150)" is not supported. Skipping.
Line #57553 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=151,160) /   1,  0,  0, -1,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  1,  1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0, -4, 10,  0,  0,  0,   0,  0,  0,  0,  1,  0,  1, -1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0,  0, -1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0, -2,   0,  0,  2, -2,  1,  0, -4,  4,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=151,160)" is not supported. Skipping.
Line #57564 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=161,170) /   0,  0,  0,  0,  0,  0,  0,  3,  0,  0, -1,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -3,  0,  0,  0,  0,  2,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  0,  2,  0,   0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  1,   0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  1,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -9, 13,  0,  0,  0,  0,  0,   2,  0,  2,  0,  2,  0,  0,  2,  0, -3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=161,170)" is not supported. Skipping.
Line #57575 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=171,180) /   0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  2,  0,  0, -1,  0,  0,  2,  0,  0,  0,   1,  0,  0, -1, -1,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  1,   1,  0,  2,  0,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0,   1,  0, -2,  0, -1,  0,  0, -1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -2,  4,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=171,180)" is not supported. Skipping.
Line #57586 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=181,190) /   0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  1,   0,  0,  2,  0,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1, -8,  3,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  6,-10,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  7, -8,  3,  0,  0,  0,  2,   0,  0,  0,  0,  1,  0, -3,  5,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -1,  0,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0, -5,  7,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=181,190)" is not supported. Skipping.
Line #57597 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=191,200) /   0,  0,  0,  0,  0,  0,  0,  2,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7,-10,  0,  0,  0,  0,  0, -2,   1,  0,  0, -2,  0,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  2, -5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6, -8,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1,  1,  0,  0, -9, 15,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -2,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -1,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=191,200)" is not supported. Skipping.
Line #57608 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=201,210) /   0,  0,  0,  0,  0,  0,  0,  1, -4,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -1,  0,  0,  2,   2,  0,  0, -2,  1,  0, -6,  8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1,  1,  0,  3, -6,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  8,-14,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=201,210)" is not supported. Skipping.
Line #57619 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=211,220) /   0,  0,  0,  0,  1,  0,  0,  8,-15,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  0,  0,   2,  0,  0, -2,  1,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  1,  0,  0,  2,   2,  0, -1, -1,  0,  0,  0,  3, -7,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -3,  4,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=211,220)" is not supported. Skipping.
Line #57630 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=221,230) /   2,  0,  0, -2,  0,  0,  0, -6,  8,  0,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -5,  6,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  0,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  1,  2,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  1,  0,  0,  1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -9,  4,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=221,230)" is not supported. Skipping.
Line #57641 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=231,240) /   0,  0,  0,  0,  0,  0,  0,  2,  0, -4,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  1,   0,  0,  0,  0,  0,  0,  7,-11,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  3, -5,  4,  0,  0,  0,  0,  2,   0,  0,  1, -1,  0,  0,  0, -1,  0, -1,  1,  0,  0,  0,   2,  0,  0,  0,  0,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  8,-15,  0,  0,  0,  0, -2,   0,  0,  1, -1,  2,  0,  0, -2,  2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  2,   0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  0, -1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=231,240)" is not supported. Skipping.
Line #57652 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=241,250) /   0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -8,  3,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  2, -4,  0, -3,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  3, -5,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3,  0, -3,  0,  0,  0,  2,   0,  0,  2, -2,  2,  0, -8, 11,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5, -8,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -2,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=241,250)" is not supported. Skipping.
Line #57663 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=251,260) /   0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  1,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  5, -9,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  7, -9,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  2, -1,  0,  0,  0,  0,  0,  0,   1,  0, -2, -2, -2,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  3, -3,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=251,260)" is not supported. Skipping.
Line #57674 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=261,270) /   0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  2, -5,  0,  0,  2,   2,  0,  0, -2, -1,  0,  0, -2,  0,  0,  5,  0,  0,  0,   2,  0,  0, -2, -1,  0, -6,  8,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8, -8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3,  0,  2, -5,  0,  0,  2,   0,  0,  0,  0,  1,  0,  3, -7,  4,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=261,270)" is not supported. Skipping.
Line #57685 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=271,280) /   0,  0,  1, -1,  0,  0,  0, -1,  0, -2,  5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3,  0, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0, 11,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  6,-15,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3,  0,  1,  0,  0,  0,  2,   1,  0,  0, -1,  0,  0,  0, -3,  4,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -3,  7, -4,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5,  0, -2,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=271,280)" is not supported. Skipping.
Line #57696 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=281,290) /   0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0,  0,  1,   0,  0,  2, -2,  2,  0, -5,  6,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  2,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -8,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  6,-11,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=281,290)" is not supported. Skipping.
Line #57707 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=291,300) /   0,  0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0, -2,   0,  0,  1, -1,  1,  0,  0, -1,  0,  3,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  9,-12,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,  1,   0,  0,  1, -1,  0,  0, -8, 12,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -2,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0, -1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=291,300)" is not supported. Skipping.
Line #57718 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=301,310) /   0,  0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1, -1,  0,  0,  0, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1, -5,  0,  0,  0,  0, -2,   2,  0,  0, -2,  0,  0,  0, -2,  0,  3, -1,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -2,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5, -9,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=301,310)" is not supported. Skipping.
Line #57729 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=311,320) /   0,  0,  0,  0,  0,  0,  9, -9,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  3,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  2, -4,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  1,   0,  0,  1, -1,  2,  0,  0, -1,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -9,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  2,   0,  0,  2,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=311,320)" is not supported. Skipping.
Line #57740 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=321,330) /   0,  0,  2,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5,  0, -3,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  0,   2,  0, -1, -1, -1,  0,  0, -1,  0,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  4, -3,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  5,-10,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  8,-13,  0,  0,  0,  0,  0,  1,   0,  0,  2, -2,  1, -1,  0,  2,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  2,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=321,330)" is not supported. Skipping.
Line #57751 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=331,340) /   0,  0,  0,  0,  1,  0,  3, -5,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  2, -2,  0,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  9, -9,  0,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0,  1, -1,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -8, 11,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -2,  0,  0,  2,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0, -1,  2,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  2, -6,  0,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=331,340)" is not supported. Skipping.
Line #57762 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=341,350) /   0,  0,  0,  0,  0,  0,  0,  8,-15,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  5, -2,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  7,-13,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3,  0, -2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  3,  0,  0,  0,  2,   0,  0,  2, -2,  1,  0,  0, -2,  0,  3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8, -8,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  8,-10,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=341,350)" is not supported. Skipping.
Line #57773 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=351,360) /   0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0, -4,  0,  0,  0,  0,   2,  0,  0, -2, -1,  0,  0, -5,  6,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  0,  0, -2,   2,  0, -1, -1, -1,  0,  0,  3, -7,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0, -1,  1,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=351,360)" is not supported. Skipping.
Line #57784 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=361,370) /   2,  0,  0, -2,  0,  0,  0, -2,  0,  4, -3,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  6,-11,  0,  0,  0,  0,  0,   2,  0,  0, -2,  1,  0,  0, -6,  8,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -8,  1,  5,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  6, -5,  0,  0,  0,  0,  2,   1,  0, -2, -2, -2,  0, -3,  3,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  2,  0,  0,  0, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0,   0,  0,  0,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  6,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=361,370)" is not supported. Skipping.
Line #57795 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=371,380) /   0,  0,  0,  0,  0,  0,  0,  6, -7,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4,  0,  0, -2,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  3,  0,  0, -2,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  1, -6,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  2,   0,  0,  0,  0,  0,  0,  3, -5,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  7,-13,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  0, -2,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=371,380)" is not supported. Skipping.
Line #57806 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=381,390) /   0,  0,  1, -1,  0,  0,  0, -1,  0,  0,  2,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -8, 15,  0,  0,  0,  0,  0,   2,  0,  0, -2, -2,  0, -3,  3,  0,  0,  0,  0,  0,  0,   2,  0, -1, -1, -1,  0,  0, -1,  0,  2,  0,  0,  0,  0,   1,  0,  2, -2,  2,  0,  0, -2,  0,  2,  0,  0,  0,  0,   1,  0, -1,  1, -1,  0,-18, 17,  0,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0,  0,  1,  0, -1,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  2, -2, -1,  0, -5,  6,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  2,  0,  0, -1,  0,  1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=381,390)" is not supported. Skipping.
Line #57817 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=391,400) /   0,  0,  0,  0,  1,  0,  2, -2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-16,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  2,   0,  0,  0,  0,  2,  0,  0, -1,  2,  0,  0,  0,  0,  0,   2,  0, -1, -1, -2,  0,  0, -1,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6,-10,  0,  0,  0,  0,  0, -1,   0,  0,  1, -1,  1,  0,  0, -1,  0, -2,  4,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2,  2,  0,  0,  0,  0,  2,   2,  0,  0, -2, -1,  0,  0, -2,  0,  4, -5,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=391,400)" is not supported. Skipping.
Line #57828 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=401,410) /   2,  0,  0, -2, -1,  0, -3,  3,  0,  0,  0,  0,  0,  0,   2,  0, -1, -1, -1,  0,  0, -1,  0,  0,  0,  0,  0,  0,   1,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0,  0,  0,  0,   1,  0,  0, -1, -1,  0,  0, -2,  2,  0,  0,  0,  0,  0,   1,  0, -1, -1, -1,  0, 20,-20,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  1, -2,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -2,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  5, -8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  0,  0,  0, -1,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=401,410)" is not supported. Skipping.
Line #57839 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=411,420) /   0,  0,  0,  0,  0,  0,  9,-11,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  5, -3,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  1,   0,  0,  0,  0,  0,  0,  6, -7,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0, -2,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0, -2,  0,  0,  0,   0,  0,  1, -1,  2,  0,  0, -1,  0, -2,  5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=411,420)" is not supported. Skipping.
Line #57850 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=421,430) /   0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5, -8,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2, -6,  0,  0,  0,  0, -2,   1,  0,  0, -2,  0,  0, 20,-21,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-12,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -4,  0,  0,  0,  0,  0,   0,  0,  1, -1,  2,  0,  0, -1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  8,-12,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  9,-17,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=421,430)" is not supported. Skipping.
Line #57861 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=431,440) /   0,  0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -8,  1,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -6,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2, -7,  0,  0,  0,  0, -2,   1,  0,  0, -1,  1,  0,  0, -3,  4,  0,  0,  0,  0,  0,   1,  0, -2,  0, -2,  0,-10,  3,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -9, 17,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -4,  0,  0,  0,  0,  0, -2,   1,  0, -2, -2, -2,  0,  0, -2,  0,  3,  0,  0,  0,  0,   1,  0, -1,  1, -1,  0,  0,  1,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=431,440)" is not supported. Skipping.
Line #57872 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=441,450) /   0,  0,  2, -2,  2,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  1, -1,  2,  0,  0, -1,  0,  0,  1,  0,  0,  0,   0,  0,  1, -1,  2,  0, -5,  7,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  2, -2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5,-10,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  4,  0, -4,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0, -5,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=441,450)" is not supported. Skipping.
Line #57883 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=451,460) /   0,  0,  0,  0,  0,  0,  0,  1,  0, -5,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  1,  0, -2,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1,  0, -2,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -3,  0,  0,  0,  0,  0,  1,   1,  0,  0, -2,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -7,  4,  0,  0,  0,  0,  0,   2,  0,  2,  0,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1, -1,  0,  0, -1,  0, -1,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  1,  0, -2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  6,-10,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=451,460)" is not supported. Skipping.
Line #57894 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=461,470) /   1,  0,  0, -1,  1,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0,  4, -8,  3,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0,  1,  0, -1,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -4,  8, -3,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -3,  0,  3,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0, -5,  5,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  1, -3,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -4,  6,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  0,  0, -1,  0,  0,   0,  0,  1, -1,  1,  0, -5,  6,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=461,470)" is not supported. Skipping.
Line #57905 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=471,480) /   0,  0,  0,  0,  1,  0,  3, -4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7,-10,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  5, -5,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  3, -8,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  2, -5,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  7, -9,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  7, -8,  0,  0,  0,  0,  2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=471,480)" is not supported. Skipping.
Line #57916 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=481,490) /   0,  0,  0,  0,  0,  0,  0,  3,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  3, -8,  3,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -2,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  2, -4,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0, -1,   2,  0,  0, -2, -1,  0,  0, -6,  8,  0,  0,  0,  0,  0,   2,  0, -1, -1,  1,  0,  0,  3, -7,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -7,  9,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,  0, -1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=481,490)" is not supported. Skipping.
Line #57927 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=491,500) /   0,  0,  1, -1,  2,  0, -8, 12,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,  0, -2,  0,  2,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  2, -2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7, -8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,   2,  0,  0, -2,  1,  0,  0, -5,  6,  0,  0,  0,  0,  0,   2,  0,  0, -2, -1,  0,  0, -2,  0,  3, -1,  0,  0,  0,   1,  0,  1,  1,  1,  0,  0,  1,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  1,  0,  0, -2,  0,  2,  0,  0,  0,  0,   1,  0,  0, -2, -1,  0,  0, -2,  0,  2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=491,500)" is not supported. Skipping.
Line #57938 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=501,510) /   1,  0,  0, -1, -1,  0,  0, -3,  4,  0,  0,  0,  0,  0,   1,  0, -1,  0, -1,  0, -3,  5,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -4,  4,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -2,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0, -8, 11,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  0,  0,  0, -9, 13,  0,  0,  0,  0,  0,   0,  0,  1,  1,  2,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0,  1, -4,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0,  0, -1,  0,  1, -3,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0,  7,-13,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=501,510)" is not supported. Skipping.
Line #57949 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=511,520) /   0,  0,  0,  0,  1,  0,  0,  2,  0, -2,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -2,  2,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  7,-11,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  6, -6,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  6, -4,  0,  0,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  4, -2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -4,  0,  0,  0,  0,  0,  1 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=511,520)" is not supported. Skipping.
Line #57960 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=521,530) /   0,  0,  0,  0,  0,  0,  1, -4,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  9,-17,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  7, -7,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  4, -8,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4, -7,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  1,  0,  1,  0,  0,  0,  1,   0,  0,  0,  0,  0,  0,  0,  1,  0, -4,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -4,  8, -3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=521,530)" is not supported. Skipping.
Line #57971 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=531,540) /   2,  0,  0, -2,  0,  0, -2,  2,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,  0, -4,  8, -3,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0, -1,  1,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0, 17,-16,  0, -2,  0,  0,  0,  0,   1,  0,  0, -1,  0,  0,  0, -2,  2,  0,  0,  0,  0,  0,   0,  0,  2, -2,  0,  0,  0, -2,  0,  2,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  3,  0, -4,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=531,540)" is not supported. Skipping.
Line #57982 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=541,550) /   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1, -2, -2,   0,  0,  0,  0,  0,  0,  0,  2,  1,  0,  0,  0,  0,  2,   2,  0,  0, -2,  0,  0,  0, -4,  4,  0,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -2,  0,  2,  2,  0,  0,  0,   1,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,  0, -1,  0,  1,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0, -3,  3,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  1, -1,  0,  0,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  0,  4, -8,  3,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  0, -4,  8, -3,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=541,550)" is not supported. Skipping.
Line #57993 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=551,560) /   1,  0,  0, -2,  0,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  0,  0, -4,  4,  0,  0,  0,  0,  0,  0,   0,  0,  1,  1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  3, -6,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -2,  2,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0,  1,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0,  0,  1,  0,  0,  0,   0,  0,  1, -1,  0,  0, -4,  5,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  0,  2,  0,  0,  0, -1,  0,  1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=551,560)" is not supported. Skipping.
Line #58004 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=561,570) /   0,  0,  0,  0,  0,  0,  8, -9,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -6,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1,  1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  3, -5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -2,  0,  0,  0,   2,  0, -2, -2, -2,  0,  0, -2,  0,  2,  0,  0,  0,  0,   1,  0,  0,  0,  1,  0,-10,  3,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0, -1,  0,-10,  3,  0,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0,  2, -3,  0,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0,  2, -2,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=561,570)" is not supported. Skipping.
Line #58015 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=571,580) /   0,  0,  2,  0,  2,  0, -2,  3,  0,  0,  0,  0,  0,  0,   0,  0,  2,  0,  2,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  2,  0,  0,  0,  0,  1,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0,  0, -1,  0,  2,  0,  0,  0,  0,   2,  0,  2, -2,  2,  0,  0, -2,  0,  3,  0,  0,  0,  0,   2,  0,  1, -3,  1,  0, -6,  7,  0,  0,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0,  2, -5,  0,  0,  0,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -2,  0,  5, -5,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -2,  0,  1,  5,  0,  0,  0,   2,  0,  0, -2,  0,  0,  0, -2,  0,  0,  5,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=571,580)" is not supported. Skipping.
Line #58026 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=581,590) /   2,  0,  0, -2,  0,  0,  0, -2,  0,  0,  2,  0,  0,  0,   2,  0,  0, -2,  0,  0, -4,  4,  0,  0,  0,  0,  0,  0,   2,  0, -2,  0, -2,  0,  0,  5, -9,  0,  0,  0,  0,  0,   2,  0, -1, -1,  0,  0,  0, -1,  0,  3,  0,  0,  0,  0,   1,  0,  2,  0,  2,  0,  1, -1,  0,  0,  0,  0,  0,  0,   1,  0,  2,  0,  2,  0,  0,  4, -8,  3,  0,  0,  0,  0,   1,  0,  2,  0,  2,  0,  0, -4,  8, -3,  0,  0,  0,  0,   1,  0,  2,  0,  2,  0, -1,  1,  0,  0,  0,  0,  0,  0,   1,  0,  2, -2,  2,  0, -3,  3,  0,  0,  0,  0,  0,  0,   1,  0,  0,  0,  0,  0,  0,  1,  0, -1,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=581,590)" is not supported. Skipping.
Line #58037 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=591,600) /   1,  0,  0,  0,  0,  0,  0, -2,  0,  3,  0,  0,  0,  0,   1,  0,  0, -2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0,   1,  0, -2, -2, -2,  0,  0,  1,  0, -1,  0,  0,  0,  0,   1,  0, -1,  1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,   1,  0, -1, -1,  0,  0,  0,  8,-15,  0,  0,  0,  0,  0,   0,  0,  2,  2,  2,  0,  0,  2,  0, -2,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  1, -1,  0,  0,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0, -2,  0,  1,  0,  0,  0,  0,   0,  0,  2, -2,  1,  0,  0,-10, 15,  0,  0,  0,  0,  0,   0,  0,  2, -2,  0, -1,  0,  2,  0,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=591,600)" is not supported. Skipping.
Line #58048 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=601,610) /   0,  0,  1, -1,  2,  0,  0, -1,  0,  0, -1,  0,  0,  0,   0,  0,  1, -1,  2,  0, -3,  4,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -4,  6,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  1,  0, -1,  2,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0,  1,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0,  0, -1,  0,  0, -2,  0,  0,  0,   0,  0,  1, -1,  0,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1,  0,  0, -1,  0,  0,  0,  0,  0,  0,  0,   0,  0,  1, -1, -1,  0, -5,  7,  0,  0,  0,  0,  0,  0,   0,  0,  0,  2,  0,  0,  0,  2,  0, -2,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=601,610)" is not supported. Skipping.
Line #58059 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=611,620) /   0,  0,  0,  2,  0,  0, -2,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  2,  0, -3,  5,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  1,  0, -1,  2,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  9,-13,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  8,-14,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  8,-11,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6, -8,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  6, -7,  0,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=611,620)" is not supported. Skipping.
Line #58070 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=621,630) /   0,  0,  0,  0,  0,  0,  5, -6, -4,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  5, -4,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  4, -8,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  4, -5,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  3, -3,  0,  2,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  3, -1,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  2,  0,  0,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  1, -1,  0,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  7,-12,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  6, -9,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=621,630)" is not supported. Skipping.
Line #58081 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=631,640) /   0,  0,  0,  0,  0,  0,  0,  6, -8,  1,  5,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  6, -4,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  6,-10,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5,  0, -4,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  5, -9,  0,  0,  0,  0, -1,   0,  0,  0,  0,  0,  0,  0,  5, -8,  3,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  5, -7,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  5, -6,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  5,-16,  4,  5,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  5,-13,  0,  0,  0,  0, -2 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=631,640)" is not supported. Skipping.
Line #58092 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=641,650) /   0,  0,  0,  0,  0,  0,  0,  3,  0, -5,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3, -9,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  3, -7,  0,  0,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  2,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  2,  0,  0, -3,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  2, -8,  1,  5,  0,  0, -2,   0,  0,  0,  0,  0,  0,  0,  1,  0,  1, -5,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  2,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  1,  0,  0, -3,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  1,  0, -3,  5,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=641,650)" is not supported. Skipping.
Line #58101 in sofapy.f:"      DATA ((MFAPL(I,J),I=1,14),J=651,NFPL) /   0,  0,  0,  0,  0,  0,  0,  1, -3,  0,  0,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  2, -6,  3,  0, -2,   0,  0,  0,  0,  0,  0,  0,  0,  0,  1, -2,  0,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,   0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,   0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0 /"
	analyzeline: implied-DO list "((mfapl(i,j),i=1,14),j=651,nfpl)" is not supported. Skipping.
Line #58112 in sofapy.f:"      DATA (NC(I),I=1,100) /    1,   21,   37,   51,   65,   79,   91,  103,  115,  127,  139,  151,  163,  172,  184,  196,  207,  219,  231,  240,  252,  261,  273,  285,  297,  309,  318,  327,  339,  351,  363,  372,  384,  396,  405,  415,  423,  435,  444,  452,  460,  467,  474,  482,  490,  498,  506,  513,  521,  528,  536,  543,  551,  559,  566,  574,  582,  590,  597,  605,  613,  620,  628,  636,  644,  651,  658,  666,  674,  680,  687,  695,  702,  710,  717,  725,  732,  739,  746,  753,  760,  767,  774,  782,  790,  798,  805,  812,  819,  826,  833,  840,  846,  853,  860,  867,  874,  881,  888,  895 /"
	analyzeline: implied-DO list "(nc(i),i=1,100)" is not supported. Skipping.
Line #58123 in sofapy.f:"      DATA (NC(I),I=101,200) /  901,  908,  914,  921,  928,  934,  941,  948,  955,  962,  969,  976,  982,  989,  996, 1003, 1010, 1017, 1024, 1031, 1037, 1043, 1050, 1057, 1064, 1071, 1078, 1084, 1091, 1098, 1104, 1112, 1118, 1124, 1131, 1138, 1145, 1151, 1157, 1164, 1171, 1178, 1185, 1192, 1199, 1205, 1212, 1218, 1226, 1232, 1239, 1245, 1252, 1259, 1266, 1272, 1278, 1284, 1292, 1298, 1304, 1310, 1316, 1323, 1329, 1335, 1341, 1347, 1353, 1359, 1365, 1371, 1377, 1383, 1389, 1396, 1402, 1408, 1414, 1420, 1426, 1434, 1440, 1446, 1452, 1459, 1465, 1471, 1477, 1482, 1488, 1493, 1499, 1504, 1509, 1514, 1520, 1527, 1532, 1538 /"
	analyzeline: implied-DO list "(nc(i),i=101,200)" is not supported. Skipping.
Line #58134 in sofapy.f:"      DATA (NC(I),I=201,300) / 1543, 1548, 1553, 1558, 1564, 1569, 1574, 1579, 1584, 1589, 1594, 1596, 1598, 1600, 1602, 1605, 1608, 1610, 1612, 1617, 1619, 1623, 1625, 1627, 1629, 1632, 1634, 1640, 1642, 1644, 1646, 1648, 1650, 1652, 1654, 1658, 1660, 1662, 1664, 1668, 1670, 1672, 1673, 1675, 1679, 1681, 1683, 1684, 1686, 1688, 1690, 1693, 1695, 1697, 1701, 1703, 1705, 1707, 1709, 1711, 1712, 1715, 1717, 1721, 1723, 1725, 1727, 1729, 1731, 1733, 1735, 1737, 1739, 1741, 1743, 1745, 1747, 1749, 1751, 1753, 1755, 1757, 1759, 1761, 1762, 1764, 1766, 1768, 1769, 1771, 1773, 1775, 1777, 1779, 1781, 1783, 1785, 1787, 1788, 1790 /"
	analyzeline: implied-DO list "(nc(i),i=201,300)" is not supported. Skipping.
Line #58145 in sofapy.f:"      DATA (NC(I),I=301,400) / 1792, 1794, 1796, 1798, 1800, 1802, 1804, 1806, 1807, 1809, 1811, 1815, 1817, 1819, 1821, 1823, 1825, 1827, 1829, 1831, 1833, 1835, 1837, 1839, 1840, 1842, 1844, 1848, 1850, 1852, 1854, 1856, 1858, 1859, 1860, 1862, 1864, 1866, 1868, 1869, 1871, 1873, 1875, 1877, 1879, 1881, 1883, 1885, 1887, 1889, 1891, 1892, 1896, 1898, 1900, 1901, 1903, 1905, 1907, 1909, 1910, 1911, 1913, 1915, 1919, 1921, 1923, 1927, 1929, 1931, 1933, 1935, 1937, 1939, 1943, 1945, 1947, 1948, 1949, 1951, 1953, 1955, 1957, 1958, 1960, 1962, 1964, 1966, 1968, 1970, 1971, 1973, 1974, 1975, 1977, 1979, 1980, 1981, 1982, 1984 /"
	analyzeline: implied-DO list "(nc(i),i=301,400)" is not supported. Skipping.
Line #58156 in sofapy.f:"      DATA (NC(I),I=401,500) / 1986, 1988, 1990, 1992, 1994, 1995, 1997, 1999, 2001, 2003, 2005, 2007, 2008, 2009, 2011, 2013, 2015, 2017, 2019, 2021, 2023, 2024, 2025, 2027, 2029, 2031, 2033, 2035, 2037, 2041, 2043, 2045, 2046, 2047, 2049, 2051, 2053, 2055, 2056, 2057, 2059, 2061, 2063, 2065, 2067, 2069, 2070, 2071, 2072, 2074, 2076, 2078, 2080, 2082, 2084, 2086, 2088, 2090, 2092, 2094, 2095, 2096, 2097, 2099, 2101, 2105, 2106, 2107, 2108, 2109, 2110, 2111, 2113, 2115, 2119, 2121, 2123, 2125, 2127, 2129, 2131, 2133, 2135, 2136, 2137, 2139, 2141, 2143, 2145, 2147, 2149, 2151, 2153, 2155, 2157, 2159, 2161, 2163, 2165, 2167 /"
	analyzeline: implied-DO list "(nc(i),i=401,500)" is not supported. Skipping.
Line #58167 in sofapy.f:"      DATA (NC(I),I=501,600) / 2169, 2171, 2173, 2175, 2177, 2179, 2181, 2183, 2185, 2186, 2187, 2188, 2192, 2193, 2195, 2197, 2199, 2201, 2203, 2205, 2207, 2209, 2211, 2213, 2217, 2219, 2221, 2223, 2225, 2227, 2229, 2231, 2233, 2234, 2235, 2236, 2237, 2238, 2239, 2240, 2241, 2244, 2246, 2248, 2250, 2252, 2254, 2256, 2258, 2260, 2262, 2264, 2266, 2268, 2270, 2272, 2274, 2276, 2278, 2280, 2282, 2284, 2286, 2288, 2290, 2292, 2294, 2296, 2298, 2300, 2302, 2303, 2304, 2305, 2306, 2307, 2309, 2311, 2313, 2315, 2317, 2319, 2321, 2323, 2325, 2327, 2329, 2331, 2333, 2335, 2337, 2341, 2343, 2345, 2347, 2349, 2351, 2352, 2355, 2356 /"
	analyzeline: implied-DO list "(nc(i),i=501,600)" is not supported. Skipping.
Line #58178 in sofapy.f:"      DATA (NC(I),I=601,700) / 2357, 2358, 2359, 2361, 2363, 2364, 2365, 2366, 2367, 2368, 2369, 2370, 2371, 2372, 2373, 2374, 2376, 2378, 2380, 2382, 2384, 2385, 2386, 2387, 2388, 2389, 2390, 2391, 2392, 2393, 2394, 2395, 2396, 2397, 2398, 2399, 2400, 2401, 2402, 2403, 2404, 2405, 2406, 2407, 2408, 2409, 2410, 2411, 2412, 2413, 2414, 2415, 2417, 2418, 2430, 2438, 2445, 2453, 2460, 2468, 2474, 2480, 2488, 2496, 2504, 2512, 2520, 2527, 2535, 2543, 2550, 2558, 2566, 2574, 2580, 2588, 2596, 2604, 2612, 2619, 2627, 2634, 2642, 2648, 2656, 2664, 2671, 2679, 2685, 2693, 2701, 2709, 2717, 2725, 2733, 2739, 2747, 2753, 2761, 2769 /"
	analyzeline: implied-DO list "(nc(i),i=601,700)" is not supported. Skipping.
Line #58189 in sofapy.f:"      DATA (NC(I),I=701,800) / 2777, 2785, 2793, 2801, 2809, 2817, 2825, 2833, 2841, 2848, 2856, 2864, 2872, 2878, 2884, 2892, 2898, 2906, 2914, 2922, 2930, 2938, 2944, 2952, 2958, 2966, 2974, 2982, 2988, 2996, 3001, 3009, 3017, 3025, 3032, 3039, 3045, 3052, 3059, 3067, 3069, 3076, 3083, 3090, 3098, 3105, 3109, 3111, 3113, 3120, 3124, 3128, 3132, 3136, 3140, 3144, 3146, 3150, 3158, 3161, 3165, 3166, 3168, 3172, 3176, 3180, 3182, 3185, 3189, 3193, 3194, 3197, 3200, 3204, 3208, 3212, 3216, 3219, 3221, 3222, 3226, 3230, 3234, 3238, 3242, 3243, 3247, 3251, 3254, 3258, 3262, 3266, 3270, 3274, 3275, 3279, 3283, 3287, 3289, 3293 /"
	analyzeline: implied-DO list "(nc(i),i=701,800)" is not supported. Skipping.
Line #58200 in sofapy.f:"      DATA (NC(I),I=801,900) / 3296, 3300, 3303, 3307, 3311, 3315, 3319, 3321, 3324, 3327, 3330, 3334, 3338, 3340, 3342, 3346, 3350, 3354, 3358, 3361, 3365, 3369, 3373, 3377, 3381, 3385, 3389, 3393, 3394, 3398, 3402, 3406, 3410, 3413, 3417, 3421, 3425, 3429, 3433, 3435, 3439, 3443, 3446, 3450, 3453, 3457, 3458, 3461, 3464, 3468, 3472, 3476, 3478, 3481, 3485, 3489, 3493, 3497, 3501, 3505, 3507, 3511, 3514, 3517, 3521, 3524, 3525, 3527, 3529, 3533, 3536, 3540, 3541, 3545, 3548, 3551, 3555, 3559, 3563, 3567, 3569, 3570, 3574, 3576, 3578, 3582, 3586, 3590, 3593, 3596, 3600, 3604, 3608, 3612, 3616, 3620, 3623, 3626, 3630, 3632 /"
	analyzeline: implied-DO list "(nc(i),i=801,900)" is not supported. Skipping.
Line #58211 in sofapy.f:"      DATA (NC(I),I=901,1000) / 3636, 3640, 3643, 3646, 3648, 3652, 3656, 3660, 3664, 3667, 3669, 3671, 3675, 3679, 3683, 3687, 3689, 3693, 3694, 3695, 3699, 3703, 3705, 3707, 3710, 3713, 3717, 3721, 3725, 3729, 3733, 3736, 3740, 3744, 3748, 3752, 3754, 3757, 3759, 3763, 3767, 3770, 3773, 3777, 3779, 3783, 3786, 3790, 3794, 3798, 3801, 3805, 3809, 3813, 3817, 3821, 3825, 3827, 3831, 3835, 3836, 3837, 3840, 3844, 3848, 3852, 3856, 3859, 3863, 3867, 3869, 3871, 3875, 3879, 3883, 3887, 3890, 3894, 3898, 3901, 3905, 3909, 3913, 3917, 3921, 3922, 3923, 3924, 3926, 3930, 3932, 3936, 3938, 3940, 3944, 3948, 3952, 3956, 3959, 3963 /"
	analyzeline: implied-DO list "(nc(i),i=901,1000)" is not supported. Skipping.
Line #58222 in sofapy.f:"      DATA (NC(I),I=1001,1100) / 3965, 3969, 3973, 3977, 3979, 3981, 3982, 3986, 3989, 3993, 3997, 4001, 4004, 4006, 4009, 4012, 4016, 4020, 4024, 4026, 4028, 4032, 4036, 4040, 4044, 4046, 4050, 4054, 4058, 4060, 4062, 4063, 4064, 4068, 4071, 4075, 4077, 4081, 4083, 4087, 4089, 4091, 4095, 4099, 4101, 4103, 4105, 4107, 4111, 4115, 4119, 4123, 4127, 4129, 4131, 4135, 4139, 4141, 4143, 4145, 4149, 4153, 4157, 4161, 4165, 4169, 4173, 4177, 4180, 4183, 4187, 4191, 4195, 4198, 4201, 4205, 4209, 4212, 4213, 4216, 4217, 4221, 4223, 4226, 4230, 4234, 4236, 4240, 4244, 4248, 4252, 4256, 4258, 4262, 4264, 4266, 4268, 4270, 4272, 4276 /"
	analyzeline: implied-DO list "(nc(i),i=1001,1100)" is not supported. Skipping.
Line #58233 in sofapy.f:"      DATA (NC(I),I=1101,1200) / 4279, 4283, 4285, 4287, 4289, 4293, 4295, 4299, 4300, 4301, 4305, 4309, 4313, 4317, 4319, 4323, 4325, 4329, 4331, 4333, 4335, 4337, 4341, 4345, 4349, 4351, 4353, 4357, 4361, 4365, 4367, 4369, 4373, 4377, 4381, 4383, 4387, 4389, 4391, 4395, 4399, 4403, 4407, 4411, 4413, 4414, 4415, 4418, 4419, 4421, 4423, 4427, 4429, 4431, 4433, 4435, 4437, 4439, 4443, 4446, 4450, 4452, 4456, 4458, 4460, 4462, 4466, 4469, 4473, 4477, 4481, 4483, 4487, 4489, 4491, 4493, 4497, 4499, 4501, 4504, 4506, 4510, 4513, 4514, 4515, 4518, 4521, 4522, 4525, 4526, 4527, 4530, 4533, 4534, 4537, 4541, 4542, 4543, 4544, 4545 /"
	analyzeline: implied-DO list "(nc(i),i=1101,1200)" is not supported. Skipping.
Line #58244 in sofapy.f:"      DATA (NC(I),I=1201,1300) / 4546, 4547, 4550, 4553, 4554, 4555, 4558, 4561, 4564, 4567, 4568, 4571, 4574, 4575, 4578, 4581, 4582, 4585, 4586, 4588, 4590, 4592, 4596, 4598, 4602, 4604, 4608, 4612, 4613, 4616, 4619, 4622, 4623, 4624, 4625, 4626, 4629, 4632, 4633, 4636, 4639, 4640, 4641, 4642, 4643, 4644, 4645, 4648, 4649, 4650, 4651, 4652, 4653, 4656, 4657, 4660, 4661, 4664, 4667, 4670, 4671, 4674, 4675, 4676, 4677, 4678, 4681, 4682, 4683, 4684, 4687, 4688, 4689, 4692, 4693, 4696, 4697, 4700, 4701, 4702, 4703, 4704, 4707, 4708, 4711, 4712, 4715, 4716, 4717, 4718, 4719, 4720, 4721, 4722, 4723, 4726, 4729, 4730, 4733, 4736 /"
	analyzeline: implied-DO list "(nc(i),i=1201,1300)" is not supported. Skipping.
Line #58248 in sofapy.f:"      DATA (NC(I),I=1301,NF) / 4737, 4740, 4741, 4742, 4745, 4746, 4749, 4752, 4753 /"
	analyzeline: implied-DO list "(nc(i),i=1301,nf)" is not supported. Skipping.
Line #58268 in sofapy.f:"      DATA (A(I),I=1,133) /-6844318.44D0,9205236.26D0,1328.67D0,1538.18D0,205833.11D0,153041.79D0,-3309.73D0,853.32D0,2037.98D0,-2301.27D0,81.46D0,120.56D0,-20.39D0,-15.22D0,1.73D0,-1.61D0,-0.1D0,0.11D0,-0.02D0,-0.02D0,-523908.04D0,573033.42D0,-544.75D0,-458.66D0,12814.01D0,11714.49D0,198.97D0,-290.91D0,155.74D0,-143.27D0,-2.75D0,-1.03D0,-1.27D0,-1.16D0,    0D0,-0.01D0,-90552.22D0,97846.69D0,111.23D0,137.41D0,2187.91D0,2024.68D0,41.44D0,-51.26D0,26.92D0,-24.46D0,-0.46D0,-0.28D0,-0.22D0, -0.2D0,82168.76D0,-89618.24D0,-27.64D0,-29.05D0,-2004.36D0,-1837.32D0,-36.07D0,48D0,-24.43D0,22.41D0, 0.47D0, 0.24D0,  0.2D0, 0.18D0,58707.02D0,7387.02D0,470.05D0,-192.4D0,164.33D0,-1312.21D0,-179.73D0,-28.93D0,-17.36D0,-1.83D0, -0.5D0, 3.57D0,    0D0, 0.13D0,-20557.78D0,22438.42D0,-20.84D0,-17.4D0,501.82D0,459.68D0,59.2D0,-67.3D0,6.08D0,-5.61D0,-1.36D0,-1.19D0,28288.28D0,-674.99D0,-34.69D0,35.8D0,-15.07D0,-632.54D0,-11.19D0,0.78D0,-8.41D0, 0.17D0, 0.01D0, 0.07D0,-15406.85D0,20069.5D0,15.12D0,31.8D0,448.76D0,344.5D0,-5.77D0,1.41D0,4.59D0,-5.02D0, 0.17D0, 0.24D0,-11991.74D0,12902.66D0,32.46D0,36.7D0,288.49D0,268.14D0,5.7D0,-7.06D0, 3.57D0,-3.23D0,-0.06D0,-0.04D0,-8584.95D0,-9592.72D0,4.42D0,-13.2D0,-214.5D0,192.06D0,23.87D0 /"
	analyzeline: implied-DO list "(a(i),i=1,133)" is not supported. Skipping.
Line #58288 in sofapy.f:"      DATA (A(I),I=134,273) /29.83D0, 2.54D0,  2.4D0,  0.6D0,-0.48D0,5095.5D0,-6918.22D0, 7.19D0, 3.92D0,-154.91D0,-113.94D0,2.86D0,-1.04D0,-1.52D0, 1.73D0,-0.07D0, -0.1D0,-4910.93D0,-5331.13D0,0.76D0,0.4D0,-119.21D0,109.81D0,2.16D0,3.2D0, 1.46D0, 1.33D0, 0.04D0,-0.02D0,-6245.02D0,-123.48D0,-6.68D0,-8.2D0,-2.76D0,139.64D0,2.71D0, 0.15D0, 1.86D0,2511.85D0,-3323.89D0,1.07D0,-0.9D0,-74.33D0,-56.17D0,1.16D0,-0.01D0,-0.75D0, 0.83D0,-0.02D0,-0.04D0,2307.58D0,3143.98D0,-7.52D0,7.5D0,70.31D0,-51.6D0,1.46D0,0.16D0,-0.69D0,-0.79D0, 0.02D0,-0.05D0,2372.58D0,2554.51D0,5.93D0, -6.6D0,57.12D0,-53.05D0,-0.96D0,-1.24D0,-0.71D0,-0.64D0,-0.01D0,-2053.16D0,2636.13D0,5.13D0,7.8D0,58.94D0,45.91D0,-0.42D0,-0.12D0, 0.61D0,-0.66D0, 0.02D0, 0.03D0,-1825.49D0,-2423.59D0, 1.23D0,   -2D0,-54.19D0,40.82D0,-1.07D0,-1.02D0,0.54D0, 0.61D0,-0.04D0, 0.04D0,2521.07D0,-122.28D0,-5.97D0,2.9D0,-2.73D0,-56.37D0,-0.82D0,0.13D0,-0.75D0,-1534.09D0,1645.01D0,6.29D0,  6.8D0,36.78D0, 34.3D0, 0.92D0,-1.25D0, 0.46D0,-0.41D0,-0.02D0,-0.01D0,1898.27D0,47.7D0,-0.72D0, 2.5D0, 1.07D0,-42.45D0,-0.94D0, 0.02D0,-0.56D0,-1292.02D0,-1387D0, 0D0,    0D0,-31.01D0,28.89D0, 0.68D0,    0D0, 0.38D0, 0.35D0,-0.01D0,-0.01D0,-1234.96D0 /"
	analyzeline: implied-DO list "(a(i),i=134,273)" is not supported. Skipping.
Line #58308 in sofapy.f:"      DATA (A(I),I=274,415) /1323.81D0,5.21D0, 5.9D0, 29.6D0,27.61D0, 0.74D0,-1.22D0, 0.37D0,-0.33D0,-0.02D0,-0.01D0,1137.48D0,-1233.89D0,-0.04D0,-0.3D0,-27.59D0,-25.43D0,-0.61D0,  1D0,-0.34D0, 0.31D0, 0.01D0, 0.01D0,-813.13D0,-1075.6D0,0.4D0,0.3D0,-24.05D0,18.18D0,-0.4D0,-0.01D0, 0.24D0, 0.27D0,-0.01D0, 0.01D0,1163.22D0,-60.9D0,-2.94D0,1.3D0,-1.36D0,-26.01D0,-0.58D0,0.07D0,-0.35D0,1029.7D0,-55.55D0,-2.63D0,  1.1D0,-1.25D0,-23.02D0,-0.52D0,0.06D0,-0.31D0,-556.26D0,852.85D0,3.16D0,-4.48D0,19.06D0,12.44D0,-0.81D0,-0.27D0, 0.17D0,-0.21D0,    0D0, 0.02D0,-603.52D0,-800.34D0, 0.44D0,  0.1D0,-17.9D0,13.49D0,-0.08D0,-0.01D0, 0.18D0,  0.2D0,-0.01D0, 0.01D0,-628.24D0,684.99D0,-0.64D0,-0.5D0,15.32D0,14.05D0, 3.18D0,-4.19D0, 0.19D0,-0.17D0,-0.09D0,-0.07D0,-866.48D0,-16.26D0,0.52D0,-1.3D0,-0.36D0,19.37D0,0.43D0,-0.01D0, 0.26D0,-512.37D0,695.54D0,-1.47D0,-1.4D0,15.55D0,11.46D0,-0.16D0, 0.03D0, 0.15D0,-0.17D0, 0.01D0, 0.01D0,506.65D0,643.75D0,2.54D0,-2.62D0, 14.4D0,-11.33D0,-0.77D0,-0.06D0,-0.15D0,-0.16D0,    0D0, 0.01D0,664.57D0,16.81D0,-0.4D0,    1D0, 0.38D0,-14.86D0,-3.71D0,-0.09D0,-0.2D0,405.91D0,522.11D0,0.99D0,-1.5D0,11.67D0,-9.08D0,-0.25D0,-0.02D0,-0.12D0,-0.13D0,-305.78D0 /"
	analyzeline: implied-DO list "(a(i),i=274,415)" is not supported. Skipping.
Line #58328 in sofapy.f:"      DATA (A(I),I=416,566) /326.6D0, 1.75D0,  1.9D0,  7.3D0, 6.84D0,  0.2D0,-0.04D0,300.99D0,-325.03D0,-0.44D0,-0.5D0,-7.27D0,-6.73D0,-1.01D0,0.01D0,    0D0, 0.08D0,    0D0, 0.02D0,438.51D0,10.47D0,-0.56D0,-0.2D0, 0.24D0,-9.81D0,-0.24D0, 0.01D0,-0.13D0,-264.02D0,335.24D0,0.99D0,1.4D0, 7.49D0,  5.9D0,-0.27D0,-0.02D0,284.09D0,307.03D0,0.32D0,-0.4D0, 6.87D0,-6.35D0,-0.99D0,-0.01D0,-250.54D0,327.11D0,0.08D0,0.4D0, 7.31D0,  5.6D0, -0.3D0,230.72D0,-304.46D0,0.08D0,-0.1D0,-6.81D0,-5.16D0, 0.27D0,229.78D0,304.17D0,-0.6D0, 0.5D0,  6.8D0,-5.14D0, 0.33D0, 0.01D0,256.3D0,-276.81D0,-0.28D0,-0.4D0,-6.19D0,-5.73D0,-0.14D0, 0.01D0,-212.82D0,269.45D0,0.84D0,1.2D0, 6.02D0, 4.76D0, 0.14D0,-0.02D0,196.64D0,272.05D0,-0.84D0,0.9D0, 6.08D0, -4.4D0, 0.35D0, 0.02D0,188.95D0,272.22D0,-0.12D0,0.3D0, 6.09D0,-4.22D0, 0.34D0,-292.37D0,-5.1D0,-0.32D0,-0.4D0,-0.11D0, 6.54D0, 0.14D0, 0.01D0,161.79D0,-220.67D0,0.24D0,0.1D0,-4.93D0,-3.62D0,-0.08D0,261.54D0,-19.94D0,-0.95D0,0.2D0,-0.45D0,-5.85D0,-0.13D0, 0.02D0,142.16D0,-190.79D0,0.2D0, 0.1D0,-4.27D0,-3.18D0,-0.07D0,187.95D0,-4.11D0,-0.24D0,  0.3D0,-0.09D0, -4.2D0,-0.09D0, 0.01D0,    0D0,    0D0,-79.08D0,167.9D0,0.04D0,    0D0, 3.75D0, 1.77D0,121.98D0,131.04D0,-0.08D0, 0.1D0, 2.93D0,-2.73D0,-0.06D0,-172.95D0 /"
	analyzeline: implied-DO list "(a(i),i=416,566)" is not supported. Skipping.
Line #58348 in sofapy.f:"      DATA (A(I),I=567,713) /-8.11D0, -0.4D0, -0.2D0,-0.18D0, 3.87D0, 0.09D0, 0.01D0,-160.15D0,-55.3D0,-14.04D0,13.9D0,-1.23D0,3.58D0, 0.4D0, 0.31D0,-115.4D0,123.2D0, 0.6D0,  0.7D0, 2.75D0, 2.58D0, 0.08D0,-0.01D0,-168.26D0, -2D0,  0.2D0, -0.2D0,-0.04D0, 3.76D0, 0.08D0,-114.49D0,123.2D0,0.32D0, 0.4D0, 2.75D0, 2.56D0, 0.07D0,-0.01D0,112.14D0,120.7D0,0.28D0, -0.3D0,  2.7D0,-2.51D0,-0.07D0,-0.01D0,161.34D0,4.03D0,  0.2D0,  0.2D0, 0.09D0,-3.61D0,-0.08D0,91.31D0,126.64D0,-0.4D0,  0.4D0, 2.83D0,-2.04D0,-0.04D0, 0.01D0,105.29D0,112.9D0, 0.44D0, -0.5D0, 2.52D0,-2.35D0,-0.07D0,-0.01D0,98.69D0,-106.2D0,-0.28D0,-0.3D0,-2.37D0,-2.21D0,-0.06D0, 0.01D0,86.74D0,-112.94D0,-0.08D0,-0.2D0,-2.53D0,-1.94D0,-0.05D0,-134.81D0, 3.51D0,  0.2D0, -0.2D0, 0.08D0, 3.01D0, 0.07D0,79.03D0,107.31D0,-0.24D0,  0.2D0,  2.4D0,-1.77D0,-0.04D0, 0.01D0,132.81D0,-10.77D0,-0.52D0, 0.1D0,-0.24D0,-2.97D0,-0.07D0, 0.01D0,-130.31D0,-0.9D0,0.04D0,    0D0,    0D0, 2.91D0,-78.56D0,85.32D0,    0D0,    0D0, 1.91D0, 1.76D0, 0.04D0,    0D0,    0D0,-41.53D0, 89.1D0, 0.02D0,    0D0, 1.99D0, 0.93D0,66.03D0,  -71D0, -0.2D0, -0.2D0,-1.59D0,-1.48D0,-0.04D0, 60.5D0, 64.7D0, 0.36D0, -0.4D0, 1.45D0,-1.35D0,-0.04D0,-0.01D0,-52.27D0,-70.01D0,  0D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=567,713)" is not supported. Skipping.
Line #58368 in sofapy.f:"      DATA (A(I),I=714,865) /-1.57D0, 1.17D0, 0.03D0,-52.95D0,66.29D0,0.32D0,  0.4D0, 1.48D0, 1.18D0, 0.04D0,-0.01D0,51.02D0,67.25D0,    0D0,    0D0,  1.5D0,-1.14D0,-0.03D0,-55.66D0,-60.92D0,0.16D0,-0.2D0,-1.36D0, 1.24D0, 0.03D0,-54.81D0,-59.2D0,-0.08D0, 0.2D0,-1.32D0, 1.23D0, 0.03D0,51.32D0,-55.6D0,    0D0,    0D0,-1.24D0,-1.15D0,-0.03D0,48.29D0, 51.8D0,  0.2D0, -0.2D0, 1.16D0,-1.08D0,-0.03D0,-45.59D0, -49D0,-0.12D0,  0.1D0, -1.1D0, 1.02D0, 0.03D0,40.54D0,-52.69D0,-0.04D0, -0.1D0,-1.18D0,-0.91D0,-0.02D0,-40.58D0,-49.51D0, -1D0,    1D0,-1.11D0, 0.91D0, 0.04D0, 0.02D0,-43.76D0,46.5D0, 0.36D0,  0.4D0, 1.04D0, 0.98D0, 0.03D0,-0.01D0,62.65D0,   -5D0,-0.24D0,    0D0,-0.11D0, -1.4D0,-0.03D0, 0.01D0,-38.57D0,49.59D0,0.08D0,  0.1D0, 1.11D0, 0.86D0, 0.02D0,-33.22D0,-44.04D0,0.08D0,-0.1D0,-0.98D0, 0.74D0, 0.02D0,37.15D0,-39.9D0,-0.12D0, -0.1D0,-0.89D0,-0.83D0,-0.02D0,36.68D0,-39.5D0,-0.04D0, -0.1D0,-0.88D0,-0.82D0,-0.02D0,-53.22D0,-3.91D0,-0.2D0,    0D0,-0.09D0, 1.19D0, 0.03D0,32.43D0,-42.19D0,-0.04D0,-0.1D0,-0.94D0,-0.73D0,-0.02D0,  -51D0, -2.3D0,-0.12D0, -0.1D0,    0D0, 1.14D0,-29.53D0,-39.11D0,0.04D0,   0D0,-0.87D0, 0.66D0, 0.02D0, 28.5D0,-38.92D0,-0.08D0,-0.1D0,-0.87D0,-0.64D0,-0.02D0,26.54D0,36.95D0,-0.12D0,  0.1D0, 0.83D0,-0.59D0 /"
	analyzeline: implied-DO list "(a(i),i=714,865)" is not supported. Skipping.
Line #58388 in sofapy.f:"      DATA (A(I),I=866,1017) /-0.01D0,26.54D0,34.59D0, 0.04D0, -0.1D0, 0.77D0,-0.59D0,-0.02D0,28.35D0,-32.55D0,-0.16D0, 0.2D0,-0.73D0,-0.63D0,-0.01D0,  -28D0, 30.4D0,    0D0,    0D0, 0.68D0, 0.63D0, 0.01D0,-27.61D0,29.4D0,  0.2D0,  0.2D0, 0.66D0, 0.62D0, 0.02D0,40.33D0,  0.4D0,-0.04D0,  0.1D0,    0D0, -0.9D0,-23.28D0,31.61D0,-0.08D0,-0.1D0, 0.71D0, 0.52D0, 0.01D0,37.75D0,  0.8D0, 0.04D0,  0.1D0,    0D0,-0.84D0,23.66D0, 25.8D0,    0D0,    0D0, 0.58D0,-0.53D0,-0.01D0,21.01D0,-27.91D0,   0D0,    0D0,-0.62D0,-0.47D0,-0.01D0,-34.81D0,2.89D0, 0.04D0,    0D0,    0D0, 0.78D0,-23.49D0,-25.31D0,  0D0,    0D0,-0.57D0, 0.53D0, 0.01D0,-23.47D0,25.2D0, 0.16D0,  0.2D0, 0.56D0, 0.52D0, 0.02D0,19.58D0, 27.5D0,-0.12D0,  0.1D0, 0.62D0,-0.44D0,-0.01D0,-22.67D0,-24.4D0,-0.08D0, 0.1D0,-0.55D0, 0.51D0, 0.01D0,-19.97D0,  25D0, 0.12D0,  0.2D0, 0.56D0, 0.45D0, 0.01D0,21.28D0,-22.8D0,-0.08D0, -0.1D0,-0.51D0,-0.48D0,-0.01D0,-30.47D0,0.91D0, 0.04D0,    0D0,    0D0, 0.68D0,18.58D0,   24D0, 0.04D0, -0.1D0, 0.54D0,-0.42D0,-0.01D0,-18.02D0,24.4D0,-0.04D0, -0.1D0, 0.55D0,  0.4D0, 0.01D0,17.74D0, 22.5D0, 0.08D0, -0.1D0,  0.5D0, -0.4D0,-0.01D0,-19.41D0,20.7D0, 0.08D0,  0.1D0, 0.46D0, 0.43D0, 0.01D0,-18.64D0,20.11D0,   0D0,    0D0, 0.45D0, 0.42D0, 0.01D0,-16.75D0 /"
	analyzeline: implied-DO list "(a(i),i=866,1017)" is not supported. Skipping.
Line #58408 in sofapy.f:"      DATA (A(I),I=1018,1169) / 21.6D0, 0.04D0,  0.1D0, 0.48D0, 0.37D0, 0.01D0,-18.42D0, -20D0,    0D0,    0D0,-0.45D0, 0.41D0, 0.01D0,-26.77D0,1.41D0, 0.08D0,    0D0,    0D0,  0.6D0,-26.17D0,-0.19D0,   0D0,    0D0,    0D0, 0.59D0,-15.52D0,20.51D0,   0D0,    0D0, 0.46D0, 0.35D0, 0.01D0,-25.42D0,-1.91D0,-0.08D0,   0D0,-0.04D0, 0.57D0, 0.45D0,-17.42D0, 18.1D0,    0D0,    0D0,  0.4D0, 0.39D0, 0.01D0,16.39D0,-17.6D0,-0.08D0, -0.1D0,-0.39D0,-0.37D0,-0.01D0,-14.37D0,18.91D0,   0D0,    0D0, 0.42D0, 0.32D0, 0.01D0,23.39D0, -2.4D0,-0.12D0,    0D0,    0D0,-0.52D0,14.32D0,-18.5D0,-0.04D0, -0.1D0,-0.41D0,-0.32D0,-0.01D0,15.69D0,17.08D0,    0D0,    0D0, 0.38D0,-0.35D0,-0.01D0,-22.99D0, 0.5D0, 0.04D0,    0D0,    0D0, 0.51D0,    0D0,    0D0,14.47D0,-17.6D0,-0.01D0,    0D0,-0.39D0,-0.32D0,-13.33D0,18.4D0,-0.04D0, -0.1D0, 0.41D0,  0.3D0,22.47D0, -0.6D0,-0.04D0,    0D0,    0D0, -0.5D0,-12.78D0,-17.41D0,0.04D0,   0D0,-0.39D0, 0.29D0, 0.01D0,-14.1D0,-15.31D0,0.04D0,    0D0,-0.34D0, 0.32D0, 0.01D0,11.98D0,16.21D0,-0.04D0,    0D0, 0.36D0,-0.27D0,-0.01D0,19.65D0, -1.9D0,-0.08D0,    0D0,    0D0,-0.44D0,19.61D0, -1.5D0,-0.08D0,    0D0,    0D0,-0.44D0,13.41D0,-14.3D0,-0.04D0, -0.1D0,-0.32D0, -0.3D0,-0.01D0,-13.29D0,14.4D0,    0D0,    0D0, 0.32D0,  0.3D0 /"
	analyzeline: implied-DO list "(a(i),i=1018,1169)" is not supported. Skipping.
Line #58428 in sofapy.f:"      DATA (A(I),I=1170,1321) / 0.01D0,11.14D0,-14.4D0,-0.04D0,    0D0,-0.32D0,-0.25D0,-0.01D0,12.24D0,-13.38D0,0.04D0,    0D0, -0.3D0,-0.27D0,-0.01D0,10.07D0,-13.81D0,0.04D0,    0D0,-0.31D0,-0.23D0,-0.01D0,10.46D0, 13.1D0, 0.08D0, -0.1D0, 0.29D0,-0.23D0,-0.01D0,16.55D0,-1.71D0,-0.08D0,    0D0,    0D0,-0.37D0, 9.75D0,-12.8D0,    0D0,    0D0,-0.29D0,-0.22D0,-0.01D0, 9.11D0, 12.8D0,    0D0,    0D0, 0.29D0, -0.2D0,    0D0,    0D0,-6.44D0,-13.8D0,    0D0,    0D0,-0.31D0, 0.14D0,-9.19D0,  -12D0,    0D0,    0D0,-0.27D0, 0.21D0,-10.3D0, 10.9D0, 0.08D0,  0.1D0, 0.24D0, 0.23D0, 0.01D0,14.92D0, -0.8D0,-0.04D0,    0D0,    0D0,-0.33D0,10.02D0,-10.8D0,    0D0,    0D0,-0.24D0,-0.22D0,-0.01D0,-9.75D0, 10.4D0, 0.04D0,    0D0, 0.23D0, 0.22D0, 0.01D0, 9.67D0,-10.4D0,-0.04D0,    0D0,-0.23D0,-0.22D0,-0.01D0,-8.28D0,-11.2D0, 0.04D0,    0D0,-0.25D0, 0.19D0,13.32D0,-1.41D0,-0.08D0,    0D0,    0D0, -0.3D0, 8.27D0, 10.5D0, 0.04D0,    0D0, 0.23D0,-0.19D0,    0D0,    0D0,13.13D0,    0D0,    0D0,    0D0,    0D0,-0.29D0,-12.93D0, 0.7D0, 0.04D0,    0D0,    0D0, 0.29D0, 7.91D0,-10.2D0,    0D0,    0D0,-0.23D0,-0.18D0,-7.84D0,  -10D0,-0.04D0,    0D0,-0.22D0, 0.18D0, 7.44D0,  9.6D0,    0D0,    0D0, 0.21D0,-0.17D0,-7.64D0,  9.4D0, 0.08D0,  0.1D0, 0.21D0, 0.17D0 /"
	analyzeline: implied-DO list "(a(i),i=1170,1321)" is not supported. Skipping.
Line #58448 in sofapy.f:"      DATA (A(I),I=1322,1473) / 0.01D0,-11.38D0, 0.6D0, 0.04D0,    0D0,    0D0, 0.25D0,-7.48D0,  8.3D0,    0D0,    0D0, 0.19D0, 0.17D0,-10.98D0,-0.2D0,    0D0,    0D0,    0D0, 0.25D0,10.98D0,  0.2D0,    0D0,    0D0,    0D0,-0.25D0,  7.4D0, -7.9D0,-0.04D0,    0D0,-0.18D0,-0.17D0,-6.09D0,  8.4D0,-0.04D0,    0D0, 0.19D0, 0.14D0,-6.94D0,-7.49D0,    0D0,    0D0,-0.17D0, 0.16D0, 6.92D0,  7.5D0, 0.04D0,    0D0, 0.17D0,-0.15D0,  6.2D0, 8.09D0,    0D0,    0D0, 0.18D0,-0.14D0,-6.12D0,  7.8D0, 0.04D0,    0D0, 0.17D0, 0.14D0, 5.85D0, -7.5D0,    0D0,    0D0,-0.17D0,-0.13D0,-6.48D0,  6.9D0, 0.08D0,  0.1D0, 0.15D0, 0.14D0, 0.01D0, 6.32D0,  6.9D0,    0D0,    0D0, 0.15D0,-0.14D0, 5.61D0, -7.2D0,    0D0,    0D0,-0.16D0,-0.13D0, 9.07D0,    0D0,    0D0,    0D0,    0D0, -0.2D0, 5.25D0,  6.9D0,    0D0,    0D0, 0.15D0,-0.12D0,-8.47D0, -0.4D0,    0D0,    0D0,    0D0, 0.19D0, 6.32D0,-5.39D0,-1.11D0,  1.1D0,-0.12D0,-0.14D0, 0.02D0, 0.02D0, 5.73D0, -6.1D0,-0.04D0,    0D0,-0.14D0,-0.13D0,  4.7D0,  6.6D0,-0.04D0,    0D0, 0.15D0,-0.11D0, -4.9D0, -6.4D0,    0D0,    0D0,-0.14D0, 0.11D0,-5.33D0,  5.6D0, 0.04D0,  0.1D0, 0.13D0, 0.12D0, 0.01D0,-4.81D0,    6D0, 0.04D0,    0D0, 0.13D0, 0.11D0, 5.13D0,  5.5D0, 0.04D0,    0D0, 0.12D0,-0.11D0,  4.5D0,  5.9D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=1322,1473)" is not supported. Skipping.
Line #58468 in sofapy.f:"      DATA (A(I),I=1474,1625) /    0D0, 0.13D0, -0.1D0,-4.22D0,  6.1D0,    0D0,    0D0, 0.14D0,-4.53D0,  5.7D0,    0D0,    0D0, 0.13D0,  0.1D0, 4.18D0,  5.7D0,    0D0,    0D0, 0.13D0,-4.75D0,-5.19D0,    0D0,    0D0,-0.12D0, 0.11D0,-4.06D0,  5.6D0,    0D0,    0D0, 0.13D0,-3.98D0,  5.6D0,-0.04D0,    0D0, 0.13D0, 4.02D0, -5.4D0,    0D0,    0D0,-0.12D0, 4.49D0, -4.9D0,-0.04D0,    0D0,-0.11D0, -0.1D0,-3.62D0, -5.4D0,-0.16D0,  0.2D0,-0.12D0,    0D0, 0.01D0, 4.38D0,  4.8D0,    0D0,    0D0, 0.11D0, -6.4D0, -0.1D0,    0D0,    0D0,    0D0, 0.14D0,-3.98D0,    5D0, 0.04D0,    0D0, 0.11D0,-3.82D0,   -5D0,    0D0,    0D0,-0.11D0,-3.71D0, 5.07D0,    0D0,    0D0, 0.11D0, 4.14D0,  4.4D0,    0D0,    0D0,  0.1D0,-6.01D0, -0.5D0,-0.04D0,    0D0,    0D0, 0.13D0,-4.04D0, 4.39D0,    0D0,    0D0,  0.1D0, 3.45D0,-4.72D0,    0D0,    0D0,-0.11D0, 3.31D0, 4.71D0,    0D0,    0D0, 0.11D0, 3.26D0, -4.5D0,    0D0,    0D0, -0.1D0,-3.26D0, -4.5D0,    0D0,    0D0, -0.1D0,-3.34D0, -4.4D0,    0D0,    0D0, -0.1D0,-3.74D0,   -4D0,  3.7D0,    4D0, 3.34D0, -4.3D0,  3.3D0, -4.3D0,-3.66D0,  3.9D0, 0.04D0, 3.66D0,  3.9D0, 0.04D0,-3.62D0, -3.9D0,-3.61D0,  3.9D0, -0.2D0,  5.3D0,    0D0,    0D0, 0.12D0, 3.06D0,  4.3D0,  3.3D0,    4D0,  0.4D0,  0.2D0,  3.1D0,  4.1D0,-3.06D0 /"
	analyzeline: implied-DO list "(a(i),i=1474,1625)" is not supported. Skipping.
Line #58488 in sofapy.f:"      DATA (A(I),I=1626,1777) /  3.9D0, -3.3D0, -3.6D0, -3.3D0, 3.36D0, 0.01D0, 3.14D0,  3.4D0,-4.57D0, -0.2D0,    0D0,    0D0,    0D0,  0.1D0, -2.7D0, -3.6D0, 2.94D0, -3.2D0, -2.9D0,  3.2D0, 2.47D0, -3.4D0, 2.55D0, -3.3D0,  2.8D0,-3.08D0, 2.51D0,  3.3D0, -4.1D0,  0.3D0,-0.12D0, -0.1D0,  4.1D0,  0.2D0,-2.74D0,    3D0, 2.46D0, 3.23D0,-3.66D0,  1.2D0, -0.2D0,  0.2D0, 3.74D0, -0.4D0,-2.51D0, -2.8D0,-3.74D0, 2.27D0, -2.9D0,    0D0,    0D0, -2.5D0,  2.7D0,-2.51D0,  2.6D0, -3.5D0,  0.2D0, 3.38D0,-2.22D0, -2.5D0, 3.26D0, -0.4D0, 1.95D0, -2.6D0, 3.22D0, -0.4D0,-0.04D0,-1.79D0, -2.6D0, 1.91D0,  2.5D0, 0.74D0, 3.05D0,-0.04D0, 0.08D0, 2.11D0, -2.3D0,-2.11D0,  2.2D0,-1.87D0, -2.4D0, 2.03D0, -2.2D0,-2.03D0,  2.2D0, 2.98D0,    0D0,    0D0, 2.98D0,-1.71D0,  2.4D0, 2.94D0, -0.1D0,-0.12D0,  0.1D0, 1.67D0,  2.4D0,-1.79D0,  2.3D0,-1.79D0,  2.2D0,-1.67D0,  2.2D0, 1.79D0,   -2D0, 1.87D0, -1.9D0, 1.63D0, -2.1D0,-1.59D0,  2.1D0, 1.55D0, -2.1D0,-1.55D0,  2.1D0,-2.59D0, -0.2D0,-1.75D0, -1.9D0,-1.75D0,  1.9D0,-1.83D0, -1.8D0, 1.51D0,    2D0,-1.51D0,   -2D0, 1.71D0,  1.8D0, 1.31D0,  2.1D0,-1.43D0,    2D0, 1.43D0,    2D0,-2.43D0,-1.51D0,  1.9D0,-1.47D0,  1.9D0, 2.39D0,  0.2D0,-2.39D0, 1.39D0,  1.9D0, 1.39D0, -1.8D0, 1.47D0, -1.6D0, 1.47D0, -1.6D0, 1.43D0 /"
	analyzeline: implied-DO list "(a(i),i=1626,1777)" is not supported. Skipping.
Line #58508 in sofapy.f:"      DATA (A(I),I=1778,1929) / -1.5D0,-1.31D0,  1.6D0, 1.27D0, -1.6D0,-1.27D0,  1.6D0, 1.27D0, -1.6D0, 2.03D0, 1.35D0,  1.5D0,-1.39D0, -1.4D0, 1.95D0, -0.2D0,-1.27D0, 1.49D0, 1.19D0,  1.5D0, 1.27D0,  1.4D0, 1.15D0,  1.5D0, 1.87D0, -0.1D0,-1.12D0, -1.5D0, 1.87D0,-1.11D0, -1.5D0,-1.11D0, -1.5D0,    0D0,    0D0, 1.19D0,  1.4D0, 1.27D0, -1.3D0,-1.27D0, -1.3D0,-1.15D0,  1.4D0,-1.23D0,  1.3D0,-1.23D0, -1.3D0, 1.22D0,-1.29D0, 1.07D0, -1.4D0, 1.75D0, -0.2D0,-1.03D0, -1.4D0,-1.07D0,  1.2D0,-1.03D0, 1.15D0, 1.07D0,  1.1D0, 1.51D0,-1.03D0,  1.1D0, 1.03D0, -1.1D0,    0D0,    0D0,-1.03D0, -1.1D0, 0.91D0, -1.2D0,-0.88D0, -1.2D0,-0.88D0,  1.2D0,-0.95D0,  1.1D0,-0.95D0, -1.1D0, 1.43D0,-1.39D0, 0.95D0,   -1D0,-0.95D0,    1D0, -0.8D0,  1.1D0, 0.91D0,   -1D0,-1.35D0, 0.88D0,    1D0,-0.83D0,    1D0,-0.91D0,  0.9D0, 0.91D0,  0.9D0, 0.88D0, -0.9D0,-0.76D0,   -1D0,-0.76D0,    1D0, 0.76D0,    1D0,-0.72D0,    1D0, 0.84D0, -0.9D0, 0.84D0,  0.9D0, 1.23D0,    0D0,    0D0,-0.52D0, -1.1D0,-0.68D0,    1D0, 1.19D0, -0.2D0, 1.19D0, 0.76D0,  0.9D0, 1.15D0, -0.1D0, 1.15D0, -0.1D0, 0.72D0, -0.9D0,-1.15D0,-1.15D0, 0.68D0,  0.9D0,-0.68D0,  0.9D0,-1.11D0,    0D0,    0D0,  0.2D0, 0.79D0,  0.8D0,-1.11D0, -0.1D0,    0D0,    0D0,-0.48D0,   -1D0,-0.76D0, -0.8D0,-0.72D0 /"
	analyzeline: implied-DO list "(a(i),i=1778,1929)" is not supported. Skipping.
Line #58528 in sofapy.f:"      DATA (A(I),I=1930,2081) / -0.8D0,-1.07D0, -0.1D0, 0.64D0,  0.8D0,-0.64D0, -0.8D0, 0.64D0,  0.8D0,  0.4D0,  0.6D0, 0.52D0, -0.5D0, -0.6D0, -0.8D0,-0.71D0,  0.7D0,-0.99D0, 0.99D0, 0.56D0,  0.8D0,-0.56D0,  0.8D0, 0.68D0, -0.7D0, 0.68D0,  0.7D0,-0.95D0,-0.64D0,  0.7D0, 0.64D0,  0.7D0, -0.6D0,  0.7D0, -0.6D0, -0.7D0,-0.91D0, -0.1D0,-0.51D0, 0.76D0,-0.91D0,-0.56D0,  0.7D0, 0.88D0, 0.88D0,-0.63D0, -0.6D0, 0.55D0, -0.6D0, -0.8D0,  0.8D0, -0.8D0,-0.52D0,  0.6D0, 0.52D0,  0.6D0, 0.52D0, -0.6D0,-0.48D0,  0.6D0, 0.48D0,  0.6D0, 0.48D0,  0.6D0,-0.76D0, 0.44D0, -0.6D0, 0.52D0, -0.5D0,-0.52D0,  0.5D0,  0.4D0,  0.6D0, -0.4D0, -0.6D0,  0.4D0, -0.6D0, 0.72D0,-0.72D0,-0.51D0, -0.5D0,-0.48D0,  0.5D0, 0.48D0, -0.5D0,-0.48D0,  0.5D0,-0.48D0,  0.5D0, 0.48D0, -0.5D0,-0.48D0, -0.5D0,-0.68D0,-0.68D0, 0.44D0,  0.5D0,-0.64D0, -0.1D0,-0.64D0, -0.1D0, -0.4D0,  0.5D0,  0.4D0,  0.5D0,  0.4D0,  0.5D0,    0D0,    0D0, -0.4D0, -0.5D0,-0.36D0, -0.5D0, 0.36D0, -0.5D0,  0.6D0, -0.6D0,  0.4D0, -0.4D0,  0.4D0,  0.4D0, -0.4D0,  0.4D0, -0.4D0,  0.4D0,-0.56D0,-0.56D0, 0.36D0, -0.4D0,-0.36D0,  0.4D0, 0.36D0, -0.4D0,-0.36D0, -0.4D0, 0.36D0,  0.4D0, 0.36D0,  0.4D0,-0.52D0, 0.52D0, 0.52D0, 0.32D0,  0.4D0,-0.32D0,  0.4D0,-0.32D0,  0.4D0,-0.32D0,  0.4D0, 0.32D0, -0.4D0 /"
	analyzeline: implied-DO list "(a(i),i=1930,2081)" is not supported. Skipping.
Line #58548 in sofapy.f:"      DATA (A(I),I=2082,2233) /-0.32D0, -0.4D0, 0.32D0, -0.4D0, 0.28D0, -0.4D0,-0.28D0,  0.4D0, 0.28D0, -0.4D0, 0.28D0,  0.4D0, 0.48D0,-0.48D0, 0.48D0, 0.36D0, -0.3D0,-0.36D0, -0.3D0,    0D0,    0D0,  0.2D0,  0.4D0,-0.44D0, 0.44D0,-0.44D0,-0.44D0,-0.44D0,-0.44D0, 0.32D0, -0.3D0, 0.32D0,  0.3D0, 0.24D0,  0.3D0,-0.12D0, -0.1D0,-0.28D0,  0.3D0, 0.28D0,  0.3D0, 0.28D0,  0.3D0, 0.28D0, -0.3D0, 0.28D0, -0.3D0, 0.28D0, -0.3D0, 0.28D0,  0.3D0,-0.28D0,  0.3D0,  0.4D0,  0.4D0,-0.24D0,  0.3D0, 0.24D0, -0.3D0, 0.24D0, -0.3D0,-0.24D0, -0.3D0, 0.24D0,  0.3D0, 0.24D0, -0.3D0,-0.24D0,  0.3D0, 0.24D0, -0.3D0,-0.24D0, -0.3D0, 0.24D0, -0.3D0, 0.24D0,  0.3D0,-0.24D0,  0.3D0,-0.24D0,  0.3D0,  0.2D0, -0.3D0,  0.2D0, -0.3D0,  0.2D0, -0.3D0,  0.2D0,  0.3D0,  0.2D0, -0.3D0,  0.2D0, -0.3D0,  0.2D0,  0.3D0,  0.2D0,  0.3D0, -0.2D0, -0.3D0,  0.2D0, -0.3D0,  0.2D0, -0.3D0,-0.36D0,-0.36D0,-0.36D0,-0.04D0,  0.3D0, 0.12D0, -0.1D0,-0.32D0,-0.24D0,  0.2D0, 0.24D0,  0.2D0,  0.2D0, -0.2D0, -0.2D0, -0.2D0, -0.2D0, -0.2D0,  0.2D0,  0.2D0,  0.2D0, -0.2D0,  0.2D0,  0.2D0,  0.2D0,  0.2D0, -0.2D0, -0.2D0,    0D0,    0D0, -0.2D0, -0.2D0, -0.2D0,  0.2D0, -0.2D0,  0.2D0,  0.2D0, -0.2D0, -0.2D0, -0.2D0,  0.2D0,  0.2D0,  0.2D0,  0.2D0,  0.2D0, -0.2D0,  0.2D0, -0.2D0, 0.28D0 /"
	analyzeline: implied-DO list "(a(i),i=2082,2233)" is not supported. Skipping.
Line #58568 in sofapy.f:"      DATA (A(I),I=2234,2385) / 0.28D0, 0.28D0, 0.28D0, 0.28D0, 0.28D0,-0.28D0, 0.28D0, 0.12D0,    0D0, 0.24D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0, 0.16D0,  0.2D0,-0.16D0,  0.2D0, 0.16D0,  0.2D0,-0.16D0,  0.2D0,-0.16D0,  0.2D0,-0.16D0,  0.2D0, 0.16D0, -0.2D0, 0.16D0,  0.2D0, 0.16D0, -0.2D0,-0.16D0,  0.2D0,-0.16D0, -0.2D0,-0.16D0,  0.2D0, 0.16D0,  0.2D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0, 0.16D0,  0.2D0, 0.16D0,  0.2D0, 0.16D0,  0.2D0,-0.16D0, -0.2D0, 0.16D0,  0.2D0,-0.16D0,  0.2D0, 0.16D0,  0.2D0,-0.16D0, -0.2D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0,-0.16D0, -0.2D0, 0.24D0,-0.24D0,-0.24D0, 0.24D0, 0.24D0, 0.12D0,  0.2D0, 0.12D0,  0.2D0,-0.12D0, -0.2D0, 0.12D0, -0.2D0, 0.12D0, -0.2D0,-0.12D0,  0.2D0,-0.12D0,  0.2D0,-0.12D0, -0.2D0, 0.12D0,  0.2D0, 0.12D0,  0.2D0, 0.12D0, -0.2D0,-0.12D0,  0.2D0, 0.12D0, -0.2D0,-0.12D0,  0.2D0, 0.12D0,  0.2D0,    0D0,    0D0,-0.12D0,  0.2D0,-0.12D0,  0.2D0, 0.12D0, -0.2D0,-0.12D0,  0.2D0, 0.12D0,  0.2D0,    0D0,-0.21D0, -0.2D0,    0D0,    0D0,  0.2D0, -0.2D0, -0.2D0, -0.2D0,  0.2D0,-0.16D0, -0.1D0,    0D0, 0.17D0, 0.16D0, 0.16D0, 0.16D0, 0.16D0,-0.16D0, 0.16D0, 0.16D0,-0.16D0, 0.16D0,-0.16D0, 0.16D0, 0.12D0,  0.1D0, 0.12D0, -0.1D0,-0.12D0,  0.1D0,-0.12D0,  0.1D0, 0.12D0, -0.1D0,-0.12D0, 0.12D0 /"
	analyzeline: implied-DO list "(a(i),i=2234,2385)" is not supported. Skipping.
Line #58588 in sofapy.f:"      DATA (A(I),I=2386,2537) /-0.12D0, 0.12D0,-0.12D0, 0.12D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0, 0.12D0, 0.12D0, 0.12D0, 0.12D0,-0.12D0,-0.12D0, 0.12D0, 0.12D0, 0.12D0,-0.12D0, 0.12D0,-0.12D0,-0.12D0,-0.12D0, 0.12D0,-0.12D0,-0.12D0, 0.12D0,    0D0, 0.11D0, 0.11D0,-122.67D0,164.7D0,203.78D0,273.5D0,3.58D0,2.74D0,6.18D0,-4.56D0,    0D0,-0.04D0,    0D0,-0.07D0,57.44D0,-77.1D0,95.82D0,128.6D0,-1.77D0,-1.28D0, 2.85D0,-2.14D0,82.14D0, 89.5D0,    0D0,    0D0,    2D0,-1.84D0,-0.04D0,47.73D0,-64.1D0,23.79D0, 31.9D0,-1.45D0,-1.07D0, 0.69D0,-0.53D0,-46.38D0,50.5D0,    0D0,    0D0, 1.13D0, 1.04D0, 0.02D0,-18.38D0,   0D0, 63.8D0,    0D0,    0D0, 0.41D0,    0D0,-1.43D0,59.07D0,    0D0,    0D0,    0D0,    0D0,-1.32D0,57.28D0,    0D0,    0D0,    0D0,    0D0,-1.28D0,-48.65D0,   0D0,-1.15D0,    0D0,    0D0, 1.09D0,    0D0, 0.03D0,-18.3D0, 24.6D0,-17.3D0,-23.2D0, 0.56D0, 0.41D0,-0.51D0, 0.39D0,-16.91D0,26.9D0, 8.43D0, 13.3D0,  0.6D0, 0.38D0, 0.31D0,-0.19D0, 1.23D0, -1.7D0,-19.13D0,-25.7D0,-0.03D0,-0.03D0,-0.58D0,0.43D0,-0.72D0,  0.9D0,-17.34D0,-23.3D0,0.03D0, 0.02D0,-0.52D0, 0.39D0,-19.49D0,-21.3D0,    0D0,    0D0,-0.48D0, 0.44D0, 0.01D0,20.57D0,-20.1D0, 0.64D0,  0.7D0,-0.45D0,-0.46D0,    0D0,-0.01D0, 4.89D0,  5.9D0,-16.55D0 /"
	analyzeline: implied-DO list "(a(i),i=2386,2537)" is not supported. Skipping.
Line #58608 in sofapy.f:"      DATA (A(I),I=2538,2689) / 19.9D0, 0.14D0,-0.11D0, 0.44D0, 0.37D0,18.22D0, 19.8D0,    0D0,    0D0, 0.44D0,-0.41D0,-0.01D0, 4.89D0, -5.3D0,-16.51D0, -18D0,-0.11D0,-0.11D0,-0.41D0, 0.37D0,-17.86D0,   0D0, 17.1D0,    0D0,    0D0,  0.4D0,    0D0,-0.38D0, 0.32D0,    0D0,24.42D0,    0D0,    0D0,-0.01D0,    0D0,-0.55D0,-23.79D0,   0D0,    0D0,    0D0,    0D0, 0.53D0,14.72D0,  -16D0,-0.32D0,    0D0,-0.36D0,-0.33D0,-0.01D0, 0.01D0, 3.34D0, -4.5D0,11.86D0, 15.9D0,-0.11D0,-0.07D0, 0.35D0,-0.27D0,-3.26D0,  4.4D0,11.62D0, 15.6D0, 0.09D0, 0.07D0, 0.35D0,-0.26D0,-19.53D0,   0D0, 5.09D0,    0D0,    0D0, 0.44D0,    0D0,-0.11D0,-13.48D0,14.7D0,    0D0,    0D0, 0.33D0,  0.3D0, 0.01D0,10.86D0,-14.6D0, 3.18D0,  4.3D0,-0.33D0,-0.24D0, 0.09D0,-0.07D0,-11.3D0,-15.1D0,    0D0,    0D0,-0.34D0, 0.25D0, 0.01D0, 2.03D0, -2.7D0,10.82D0, 14.5D0,-0.07D0,-0.05D0, 0.32D0,-0.24D0,17.46D0,    0D0,    0D0,    0D0,    0D0,-0.39D0,16.43D0,    0D0, 0.52D0,    0D0,    0D0,-0.37D0,    0D0,-0.01D0, 9.35D0,    0D0,13.29D0,    0D0,    0D0,-0.21D0,    0D0, -0.3D0,-10.42D0,11.4D0,    0D0,    0D0, 0.25D0, 0.23D0, 0.01D0, 0.44D0,  0.5D0,-10.38D0, 11.3D0, 0.02D0,-0.01D0, 0.25D0, 0.23D0,-14.64D0,   0D0,    0D0,    0D0,    0D0, 0.33D0, 0.56D0,  0.8D0,-8.67D0, 11.7D0, 0.02D0 /"
	analyzeline: implied-DO list "(a(i),i=2538,2689)" is not supported. Skipping.
Line #58628 in sofapy.f:"      DATA (A(I),I=2690,2841) /-0.01D0, 0.26D0, 0.19D0,13.88D0,    0D0,-2.47D0,    0D0,    0D0,-0.31D0,    0D0, 0.06D0,-1.99D0,  2.7D0, 7.72D0, 10.3D0, 0.06D0, 0.04D0, 0.23D0,-0.17D0, -0.2D0,    0D0,13.05D0,    0D0,    0D0,    0D0,    0D0,-0.29D0, 6.92D0, -9.3D0, 3.34D0,  4.5D0,-0.21D0,-0.15D0,  0.1D0,-0.07D0, -6.6D0,    0D0, 10.7D0,    0D0,    0D0, 0.15D0,    0D0,-0.24D0,-8.04D0, -8.7D0,    0D0,    0D0,-0.19D0, 0.18D0,-10.58D0,   0D0, -3.1D0,    0D0,    0D0, 0.24D0,    0D0, 0.07D0,-7.32D0,    8D0,-0.12D0, -0.1D0, 0.18D0, 0.16D0, 1.63D0,  1.7D0, 6.96D0, -7.6D0, 0.03D0,-0.04D0,-0.17D0,-0.16D0,-3.62D0,    0D0, 9.86D0,    0D0,    0D0, 0.08D0,    0D0,-0.22D0,  0.2D0, -0.2D0,-6.88D0, -7.5D0,    0D0,    0D0,-0.17D0, 0.15D0,-8.99D0,    0D0, 4.02D0,    0D0,    0D0,  0.2D0,    0D0,-0.09D0,-1.07D0,  1.4D0,-5.69D0, -7.7D0, 0.03D0, 0.02D0,-0.17D0, 0.13D0, 6.48D0, -7.2D0,-0.48D0, -0.5D0,-0.16D0,-0.14D0,-0.01D0, 0.01D0, 5.57D0, -7.5D0, 1.07D0,  1.4D0,-0.17D0,-0.12D0, 0.03D0,-0.02D0, 8.71D0,    0D0, 3.54D0,    0D0,    0D0,-0.19D0,    0D0,-0.08D0,  0.4D0,    0D0, 9.27D0,    0D0,    0D0,-0.01D0,    0D0,-0.21D0,-6.13D0,  6.7D0,-1.19D0, -1.3D0, 0.15D0, 0.14D0,-0.03D0, 0.03D0, 5.21D0, -5.7D0,-2.51D0, -2.6D0,-0.13D0,-0.12D0,-0.06D0, 0.06D0, 5.69D0 /"
	analyzeline: implied-DO list "(a(i),i=2690,2841)" is not supported. Skipping.
Line #58648 in sofapy.f:"      DATA (A(I),I=2842,2993) / -6.2D0,-0.12D0, -0.1D0,-0.14D0,-0.13D0,-0.01D0, 2.03D0, -2.7D0, 4.53D0,  6.1D0,-0.06D0,-0.05D0, 0.14D0, -0.1D0, 5.01D0,  5.5D0,-2.51D0,  2.7D0, 0.12D0,-0.11D0, 0.06D0, 0.06D0,-1.91D0,  2.6D0,-4.38D0, -5.9D0, 0.06D0, 0.04D0,-0.13D0,  0.1D0, 4.65D0, -6.3D0,    0D0,    0D0,-0.14D0, -0.1D0,-5.29D0,  5.7D0,    0D0,    0D0, 0.13D0, 0.12D0,-2.23D0,   -4D0,-4.65D0,  4.2D0,-0.09D0, 0.05D0,  0.1D0,  0.1D0,-4.53D0,  6.1D0,    0D0,    0D0, 0.14D0,  0.1D0, 2.47D0,  2.7D0,-4.46D0,  4.9D0, 0.06D0,-0.06D0, 0.11D0,  0.1D0,-5.05D0,  5.5D0, 0.84D0,  0.9D0, 0.12D0, 0.11D0, 0.02D0,-0.02D0, 4.97D0, -5.4D0,-1.71D0,    0D0,-0.12D0,-0.11D0,    0D0, 0.04D0,-0.99D0, -1.3D0, 4.22D0, -5.7D0,-0.03D0, 0.02D0,-0.13D0,-0.09D0, 0.99D0,  1.4D0, 4.22D0, -5.6D0, 0.03D0,-0.02D0,-0.13D0,-0.09D0,-4.69D0, -5.2D0,    0D0,    0D0,-0.12D0,  0.1D0,-3.42D0,    0D0, 6.09D0,    0D0,    0D0, 0.08D0,    0D0,-0.14D0,-4.65D0, -5.1D0,    0D0,    0D0,-0.11D0,  0.1D0,    0D0,    0D0,-4.53D0,   -5D0,    0D0,    0D0,-0.11D0,  0.1D0,-2.43D0, -2.7D0,-3.82D0,  4.2D0,-0.06D0, 0.05D0,  0.1D0, 0.09D0,    0D0,    0D0,-4.53D0,  4.9D0,    0D0,    0D0, 0.11D0,  0.1D0,-4.49D0, -4.9D0,    0D0,    0D0,-0.11D0,  0.1D0, 2.67D0, -2.9D0,-3.62D0, -3.9D0,-0.06D0,-0.06D0 /"
	analyzeline: implied-DO list "(a(i),i=2842,2993)" is not supported. Skipping.
Line #58668 in sofapy.f:"      DATA (A(I),I=2994,3145) /-0.09D0, 0.08D0, 3.94D0, -5.3D0,    0D0,    0D0,-0.12D0,-3.38D0,  3.7D0,-2.78D0, -3.1D0, 0.08D0, 0.08D0,-0.07D0, 0.06D0, 3.18D0, -3.5D0,-2.82D0, -3.1D0,-0.08D0,-0.07D0,-0.07D0, 0.06D0,-5.77D0,    0D0, 1.87D0,    0D0,    0D0, 0.13D0,    0D0,-0.04D0, 3.54D0, -4.8D0,-0.64D0, -0.9D0,-0.11D0,    0D0,-0.02D0, -3.5D0, -4.7D0, 0.68D0, -0.9D0,-0.11D0,    0D0,-0.02D0, 5.49D0,    0D0,    0D0,    0D0,    0D0,-0.12D0, 1.83D0, -2.5D0, 2.63D0,  3.5D0,-0.06D0,    0D0, 0.08D0, 3.02D0, -4.1D0, 0.68D0,  0.9D0,-0.09D0,    0D0, 0.02D0,    0D0,    0D0, 5.21D0,    0D0,    0D0,    0D0,    0D0,-0.12D0,-3.54D0,  3.8D0,  2.7D0,  3.6D0,-1.35D0,  1.8D0, 0.08D0,    0D0, 0.04D0, -2.9D0,  3.9D0, 0.68D0,  0.9D0, 0.09D0,    0D0, 0.02D0,  0.8D0, -1.1D0,-2.78D0, -3.7D0,-0.02D0,    0D0,-0.08D0,  4.1D0,    0D0,-2.39D0,    0D0,    0D0,-0.09D0,    0D0, 0.05D0,-1.59D0,  2.1D0, 2.27D0,    3D0, 0.05D0,    0D0, 0.07D0,-2.63D0,  3.5D0,-0.48D0, -0.6D0,-2.94D0, -3.2D0,-2.94D0,  3.2D0, 2.27D0,   -3D0,-1.11D0, -1.5D0,-0.07D0,    0D0,-0.03D0,-0.56D0, -0.8D0,-2.35D0,  3.1D0,    0D0, -0.6D0,-3.42D0,  1.9D0,-0.12D0, -0.1D0, 2.63D0, -2.9D0, 2.51D0,  2.8D0,-0.64D0,  0.7D0,-0.48D0, -0.6D0, 2.19D0, -2.9D0, 0.24D0, -0.3D0, 2.15D0,  2.9D0, 2.15D0, -2.9D0 /"
	analyzeline: implied-DO list "(a(i),i=2994,3145)" is not supported. Skipping.
Line #58688 in sofapy.f:"      DATA (A(I),I=3146,3297) / 0.52D0,  0.7D0, 2.07D0, -2.8D0, -3.1D0,    0D0, 1.79D0,    0D0,    0D0, 0.07D0,    0D0,-0.04D0, 0.88D0,    0D0,-3.46D0, 2.11D0,  2.8D0,-0.36D0,  0.5D0, 3.54D0, -0.2D0, -3.5D0,-1.39D0,  1.5D0,-1.91D0, -2.1D0,-1.47D0,    2D0, 1.39D0,  1.9D0, 2.07D0, -2.3D0, 0.91D0,    1D0, 1.99D0, -2.7D0,  3.3D0,    0D0,  0.6D0,-0.44D0, -0.7D0,-1.95D0,  2.6D0, 2.15D0, -2.4D0, -0.6D0, -0.7D0,  3.3D0, 0.84D0,    0D0, -3.1D0, -3.1D0,    0D0,-0.72D0,-0.32D0,  0.4D0,-1.87D0, -2.5D0, 1.87D0, -2.5D0, 0.32D0,  0.4D0,-0.24D0,  0.3D0,-1.87D0, -2.5D0,-0.24D0, -0.3D0, 1.87D0, -2.5D0, -2.7D0,    0D0, 1.55D0, 2.03D0,  2.2D0,-2.98D0,-1.99D0, -2.2D0, 0.12D0, -0.1D0, -0.4D0,  0.5D0, 1.59D0,  2.1D0,    0D0,    0D0,-1.79D0,    2D0,-1.03D0,  1.4D0,-1.15D0, -1.6D0, 0.32D0,  0.5D0, 1.39D0, -1.9D0, 2.35D0,-1.27D0,  1.7D0,  0.6D0,  0.8D0,-0.32D0, -0.4D0, 1.35D0, -1.8D0, 0.44D0,    0D0, 2.23D0,-0.84D0,  0.9D0,-1.27D0, -1.4D0,-1.47D0,  1.6D0,-0.28D0, -0.3D0,-0.28D0,  0.4D0,-1.27D0, -1.7D0, 0.28D0, -0.4D0,-1.43D0, -1.5D0,    0D0,    0D0,-1.27D0, -1.7D0, 2.11D0,-0.32D0, -0.4D0,-1.23D0,  1.6D0, 1.19D0, -1.3D0,-0.72D0, -0.8D0, 0.72D0, -0.8D0,-1.15D0, -1.3D0,-1.35D0, -1.5D0,-1.19D0, -1.6D0,-0.12D0,  0.2D0, 1.79D0,    0D0,-0.88D0,-0.28D0,  0.4D0 /"
	analyzeline: implied-DO list "(a(i),i=3146,3297)" is not supported. Skipping.
Line #58708 in sofapy.f:"      DATA (A(I),I=3298,3449) / 1.11D0,  1.5D0,-1.83D0,    0D0, 0.56D0,-0.12D0,  0.1D0,-1.27D0, -1.4D0,    0D0,    0D0, 1.15D0,  1.5D0,-0.12D0,  0.2D0, 1.11D0,  1.5D0, 0.36D0, -0.5D0,-1.07D0, -1.4D0,-1.11D0,  1.5D0, 1.67D0,    0D0,  0.8D0,-1.11D0,    0D0, 1.43D0, 1.23D0, -1.3D0,-0.24D0,-1.19D0, -1.3D0,-0.24D0,  0.2D0,-0.44D0, -0.9D0,-0.95D0,  1.1D0, 1.07D0, -1.4D0, 1.15D0, -1.3D0, 1.03D0, -1.1D0,-0.56D0, -0.6D0,-0.68D0,  0.9D0,-0.76D0,   -1D0,-0.24D0, -0.3D0, 0.95D0, -1.3D0, 0.56D0,  0.7D0, 0.84D0, -1.1D0,-0.56D0,    0D0,-1.55D0, 0.91D0, -1.3D0, 0.28D0,  0.3D0, 0.16D0, -0.2D0, 0.95D0,  1.3D0,  0.4D0, -0.5D0,-0.88D0, -1.2D0, 0.95D0, -1.1D0,-0.48D0, -0.5D0,    0D0,    0D0,-1.07D0,  1.2D0, 0.44D0, -0.5D0, 0.95D0,  1.1D0,    0D0,    0D0, 0.92D0, -1.3D0, 0.95D0,    1D0,-0.52D0,  0.6D0, 1.59D0, 0.24D0, -0.4D0, 0.91D0,  1.2D0, 0.84D0, -1.1D0,-0.44D0, -0.6D0, 0.84D0,  1.1D0,-0.44D0,  0.6D0,-0.44D0,  0.6D0,-0.84D0, -1.1D0, -0.8D0,    0D0, 1.35D0, 0.76D0,  0.2D0,-0.91D0,   -1D0,  0.2D0, -0.3D0,-0.91D0, -1.2D0,-0.95D0,    1D0,-0.48D0, -0.5D0, 0.88D0,    1D0, 0.48D0, -0.5D0,-0.95D0, -1.1D0,  0.2D0, -0.2D0,-0.99D0,  1.1D0,-0.84D0,  1.1D0,-0.24D0, -0.3D0,  0.2D0, -0.3D0, 0.84D0,  1.1D0,-1.39D0,    0D0,-0.28D0,-0.16D0,  0.2D0, 0.84D0,  1.1D0 /"
	analyzeline: implied-DO list "(a(i),i=3298,3449)" is not supported. Skipping.
Line #58728 in sofapy.f:"      DATA (A(I),I=3450,3601) /    0D0,    0D0, 1.39D0,    0D0,    0D0,-0.95D0,    1D0, 1.35D0,-0.99D0,    0D0, 0.88D0,-0.52D0,    0D0,-1.19D0,  0.2D0,  0.2D0, 0.76D0,   -1D0,    0D0,    0D0, 0.76D0,    1D0,    0D0,    0D0, 0.76D0,    1D0,-0.76D0,    1D0,    0D0,    0D0, 1.23D0, 0.76D0,  0.8D0,-0.32D0,  0.4D0,-0.72D0,  0.8D0, -0.4D0, -0.4D0,    0D0,    0D0, -0.8D0, -0.9D0,-0.68D0,  0.9D0,-0.16D0, -0.2D0,-0.16D0, -0.2D0, 0.68D0, -0.9D0,-0.36D0,  0.5D0,-0.56D0, -0.8D0, 0.72D0, -0.9D0, 0.44D0, -0.6D0,-0.48D0, -0.7D0,-0.16D0,    0D0,-1.11D0, 0.32D0,    0D0,-1.07D0,  0.6D0, -0.8D0,-0.28D0, -0.4D0,-0.64D0,    0D0, 0.91D0, 1.11D0, 0.64D0, -0.9D0, 0.76D0, -0.8D0,    0D0,    0D0,-0.76D0, -0.8D0, 1.03D0,    0D0,-0.36D0,-0.64D0, -0.7D0, 0.36D0, -0.4D0, 1.07D0, 0.36D0, -0.5D0,-0.52D0, -0.7D0,  0.6D0,    0D0, 0.88D0, 0.95D0,    0D0, 0.48D0, 0.16D0, -0.2D0,  0.6D0,  0.8D0, 0.16D0, -0.2D0, -0.6D0, -0.8D0,    0D0,   -1D0, 0.12D0,  0.2D0, 0.16D0, -0.2D0, 0.68D0,  0.7D0, 0.59D0, -0.8D0,-0.99D0,-0.56D0, -0.6D0, 0.36D0, -0.4D0,-0.68D0, -0.7D0,-0.68D0, -0.7D0,-0.36D0, -0.5D0,-0.44D0,  0.6D0, 0.64D0,  0.7D0,-0.12D0,  0.1D0,-0.52D0,  0.6D0, 0.36D0,  0.4D0,    0D0,    0D0, 0.95D0,-0.84D0,    0D0, 0.44D0, 0.56D0,  0.6D0, 0.32D0, -0.3D0,    0D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=3450,3601)" is not supported. Skipping.
Line #58748 in sofapy.f:"      DATA (A(I),I=3602,3753) /  0.6D0,  0.7D0,    0D0,    0D0,  0.6D0,  0.7D0,-0.12D0, -0.2D0, 0.52D0, -0.7D0,    0D0,    0D0, 0.56D0,  0.7D0,-0.12D0,  0.1D0,-0.52D0, -0.7D0,    0D0,    0D0, 0.88D0,-0.76D0,    0D0,-0.44D0,    0D0,    0D0,-0.52D0, -0.7D0, 0.52D0, -0.7D0, 0.36D0, -0.4D0,-0.44D0, -0.5D0,    0D0,    0D0,  0.6D0,  0.6D0, 0.84D0,    0D0, 0.12D0,-0.24D0,    0D0,  0.8D0,-0.56D0,  0.6D0,-0.32D0, -0.3D0, 0.48D0, -0.5D0, 0.28D0, -0.3D0,-0.48D0, -0.5D0, 0.12D0,  0.2D0, 0.48D0, -0.6D0, 0.48D0,  0.6D0,-0.12D0,  0.2D0, 0.24D0,    0D0, 0.76D0,-0.52D0, -0.6D0,-0.52D0,  0.6D0, 0.48D0, -0.5D0,-0.24D0, -0.3D0, 0.12D0, -0.1D0, 0.48D0,  0.6D0, 0.52D0, -0.2D0, 0.36D0,  0.4D0,-0.44D0,  0.5D0,-0.24D0, -0.3D0,-0.48D0, -0.6D0,-0.44D0, -0.6D0,-0.12D0,  0.1D0, 0.76D0, 0.76D0,  0.2D0, -0.2D0, 0.48D0,  0.5D0,  0.4D0, -0.5D0,-0.24D0, -0.3D0, 0.44D0, -0.6D0, 0.44D0, -0.6D0, 0.36D0,    0D0,-0.64D0, 0.72D0,    0D0,-0.12D0,    0D0, -0.1D0, -0.4D0, -0.6D0, -0.2D0, -0.2D0,-0.44D0,  0.5D0,-0.44D0,  0.5D0,  0.2D0,  0.2D0,-0.44D0, -0.5D0,  0.2D0, -0.2D0, -0.2D0,  0.2D0,-0.44D0, -0.5D0, 0.64D0,    0D0, 0.32D0,-0.36D0,  0.5D0, -0.2D0, -0.3D0, 0.12D0, -0.1D0, 0.48D0,  0.5D0,-0.12D0,  0.3D0,-0.36D0, -0.5D0,    0D0,    0D0, 0.48D0,  0.5D0,-0.48D0,  0.5D0 /"
	analyzeline: implied-DO list "(a(i),i=3602,3753)" is not supported. Skipping.
Line #58768 in sofapy.f:"      DATA (A(I),I=3754,3905) / 0.68D0,    0D0,-0.12D0, 0.56D0, -0.4D0, 0.44D0, -0.5D0,-0.12D0, -0.1D0, 0.24D0,  0.3D0, -0.4D0,  0.4D0, 0.64D0,    0D0,-0.24D0, 0.64D0,    0D0, -0.2D0,    0D0,    0D0, 0.44D0, -0.5D0, 0.44D0,  0.5D0,-0.12D0,  0.2D0,-0.36D0, -0.5D0, 0.12D0,    0D0, 0.64D0, -0.4D0,  0.5D0,    0D0,  0.1D0,    0D0,    0D0, -0.4D0,  0.5D0,    0D0,    0D0, -0.4D0, -0.5D0, 0.56D0,    0D0, 0.28D0,    0D0,  0.1D0, 0.36D0,  0.5D0,    0D0, -0.1D0, 0.36D0, -0.5D0, 0.36D0,  0.5D0,    0D0, -0.1D0, 0.24D0, -0.2D0,-0.36D0, -0.4D0, 0.16D0,  0.2D0,  0.4D0, -0.4D0,    0D0,    0D0,-0.36D0, -0.5D0,-0.36D0, -0.5D0,-0.32D0, -0.5D0,-0.12D0,  0.1D0,  0.2D0,  0.2D0,-0.36D0,  0.4D0, -0.6D0,  0.6D0, 0.28D0,    0D0, 0.52D0, 0.12D0, -0.1D0,  0.4D0,  0.4D0,    0D0, -0.5D0,  0.2D0, -0.2D0,-0.32D0,  0.4D0, 0.16D0,  0.2D0,-0.16D0,  0.2D0, 0.32D0,  0.4D0, 0.56D0,    0D0,-0.12D0, 0.32D0, -0.4D0,-0.16D0, -0.2D0,    0D0,    0D0,  0.4D0,  0.4D0, -0.4D0, -0.4D0, -0.4D0,  0.4D0,-0.36D0,  0.4D0, 0.12D0,  0.1D0,    0D0,  0.1D0, 0.36D0,  0.4D0,    0D0, -0.1D0, 0.36D0,  0.4D0,-0.36D0,  0.4D0,    0D0,  0.1D0, 0.32D0,    0D0, 0.44D0, 0.12D0,  0.2D0, 0.28D0, -0.4D0,    0D0,    0D0, 0.36D0,  0.4D0, 0.32D0, -0.4D0,-0.16D0, 0.12D0,  0.1D0, 0.32D0, -0.4D0,  0.2D0 /"
	analyzeline: implied-DO list "(a(i),i=3754,3905)" is not supported. Skipping.
Line #58788 in sofapy.f:"      DATA (A(I),I=3906,4057) /  0.3D0,-0.24D0,  0.3D0,    0D0,  0.1D0, 0.32D0,  0.4D0,    0D0, -0.1D0,-0.32D0, -0.4D0,-0.32D0,  0.4D0,    0D0,  0.1D0,-0.52D0,-0.52D0, 0.52D0, 0.32D0, -0.4D0,    0D0,    0D0, 0.32D0,  0.4D0, 0.32D0, -0.4D0,    0D0,    0D0,-0.32D0, -0.4D0,-0.32D0,  0.4D0, 0.32D0,  0.4D0,    0D0,    0D0, 0.32D0,  0.4D0,    0D0,    0D0,-0.32D0, -0.4D0,    0D0,    0D0, 0.32D0,  0.4D0, 0.16D0,  0.2D0, 0.32D0, -0.3D0,-0.16D0,    0D0,-0.48D0, -0.2D0,  0.2D0,-0.28D0, -0.3D0, 0.28D0, -0.4D0,    0D0,    0D0, 0.28D0, -0.4D0,    0D0,    0D0, 0.28D0, -0.4D0,    0D0,    0D0,-0.28D0, -0.4D0, 0.28D0,  0.4D0,-0.28D0, -0.4D0,-0.48D0, -0.2D0,  0.2D0, 0.24D0,  0.3D0, 0.44D0,    0D0, 0.16D0, 0.24D0,  0.3D0, 0.16D0, -0.2D0, 0.24D0,  0.3D0,-0.12D0,  0.2D0,  0.2D0,  0.3D0,-0.16D0,  0.2D0,    0D0,    0D0, 0.44D0,-0.32D0,  0.3D0, 0.24D0,    0D0,-0.36D0, 0.36D0,    0D0, 0.24D0, 0.12D0, -0.2D0,  0.2D0,  0.3D0,-0.12D0,    0D0,-0.28D0,  0.3D0,-0.24D0,  0.3D0, 0.12D0,  0.1D0,-0.28D0, -0.3D0,-0.28D0,  0.3D0,    0D0,    0D0,-0.28D0, -0.3D0,    0D0,    0D0,-0.28D0, -0.3D0,    0D0,    0D0, 0.28D0,  0.3D0,    0D0,    0D0,-0.28D0, -0.3D0,-0.28D0,  0.3D0,    0D0,    0D0,-0.28D0, -0.3D0,    0D0,    0D0, 0.28D0,  0.3D0,    0D0,    0D0,-0.28D0,  0.3D0 /"
	analyzeline: implied-DO list "(a(i),i=3906,4057)" is not supported. Skipping.
Line #58808 in sofapy.f:"      DATA (A(I),I=4058,4209) / 0.28D0, -0.3D0,-0.28D0,  0.3D0,  0.4D0,  0.4D0,-0.24D0,  0.3D0,    0D0, -0.1D0, 0.16D0,    0D0, 0.36D0, -0.2D0,  0.3D0,-0.12D0, -0.1D0,-0.24D0, -0.3D0,    0D0,    0D0,-0.24D0,  0.3D0,-0.24D0,  0.3D0,    0D0,    0D0,-0.24D0,  0.3D0,-0.24D0,  0.3D0, 0.24D0, -0.3D0,    0D0,    0D0, 0.24D0, -0.3D0,    0D0,    0D0, 0.24D0,  0.3D0, 0.24D0, -0.3D0, 0.24D0,  0.3D0,-0.24D0,  0.3D0,-0.24D0,  0.3D0, -0.2D0,  0.2D0,-0.16D0, -0.2D0,    0D0,    0D0,-0.32D0,  0.2D0,    0D0,  0.1D0,  0.2D0, -0.3D0,  0.2D0, -0.2D0, 0.12D0,  0.2D0,-0.16D0,  0.2D0, 0.16D0,  0.2D0,  0.2D0,  0.3D0,  0.2D0,  0.3D0,    0D0,    0D0, -0.2D0,  0.3D0,    0D0,    0D0,  0.2D0,  0.3D0, -0.2D0, -0.3D0, -0.2D0, -0.3D0,  0.2D0, -0.3D0,    0D0,    0D0,  0.2D0,  0.3D0,    0D0,    0D0,  0.2D0,  0.3D0,    0D0,    0D0,  0.2D0,  0.3D0,    0D0,    0D0,  0.2D0,  0.3D0,    0D0,    0D0,  0.2D0, -0.3D0,    0D0,    0D0, -0.2D0, -0.3D0,    0D0,    0D0, -0.2D0,  0.3D0,    0D0,    0D0, -0.2D0,  0.3D0,    0D0,    0D0, 0.36D0,    0D0,    0D0, 0.36D0, 0.12D0,  0.1D0,-0.24D0,  0.2D0, 0.12D0, -0.2D0,-0.16D0, -0.2D0,-0.13D0,  0.1D0, 0.22D0, 0.21D0,  0.2D0,    0D0,-0.28D0, 0.32D0,    0D0,-0.12D0, -0.2D0, -0.2D0, 0.12D0, -0.1D0, 0.12D0,  0.1D0, -0.2D0,  0.2D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=4058,4209)" is not supported. Skipping.
Line #58828 in sofapy.f:"      DATA (A(I),I=4210,4361) /    0D0,-0.32D0, 0.32D0,    0D0,    0D0, 0.32D0, 0.32D0,    0D0,    0D0,-0.24D0, -0.2D0, 0.24D0,  0.2D0,  0.2D0,    0D0,-0.24D0,    0D0,    0D0,-0.24D0, -0.2D0,    0D0,    0D0, 0.24D0,  0.2D0,-0.24D0, -0.2D0,    0D0,    0D0,-0.24D0,  0.2D0, 0.16D0, -0.2D0, 0.12D0,  0.1D0,  0.2D0,  0.2D0,    0D0, -0.1D0,-0.12D0,  0.1D0,-0.16D0, -0.2D0,-0.12D0, -0.1D0,-0.16D0,  0.2D0,  0.2D0,  0.2D0,    0D0,    0D0, -0.2D0,  0.2D0, -0.2D0,  0.2D0, -0.2D0,  0.2D0, -0.2D0,  0.2D0,  0.2D0, -0.2D0, -0.2D0, -0.2D0,    0D0,    0D0, -0.2D0,  0.2D0,  0.2D0,    0D0, -0.2D0,    0D0,    0D0, -0.2D0,  0.2D0, -0.2D0,  0.2D0, -0.2D0, -0.2D0, -0.2D0, -0.2D0,    0D0,    0D0,  0.2D0,  0.2D0,  0.2D0,  0.2D0, 0.12D0, -0.2D0,-0.12D0, -0.1D0, 0.28D0,-0.28D0, 0.16D0, -0.2D0,    0D0, -0.1D0,    0D0,  0.1D0,-0.16D0,  0.2D0,    0D0, -0.1D0,-0.16D0, -0.2D0,    0D0, -0.1D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0,    0D0,    0D0, 0.16D0,  0.2D0,-0.16D0,  0.2D0,    0D0,    0D0, 0.16D0,  0.2D0, 0.16D0, -0.2D0, 0.16D0, -0.2D0,-0.16D0,  0.2D0, 0.16D0, -0.2D0,    0D0,    0D0, 0.16D0,  0.2D0,    0D0,    0D0, 0.16D0,  0.2D0,    0D0,    0D0,-0.16D0, -0.2D0, 0.16D0, -0.2D0,-0.16D0, -0.2D0,    0D0,    0D0,-0.16D0, -0.2D0,    0D0,    0D0,-0.16D0,  0.2D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=4210,4361)" is not supported. Skipping.
Line #58848 in sofapy.f:"      DATA (A(I),I=4362,4513) /    0D0, 0.16D0, -0.2D0, 0.16D0,  0.2D0, 0.16D0,  0.2D0,    0D0,    0D0,-0.16D0, -0.2D0,    0D0,    0D0,-0.16D0, -0.2D0,    0D0,    0D0, 0.16D0,  0.2D0, 0.16D0,  0.2D0,    0D0,    0D0, 0.16D0,  0.2D0, 0.16D0, -0.2D0, 0.16D0,  0.2D0,    0D0,    0D0,-0.16D0,  0.2D0,    0D0,  0.1D0, 0.12D0, -0.2D0, 0.12D0, -0.2D0,    0D0, -0.1D0,    0D0, -0.1D0, 0.12D0,  0.2D0,    0D0, -0.1D0,-0.12D0,  0.2D0,-0.15D0,  0.2D0,-0.24D0, 0.24D0,    0D0,    0D0, 0.24D0, 0.24D0, 0.12D0, -0.2D0,-0.12D0, -0.2D0,    0D0,    0D0, 0.12D0,  0.2D0, 0.12D0, -0.2D0, 0.12D0,  0.2D0, 0.12D0,  0.2D0, 0.12D0,  0.2D0, 0.12D0, -0.2D0,-0.12D0,  0.2D0,    0D0,    0D0, 0.12D0,  0.2D0, 0.12D0,    0D0, -0.2D0,    0D0,    0D0,-0.12D0, -0.2D0, 0.12D0, -0.2D0,    0D0,    0D0, 0.12D0,  0.2D0,-0.12D0,  0.2D0,-0.12D0,  0.2D0, 0.12D0, -0.2D0,    0D0,    0D0, 0.12D0,  0.2D0,  0.2D0,    0D0, 0.12D0,    0D0,    0D0,-0.12D0,  0.2D0,    0D0,    0D0,-0.12D0, -0.2D0,    0D0,    0D0,-0.12D0, -0.2D0,-0.12D0, -0.2D0,    0D0,    0D0, 0.12D0, -0.2D0, 0.12D0, -0.2D0, 0.12D0,  0.2D0,-0.12D0, -0.2D0,    0D0,    0D0, 0.12D0, -0.2D0, 0.12D0, -0.2D0, 0.12D0,  0.2D0, 0.12D0,    0D0,  0.2D0,-0.12D0, -0.2D0,    0D0,    0D0, 0.12D0,  0.2D0,-0.16D0,    0D0, 0.16D0, -0.2D0 /"
	analyzeline: implied-DO list "(a(i),i=4362,4513)" is not supported. Skipping.
Line #58868 in sofapy.f:"      DATA (A(I),I=4514,4665) /  0.2D0,    0D0,    0D0, -0.2D0,    0D0,    0D0, -0.2D0,  0.2D0,    0D0,    0D0,  0.2D0,  0.2D0, -0.2D0,    0D0,    0D0, -0.2D0, 0.12D0,    0D0,-0.16D0,  0.2D0,    0D0,    0D0,  0.2D0, 0.12D0, -0.1D0,    0D0,  0.1D0, 0.16D0,-0.16D0,-0.16D0,-0.16D0,-0.16D0,-0.16D0,    0D0,    0D0,-0.16D0,    0D0,    0D0,-0.16D0,-0.16D0,-0.16D0,    0D0,    0D0,-0.16D0,    0D0,    0D0, 0.16D0,    0D0,    0D0, 0.16D0,    0D0,    0D0, 0.16D0, 0.16D0,    0D0,    0D0,-0.16D0,    0D0,    0D0,-0.16D0,-0.16D0,    0D0,    0D0, 0.16D0,    0D0,    0D0,-0.16D0,-0.16D0,    0D0,    0D0,-0.16D0,-0.16D0, 0.12D0,  0.1D0, 0.12D0, -0.1D0, 0.12D0,  0.1D0,    0D0,    0D0, 0.12D0,  0.1D0,-0.12D0,  0.1D0,    0D0,    0D0, 0.12D0,  0.1D0, 0.12D0, -0.1D0,    0D0,    0D0,-0.12D0, -0.1D0,    0D0,    0D0, 0.12D0,  0.1D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0,-0.12D0,    0D0,    0D0, 0.12D0, 0.12D0, 0.12D0, 0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0, 0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0, 0.12D0,-0.12D0,-0.12D0, 0.12D0, 0.12D0,-0.12D0,-0.12D0,    0D0,    0D0, 0.12D0,-0.12D0, 0.12D0, 0.12D0,-0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,    0D0,    0D0,-0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0 /"
	analyzeline: implied-DO list "(a(i),i=4514,4665)" is not supported. Skipping.
Line #58883 in sofapy.f:"      DATA (A(I),I=4666,NA) / 0.12D0,    0D0,    0D0, 0.12D0,-0.12D0,    0D0,    0D0,-0.12D0, 0.12D0,-0.12D0,-0.12D0, 0.12D0,    0D0,    0D0, 0.12D0, 0.12D0, 0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,    0D0,    0D0, 0.12D0, 0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,    0D0,    0D0, 0.12D0,-0.12D0,-0.12D0,-0.12D0,-0.12D0, 0.12D0, 0.12D0,-0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,    0D0,    0D0,-0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0,-0.12D0,-0.12D0,    0D0,    0D0,-0.12D0,-0.12D0, 0.12D0,    0D0,    0D0, 0.12D0, 0.12D0,    0D0,    0D0, 0.12D0,    0D0,    0D0, 0.12D0, 0.12D0, 0.08D0,    0D0, 0.04D0 /"
	analyzeline: implied-DO list "(a(i),i=4666,na)" is not supported. Skipping.
Post-processing...
	Block: sofapy
			Block: iau_a2af
			Block: iau_a2tf
			Block: iau_ab
			Block: iau_ae2hd
			Block: iau_af2a
			Block: iau_anp
			Block: iau_anpm
			Block: iau_apcg
			Block: iau_apcg13
			Block: iau_apci
			Block: iau_apci13
			Block: iau_apco
			Block: iau_apco13
			Block: iau_apcs
			Block: iau_apcs13
			Block: iau_aper
			Block: iau_aper13
			Block: iau_apio
			Block: iau_apio13
			Block: iau_atci13
			Block: iau_atciq
			Block: iau_atciqn
			Block: iau_atciqz
			Block: iau_atco13
			Block: iau_atic13
			Block: iau_aticq
			Block: iau_aticqn
			Block: iau_atio13
			Block: iau_atioq
			Block: iau_atoc13
			Block: iau_atoi13
			Block: iau_atoiq
			Block: iau_bi00
			Block: iau_bp00
			Block: iau_bp06
			Block: iau_bpn2xy
			Block: iau_c2i00a
			Block: iau_c2i00b
			Block: iau_c2i06a
			Block: iau_c2ibpn
			Block: iau_c2ixy
			Block: iau_c2ixys
			Block: iau_c2s
			Block: iau_c2t00a
			Block: iau_c2t00b
			Block: iau_c2t06a
			Block: iau_c2tceo
			Block: iau_c2tcio
			Block: iau_c2teqx
			Block: iau_c2tpe
			Block: iau_c2txy
			Block: iau_cal2jd
			Block: iau_cp
			Block: iau_cpv
			Block: iau_cr
			Block: iau_d2dtf
			Block: iau_d2tf
			Block: iau_dat
			Block: iau_dtdb
			Block: iau_dtf2d
			Block: iau_eceq06
			Block: iau_ecm06
			Block: iau_ee00
			Block: iau_ee00a
			Block: iau_ee00b
			Block: iau_ee06a
			Block: iau_eect00
			Block: iau_eform
			Block: iau_eo06a
			Block: iau_eors
			Block: iau_epb
			Block: iau_epb2jd
			Block: iau_epj
			Block: iau_epj2jd
			Block: iau_epv00
			Block: iau_eqec06
			Block: iau_eqeq94
			Block: iau_era00
			Block: iau_fad03
			Block: iau_fae03
			Block: iau_faf03
			Block: iau_faju03
			Block: iau_fal03
			Block: iau_falp03
			Block: iau_fama03
			Block: iau_fame03
			Block: iau_fane03
			Block: iau_faom03
			Block: iau_fapa03
			Block: iau_fasa03
			Block: iau_faur03
			Block: iau_fave03
			Block: iau_fk425
			Block: iau_fk45z
			Block: iau_fk524
			Block: iau_fk52h
			Block: iau_fk54z
			Block: iau_fk5hip
			Block: iau_fk5hz
			Block: iau_fw2m
			Block: iau_fw2xy
			Block: iau_g2icrs
			Block: iau_gc2gd
			Block: iau_gc2gde
			Block: iau_gd2gc
			Block: iau_gd2gce
			Block: iau_gmst00
			Block: iau_gmst06
			Block: iau_gmst82
			Block: iau_gst00a
			Block: iau_gst00b
			Block: iau_gst06
			Block: iau_gst06a
			Block: iau_gst94
			Block: iau_h2fk5
			Block: iau_hd2ae
			Block: iau_hd2pa
			Block: iau_hfk5z
			Block: iau_icrs2g
			Block: iau_ir
			Block: iau_jd2cal
			Block: iau_jdcalf
			Block: iau_ld
			Block: iau_ldn
			Block: iau_ldsun
			Block: iau_lteceq
			Block: iau_ltecm
			Block: iau_lteqec
			Block: iau_ltp
			Block: iau_ltpb
			Block: iau_ltpecl
			Block: iau_ltpequ
			Block: iau_num00a
			Block: iau_num00b
			Block: iau_num06a
			Block: iau_numat
			Block: iau_nut00a
			Block: iau_nut00b
			Block: iau_nut06a
			Block: iau_nut80
			Block: iau_nutm80
			Block: iau_obl06
			Block: iau_obl80
			Block: iau_p06e
			Block: iau_p2pv
			Block: iau_p2s
			Block: iau_pap
			Block: iau_pas
			Block: iau_pb06
			Block: iau_pdp
			Block: iau_pfw06
			Block: iau_plan94
			Block: iau_pm
			Block: iau_pmat00
			Block: iau_pmat06
			Block: iau_pmat76
			Block: iau_pmp
			Block: iau_pmpx
			Block: iau_pmsafe
			Block: iau_pn
			Block: iau_pn00
			Block: iau_pn00a
			Block: iau_pn00b
			Block: iau_pn06
			Block: iau_pn06a
			Block: iau_pnm00a
			Block: iau_pnm00b
			Block: iau_pnm06a
			Block: iau_pnm80
			Block: iau_pom00
			Block: iau_ppp
			Block: iau_ppsp
			Block: iau_pr00
			Block: iau_prec76
			Block: iau_pv2p
			Block: iau_pv2s
			Block: iau_pvdpv
			Block: iau_pvm
			Block: iau_pvmpv
			Block: iau_pvppv
			Block: iau_pvstar
			Block: iau_pvtob
			Block: iau_pvu
			Block: iau_pvup
			Block: iau_pvxpv
			Block: iau_pxp
			Block: iau_refco
			Block: iau_rm2v
			Block: iau_rv2m
			Block: iau_rx
			Block: iau_rxp
			Block: iau_rxpv
			Block: iau_rxr
			Block: iau_ry
			Block: iau_rz
			Block: iau_s00
			Block: iau_s00a
			Block: iau_s00b
			Block: iau_s06
			Block: iau_s06a
			Block: iau_s2c
			Block: iau_s2p
			Block: iau_s2pv
			Block: iau_s2xpv
			Block: iau_sepp
			Block: iau_seps
			Block: iau_sp00
			Block: iau_starpm
			Block: iau_starpv
			Block: iau_sxp
			Block: iau_sxpv
			Block: iau_taitt
			Block: iau_taiut1
			Block: iau_taiutc
			Block: iau_tcbtdb
			Block: iau_tcgtt
			Block: iau_tdbtcb
			Block: iau_tdbtt
			Block: iau_tf2a
			Block: iau_tf2d
			Block: iau_tpors
			Block: iau_tporv
			Block: iau_tpsts
			Block: iau_tpstv
			Block: iau_tpxes
			Block: iau_tpxev
			Block: iau_tr
			Block: iau_trxp
			Block: iau_trxpv
			Block: iau_tttai
			Block: iau_tttcg
			Block: iau_tttdb
			Block: iau_ttut1
			Block: iau_ut1tai
			Block: iau_ut1tt
			Block: iau_ut1utc
			Block: iau_utctai
			Block: iau_utcut1
			Block: iau_xy06
			Block: iau_xys00a
			Block: iau_xys00b
			Block: iau_xys06a
			Block: iau_zp
			Block: iau_zpv
			Block: iau_zr
Post-processing (stage 2)...
Building modules...
	Building module "sofapy"...
		Constructing wrapper function "iau_a2af"...
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
		  sign,idmsf = iau_a2af(ndp,angle)
		Constructing wrapper function "iau_a2tf"...
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
		  sign,ihmsf = iau_a2tf(ndp,angle)
		Constructing wrapper function "iau_ab"...
		  ppr = iau_ab(pnat,v,s,bm1)
		Constructing wrapper function "iau_ae2hd"...
		  ha,dec = iau_ae2hd(az,el,phi)
		Constructing wrapper function "iau_af2a"...
		  asec,rad,j = iau_af2a(s,ideg,iamin,asec)
		Creating wrapper for Fortran function "iau_anp"("iau_anp")...
		Constructing wrapper function "iau_anp"...
		  iau_anp = iau_anp(a)
		Creating wrapper for Fortran function "iau_anpm"("iau_anpm")...
		Constructing wrapper function "iau_anpm"...
		  iau_anpm = iau_anpm(a)
		Constructing wrapper function "iau_apcg"...
		  astrom = iau_apcg(date1,date2,ebpv,ehp)
		Constructing wrapper function "iau_apcg13"...
		  astrom = iau_apcg13(date1,date2)
		Constructing wrapper function "iau_apci"...
		  astrom = iau_apci(date1,date2,ebpv,ehp,x,y,s)
		Constructing wrapper function "iau_apci13"...
		  astrom,eo = iau_apci13(date1,date2)
		Constructing wrapper function "iau_apco"...
		  astrom = iau_apco(date1,date2,ebpv,ehp,x,y,s,theta,elong,phi,hm,xp,yp,sp,refa,refb)
		Constructing wrapper function "iau_apco13"...
		  astrom,eo,j = iau_apco13(utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_apcs"...
		  astrom = iau_apcs(date1,date2,pv,ebpv,ehp)
		Constructing wrapper function "iau_apcs13"...
		  astrom = iau_apcs13(date1,date2,pv)
		Constructing wrapper function "iau_aper"...
		  astrom = iau_aper(theta)
		Constructing wrapper function "iau_aper13"...
		  astrom = iau_aper13(ut11,ut12)
		Constructing wrapper function "iau_apio"...
		  astrom = iau_apio(sp,theta,elong,phi,hm,xp,yp,refa,refb)
		Constructing wrapper function "iau_apio13"...
		  astrom,j = iau_apio13(utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_atci13"...
		  ri,di,eo = iau_atci13(rc,dc,pr,pd,px,rv,date1,date2)
		Constructing wrapper function "iau_atciq"...
		  ri,di = iau_atciq(rc,dc,pr,pd,px,rv,astrom)
		Constructing wrapper function "iau_atciqn"...
		  ri,di = iau_atciqn(rc,dc,pr,pd,px,rv,astrom,b,[n])
		Constructing wrapper function "iau_atciqz"...
		  ri,di = iau_atciqz(rc,dc,astrom)
		Constructing wrapper function "iau_atco13"...
		  aob,zob,hob,dob,rob,eo,j = iau_atco13(rc,dc,pr,pd,px,rv,utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_atic13"...
		  rc,dc,eo = iau_atic13(ri,di,date1,date2)
		Constructing wrapper function "iau_aticq"...
		  rc,dc = iau_aticq(ri,di,astrom)
		Constructing wrapper function "iau_aticqn"...
		  rc,dc = iau_aticqn(ri,di,astrom,b,[n])
		Constructing wrapper function "iau_atio13"...
		  aob,zob,hob,dob,rob,j = iau_atio13(ri,di,utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_atioq"...
		  aob,zob,hob,dob,rob = iau_atioq(ri,di,astrom)
		Constructing wrapper function "iau_atoc13"...
		  rc,dc,j = iau_atoc13(type_bn,ob1,ob2,utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_atoi13"...
		  ri,di,j = iau_atoi13(type_bn,ob1,ob2,utc1,utc2,dut1,elong,phi,hm,xp,yp,phpa,tc,rh,wl)
		Constructing wrapper function "iau_atoiq"...
		  ri,di = iau_atoiq(type_bn,ob1,ob2,astrom)
		Constructing wrapper function "iau_bi00"...
		  dpsibi,depsbi,dra = iau_bi00()
		Constructing wrapper function "iau_bp00"...
		  rb,rp,rbp = iau_bp00(date1,date2)
		Constructing wrapper function "iau_bp06"...
		  rb,rp,rbp = iau_bp06(date1,date2)
		Constructing wrapper function "iau_bpn2xy"...
		  x,y = iau_bpn2xy(rbpn)
		Constructing wrapper function "iau_c2i00a"...
		  rc2i = iau_c2i00a(date1,date2)
		Constructing wrapper function "iau_c2i00b"...
		  rc2i = iau_c2i00b(date1,date2)
		Constructing wrapper function "iau_c2i06a"...
		  rc2i = iau_c2i06a(date1,date2)
		Constructing wrapper function "iau_c2ibpn"...
		  rc2i = iau_c2ibpn(date1,date2,rbpn)
		Constructing wrapper function "iau_c2ixy"...
		  rc2i = iau_c2ixy(date1,date2,x,y)
		Constructing wrapper function "iau_c2ixys"...
		  rc2i = iau_c2ixys(x,y,s)
		Constructing wrapper function "iau_c2s"...
		  theta,phi = iau_c2s(p)
		Constructing wrapper function "iau_c2t00a"...
		  rc2t = iau_c2t00a(tta,ttb,uta,utb,xp,yp)
		Constructing wrapper function "iau_c2t00b"...
		  rc2t = iau_c2t00b(tta,ttb,uta,utb,xp,yp)
		Constructing wrapper function "iau_c2t06a"...
		  rc2t = iau_c2t06a(tta,ttb,uta,utb,xp,yp)
		Constructing wrapper function "iau_c2tceo"...
		  rc2t = iau_c2tceo(rc2i,era,rpom)
		Constructing wrapper function "iau_c2tcio"...
		  rc2t = iau_c2tcio(rc2i,era,rpom)
		Constructing wrapper function "iau_c2teqx"...
		  rc2t = iau_c2teqx(rbpn,gst,rpom)
		Constructing wrapper function "iau_c2tpe"...
		  rc2t = iau_c2tpe(tta,ttb,uta,utb,dpsi,deps,xp,yp)
		Constructing wrapper function "iau_c2txy"...
		  rc2t = iau_c2txy(tta,ttb,uta,utb,x,y,xp,yp)
		Constructing wrapper function "iau_cal2jd"...
		  djm0,djm,j = iau_cal2jd(iy,im,id)
		Constructing wrapper function "iau_cp"...
		  c = iau_cp(p)
		Constructing wrapper function "iau_cpv"...
		  c = iau_cpv(pv)
		Constructing wrapper function "iau_cr"...
		  c = iau_cr(r)
		Constructing wrapper function "iau_d2dtf"...
		  iy,im,id,ihmsf,j = iau_d2dtf(scale,ndp,d1,d2)
		Constructing wrapper function "iau_d2tf"...
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
getstrlength:intent(hide): expected a string with defined length but got: {'typespec': 'character', 'charselector': {'*': '(*)'}, 'attrspec': [], 'intent': ['out']}
		  sign,ihmsf = iau_d2tf(ndp,days)
		Constructing wrapper function "iau_dat"...
		  deltat,j = iau_dat(iy,im,id,fd)
		Creating wrapper for Fortran function "iau_dtdb"("iau_dtdb")...
		Constructing wrapper function "iau_dtdb"...
		  iau_dtdb = iau_dtdb(date1,date2,ut,elong,u,v)
		Constructing wrapper function "iau_dtf2d"...
		  d1,d2,j = iau_dtf2d(scale,iy,im,id,ihr,imn,sec)
		Constructing wrapper function "iau_eceq06"...
		  dr,dd = iau_eceq06(date1,date2,dl,db)
		Constructing wrapper function "iau_ecm06"...
		  rm = iau_ecm06(date1,date2)
		Creating wrapper for Fortran function "iau_ee00"("iau_ee00")...
		Constructing wrapper function "iau_ee00"...
		  iau_ee00 = iau_ee00(date1,date2,epsa,dpsi)
		Creating wrapper for Fortran function "iau_ee00a"("iau_ee00a")...
		Constructing wrapper function "iau_ee00a"...
		  iau_ee00a = iau_ee00a(date1,date2)
		Creating wrapper for Fortran function "iau_ee00b"("iau_ee00b")...
		Constructing wrapper function "iau_ee00b"...
		  iau_ee00b = iau_ee00b(date1,date2)
		Creating wrapper for Fortran function "iau_ee06a"("iau_ee06a")...
		Constructing wrapper function "iau_ee06a"...
		  iau_ee06a = iau_ee06a(date1,date2)
		Creating wrapper for Fortran function "iau_eect00"("iau_eect00")...
		Constructing wrapper function "iau_eect00"...
		  iau_eect00 = iau_eect00(date1,date2)
		Constructing wrapper function "iau_eform"...
		  a,f,j = iau_eform(n)
		Creating wrapper for Fortran function "iau_eo06a"("iau_eo06a")...
		Constructing wrapper function "iau_eo06a"...
		  iau_eo06a = iau_eo06a(date1,date2)
		Creating wrapper for Fortran function "iau_eors"("iau_eors")...
		Constructing wrapper function "iau_eors"...
		  iau_eors = iau_eors(rnpb,s)
		Creating wrapper for Fortran function "iau_epb"("iau_epb")...
		Constructing wrapper function "iau_epb"...
		  iau_epb = iau_epb(dj1,dj2)
		Constructing wrapper function "iau_epb2jd"...
		  djm0,djm = iau_epb2jd(epb)
		Creating wrapper for Fortran function "iau_epj"("iau_epj")...
		Constructing wrapper function "iau_epj"...
		  iau_epj = iau_epj(dj1,dj2)
		Constructing wrapper function "iau_epj2jd"...
		  djm0,djm = iau_epj2jd(epj)
		Constructing wrapper function "iau_epv00"...
		  pvh,pvb,jstat = iau_epv00(date1,date2)
		Constructing wrapper function "iau_eqec06"...
		  dl,db = iau_eqec06(date1,date2,dr,dd)
		Creating wrapper for Fortran function "iau_eqeq94"("iau_eqeq94")...
		Constructing wrapper function "iau_eqeq94"...
		  iau_eqeq94 = iau_eqeq94(date1,date2)
		Creating wrapper for Fortran function "iau_era00"("iau_era00")...
		Constructing wrapper function "iau_era00"...
		  iau_era00 = iau_era00(dj1,dj2)
		Creating wrapper for Fortran function "iau_fad03"("iau_fad03")...
		Constructing wrapper function "iau_fad03"...
		  iau_fad03 = iau_fad03(t)
		Creating wrapper for Fortran function "iau_fae03"("iau_fae03")...
		Constructing wrapper function "iau_fae03"...
		  iau_fae03 = iau_fae03(t)
		Creating wrapper for Fortran function "iau_faf03"("iau_faf03")...
		Constructing wrapper function "iau_faf03"...
		  iau_faf03 = iau_faf03(t)
		Creating wrapper for Fortran function "iau_faju03"("iau_faju03")...
		Constructing wrapper function "iau_faju03"...
		  iau_faju03 = iau_faju03(t)
		Creating wrapper for Fortran function "iau_fal03"("iau_fal03")...
		Constructing wrapper function "iau_fal03"...
		  iau_fal03 = iau_fal03(t)
		Creating wrapper for Fortran function "iau_falp03"("iau_falp03")...
		Constructing wrapper function "iau_falp03"...
		  iau_falp03 = iau_falp03(t)
		Creating wrapper for Fortran function "iau_fama03"("iau_fama03")...
		Constructing wrapper function "iau_fama03"...
		  iau_fama03 = iau_fama03(t)
		Creating wrapper for Fortran function "iau_fame03"("iau_fame03")...
		Constructing wrapper function "iau_fame03"...
		  iau_fame03 = iau_fame03(t)
		Creating wrapper for Fortran function "iau_fane03"("iau_fane03")...
		Constructing wrapper function "iau_fane03"...
		  iau_fane03 = iau_fane03(t)
		Creating wrapper for Fortran function "iau_faom03"("iau_faom03")...
		Constructing wrapper function "iau_faom03"...
		  iau_faom03 = iau_faom03(t)
		Creating wrapper for Fortran function "iau_fapa03"("iau_fapa03")...
		Constructing wrapper function "iau_fapa03"...
		  iau_fapa03 = iau_fapa03(t)
		Creating wrapper for Fortran function "iau_fasa03"("iau_fasa03")...
		Constructing wrapper function "iau_fasa03"...
		  iau_fasa03 = iau_fasa03(t)
		Creating wrapper for Fortran function "iau_faur03"("iau_faur03")...
		Constructing wrapper function "iau_faur03"...
		  iau_faur03 = iau_faur03(t)
		Creating wrapper for Fortran function "iau_fave03"("iau_fave03")...
		Constructing wrapper function "iau_fave03"...
		  iau_fave03 = iau_fave03(t)
		Constructing wrapper function "iau_fk425"...
		  r2000,d2000,dr2000,dd2000,p2000,v2000 = iau_fk425(r1950,d1950,dr1950,dd1950,p1950,v1950)
		Constructing wrapper function "iau_fk45z"...
		  r2000,d2000 = iau_fk45z(r1950,d1950,bepoch)
		Constructing wrapper function "iau_fk524"...
		  r1950,d1950,dr1950,dd1950,p1950,v1950 = iau_fk524(r2000,d2000,dr2000,dd2000,p2000,v2000)
		Constructing wrapper function "iau_fk52h"...
		  rh,dh,drh,ddh,pxh,rvh = iau_fk52h(r5,d5,dr5,dd5,px5,rv5)
		Constructing wrapper function "iau_fk54z"...
		  r1950,d1950,dr1950,dd1950 = iau_fk54z(r2000,d2000,bepoch)
		Constructing wrapper function "iau_fk5hip"...
		  r5h,s5h = iau_fk5hip()
		Constructing wrapper function "iau_fk5hz"...
		  rh,dh = iau_fk5hz(r5,d5,date1,date2)
		Constructing wrapper function "iau_fw2m"...
		  r = iau_fw2m(gamb,phib,psi,eps)
		Constructing wrapper function "iau_fw2xy"...
		  x,y = iau_fw2xy(gamb,phib,psi,eps)
		Constructing wrapper function "iau_g2icrs"...
		  dr,dd = iau_g2icrs(dl,db)
		Constructing wrapper function "iau_gc2gd"...
		  elong,phi,height,j = iau_gc2gd(n,xyz)
		Constructing wrapper function "iau_gc2gde"...
		  elong,phi,height,j = iau_gc2gde(a,f,xyz)
		Constructing wrapper function "iau_gd2gc"...
		  xyz,j = iau_gd2gc(n,elong,phi,height)
		Constructing wrapper function "iau_gd2gce"...
		  xyz,j = iau_gd2gce(a,f,elong,phi,height)
		Creating wrapper for Fortran function "iau_gmst00"("iau_gmst00")...
		Constructing wrapper function "iau_gmst00"...
		  iau_gmst00 = iau_gmst00(uta,utb,tta,ttb)
		Creating wrapper for Fortran function "iau_gmst06"("iau_gmst06")...
		Constructing wrapper function "iau_gmst06"...
		  iau_gmst06 = iau_gmst06(uta,utb,tta,ttb)
		Creating wrapper for Fortran function "iau_gmst82"("iau_gmst82")...
		Constructing wrapper function "iau_gmst82"...
		  iau_gmst82 = iau_gmst82(dj1,dj2)
		Creating wrapper for Fortran function "iau_gst00a"("iau_gst00a")...
		Constructing wrapper function "iau_gst00a"...
		  iau_gst00a = iau_gst00a(uta,utb,tta,ttb)
		Creating wrapper for Fortran function "iau_gst00b"("iau_gst00b")...
		Constructing wrapper function "iau_gst00b"...
		  iau_gst00b = iau_gst00b(uta,utb)
		Creating wrapper for Fortran function "iau_gst06"("iau_gst06")...
		Constructing wrapper function "iau_gst06"...
		  iau_gst06 = iau_gst06(uta,utb,tta,ttb,rnpb)
		Creating wrapper for Fortran function "iau_gst06a"("iau_gst06a")...
		Constructing wrapper function "iau_gst06a"...
		  iau_gst06a = iau_gst06a(uta,utb,tta,ttb)
		Creating wrapper for Fortran function "iau_gst94"("iau_gst94")...
		Constructing wrapper function "iau_gst94"...
		  iau_gst94 = iau_gst94(uta,utb)
		Constructing wrapper function "iau_h2fk5"...
		  r5,d5,dr5,dd5,px5,rv5 = iau_h2fk5(rh,dh,drh,ddh,pxh,rvh)
		Constructing wrapper function "iau_hd2ae"...
		  az,el = iau_hd2ae(ha,dec,phi)
		Creating wrapper for Fortran function "iau_hd2pa"("iau_hd2pa")...
		Constructing wrapper function "iau_hd2pa"...
		  iau_hd2pa = iau_hd2pa(ha,dec,phi)
		Constructing wrapper function "iau_hfk5z"...
		  r5,d5,dr5,dd5 = iau_hfk5z(rh,dh,date1,date2)
		Constructing wrapper function "iau_icrs2g"...
		  dl,db = iau_icrs2g(dr,dd)
		Constructing wrapper function "iau_ir"...
		  r = iau_ir()
		Constructing wrapper function "iau_jd2cal"...
		  iy,im,id,fd,j = iau_jd2cal(dj1,dj2)
		Constructing wrapper function "iau_jdcalf"...
		  iymdf,j = iau_jdcalf(ndp,dj1,dj2)
		Constructing wrapper function "iau_ld"...
		  p1 = iau_ld(bm,p,q,e,em,dlim)
		Constructing wrapper function "iau_ldn"...
		  sn = iau_ldn(b,ob,sc,[n])
		Constructing wrapper function "iau_ldsun"...
		  p1 = iau_ldsun(p,e,em)
		Constructing wrapper function "iau_lteceq"...
		  dr,dd = iau_lteceq(epj,dl,db)
		Constructing wrapper function "iau_ltecm"...
		  rm = iau_ltecm(epj)
		Constructing wrapper function "iau_lteqec"...
		  dl,db = iau_lteqec(epj,dr,dd)
		Constructing wrapper function "iau_ltp"...
		  rp = iau_ltp(epj)
		Constructing wrapper function "iau_ltpb"...
		  rpb = iau_ltpb(epj)
		Constructing wrapper function "iau_ltpecl"...
		  vec = iau_ltpecl(epj)
		Constructing wrapper function "iau_ltpequ"...
		  veq = iau_ltpequ(epj)
		Constructing wrapper function "iau_num00a"...
		  rmatn = iau_num00a(date1,date2)
		Constructing wrapper function "iau_num00b"...
		  rmatn = iau_num00b(date1,date2)
		Constructing wrapper function "iau_num06a"...
		  rmatn = iau_num06a(date1,date2)
		Constructing wrapper function "iau_numat"...
		  rmatn = iau_numat(epsa,dpsi,deps)
		Constructing wrapper function "iau_nut00a"...
		  dpsi,deps = iau_nut00a(date1,date2)
		Constructing wrapper function "iau_nut00b"...
		  dpsi,deps = iau_nut00b(date1,date2)
		Constructing wrapper function "iau_nut06a"...
		  dpsi,deps = iau_nut06a(date1,date2)
		Constructing wrapper function "iau_nut80"...
		  dpsi,deps = iau_nut80(date1,date2)
		Constructing wrapper function "iau_nutm80"...
		  rmatn = iau_nutm80(date1,date2)
		Creating wrapper for Fortran function "iau_obl06"("iau_obl06")...
		Constructing wrapper function "iau_obl06"...
		  iau_obl06 = iau_obl06(date1,date2)
		Creating wrapper for Fortran function "iau_obl80"("iau_obl80")...
		Constructing wrapper function "iau_obl80"...
		  iau_obl80 = iau_obl80(date1,date2)
		Constructing wrapper function "iau_p06e"...
		  eps0,psia,oma,bpa,bqa,pia,bpia,epsa,chia,za,zetaa,thetaa,pa,gam,phi,psi = iau_p06e(date1,date2)
		Constructing wrapper function "iau_p2pv"...
		  pv = iau_p2pv(p)
		Constructing wrapper function "iau_p2s"...
		  theta,phi,r = iau_p2s(p)
		Constructing wrapper function "iau_pap"...
		  theta = iau_pap(a,b)
		Constructing wrapper function "iau_pas"...
		  theta = iau_pas(al,ap,bl,bp)
		Constructing wrapper function "iau_pb06"...
		  bzeta,bz,btheta = iau_pb06(date1,date2)
		Constructing wrapper function "iau_pdp"...
		  adb = iau_pdp(a,b)
		Constructing wrapper function "iau_pfw06"...
		  gamb,phib,psib,epsa = iau_pfw06(date1,date2)
		Constructing wrapper function "iau_plan94"...
		  pv,j = iau_plan94(date1,date2,np)
		Constructing wrapper function "iau_pm"...
		  r = iau_pm(p)
		Constructing wrapper function "iau_pmat00"...
		  rbp = iau_pmat00(date1,date2)
		Constructing wrapper function "iau_pmat06"...
		  rbp = iau_pmat06(date1,date2)
		Constructing wrapper function "iau_pmat76"...
		  rmatp = iau_pmat76(date1,date2)
		Constructing wrapper function "iau_pmp"...
		  amb = iau_pmp(a,b)
		Constructing wrapper function "iau_pmpx"...
		  pco = iau_pmpx(rc,dc,pr,pd,px,rv,pmt,pob)
		Constructing wrapper function "iau_pmsafe"...
		  ra2,dec2,pmr2,pmd2,px2,rv2,j = iau_pmsafe(ra1,dec1,pmr1,pmd1,px1,rv1,ep1a,ep1b,ep2a,ep2b)
		Constructing wrapper function "iau_pn"...
		  r,u = iau_pn(p)
		Constructing wrapper function "iau_pn00"...
		  epsa,rb,rp,rbp,rn,rbpn = iau_pn00(date1,date2,dpsi,deps)
		Constructing wrapper function "iau_pn00a"...
		  dpsi,deps,epsa,rb,rp,rbp,rn,rbpn = iau_pn00a(date1,date2)
		Constructing wrapper function "iau_pn00b"...
		  dpsi,deps,epsa,rb,rp,rbp,rn,rbpn = iau_pn00b(date1,date2)
		Constructing wrapper function "iau_pn06"...
		  epsa,rb,rp,rbp,rn,rbpn = iau_pn06(date1,date2,dpsi,deps)
		Constructing wrapper function "iau_pn06a"...
		  dpsi,deps,epsa,rb,rp,rbp,rn,rbpn = iau_pn06a(date1,date2)
		Constructing wrapper function "iau_pnm00a"...
		  rbpn = iau_pnm00a(date1,date2)
		Constructing wrapper function "iau_pnm00b"...
		  rbpn = iau_pnm00b(date1,date2)
		Constructing wrapper function "iau_pnm06a"...
		  rnpb = iau_pnm06a(date1,date2)
		Constructing wrapper function "iau_pnm80"...
		  rmatpn = iau_pnm80(date1,date2)
		Constructing wrapper function "iau_pom00"...
		  rpom = iau_pom00(xp,yp,sp)
		Constructing wrapper function "iau_ppp"...
		  apb = iau_ppp(a,b)
		Constructing wrapper function "iau_ppsp"...
		  apsb = iau_ppsp(a,s,b)
		Constructing wrapper function "iau_pr00"...
		  dpsipr,depspr = iau_pr00(date1,date2)
		Constructing wrapper function "iau_prec76"...
		  zeta,z,theta = iau_prec76(date01,date02,date11,date12)
		Constructing wrapper function "iau_pv2p"...
		  p = iau_pv2p(pv)
		Constructing wrapper function "iau_pv2s"...
		  theta,phi,r,td,pd,rd = iau_pv2s(pv)
		Constructing wrapper function "iau_pvdpv"...
		  adb = iau_pvdpv(a,b)
		Constructing wrapper function "iau_pvm"...
		  r,s = iau_pvm(pv)
		Constructing wrapper function "iau_pvmpv"...
		  amb = iau_pvmpv(a,b)
		Constructing wrapper function "iau_pvppv"...
		  apb = iau_pvppv(a,b)
		Constructing wrapper function "iau_pvstar"...
		  ra,dec,pmr,pmd,px,rv,j = iau_pvstar(pv)
		Constructing wrapper function "iau_pvtob"...
		  pv = iau_pvtob(elong,phi,hm,xp,yp,sp,theta)
		Constructing wrapper function "iau_pvu"...
		  upv = iau_pvu(dt,pv)
		Constructing wrapper function "iau_pvup"...
		  p = iau_pvup(dt,pv)
		Constructing wrapper function "iau_pvxpv"...
		  axb = iau_pvxpv(a,b)
		Constructing wrapper function "iau_pxp"...
		  axb = iau_pxp(a,b)
		Constructing wrapper function "iau_refco"...
		  refa,refb = iau_refco(phpa,tc,rh,wl)
		Constructing wrapper function "iau_rm2v"...
		  iau_rm2v(r,w)
		Constructing wrapper function "iau_rv2m"...
		  iau_rv2m(w,r)
		Constructing wrapper function "iau_rx"...
		  iau_rx(phi,r)
		Constructing wrapper function "iau_rxp"...
		  iau_rxp(r,p,rp)
		Constructing wrapper function "iau_rxpv"...
		  iau_rxpv(r,pv,rpv)
		Constructing wrapper function "iau_rxr"...
		  iau_rxr(a,b,atb)
		Constructing wrapper function "iau_ry"...
		  iau_ry(theta,r)
		Constructing wrapper function "iau_rz"...
		  iau_rz(psi,r)
		Creating wrapper for Fortran function "iau_s00"("iau_s00")...
		Constructing wrapper function "iau_s00"...
		  iau_s00 = iau_s00(date1,date2,x,y)
		Creating wrapper for Fortran function "iau_s00a"("iau_s00a")...
		Constructing wrapper function "iau_s00a"...
		  iau_s00a = iau_s00a(date1,date2)
		Creating wrapper for Fortran function "iau_s00b"("iau_s00b")...
		Constructing wrapper function "iau_s00b"...
		  iau_s00b = iau_s00b(date1,date2)
		Creating wrapper for Fortran function "iau_s06"("iau_s06")...
		Constructing wrapper function "iau_s06"...
		  iau_s06 = iau_s06(date1,date2,x,y)
		Creating wrapper for Fortran function "iau_s06a"("iau_s06a")...
		Constructing wrapper function "iau_s06a"...
		  iau_s06a = iau_s06a(date1,date2)
		Constructing wrapper function "iau_s2c"...
		  c = iau_s2c(theta,phi)
		Constructing wrapper function "iau_s2p"...
		  p = iau_s2p(theta,phi,r)
		Constructing wrapper function "iau_s2pv"...
		  pv = iau_s2pv(theta,phi,r,td,pd,rd)
		Constructing wrapper function "iau_s2xpv"...
		  spv = iau_s2xpv(s1,s2,pv)
		Constructing wrapper function "iau_sepp"...
		  s = iau_sepp(a,b)
		Constructing wrapper function "iau_seps"...
		  s = iau_seps(al,ap,bl,bp)
		Creating wrapper for Fortran function "iau_sp00"("iau_sp00")...
		Constructing wrapper function "iau_sp00"...
		  iau_sp00 = iau_sp00(date1,date2)
		Constructing wrapper function "iau_starpm"...
		  ra2,dec2,pmr2,pmd2,px2,rv2,j = iau_starpm(ra1,dec1,pmr1,pmd1,px1,rv1,ep1a,ep1b,ep2a,ep2b)
		Constructing wrapper function "iau_starpv"...
		  pv,j = iau_starpv(ra,dec,pmr,pmd,px,rv)
		Constructing wrapper function "iau_sxp"...
		  sp = iau_sxp(s,p)
		Constructing wrapper function "iau_sxpv"...
		  spv = iau_sxpv(s,pv)
		Constructing wrapper function "iau_taitt"...
		  tt1,tt2,j = iau_taitt(tai1,tai2)
		Constructing wrapper function "iau_taiut1"...
		  ut11,ut12,j = iau_taiut1(tai1,tai2,dta)
		Constructing wrapper function "iau_taiutc"...
		  utc1,utc2,j = iau_taiutc(tai1,tai2)
		Constructing wrapper function "iau_tcbtdb"...
		  tdb1,tdb2,j = iau_tcbtdb(tcb1,tcb2)
		Constructing wrapper function "iau_tcgtt"...
		  tt1,tt2,j = iau_tcgtt(tcg1,tcg2)
		Constructing wrapper function "iau_tdbtcb"...
		  tcb1,tcb2,j = iau_tdbtcb(tdb1,tdb2)
		Constructing wrapper function "iau_tdbtt"...
		  tt1,tt2,j = iau_tdbtt(tdb1,tdb2,dtr)
		Constructing wrapper function "iau_tf2a"...
		  rad,j = iau_tf2a(s,ihour,imin,sec)
		Constructing wrapper function "iau_tf2d"...
		  days,j = iau_tf2d(s,ihour,imin,sec)
		Constructing wrapper function "iau_tpors"...
		  a01,b01,a02,b02,n = iau_tpors(xi,eta,a,b)
		Constructing wrapper function "iau_tporv"...
		  v01,v02,n = iau_tporv(xi,eta,v)
		Constructing wrapper function "iau_tpsts"...
		  a,b = iau_tpsts(xi,eta,a0,b0)
		Constructing wrapper function "iau_tpstv"...
		  v = iau_tpstv(xi,eta,v0)
		Constructing wrapper function "iau_tpxes"...
		  xi,eta,j = iau_tpxes(a,b,a0,b0)
		Constructing wrapper function "iau_tpxev"...
		  xi,eta,j = iau_tpxev(v,v0)
		Constructing wrapper function "iau_tr"...
		  rt = iau_tr(r)
		Constructing wrapper function "iau_trxp"...
		  trp = iau_trxp(r,p)
		Constructing wrapper function "iau_trxpv"...
		  trpv = iau_trxpv(r,pv)
		Constructing wrapper function "iau_tttai"...
		  tai1,tai2,j = iau_tttai(tt1,tt2)
		Constructing wrapper function "iau_tttcg"...
		  tcg1,tcg2,j = iau_tttcg(tt1,tt2)
		Constructing wrapper function "iau_tttdb"...
		  tdb1,tdb2,j = iau_tttdb(tt1,tt2,dtr)
		Constructing wrapper function "iau_ttut1"...
		  ut11,ut12,j = iau_ttut1(tt1,tt2,dt)
		Constructing wrapper function "iau_ut1tai"...
		  tai1,tai2,j = iau_ut1tai(ut11,ut12,dta)
		Constructing wrapper function "iau_ut1tt"...
		  tt1,tt2,j = iau_ut1tt(ut11,ut12,dt)
		Constructing wrapper function "iau_ut1utc"...
		  utc1,utc2,j = iau_ut1utc(ut11,ut12,dut1)
		Constructing wrapper function "iau_utctai"...
		  tai1,tai2,j = iau_utctai(utc1,utc2)
		Constructing wrapper function "iau_utcut1"...
		  ut11,ut12,j = iau_utcut1(utc1,utc2,dut1)
		Constructing wrapper function "iau_xy06"...
		  x,y = iau_xy06(date1,date2)
		Constructing wrapper function "iau_xys00a"...
		  x,y,s = iau_xys00a(date1,date2)
		Constructing wrapper function "iau_xys00b"...
		  x,y,s = iau_xys00b(date1,date2)
		Constructing wrapper function "iau_xys06a"...
		  x,y,s = iau_xys06a(date1,date2)
		Constructing wrapper function "iau_zp"...
		  p = iau_zp()
		Constructing wrapper function "iau_zpv"...
		  pv = iau_zpv()
		Constructing wrapper function "iau_zr"...
		  r = iau_zr()
	Wrote C/API module "sofapy" to file "/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c"
	Fortran 77 wrappers are saved to "/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapy-f2pywrappers.f"
  adding '/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c' to sources.
  adding '/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7' to include_dirs.
copying /Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/f2py/src/fortranobject.c -> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
copying /Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/f2py/src/fortranobject.h -> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
  adding '/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapy-f2pywrappers.f' to sources.
build_src: building npy-pkg config files
running build_ext
customize UnixCCompiler
customize UnixCCompiler using build_ext
get_default_fcompiler: matching types: '['gnu95', 'nag', 'absoft', 'ibm', 'intel', 'gnu', 'g95', 'pg']'
customize Gnu95FCompiler
Found executable /opt/local/bin/gfortran
customize Gnu95FCompiler
customize Gnu95FCompiler using build_ext
building 'sofapy' extension
compiling C sources
C compiler: gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/user/opt/anaconda3/include -arch x86_64 -I/Users/user/opt/anaconda3/include -arch x86_64

creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k
creating /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
compile options: '-I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7 -I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include -I/Users/user/opt/anaconda3/include/python3.7m -c'
gcc: /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
gcc: /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c
In file included from /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
                 from /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
                 from /Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61: error: no include path in which to search for limits.h
  195 | #include_next <limits.h>  /* recurse down to the real one */
      |                                                             ^
In file included from /Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10: fatal error: _stdio.h: No such file or directory
   78 | #include <_stdio.h>
      |          ^~~~~~~~~~
compilation terminated.
In file included from /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
                 from /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
                 from /Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.h:7,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c:2:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61: error: no include path in which to search for limits.h
  195 | #include_next <limits.h>  /* recurse down to the real one */
      |                                                             ^
In file included from /Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.h:7,
                 from /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c:2:
/opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10: fatal error: _stdio.h: No such file or directory
   78 | #include <_stdio.h>
      |          ^~~~~~~~~~
compilation terminated.
error: Command "gcc -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -I/Users/user/opt/anaconda3/include -arch x86_64 -I/Users/user/opt/anaconda3/include -arch x86_64 -I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7 -I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include -I/Users/user/opt/anaconda3/include/python3.7m -c /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c -o /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.o -MMD -MF /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.o.d" failed with exit status 1
(base) user at Mac-Pro src % 

From seiko at imavr.com  Sat Jan  9 01:38:20 2021
From: seiko at imavr.com (Sayed Adel)
Date: Sat, 9 Jan 2021 08:38:20 +0200
Subject: [Numpy-discussion] Sayed Adel has joined the developer team.
In-Reply-To: <CABL7CQgWPhp7mh1FYU1GGiE2czWsMQSqfgpwJgeaNnBZu5Ujcg@mail.gmail.com>
References: <CABL7CQgWPhp7mh1FYU1GGiE2czWsMQSqfgpwJgeaNnBZu5Ujcg@mail.gmail.com>
Message-ID: <AC10CDFA-4A51-4A60-990E-E7BA7680FA48@getmailspring.com>


On Jan 4 2021, at 6:52 pm, Ralf Gommers <ralf.gommers at gmail.com> wrote:
>
>
> On Mon, Jan 4, 2021 at 5:35 PM Matti Picus <matti.picus at gmail.com (mailto:matti.picus at gmail.com)> wrote:
> >
> > On 1/4/21 6:05 PM, Charles R Harris wrote:
> > > Hi All,
> > >
> > > Sayed Adel is now part of the developer team. His SIMD work has been
> > > substantial and ongoing, may it long continue. Welcome Sayed.
> > >
> > > Chuck
> > >
> > Welcome Sayed.
>
>
> Very well-deserved, thanks for all the great work Sayed!
>
> Cheers,
> Ralf
>
>

Happy to join in! Thanks for the warm welcome,
Sayed

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From seiko at imavr.com  Sat Jan  9 01:49:06 2021
From: seiko at imavr.com (seiko2plus)
Date: Fri, 8 Jan 2021 23:49:06 -0700 (MST)
Subject: [Numpy-discussion] Welcome Chunlin to the NumPy development
 team.
In-Reply-To: <CABL7CQivKhO+e8Rz4JR6Apma=bKC8i16Pz2fZYsSA6XKUVu6Bw@mail.gmail.com>
References: <CAB6mnxJbJbiJypb+Dxc0FQ4YVLinNqi=81OHpdtukZfYLiKSUw@mail.gmail.com>
 <CABL7CQivKhO+e8Rz4JR6Apma=bKC8i16Pz2fZYsSA6XKUVu6Bw@mail.gmail.com>
Message-ID: <1610174946115-0.post@n7.nabble.com>

Welcome, Chunlin!



-----
Thanks, Sayed
--
Sent from: http://numpy-discussion.10968.n7.nabble.com/

From klark--kent at yandex.ru  Sat Jan  9 14:07:34 2021
From: klark--kent at yandex.ru (klark--kent at yandex.ru)
Date: Sat, 09 Jan 2021 22:07:34 +0300
Subject: [Numpy-discussion] How to speed up array generating
Message-ID: <2342291610218355@mail.yandex.ru>

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From jfoxrabinovitz at gmail.com  Sat Jan  9 14:45:43 2021
From: jfoxrabinovitz at gmail.com (Joseph Fox-Rabinovitz)
Date: Sat, 9 Jan 2021 14:45:43 -0500
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <2342291610218355@mail.yandex.ru>
References: <2342291610218355@mail.yandex.ru>
Message-ID: <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>

What other ways have you tried?

On Sat, Jan 9, 2021 at 2:15 PM <klark--kent at yandex.ru> wrote:

> Hello. There is a random 1D array m_0 with size 3000, for example:
>
> m_0 = np.array([0, 1, 2])
>
> I need to generate two 1D arrays:
>
> m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
> m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
>
> Is there faster way to do it than this one:
>
> import numpy as npimport time
> N = 3
> m_0 = np.arange(N)
>
> t = time.time()
> m_1 = np.tile(m_0, N)
> m_2 = np.repeat(m_0, N)
> t = time.time() - t
>
> I tried other ways but they are slower or have the same time. Other NumPy operations in my code 10-100 times faster. Why the repeating an array is so slow? I need 10 times speed up. Thank you for your attantion to my problem.
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From klark--kent at yandex.ru  Sat Jan  9 15:45:54 2021
From: klark--kent at yandex.ru (klark--kent at yandex.ru)
Date: Sat, 09 Jan 2021 23:45:54 +0300
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>
References: <2342291610218355@mail.yandex.ru>
 <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>
Message-ID: <11231610225088@mail.yandex.ru>

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From kevin.k.sheppard at gmail.com  Sat Jan  9 16:12:13 2021
From: kevin.k.sheppard at gmail.com (Kevin Sheppard)
Date: Sat, 9 Jan 2021 21:12:13 +0000
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <11231610225088@mail.yandex.ru>
References: <2342291610218355@mail.yandex.ru>
 <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>
 <11231610225088@mail.yandex.ru>
Message-ID: <CAE8Ss2Hpnd3Zz3Qnb9u-HdGAhdZxh0B3miMCS7ee6dDWuc+1Dg@mail.gmail.com>

What about arange and then an integer divide or mod?

Kevin


On Sat, Jan 9, 2021, 20:54 <klark--kent at yandex.ru> wrote:

> np.meshgrid, indexing, reshape
>
> 09.01.2021, 22:30, "Joseph Fox-Rabinovitz" <jfoxrabinovitz at gmail.com>:
>
> What other ways have you tried?
>
> On Sat, Jan 9, 2021 at 2:15 PM <klark--kent at yandex.ru> wrote:
>
> Hello. There is a random 1D array m_0 with size 3000, for example:
>
> m_0 = np.array([0, 1, 2])
>
> I need to generate two 1D arrays:
>
> m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
> m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
>
> Is there faster way to do it than this one:
>
> import numpy as npimport time
> N = 3
> m_0 = np.arange(N)
>
> t = time.time()
> m_1 = np.tile(m_0, N)
> m_2 = np.repeat(m_0, N)
> t = time.time() - t
>
> I tried other ways but they are slower or have the same time. Other NumPy operations in my code 10-100 times faster. Why the repeating an array is so slow? I need 10 times speed up. Thank you for your attantion to my problem.
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
> ,
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From kevin.k.sheppard at gmail.com  Sat Jan  9 16:13:17 2021
From: kevin.k.sheppard at gmail.com (Kevin Sheppard)
Date: Sat, 9 Jan 2021 21:13:17 +0000
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <CAE8Ss2Hpnd3Zz3Qnb9u-HdGAhdZxh0B3miMCS7ee6dDWuc+1Dg@mail.gmail.com>
References: <2342291610218355@mail.yandex.ru>
 <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>
 <11231610225088@mail.yandex.ru>
 <CAE8Ss2Hpnd3Zz3Qnb9u-HdGAhdZxh0B3miMCS7ee6dDWuc+1Dg@mail.gmail.com>
Message-ID: <CAE8Ss2EE4z7Srco=s1DwABe8v5Q+tpUASKwqW_Op8mEevsDzxg@mail.gmail.com>

Actually I would try a broadcast multiply followed by ravel first.

Kevin


On Sat, Jan 9, 2021, 21:12 Kevin Sheppard <kevin.k.sheppard at gmail.com>
wrote:

> What about arange and then an integer divide or mod?
>
> Kevin
>
>
> On Sat, Jan 9, 2021, 20:54 <klark--kent at yandex.ru> wrote:
>
>> np.meshgrid, indexing, reshape
>>
>> 09.01.2021, 22:30, "Joseph Fox-Rabinovitz" <jfoxrabinovitz at gmail.com>:
>>
>> What other ways have you tried?
>>
>> On Sat, Jan 9, 2021 at 2:15 PM <klark--kent at yandex.ru> wrote:
>>
>> Hello. There is a random 1D array m_0 with size 3000, for example:
>>
>> m_0 = np.array([0, 1, 2])
>>
>> I need to generate two 1D arrays:
>>
>> m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
>> m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
>>
>> Is there faster way to do it than this one:
>>
>> import numpy as npimport time
>> N = 3
>> m_0 = np.arange(N)
>>
>> t = time.time()
>> m_1 = np.tile(m_0, N)
>> m_2 = np.repeat(m_0, N)
>> t = time.time() - t
>>
>> I tried other ways but they are slower or have the same time. Other NumPy operations in my code 10-100 times faster. Why the repeating an array is so slow? I need 10 times speed up. Thank you for your attantion to my problem.
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at python.org
>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>
>> ,
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at python.org
>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at python.org
>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>
>
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From sebastian at sipsolutions.net  Sat Jan  9 16:18:39 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Sat, 09 Jan 2021 15:18:39 -0600
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <11231610225088@mail.yandex.ru>
References: <2342291610218355@mail.yandex.ru>
 <CAAa1KPZ4_L+ixjTMg5qpGSNCFkiN1j8=betvSgd6JDD4bKmXsw@mail.gmail.com>
 <11231610225088@mail.yandex.ru>
Message-ID: <d08b4d940566f9d657f8932a0881f3f45fc9faf3.camel@sipsolutions.net>

On Sat, 2021-01-09 at 23:45 +0300, klark--kent at yandex.ru wrote:
> np.meshgrid, indexing, reshape

I would expect e.g. reshape helps if you make use of the fact that this
is very clear in 2-D. The other thing is ensuring to use the methods
`arr.reshape`, `arr.repeat`, which avoids overheads (some of which may
be optimized away in the future though).

That said, with this type of code and the small arrays in the example,
there are fairly significant overheads.  So if  you want to get serious
input or a good solution, I would suggest to give more context and
include how those lines of code are used in your program/function.

Chances are that there is a much faster and possibly more elegant way
to write it, e.g. by solving many of these at the same time, but nobody
will be able to tell unless they know how you need it. Also with more
context, the other possibility is that somone may hint at cython or
numba/transonic.

Cheers,

Sebastian


> 
> 09.01.2021, 22:30, "Joseph Fox-Rabinovitz"
> <jfoxrabinovitz at gmail.com>:
> What other ways have you tried?
> 
> On Sat, Jan 9, 2021 at 2:15 PM <klark--kent at yandex.ru> wrote:
> > Hello.?There is a random 1D array m_0 with size 3000, for example:
> > m_0 = np.array([0, 1, 2])
> > I need to generate two 1D arrays:
> > m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
> > m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
> > Is there faster way to do it than this one:
> > import numpy as np
> > import time
> > N = 3
> > m_0 = np.arange(N)
> > 
> > t = time.time()
> > m_1 = np.tile(m_0, N)
> > m_2 = np.repeat(m_0, N)
> > t = time.time() - t
> > I tried other ways but they are slower or have the same time. Other
> > NumPy operations in my code 10-100 times faster. Why the repeating
> > an array is so slow? I need 10 times speed up. Thank you for your
> > attantion to my problem.
> > _______________________________________________
> > NumPy-Discussion mailing list
> > NumPy-Discussion at python.org
> > https://mail.python.org/mailman/listinfo/numpy-discussion
> ,
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From sole at esrf.fr  Sun Jan 10 00:36:06 2021
From: sole at esrf.fr (V. Armando Sole)
Date: Sun, 10 Jan 2021 06:36:06 +0100
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <2342291610218355@mail.yandex.ru>
References: <2342291610218355@mail.yandex.ru>
Message-ID: <c95a271ac82980d638e04edcc51dd438@esrf.fr>

I guess the speed up, if any, will be machine dependent, but you can
give a try at: 

import numpy as np
import time
N = 3000
m_0 = np.arange(N)
t = time.time()
a = np.ones(N)
m_1 = np.outer(m_0, a).ravel()
m_2 = np.outer(a, m_0).ravel()
t = time.time() - t

On 2021-01-09 20:07, klark--kent at yandex.ru wrote:

> Hello. There is a random 1D array m_0 with size 3000, for example:
> 
> m_0 = np.array([0, 1, 2])
> 
> I need to generate two 1D arrays:
> 
> m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
> m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
> 
> Is there faster way to do it than this one:
> 
> import numpy as np
> import time
> N = 3
> m_0 = np.arange(N)
> 
> t = time.time()
> m_1 = np.tile(m_0, N)
> m_2 = np.repeat(m_0, N)
> t = time.time() - t
> 
> I tried other ways but they are slower or have the same time. Other NumPy operations in my code 10-100 times faster. Why the repeating an array is so slow? I need 10 times speed up. Thank you for your attantion to my problem.
> 
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
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From klark--kent at yandex.ru  Sun Jan 10 01:52:46 2021
From: klark--kent at yandex.ru (klark--kent at yandex.ru)
Date: Sun, 10 Jan 2021 09:52:46 +0300
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <c95a271ac82980d638e04edcc51dd438@esrf.fr>
References: <2342291610218355@mail.yandex.ru>
 <c95a271ac82980d638e04edcc51dd438@esrf.fr>
Message-ID: <188411610261382@mail.yandex.ru>

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From blkzol001 at myuct.ac.za  Sun Jan 10 11:59:42 2021
From: blkzol001 at myuct.ac.za (zoj613)
Date: Sun, 10 Jan 2021 09:59:42 -0700 (MST)
Subject: [Numpy-discussion] using scalar input on np.PyArray_MultiIterNew2
Message-ID: <1610297982801-0.post@n7.nabble.com>

Hi all,

I am looking for a way to use `np.PyArray_MultiIterNew2` in Cython to
broadcast parameters of a function. The requirement is that the two
arguments can be scalar and/or sequences. Using the usual `np.broadcast`
function works well but is slow when iterating over the broadcasted input in
a tight loop. I want to achieve the same using the C API.

Currently, if I used `(<double*>np.PyArray_MultiIter_DATA(bcast, i))[0]` to
iterate over the input when one of them is a scalar,
I get no errors, but I notice the output of the parent function returns an
array of zeros, which implies this approach didn't work. After
investigating, it seems that np.PyArray_MultiIter_DATA only accepts numpy
arrays.

I could write a function to handle all combinations of
scalar/array/list/tuple, and create temporary arrays to store the input
data, but that seems daunting and error prone. Is there a way I can achieve
this and have scalar arguments passed to np.PyArray_MultiIter_DATA be
converted to same-element arrays without writing my own code from scratch?

Any suggestions are welcome.



--
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From sebastian at sipsolutions.net  Sun Jan 10 13:05:01 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Sun, 10 Jan 2021 12:05:01 -0600
Subject: [Numpy-discussion] using scalar input on
 np.PyArray_MultiIterNew2
In-Reply-To: <1610297982801-0.post@n7.nabble.com>
References: <1610297982801-0.post@n7.nabble.com>
Message-ID: <64ebf3bb7c0635b9575718ea043e5836046896bf.camel@sipsolutions.net>

On Sun, 2021-01-10 at 09:59 -0700, zoj613 wrote:
> Hi all,
> 
> I am looking for a way to use `np.PyArray_MultiIterNew2` in Cython to
> broadcast parameters of a function. The requirement is that the two
> arguments can be scalar and/or sequences. Using the usual
> `np.broadcast`
> function works well but is slow when iterating over the broadcasted
> input in
> a tight loop. I want to achieve the same using the C API.

NB: There is also a different, newer, iterator (`NpyIter_New`).
Depending on what you do, that might be a lot faster and better
(although, I admit it tends to be more verbose too).
That iterator also does broadcasting, and one nice property is that it
can allocate a result array.  Most importantly, it casts for you and
allows you to take charge of the inner-loop (a one dimensional loop)
for performance.  (This is the core of how ufuncs work.)

> Currently, if I used `(<double*>np.PyArray_MultiIter_DATA(bcast,
> i))[0]` to
> iterate over the input when one of them is a scalar,
> I get no errors, but I notice the output of the parent function
> returns an
> array of zeros, which implies this approach didn't work. After
> investigating, it seems that np.PyArray_MultiIter_DATA only accepts
> numpy
> arrays.

I am honestly confused by this (did you mean a different command?).
`PyArray_MultiIter_DATA` returns a pointer to the raw data, i.e. in
cython you would probably do:

    cdef double *value_ptr = <double *>npc.PyArray_MultiIter_DATA(iter, 0)
    value_ptr[0] = 3.1416

Do want to reference the original data?  You could reference the
original data for scalars (read-only since scalars are immutable), but
for lists/tuples there is no original data to begin with (unless you
have Python objects inside, but it would seem strange if NumPy to
attempted to transparently expose that).

> I could write a function to handle all combinations of
> scalar/array/list/tuple, and create temporary arrays to store the
> input

The typical pattern is to convert everything to array first, but
`PyArray_MultiIter()` does that for you. Unless you want to optimize
that conversion away?

Cheers,

Sebastian


> data, but that seems daunting and error prone. Is there a way I can
> achieve
> this and have scalar arguments passed to np.PyArray_MultiIter_DATA be
> converted to same-element arrays without writing my own code from
> scratch?
> 
> Any suggestions are welcome.
> 
> 
> 
> --
> Sent from: http://numpy-discussion.10968.n7.nabble.com/
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
> 

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From blkzol001 at myuct.ac.za  Sun Jan 10 13:39:02 2021
From: blkzol001 at myuct.ac.za (zoj613)
Date: Sun, 10 Jan 2021 11:39:02 -0700 (MST)
Subject: [Numpy-discussion] using scalar input on
 np.PyArray_MultiIterNew2
In-Reply-To: <64ebf3bb7c0635b9575718ea043e5836046896bf.camel@sipsolutions.net>
References: <1610297982801-0.post@n7.nabble.com>
 <64ebf3bb7c0635b9575718ea043e5836046896bf.camel@sipsolutions.net>
Message-ID: <1610303942634-0.post@n7.nabble.com>

 
Sebastian Berg wrote
> On Sun, 2021-01-10 at 09:59 -0700, zoj613 wrote:
>> Hi all,
>> 
>> I am looking for a way to use `np.PyArray_MultiIterNew2` in Cython to
>> broadcast parameters of a function. The requirement is that the two
>> arguments can be scalar and/or sequences. Using the usual
>> `np.broadcast`
>> function works well but is slow when iterating over the broadcasted
>> input in
>> a tight loop. I want to achieve the same using the C API.
> 
> NB: There is also a different, newer, iterator (`NpyIter_New`).
> Depending on what you do, that might be a lot faster and better
> (although, I admit it tends to be more verbose too).
> That iterator also does broadcasting, and one nice property is that it
> can allocate a result array.  Most importantly, it casts for you and
> allows you to take charge of the inner-loop (a one dimensional loop)
> for performance.  (This is the core of how ufuncs work.)
> 
>> Currently, if I used `(&lt;double*&gt;np.PyArray_MultiIter_DATA(bcast,
>> i))[0]` to
>> iterate over the input when one of them is a scalar,
>> I get no errors, but I notice the output of the parent function
>> returns an
>> array of zeros, which implies this approach didn't work. After
>> investigating, it seems that np.PyArray_MultiIter_DATA only accepts
>> numpy
>> arrays.
> 
> I am honestly confused by this (did you mean a different command?).
> `PyArray_MultiIter_DATA` returns a pointer to the raw data, i.e. in
> cython you would probably do:
> 
>     cdef double *value_ptr = 
> <double *>
> npc.PyArray_MultiIter_DATA(iter, 0)
>     value_ptr[0] = 3.1416
> 
> Do want to reference the original data?  You could reference the
> original data for scalars (read-only since scalars are immutable), but
> for lists/tuples there is no original data to begin with (unless you
> have Python objects inside, but it would seem strange if NumPy to
> attempted to transparently expose that).
> 
>> I could write a function to handle all combinations of
>> scalar/array/list/tuple, and create temporary arrays to store the
>> input
> 
> The typical pattern is to convert everything to array first, but
> `PyArray_MultiIter()` does that for you. Unless you want to optimize
> that conversion away?
> 
> Cheers,
> 
> Sebastian
> 
> 
>> data, but that seems daunting and error prone. Is there a way I can
>> achieve
>> this and have scalar arguments passed to np.PyArray_MultiIter_DATA be
>> converted to same-element arrays without writing my own code from
>> scratch?
>> 
>> Any suggestions are welcome.
>> 
>> 
>> 
>> --
>> Sent from: http://numpy-discussion.10968.n7.nabble.com/
>> _______________________________________________
>> NumPy-Discussion mailing list
>> 

> NumPy-Discussion@

>> https://mail.python.org/mailman/listinfo/numpy-discussion
>> 
> 
> I think I wasn't clear enough in my original question. Here is what I
> have:
> a python function with the signature: def pyfunc(a, b). This function
> calls another cython function internally such that
> def pyfunc(a, b):
>     ....
>     return cfunc(a, b)
> 
> I want the pyfunc to support scalar and array_like input for both
> parameters, so that internally I can have:
> def pyfunc(a, b):
>     ....
>     # some part of the function
>     for i, j in some_broadcasted_iterator:
>         output[indx] = cfunc(i, j)
> 
> Broadcasting using python level functions allows me to do this but then
> the iteration part is slow because it uses python python code, meaning I
> can't release the gil. What I was thinking of doing is using the C API to
> create the broadcasted iterator using PyArray_MultiIterNew2 then iterating
> over that. I kept getting a zero array as output when I tested it so I
> assumed that the function doesnt work with scalars. It turns out the bug
> was caused by me using integer scalars when the C function expects doubles
> (But I fixed that after creating this post).
> 
> Now I'm left with figuring out how I can efficiently convert even
> lists/tuple inputs into a broadcasted iterator (without requiring the user
> to pass numpy arrays). When I pass a list for parameter a and a scalar for
> parameter b, the program hangs, so Im not sure if the
> PyArray_MultiIterNew2 function does it for me?
> 
> Btw, do you have a link to the more recent NpyIter_New? I couldn't find it
> reading the C-API page in the docs.
> 
> 
> 
> _______________________________________________
> NumPy-Discussion mailing list

> NumPy-Discussion@

> https://mail.python.org/mailman/listinfo/numpy-discussion
> 
> 
> signature.asc (849 bytes)
> &lt;http://numpy-discussion.10968.n7.nabble.com/attachment/48862/0/signature.asc&gt;





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From blkzol001 at myuct.ac.za  Sun Jan 10 16:18:45 2021
From: blkzol001 at myuct.ac.za (zoj613)
Date: Sun, 10 Jan 2021 14:18:45 -0700 (MST)
Subject: [Numpy-discussion] using scalar and tuple/list input on
 np.PyArray_MultiIterNew2
In-Reply-To: <1610297982801-0.post@n7.nabble.com>
References: <1610297982801-0.post@n7.nabble.com>
Message-ID: <1610313525682-0.post@n7.nabble.com>

For what it's worth, I ended up defining a function like:
cdef np.broadcast broadcast(object a, object b):
    """
    Broadcast the inputs into a multiIterator object.
    the input can be a scalar, list, tuple or numpy array or array_like
object.
    """
    cdef bint is_a_seq = is_sequence(h)
    cdef bint is_a_seq = is_sequence(z)

    h = <double>h if not is_a_seq else np.PyArray_FROM_OT(a, np.NPY_DOUBLE)
    z = <double>z if not is_b_seq else np.PyArray_FROM_OT(b, np.NPY_DOUBLE)

    return np.PyArray_MultiIterNew2(a, b)

It seems to do exactly what I want. Not sure if there are any potential bugs
that could result from this approach.



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From frederix.noel at gmail.com  Mon Jan 11 05:51:14 2021
From: frederix.noel at gmail.com (Frederix96)
Date: Mon, 11 Jan 2021 11:51:14 +0100
Subject: [Numpy-discussion] numpy.linalg interference with matplot.lib
Message-ID: <360e70ad-386d-0cd4-1b38-67ddcf411445@gmail.com>

Dear numpy community,

I am having an issue with numpy.linalg where a matrix inversion of a 
complex matrix using numpy.linalg.inv results in containing nan values 
when a plot of any kind was performed beforehand by matplotlib. For the 
specific details on the problem and what I have tried already see the 
stackoverflow post I started a month ago:

https://stackoverflow.com/questions/65183984/why-does-plotting-something-with-matplotlib-change-the-first-outcome-of-a-numpy

I know that this problem has to do with some specifics of the maschine I 
am using, as it does not happen on other maschines I tried. However it 
still appears after rebuilding my entire python enviroment. Hence I ran 
out of options appart from setting up my whole PC from scratch again, 
which I would rather not do.

Is some problem like this known in the community?

Has anyone an idea at which other specifications of my system it might 
be worth taking a look at?

Thanks a lot in advance!

Best regards,

Frederix96



From kevin.k.sheppard at gmail.com  Mon Jan 11 06:02:02 2021
From: kevin.k.sheppard at gmail.com (Kevin Sheppard)
Date: Mon, 11 Jan 2021 11:02:02 +0000
Subject: [Numpy-discussion] numpy.linalg interference with matplot.lib
In-Reply-To: <360e70ad-386d-0cd4-1b38-67ddcf411445@gmail.com>
References: <360e70ad-386d-0cd4-1b38-67ddcf411445@gmail.com>
Message-ID: <CAE8Ss2GJ_+-US6fBpXED6QrPXD-8+gGtqc3sDdr=vADhvpSD+w@mail.gmail.com>

Are you using NumPy <= 1.19.3 and WIndows 2004 or 20H2?  If so, you should
upgrade to NumPy 1.19.5.

Kevin


On Mon, Jan 11, 2021 at 10:51 AM Frederix96 <frederix.noel at gmail.com> wrote:

> Dear numpy community,
>
> I am having an issue with numpy.linalg where a matrix inversion of a
> complex matrix using numpy.linalg.inv results in containing nan values
> when a plot of any kind was performed beforehand by matplotlib. For the
> specific details on the problem and what I have tried already see the
> stackoverflow post I started a month ago:
>
>
> https://stackoverflow.com/questions/65183984/why-does-plotting-something-with-matplotlib-change-the-first-outcome-of-a-numpy
>
> I know that this problem has to do with some specifics of the maschine I
> am using, as it does not happen on other maschines I tried. However it
> still appears after rebuilding my entire python enviroment. Hence I ran
> out of options appart from setting up my whole PC from scratch again,
> which I would rather not do.
>
> Is some problem like this known in the community?
>
> Has anyone an idea at which other specifications of my system it might
> be worth taking a look at?
>
> Thanks a lot in advance!
>
> Best regards,
>
> Frederix96
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From dsm054 at gmail.com  Mon Jan 11 10:55:08 2021
From: dsm054 at gmail.com (D. S. McNeil)
Date: Mon, 11 Jan 2021 10:55:08 -0500
Subject: [Numpy-discussion] How to speed up array generating
In-Reply-To: <188411610261382@mail.yandex.ru>
References: <2342291610218355@mail.yandex.ru>
 <c95a271ac82980d638e04edcc51dd438@esrf.fr>
 <188411610261382@mail.yandex.ru>
Message-ID: <CAOX9QiCUU+6vB7kM0=gPBCj56qC+ekO-k4ehgOLNfzc+3ASuBQ@mail.gmail.com>

As Sebastian said, it's going to take more information about context.  It's
very unlikely that you actually need these particular arrays-- probably,
you're interested in some more important result which you're using these
arrays as an intermediate step to obtain.  Their structure makes that even
more likely than usual.

Without knowing how they're being used, no one can know whether they should
be replaced by a nested numba or cython loop, or a clever use of einsum, or
who knows what else.

The minimum time code can take is no time. :-)


Doug

On Sun, 10 Jan 2021 at 02:00, <klark--kent at yandex.ru> wrote:

> Thank you but the same time:
>    import numpy as np
>     import time
>     N = 3000
>     m_0 = np.arange(N)
>     a = np.ones(N)
> #===== first =========
>     t1 = time.time()
>     m_1 = np.outer(m_0, a).ravel()
>     m_2 = np.outer(a, m_0).ravel()
>     t1 = time.time() - t1
> #===== second =======
>     t2 = time.time()
>     m_3 = np.tile(m_0, N)
>     m_4  = np.repeat(m_0, N)
>     t2 = time.time() - t2
> #==================
>     np.sum(m_1 - m_3)
>     np.sum(m_2 - m_4)
>     t1
>     t2
>
> 10.01.2021, 08:37, "V. Armando Sole" <sole at esrf.fr>:
>
> I guess the speed up, if any, will be machine dependent, but you can give
> a try at:
>
> import numpy as np
> import time
> N = 3000
> m_0 = np.arange(N)
> t = time.time()
> a = np.ones(N)
> m_1 = np.outer(m_0, a).ravel()
> m_2 = np.outer(a, m_0).ravel()
> t = time.time() - t
>
>
>
>
> On 2021-01-09 20:07, klark--kent at yandex.ru wrote:
>
> Hello. There is a random 1D array m_0 with size 3000, for example:
>
> m_0 = np.array([0, 1, 2])
>
> I need to generate two 1D arrays:
>
> m_1 = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])
> m_2 = np.array([0, 0, 0, 1, 1, 1, 2, 2, 2])
>
> Is there faster way to do it than this one:
>
> import numpy as npimport time
> N = 3
> m_0 = np.arange(N)
>
> t = time.time()
> m_1 = np.tile(m_0, N)
> m_2 = np.repeat(m_0, N)
> t = time.time() - t
>
> I tried other ways but they are slower or have the same time. Other NumPy operations in my code 10-100 times faster. Why the repeating an array is so slow? I need 10 times speed up. Thank you for your attantion to my problem.
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
> ,
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From sebastian at sipsolutions.net  Mon Jan 11 11:31:30 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Mon, 11 Jan 2021 10:31:30 -0600
Subject: [Numpy-discussion] using scalar and tuple/list input on
 np.PyArray_MultiIterNew2
In-Reply-To: <1610313525682-0.post@n7.nabble.com>
References: <1610297982801-0.post@n7.nabble.com>
 <1610313525682-0.post@n7.nabble.com>
Message-ID: <bcd288dc7e5f841a791a7dad548c1209563f920d.camel@sipsolutions.net>

On Sun, 2021-01-10 at 14:18 -0700, zoj613 wrote:
> For what it's worth, I ended up defining a function like:
> cdef np.broadcast broadcast(object a, object b):
> ??? """
> ??? Broadcast the inputs into a multiIterator object.
> ??? the input can be a scalar, list, tuple or numpy array or
> array_like
> object.
> ??? """
> ??? cdef bint is_a_seq = is_sequence(h)
> ??? cdef bint is_a_seq = is_sequence(z)
> 
> ??? h = <double>h if not is_a_seq else np.PyArray_FROM_OT(a,
> np.NPY_DOUBLE)
> ??? z = <double>z if not is_b_seq else np.PyArray_FROM_OT(b,
> np.NPY_DOUBLE)
> 
> ??? return np.PyArray_MultiIterNew2(a, b)
> 
> It seems to do exactly what I want. Not sure if there are any
> potential bugs
> that could result from this approach.
> 

I guess you snipped some code away that does something with h and z?
Maybe it would help if you give an example, because I am still not sure
why `np.PyArray_MultiIterNew2(a, b)` is not what you want.

Is the issue is that you need to ensure a `double` result, and
`MultiIterNew()` will be equivalent to `np.asarray(a)` and not
`np.asarray(a, dtype=np.double)`?  If you want to ensure a double
result, I think it is likely easiest if you just call:
     a = np.PyArray_FROM_OT(a, np.NPY_DOUBLE)

unconditionally.  That is equivalent to calling `np.asarray(a,
dtype=np.double)` and will ensure that you get the double result that
you expect (it will force cast though).
You could still special case scalars of course (this is especially true
if you expect Python scalars `isinstance(a, float):` is a very fast
check.

The new iterator requires you to convert to arrays (sorry for not
copying the link, oddly enough my copy-paste was acting up), but it if
they are of a different dtype, it would allow you to cast in a buffered
way (much better if you expect large arrays, likely not for smaller
ones):
    https://numpy.org/doc/stable/reference/c-api/iterator.html#simple-iteration-example

Hope this helps.

Cheers,

Sebastian




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From blkzol001 at myuct.ac.za  Mon Jan 11 18:06:16 2021
From: blkzol001 at myuct.ac.za (zoj613)
Date: Mon, 11 Jan 2021 16:06:16 -0700 (MST)
Subject: [Numpy-discussion] using scalar and tuple/list input on
 np.PyArray_MultiIterNew2
In-Reply-To: <bcd288dc7e5f841a791a7dad548c1209563f920d.camel@sipsolutions.net>
References: <1610297982801-0.post@n7.nabble.com>
 <1610313525682-0.post@n7.nabble.com>
 <bcd288dc7e5f841a791a7dad548c1209563f920d.camel@sipsolutions.net>
Message-ID: <1610406376864-0.post@n7.nabble.com>

No, The function is what I ended up with, I just forgot to change (h, z) to
(a, b). It works fine. Yes, I want to ensure that I end up with a double
type even if an integer value is passed. I didn't think of unconditionally
using np.PyArray_From_OT() even for scalars. I guess that is probably a
better approach instead of the if statements because ultimately for that
code block I want a broacasted array as a result, not scalars.  I will
experiment with the new multi-iterator interface and see if it is better
than the current approach. Thanks!



--
Sent from: http://numpy-discussion.10968.n7.nabble.com/

From chr.albert at gmail.com  Tue Jan 12 05:11:50 2021
From: chr.albert at gmail.com (Christopher Albert)
Date: Tue, 12 Jan 2021 11:11:50 +0100
Subject: [Numpy-discussion] Compilation failures in f2py
In-Reply-To: <9728d48d-e417-d789-7a65-11ef0485a5ea@speakeasy.net>
References: <9728d48d-e417-d789-7a65-11ef0485a5ea@speakeasy.net>
Message-ID: <CACrYDbEJgD8YAPwuKtv-B9d3o7Si3TXuBk5ux14wUurV8z452Q@mail.gmail.com>

Hi Sam,

looks like the XCode command line tools containing standard headers are
either not installed or updated. Try xcode-select --install or manually
download them from https://developer.apple.com/download/more/ and maybe
uninstall/reinstall them in case updates don't work. Check with

find /Library/Developer/CommandLineTools/ -name _stdio.h

which should
give /Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include/_stdio.h
(besides possible older versions of MacOSX)

Best,

Chris




Am Sa., 9. Jan. 2021 um 03:02 Uhr schrieb Samuel Dupree <
sdupree at speakeasy.net>:

> I'm attempting to wrap a Fortran-77 source member library using f2py.
> I'm running he Anaconda distribution for Python 3.7.6 on a Mac Pro
> (2019) under Mac OS X Big Sur (ver. 11.1). The version of Xcode.app I'm
> running is 12.3. The version of NumPy I'm running is 1.18.3.
>
> The errors I'm getting are from header files the compiler can't find as
> captured in the attached log file. A sample of the kind of errors I'm
> seeing are captured below.
>
> compile options:
> '-I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
>
> -I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include
> -I/Users/user/opt/anaconda3/include/python3.7m -c'
> gcc:
>
> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
> gcc:
>
> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c
> In file included from
>
> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
>                   from
>
> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
>                   from
> /Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
>                   from
>
> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61:
>
> error: no include path in which to search for limits.h
>    195 | #include_next <limits.h>  /* recurse down to the real one */
> |                                                             ^
> In file included from
> /Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
>                   from
>
> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10:
>
> fatal error: _stdio.h: No such file or directory
>     78 | #include <_stdio.h>
>        |          ^~~~~~~~~~
> compilation terminated.
>
> Any suggestions?
>
> Sam Dupree.
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From frederix.noel at gmail.com  Tue Jan 12 06:44:42 2021
From: frederix.noel at gmail.com (Frederix96)
Date: Tue, 12 Jan 2021 12:44:42 +0100
Subject: [Numpy-discussion] numpy.linalg interference with matplot.lib
Message-ID: <55086efc-21dc-cd8b-521a-96bbc1530909@gmail.com>

Dear Kevin,

Thanks for the suggestion. I do not have those Windows Versions.
I have Microsoft Windows 10 Pro with Version 10.0.19041 Build 19041.
Anyway I still tried upgrading to 1.19.5 with no changes.

Thanks a lot!

Best regards,

Frederix96





From sebastian at sipsolutions.net  Wed Jan 13 00:08:01 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Tue, 12 Jan 2021 23:08:01 -0600
Subject: [Numpy-discussion] NumPy Development Meeting Wednesday - Triage
 Focus
Message-ID: <7a75d9cbba4fbd15287f7644d9018e20eaf638b7.camel@sipsolutions.net>

Hi all,

Our bi-weekly triage-focused NumPy development meeting is tomorrow
(Wednesday, Jan 13th) at 11 am Pacific Time (19:00 UTC).
Everyone is invited to join in and edit the work-in-progress meeting
topics and notes:
https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg

I encourage everyone to notify us of issues or PRs that you feel should
be prioritized, discussed, or reviewed.

Best regards

Sebastian

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From matti.picus at gmail.com  Wed Jan 13 10:40:17 2021
From: matti.picus at gmail.com (Matti Picus)
Date: Wed, 13 Jan 2021 17:40:17 +0200
Subject: [Numpy-discussion] NumPy EOL Versions?
In-Reply-To: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
References: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
Message-ID: <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>

This message ended up in my spam box for some reason, sorry for the late 
reply.


We typically release a new version twice a year, and support two 
versions at a time. So right now we are releasing version 1.20 and will 
support 1.19 and 1.20 for the next period. When 1.21 is released, we 
will support 1.20 and 1.21. Support for the released version is limited 
to bug fixes.


Matti


On 12/16/20 6:24 PM, Symphoni Bush - NOAA Affiliate wrote:
> I am trying to find out if there are any end-of-life versions for 
> NumPy, and if so, when do these versions typically become 
> EOL/unsupported? Thanks.
>

From ralf.gommers at gmail.com  Wed Jan 13 11:03:24 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Wed, 13 Jan 2021 17:03:24 +0100
Subject: [Numpy-discussion] NumPy EOL Versions?
In-Reply-To: <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>
References: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
 <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>
Message-ID: <CABL7CQiAOfGW_tKKf5jX+WbKEpWjdCDSSK8uSPKVJju4dtkq8w@mail.gmail.com>

On Wed, Jan 13, 2021 at 4:41 PM Matti Picus <matti.picus at gmail.com> wrote:

> This message ended up in my spam box for some reason, sorry for the late
> reply.
>
>
> We typically release a new version twice a year, and support two
> versions at a time. So right now we are releasing version 1.20 and will
> support 1.19 and 1.20 for the next period. When 1.21 is released, we
> will support 1.20 and 1.21. Support for the released version is limited
> to bug fixes.
>

Is this two-version thing actually something we're committed to doing?
Chuck started doing it at some point, which as release manager is his
decision - but I don't think we ever really decided or announced this as a
policy.

If we're committed to it, we should probably mention it somewhere in the
docs or release how-to. And I should go update our Tidelift data.

Cheers,
Ralf
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From charlesr.harris at gmail.com  Wed Jan 13 12:47:53 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Wed, 13 Jan 2021 10:47:53 -0700
Subject: [Numpy-discussion] NumPy EOL Versions?
In-Reply-To: <CABL7CQiAOfGW_tKKf5jX+WbKEpWjdCDSSK8uSPKVJju4dtkq8w@mail.gmail.com>
References: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
 <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>
 <CABL7CQiAOfGW_tKKf5jX+WbKEpWjdCDSSK8uSPKVJju4dtkq8w@mail.gmail.com>
Message-ID: <CAB6mnxJHPGoxrDWyxsOAD5LabwefQjD6ikTtu2ekhaG2Ysvz7A@mail.gmail.com>

On Wed, Jan 13, 2021 at 9:04 AM Ralf Gommers <ralf.gommers at gmail.com> wrote:

>
>
> On Wed, Jan 13, 2021 at 4:41 PM Matti Picus <matti.picus at gmail.com> wrote:
>
>> This message ended up in my spam box for some reason, sorry for the late
>> reply.
>>
>>
>> We typically release a new version twice a year, and support two
>> versions at a time. So right now we are releasing version 1.20 and will
>> support 1.19 and 1.20 for the next period. When 1.21 is released, we
>> will support 1.20 and 1.21. Support for the released version is limited
>> to bug fixes.
>>
>
> Is this two-version thing actually something we're committed to doing?
> Chuck started doing it at some point, which as release manager is his
> decision - but I don't think we ever really decided or announced this as a
> policy.
>
> If we're committed to it, we should probably mention it somewhere in the
> docs or release how-to. And I should go update our Tidelift data.
>
> Cheers,
> Ralf
>
> We only support *one* version at a time. Supporting two is hard,
backports become difficult. The only time we have supported two was the
1.16.x LTS release. At the moment things are a bit different because we are
waiting on pyarrow before releasing 1.20.0, it is a temporary measure.

The binannual release cycle is because 300-500 merges per release felt
about right. If the merge rate goes way up and stays there we may release
more often. But that is unlikely unless we get a lot more support.

Chuck
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From charlesr.harris at gmail.com  Wed Jan 13 12:50:10 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Wed, 13 Jan 2021 10:50:10 -0700
Subject: [Numpy-discussion] NumPy EOL Versions?
In-Reply-To: <CAB6mnxJHPGoxrDWyxsOAD5LabwefQjD6ikTtu2ekhaG2Ysvz7A@mail.gmail.com>
References: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
 <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>
 <CABL7CQiAOfGW_tKKf5jX+WbKEpWjdCDSSK8uSPKVJju4dtkq8w@mail.gmail.com>
 <CAB6mnxJHPGoxrDWyxsOAD5LabwefQjD6ikTtu2ekhaG2Ysvz7A@mail.gmail.com>
Message-ID: <CAB6mnxLuhR0GM=bVffPfMavmPrLyw4ZFMRLSgoYQ=p3HEH2W-A@mail.gmail.com>

On Wed, Jan 13, 2021 at 10:47 AM Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
> On Wed, Jan 13, 2021 at 9:04 AM Ralf Gommers <ralf.gommers at gmail.com>
> wrote:
>
>>
>>
>> On Wed, Jan 13, 2021 at 4:41 PM Matti Picus <matti.picus at gmail.com>
>> wrote:
>>
>>> This message ended up in my spam box for some reason, sorry for the late
>>> reply.
>>>
>>>
>>> We typically release a new version twice a year, and support two
>>> versions at a time. So right now we are releasing version 1.20 and will
>>> support 1.19 and 1.20 for the next period. When 1.21 is released, we
>>> will support 1.20 and 1.21. Support for the released version is limited
>>> to bug fixes.
>>>
>>
>> Is this two-version thing actually something we're committed to doing?
>> Chuck started doing it at some point, which as release manager is his
>> decision - but I don't think we ever really decided or announced this as a
>> policy.
>>
>> If we're committed to it, we should probably mention it somewhere in the
>> docs or release how-to. And I should go update our Tidelift data.
>>
>> Cheers,
>> Ralf
>>
>> We only support *one* version at a time. Supporting two is hard,
> backports become difficult. The only time we have supported two was the
> 1.16.x LTS release. At the moment things are a bit different because we are
> waiting on pyarrow before releasing 1.20.0, it is a temporary measure.
>
> The binannual release cycle is because 300-500 merges per release felt
> about right. If the merge rate goes way up and stays there we may release
> more often. But that is unlikely unless we get a lot more support.
>
> The fmod problem also played a role in making a 1.19.5 release. I hope
that is also a one off.

Chuck
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From ralf.gommers at gmail.com  Wed Jan 13 12:56:39 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Wed, 13 Jan 2021 18:56:39 +0100
Subject: [Numpy-discussion] NumPy EOL Versions?
In-Reply-To: <CAB6mnxLuhR0GM=bVffPfMavmPrLyw4ZFMRLSgoYQ=p3HEH2W-A@mail.gmail.com>
References: <CAA5fwB7PP-9TfXN8t_QNLY-Fi1LUfP-DX6HwXzt37DrPjFQ5mQ@mail.gmail.com>
 <bcdf483a-9433-4656-14f1-8110914fb57a@gmail.com>
 <CABL7CQiAOfGW_tKKf5jX+WbKEpWjdCDSSK8uSPKVJju4dtkq8w@mail.gmail.com>
 <CAB6mnxJHPGoxrDWyxsOAD5LabwefQjD6ikTtu2ekhaG2Ysvz7A@mail.gmail.com>
 <CAB6mnxLuhR0GM=bVffPfMavmPrLyw4ZFMRLSgoYQ=p3HEH2W-A@mail.gmail.com>
Message-ID: <CABL7CQhLFLmP=21bvUi9rRKoUj30CjR5GxC3gvU7JqTW-trfBw@mail.gmail.com>

On Wed, Jan 13, 2021 at 6:50 PM Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
> On Wed, Jan 13, 2021 at 10:47 AM Charles R Harris <
> charlesr.harris at gmail.com> wrote:
>
>>
>>
>> On Wed, Jan 13, 2021 at 9:04 AM Ralf Gommers <ralf.gommers at gmail.com>
>> wrote:
>>
>>>
>>>
>>> On Wed, Jan 13, 2021 at 4:41 PM Matti Picus <matti.picus at gmail.com>
>>> wrote:
>>>
>>>> This message ended up in my spam box for some reason, sorry for the
>>>> late
>>>> reply.
>>>>
>>>>
>>>> We typically release a new version twice a year, and support two
>>>> versions at a time. So right now we are releasing version 1.20 and will
>>>> support 1.19 and 1.20 for the next period. When 1.21 is released, we
>>>> will support 1.20 and 1.21. Support for the released version is limited
>>>> to bug fixes.
>>>>
>>>
>>> Is this two-version thing actually something we're committed to doing?
>>> Chuck started doing it at some point, which as release manager is his
>>> decision - but I don't think we ever really decided or announced this as a
>>> policy.
>>>
>>> If we're committed to it, we should probably mention it somewhere in the
>>> docs or release how-to. And I should go update our Tidelift data.
>>>
>>> Cheers,
>>> Ralf
>>>
>>> We only support *one* version at a time. Supporting two is hard,
>> backports become difficult. The only time we have supported two was the
>> 1.16.x LTS release. At the moment things are a bit different because we are
>> waiting on pyarrow before releasing 1.20.0, it is a temporary measure.
>>
>> The binannual release cycle is because 300-500 merges per release felt
>> about right. If the merge rate goes way up and stays there we may release
>> more often. But that is unlikely unless we get a lot more support.
>>
>
Thanks for clarifying Chuck, that all makes perfect sense.

Cheers,
Ralf
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From dmi1 at lanl.gov  Fri Jan 15 13:38:27 2021
From: dmi1 at lanl.gov (Israel, Daniel M)
Date: Fri, 15 Jan 2021 18:38:27 +0000
Subject: [Numpy-discussion] Subclassing vs. dispatch
Message-ID: <e2038455a6e046b3ab5205b964c7be6c@lanl.gov>

I hope this is the right place to post this.

The numpy documentation talks about two methods for making ndarray-like objects, subclassing and dispatching, but it is not clear to me which one is most appropriate for which purpose.  Can someone provide, or point me to, some guidance, about this?  I?m particularly interested in what happens if there are multiple layers of subclassing.  Can you subclass from a subclass?  Dispatch from a dispatch?  Subclass from a dispatch and vice versa?

My specific application is a pair of classes, SpectralArray and PhysicalArray that uses numpy.fft to provides a to_physical() and to_spectral() method, respectively, to simplify writing pseudo-spectral codes.  Initially this will be serial, but the implementation will eventually use a mechanism similar to mpi4py-fft to allow the arrays to be distributed.  Further, it would be nice to be able to make the code interoperable with the cupy CUDA numpy implementation, so that the sub array on each MPI process could use GPU accelerated FFTs.

Advice?  Thanks.

?
Daniel M. Israel, Ph. D.
XCP-4: Methods & Algorithms
Mailstop F644
Los Alamos National Laboratory
505 665 5664<tel:505%20665%205664>
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From sebastian at sipsolutions.net  Fri Jan 15 18:10:06 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Fri, 15 Jan 2021 17:10:06 -0600
Subject: [Numpy-discussion] Subclassing vs. dispatch
In-Reply-To: <e2038455a6e046b3ab5205b964c7be6c@lanl.gov>
References: <e2038455a6e046b3ab5205b964c7be6c@lanl.gov>
Message-ID: <027d115b6b38f209017d7db6047bb59be0dfea73.camel@sipsolutions.net>

On Fri, 2021-01-15 at 18:38 +0000, Israel, Daniel M wrote:
> I hope this is the right place to post this.
> 
> The numpy documentation talks about two methods for making ndarray-
> like objects, subclassing and dispatching, but it is not clear to me
> which one is most appropriate for which purpose.? Can someone
> provide, or point me to, some guidance, about this?? I?m particularly
> interested in what happens if there are multiple layers of
> subclassing.? Can you subclass from a subclass?? Dispatch from a
> dispatch?? Subclass from a dispatch and vice versa?

All of those things can be made to work with appropriate use of
`super()`. Subclassing and dispatching are not exclusive (an example is
astropy.quantitile`).

If you want to go well beyond typical NumPy behaviour, I would suggest
to focus on dispatching. If all you want is to add a single method,
subclassing should be a pretty good fit. (Assuming you don't mind if
some operations may end up giving you a normal array, or return your
array when a normal array would fit better.)

For example, MaskedArray in NumPy is a subclass, but adds so much
additional things that dispatching without subclassing is likely a
better fit. (Opinions will probably differ; I expect using subclassing
some things will "just work". However, sometimes the things that "just
work" may also do the wrong thing).  Ignoring the mask of a MaskedArray
is always a serious issues.

> My specific application is a pair of classes, SpectralArray and
> PhysicalArray that uses numpy.fft to provides a to_physical() and
> to_spectral() method, respectively, to simplify writing pseudo-
> spectral codes.? Initially this will be serial, but the
> implementation will eventually use a mechanism similar to mpi4py-fft
> to allow the arrays to be distributed.? Further, it would be nice to
> be able to make the code interoperable with the cupy CUDA numpy
> implementation, so that the sub array on each MPI process could use
> GPU accelerated FFTs.

It sounds like you mostly want to add a set of method, so making a
MixIn class and using subclassing may well be a good option.  You can
still add `__array_function__` or `__array_ufunc__` with a fallback to
`super()` to override specific functions.

If there is more to it (e.g. metadata for frequency scales or similar),
it may be better to skip subclassing altogether. (Just to mention: in
such a case `xarray` may be interesting.)

Since you are also looking for distributed arrays, you should probably
look into Dask (I do not know `mpyi4py` though). Dask arrays consist of
distributed NumPy or CuPy arrays and make use of the dispatching in
NumPy.
Note that NumPy arrays cannot be distributed or gpu backed, and you
cannot add using a subclass. So if that is the aim, do not subclass
ndarray unless you were prepared to create multiple (sub)classes
(ndarray, dask array, cupy array).

Cheers,

Sebastian


> 
> Advice?? Thanks.
> 
> ?
> Daniel M. Israel, Ph. D.
> XCP-4: Methods & Algorithms
> Mailstop F644
> Los Alamos National Laboratory
> 505 665 5664<tel:505%20665%205664>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From melissawm at gmail.com  Fri Jan 15 18:50:52 2021
From: melissawm at gmail.com (=?UTF-8?Q?Melissa_Mendon=C3=A7a?=)
Date: Fri, 15 Jan 2021 20:50:52 -0300
Subject: [Numpy-discussion] Documentation Team meeting - Monday January 18
In-Reply-To: <CAC7J6VZX57n+_nWL-dKe4YzqY=Nc1=LYRXkNv8+JcP=q3Vyqog@mail.gmail.com>
References: <CAC7J6Vbkch+=wQcEbJgELAphM2d2552Ywr2txrbinUR-khTR=g@mail.gmail.com>
 <CAC7J6VY9k_EGL-adWpeHLvFOEG6EBy3wauhD8cZ5vmL-JDxA0Q@mail.gmail.com>
 <CAC7J6VaNwZDbtt4FP6mX_-+iD_d=_4VVcjdGiaJj=q7eWCHewA@mail.gmail.com>
 <CAC7J6VZ2D8q0s7+rpKv7HYh9oBqwOQnUP_HjwKCjMtAnfi60Og@mail.gmail.com>
 <CAC7J6VY=vgKXySL1Euy30ZNzqkqvcr4Za1L04JZv-GCk87c1AQ@mail.gmail.com>
 <CAC7J6Vbq0vtd5JH6MXvcSj4A4aZjg+x=QdHvPyQGeGcmpp8JYg@mail.gmail.com>
 <CAC7J6VZ_+uh967zGc7qA6+KWKsP=gZ8bZecrJ9Hq9oG0JTzsOg@mail.gmail.com>
 <CAC7J6VZkder9wiEmE+Cm5Lxg0zt0t_a-KwfuvcCXZG91Wk+7kA@mail.gmail.com>
 <CAC7J6VYyt4c2qcp92iE8_BMF70cUC3-ZX5E5mqNa0zVAFryvmQ@mail.gmail.com>
 <CAC7J6VZq1DLDk--F+S6F50DHMMXOaWo6cbpSau7APHe22X_c9w@mail.gmail.com>
 <CAC7J6VaegMEY9dvMeRSe2YY=AUEJYkXNNF-KTy89zyE6LgHo5A@mail.gmail.com>
 <CAC7J6VY4_X-MyXajy0KryML03KoryKR9n5dsf5bupgv7noukUg@mail.gmail.com>
 <CAC7J6Va3n9Hdym+RmscOkDyf1ukH+DDtCv7N9D8y0cX1a+uC-A@mail.gmail.com>
 <CAC7J6VZX57n+_nWL-dKe4YzqY=Nc1=LYRXkNv8+JcP=q3Vyqog@mail.gmail.com>
Message-ID: <CAC7J6Vb5uGp-gEMudbbiWSBKo1gyMsq03M4hz9mnNYir9GcqXw@mail.gmail.com>

Hi all!

Our next Documentation Team meeting will be on *Monday, January 18* at ***4PM
UTC***. All are welcome - you don't need to already be a contributor to
join. If you have questions or are curious about what we're doing, we'll be
happy to meet you!

If you wish to join on Zoom, use this link:

https://zoom.us/j/96219574921?pwd=VTRNeGwwOUlrYVNYSENpVVBRRjlkZz09
<https://zoom.us/j/420005230>

Here's the permanent hackmd document with the meeting notes (still being
updated in the next few days!):

https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg
<https://www.google.com/url?q=https%3A%2F%2Fhackmd.io%2FoB_boakvRqKR-_2jRV-Qjg&sa=D&usd=2&usg=AFQjCNGIOzVwlfDFd6YAgBwVUjmjQKWRSw>

Hope to see you around!

** You can click this link to get the correct time at your timezone:
https://www.timeanddate.com/worldclock/fixedtime.html?msg=NumPy+Documentation+Team+Meeting&iso=20210118T16&p1=1440&ah=1


- Melissa
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From malyasova.viktoriya at yandex.ru  Sat Jan 16 07:00:26 2021
From: malyasova.viktoriya at yandex.ru (=?utf-8?B?0JLQuNC60YLQvtGA0LjRjyDQnNCw0LvRj9GB0L7QstCw?=)
Date: Sat, 16 Jan 2021 15:00:26 +0300
Subject: [Numpy-discussion] UPD: Rivest-Floyd selection algorithm
Message-ID: <691391610798103@mail.yandex.ru>

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From sebastian at sipsolutions.net  Wed Jan 20 00:16:58 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Tue, 19 Jan 2021 23:16:58 -0600
Subject: [Numpy-discussion] NumPy Community Meeting Wednesday
Message-ID: <a1edd28d1b9c4b030e80b8198865a0a2b90bf99b.camel@sipsolutions.net>

Hi all,

There will be a NumPy Community meeting Wednesday January 20th at 12pm
Pacific Time (20:00 UTC). Everyone is invited and encouraged to
join in and edit the work-in-progress meeting topics and notes at:

https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both

Best wishes

Sebastian

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From sdupree at speakeasy.net  Sat Jan 23 15:22:18 2021
From: sdupree at speakeasy.net (Samuel Dupree)
Date: Sat, 23 Jan 2021 15:22:18 -0500
Subject: [Numpy-discussion] Compilation failures in f2py
In-Reply-To: <CACrYDbEJgD8YAPwuKtv-B9d3o7Si3TXuBk5ux14wUurV8z452Q@mail.gmail.com>
References: <9728d48d-e417-d789-7a65-11ef0485a5ea@speakeasy.net>
 <CACrYDbEJgD8YAPwuKtv-B9d3o7Si3TXuBk5ux14wUurV8z452Q@mail.gmail.com>
Message-ID: <e9927121-e058-1f65-2203-7d4e04b7c141@speakeasy.net>

Chris,

Thank you for responding to my post. I uninstalled and then reinstalled 
CommandLineTools per your suggestion. I'm still getting the same error. 
It appears that gcc is not seeing any of the CommandLineTools 
directories. When I ran the command

find /Library/Developer/CommandLineTools/ -name _stdio.h

I got:

(base) user at Mac-Pro ~ % find /Library/Developer/CommandLineTools/ -name 
_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/xlocale/_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/secure/_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/xlocale/_stdio.h
/Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/secure/_stdio.h

Any suggestions?

Sam Dupree.




On January/12/2021 05:11:50, Christopher Albert wrote:
> Hi Sam,
>
> looks like the XCode command line tools containing standard headers 
> are either not installed or updated. Try xcode-select --install or 
> manually download them from https://developer.apple.com/download/more/ 
> <https://developer.apple.com/download/more/> and maybe 
> uninstall/reinstall them in case updates don't work. Check with
>
> find /Library/Developer/CommandLineTools/ -name _stdio.h
>
> which should 
> give?/Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include/_stdio.h 
> (besides possible older versions of MacOSX)
>
> Best,
>
> Chris
>
>
>
>
> Am Sa., 9. Jan. 2021 um 03:02?Uhr schrieb Samuel Dupree 
> <sdupree at speakeasy.net <mailto:sdupree at speakeasy.net>>:
>
>     I'm attempting to wrap a Fortran-77 source member library using f2py.
>     I'm running he Anaconda distribution for Python 3.7.6 on a Mac Pro
>     (2019) under Mac OS X Big Sur (ver. 11.1). The version of
>     Xcode.app I'm
>     running is 12.3. The version of NumPy I'm running is 1.18.3.
>
>     The errors I'm getting are from header files the compiler can't
>     find as
>     captured in the attached log file. A sample of the kind of errors I'm
>     seeing are captured below.
>
>     compile options:
>     '-I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
>
>     -I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include
>
>     -I/Users/user/opt/anaconda3/include/python3.7m -c'
>     gcc:
>     /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
>     gcc:
>     /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c
>     In file included from
>     /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
>     ????????????????? from
>     /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
>     ????????????????? from
>     /Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
>     ????????????????? from
>     /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
>     /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61:
>
>     error: no include path in which to search for limits.h
>     ?? 195 | #include_next <limits.h>? /* recurse down to the real one */
>     | ^
>     In file included from
>     /Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
>     ????????????????? from
>     /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
>     /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10:
>
>     fatal error: _stdio.h: No such file or directory
>     ??? 78 | #include <_stdio.h>
>     ?????? |????????? ^~~~~~~~~~
>     compilation terminated.
>
>     Any suggestions?
>
>     Sam Dupree.
>
>
>     _______________________________________________
>     NumPy-Discussion mailing list
>     NumPy-Discussion at python.org <mailto:NumPy-Discussion at python.org>
>     https://mail.python.org/mailman/listinfo/numpy-discussion
>     <https://mail.python.org/mailman/listinfo/numpy-discussion>
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From klark--kent at yandex.ru  Sun Jan 24 09:20:59 2021
From: klark--kent at yandex.ru (klark--kent at yandex.ru)
Date: Sun, 24 Jan 2021 17:20:59 +0300
Subject: [Numpy-discussion] IRFFT of sound
Message-ID: <3254501611497677@mail.yandex.ru>

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From matthieu.brucher at gmail.com  Sun Jan 24 09:45:32 2021
From: matthieu.brucher at gmail.com (Matthieu Brucher)
Date: Sun, 24 Jan 2021 14:45:32 +0000
Subject: [Numpy-discussion] IRFFT of sound
In-Reply-To: <3254501611497677@mail.yandex.ru>
References: <3254501611497677@mail.yandex.ru>
Message-ID: <CAHCaCk+eP40v=3o_L=z1x2vYtOcxgEBSTa3NZQijWFouo99_6Q@mail.gmail.com>

Hi,

You need the angle to restore the sound. Otherwise you don't get the
phase information.
Just store the angle information and apply it?

Cheers,

Matthieu

Le dim. 24 janv. 2021 ? 14:27, <klark--kent at yandex.ru> a ?crit :
>
> Hello friends!
> Maybe that's not directly a Numpy question but I think it can be solved by Numpy.
> I do RFFT of microphone sound and find its absolute value np.abs(). Than I need to do IRFFT but I don't know how to restore sinusoida after np.abs(). I can't not to use 'abs'. I need it in my code. Is there any rough way to restore sound sinusoidal signal from its absolute values. Thank you for your attention!
>
> import numpy as np
> import scipy
> import matplotlib.pyplot as plt
> from scipy.fft import rfft
> from scipy.fft import irfft
>
> amplituda = 200
> width = 20
> CHUNK = 1024
> x1 = np.arange(CHUNK)
> x2 = np.arange(CHUNK//2)
> y = []
> for i in range(len(x1)):
>     y.append(np.sin(x1[i]/width)*amplituda)
>
> fig = plt.figure()
> ax1 = fig.add_subplot(2,2,1)
> ax3 = fig.add_subplot(2,2,2)
> ax2 = fig.add_subplot(2,2,3)
> ax4 = fig.add_subplot(2,2,4)
>
> # RFFT
> y_rfft = rfft(y)
>
> # IRFFT without abs
> y_irfft = irfft(y_rfft)
>
> # IRFFT with abs
> y_irfft_abs = irfft(np.abs(y_rfft))
>
> a = ax1.plot(x1, y, color='green')
> a = ax2.plot(x2, y_rfft[1:513], color='green')
> a = ax3.plot(x1, y_irfft, color='green')
> a = ax4.plot(x1, y_irfft_abs, color='green')
>
> a = ax1.set_title('Raw signal', fontsize = 8)
> a = ax2.set_title('Spectrum (rfft)', fontsize = 8)
> a = ax3.set_title('(irfft) without abs', fontsize = 8)
> a = ax4.set_title('(irfft) with abs "np.abs(y_rfft)"', fontsize = 8)
>
> a = plt.show()
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion



-- 
Quantitative researcher, Ph.D.
Blog: http://blog.audio-tk.com/
LinkedIn: http://www.linkedin.com/in/matthieubrucher

From chr.albert at gmail.com  Mon Jan 25 03:41:16 2021
From: chr.albert at gmail.com (Christopher Albert)
Date: Mon, 25 Jan 2021 09:41:16 +0100
Subject: [Numpy-discussion] Compilation failures in f2py
In-Reply-To: <e9927121-e058-1f65-2203-7d4e04b7c141@speakeasy.net>
References: <9728d48d-e417-d789-7a65-11ef0485a5ea@speakeasy.net>
 <CACrYDbEJgD8YAPwuKtv-B9d3o7Si3TXuBk5ux14wUurV8z452Q@mail.gmail.com>
 <e9927121-e058-1f65-2203-7d4e04b7c141@speakeasy.net>
Message-ID: <CACrYDbHn7+LKrgfArK8eKbPLTx-k0Wmgu9tvYspqqDX2FeGH7A@mail.gmail.com>

Sam,

the last suggestion from my side would be to upgrade or reinstall macports
from https://www.macports.org/install.php and/or set your gcc compiler
version to the latest one via port select. Then I'm out of clues too.

Best,

Chris


Am Sa., 23. Jan. 2021 um 21:22 Uhr schrieb Samuel Dupree <
sdupree at speakeasy.net>:

> Chris,
>
> Thank you for responding to my post. I uninstalled and then reinstalled
> CommandLineTools per your suggestion. I'm still getting the same error. It
> appears that gcc is not seeing any of the CommandLineTools directories.
> When I ran the command
> find /Library/Developer/CommandLineTools/ -name _stdio.h
>
> I got:
>
> (base) user at Mac-Pro ~ % find /Library/Developer/CommandLineTools/ -name
> _stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/_stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/xlocale/_stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX11.1.sdk/usr/include/secure/_stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/_stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/xlocale/_stdio.h
>
> /Library/Developer/CommandLineTools//SDKs/MacOSX10.15.sdk/usr/include/secure/_stdio.h
>
> Any suggestions?
>
> Sam Dupree.
>
>
>
>
> On January/12/2021 05:11:50, Christopher Albert wrote:
>
> Hi Sam,
>
> looks like the XCode command line tools containing standard headers are
> either not installed or updated. Try xcode-select --install or manually
> download them from https://developer.apple.com/download/more/ and maybe
> uninstall/reinstall them in case updates don't work. Check with
>
> find /Library/Developer/CommandLineTools/ -name _stdio.h
>
> which should
> give /Library/Developer/CommandLineTools/SDKs/MacOSX10.15.sdk/usr/include/_stdio.h
> (besides possible older versions of MacOSX)
>
> Best,
>
> Chris
>
>
>
>
> Am Sa., 9. Jan. 2021 um 03:02 Uhr schrieb Samuel Dupree <
> sdupree at speakeasy.net>:
>
>> I'm attempting to wrap a Fortran-77 source member library using f2py.
>> I'm running he Anaconda distribution for Python 3.7.6 on a Mac Pro
>> (2019) under Mac OS X Big Sur (ver. 11.1). The version of Xcode.app I'm
>> running is 12.3. The version of NumPy I'm running is 1.18.3.
>>
>> The errors I'm getting are from header files the compiler can't find as
>> captured in the attached log file. A sample of the kind of errors I'm
>> seeing are captured below.
>>
>> compile options:
>> '-I/var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7
>>
>> -I/Users/user/opt/anaconda3/lib/python3.7/site-packages/numpy/core/include
>>
>> -I/Users/user/opt/anaconda3/include/python3.7m -c'
>> gcc:
>>
>> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c
>> gcc:
>>
>> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/fortranobject.c
>> In file included from
>>
>> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/syslimits.h:7,
>>                   from
>>
>> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:34,
>>                   from
>> /Users/user/opt/anaconda3/include/python3.7m/Python.h:11,
>>                   from
>>
>> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
>> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/limits.h:195:61:
>>
>> error: no include path in which to search for limits.h
>>    195 | #include_next <limits.h>  /* recurse down to the real one */
>> |                                                             ^
>> In file included from
>> /Users/user/opt/anaconda3/include/python3.7m/Python.h:25,
>>                   from
>>
>> /var/folders/2r/4bw6nw0x58z0_ybx632_h14m0000gq/T/tmp5uemdb2k/src.macosx-10.9-x86_64-3.7/sofapymodule.c:14:
>> /opt/local/lib/gcc10/gcc/x86_64-apple-darwin20/10.2.0/include-fixed/stdio.h:78:10:
>>
>> fatal error: _stdio.h: No such file or directory
>>     78 | #include <_stdio.h>
>>        |          ^~~~~~~~~~
>> compilation terminated.
>>
>> Any suggestions?
>>
>> Sam Dupree.
>>
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at python.org
>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>
>
> _______________________________________________
> NumPy-Discussion mailing listNumPy-Discussion at python.orghttps://mail.python.org/mailman/listinfo/numpy-discussion
>
>
>
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From melissawm at gmail.com  Mon Jan 25 12:44:22 2021
From: melissawm at gmail.com (=?UTF-8?Q?Melissa_Mendon=C3=A7a?=)
Date: Mon, 25 Jan 2021 14:44:22 -0300
Subject: [Numpy-discussion] NumPy video content: creating a YouTube channel
Message-ID: <CAC7J6VZwe-GavuE3t=jOoBw5AM-9H13hHXHc6g_U+xZZt=DUuw@mail.gmail.com>

Hi all,

The NumPy Documentation Team has been discussing video content as part of
our outreach and documentation efforts, in part inspired by the excellent
Spyder IDE channel [1]. At our last meeting, we realized there is already a
good amount of content about NumPy on YouTube (a few examples [2, 3, 4]).
We thought about creating a YouTube account for NumPy and listing those
videos in a playlist, initially. Eventually, we can also add our own videos
about how to contribute - we're still brainstorming on those.

I'm writing to the mailing list to ask the community for input on creating
this as an official channel for NumPy. If you have any thoughts or
questions regarding this, please let us know.

Cheers,

Melissa

[1] https://www.youtube.com/channel/UCAOyvaOj7dMnavvGUkz9Djg
[2] https://www.youtube.com/watch?v=dBTJD_FDVjU
[3] https://www.youtube.com/watch?v=lHJqOE5j6xE
[4] https://www.youtube.com/watch?v=ZB7BZMhfPgk
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From sebastian at sipsolutions.net  Mon Jan 25 20:00:36 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Mon, 25 Jan 2021 19:00:36 -0600
Subject: [Numpy-discussion] Value based promotion and user DTypes
Message-ID: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>

Hi all,

does anyone have a thought about how user DTypes (i.e. DTypes not
currently part of NumPy) should interact with the "value based
promotion" logic we currently have?
For now I can just do anything, and we will find out later.  And I will
have to do something for now, basically with the hope that it all turns
out all-right.

But there are multiple options for both what to offer to user DTypes
and where we want to move (I am using `bfloat16` as a potential DType
here).

1. The "weak" dtype option (this is what JAX does), where:

       np.array([1], dtype=bfloat16) + 4.

   returns a bfloat16, because 4. is "lower" than all floating
   point types.
   In this scheme the user defined `bfloat16` knows that the input
   is a Python float, but it does not know its value (if an
   overflow occurs during conversion, it could warn or error but
   not upcast).  For example `np.array([1], dtype=uint4) + 2**5`
   will try `uint4(2**5)` assuming it works.
   NumPy is different `2.**300` would ensure the result is a `float64`.

   If a DType does not make use of this, it would get the behaviour
   of option 2.

2. The "default" DType option: np.array([1], dtype=bfloat16) + 4. is
   always the same as `bfloat16 + float64 -> float64`.

3. Use whatever NumPy considers the "smallest appropriate dtype".
   This will not always work correctly for unsigned integers, and for
   floats this would be float16, which doesn't help with bfloat16.

4. Try to expose the actual value. (I do not want to do this, but it
   is probably a plausible extension with most other options, since
   the other options can be the "default".)


Within these options, there is one more difficulty. NumPy currently
applies the same logic for:

    np.array([1], dtype=bfloat16) + np.array(4., dtype=np.float64)

which in my opinion is wrong (the second array is typed). We do have
the same issue with deciding what to do in the future for NumPy itself.
Right now I feel that new (user) DTypes should live in the future
(whatever that future is).

I have said previously, that we could distinguish this for universal
functions.  But calls like `np.asarray(4.)` are common, and they would
lose the information that `4.` was originally a Python float.


So, recently, I was considering that a better option may be to limit
this to math Python operators: +, -, /, **, ...

Those are the places where it may make a difference to write:

    arr + 4.         vs.    arr + bfloat16(4.)
    int8_arr + 1     vs.    int8_arr + np.int8(1)
    arr += 4.      (in-place may be the most significant use-case)

while:

    np.add(int8_arr, 1)    vs.   np.add(int8_arr, np.int8(1))

is maybe less significant. On the other hand, it would add a subtle
difference between operators vs. direct ufunc calls...


In general, it may not matter: We can choose option 1 (which the
bfloat16 does not have to use), and modify it if we ever change the
logic in NumPy itself.  Basically, I will probably pick option 1 for
now and press on, and we can reconsider later.  And hope that it does
not make things even more complicated than it is now.

Or maybe better just limit it completely to always use the default for
user DTypes?


But I would be interested if the "limit to Python operators" is
something we should aim for here.  This does make a small difference,
because user DTypes could "live" in the future if we have an idea of
how that future may look like.

Cheers,

Sebastian
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From ralf.gommers at gmail.com  Tue Jan 26 00:11:46 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Tue, 26 Jan 2021 06:11:46 +0100
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
Message-ID: <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>

On Tue, Jan 26, 2021 at 2:01 AM Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> Hi all,
>
> does anyone have a thought about how user DTypes (i.e. DTypes not
> currently part of NumPy) should interact with the "value based
> promotion" logic we currently have?
> For now I can just do anything, and we will find out later.  And I will
> have to do something for now, basically with the hope that it all turns
> out all-right.
>
> But there are multiple options for both what to offer to user DTypes
> and where we want to move (I am using `bfloat16` as a potential DType
> here).
>
> 1. The "weak" dtype option (this is what JAX does), where:
>
>        np.array([1], dtype=bfloat16) + 4.
>
>    returns a bfloat16, because 4. is "lower" than all floating
>    point types.
>    In this scheme the user defined `bfloat16` knows that the input
>    is a Python float, but it does not know its value (if an
>    overflow occurs during conversion, it could warn or error but
>    not upcast).  For example `np.array([1], dtype=uint4) + 2**5`
>    will try `uint4(2**5)` assuming it works.
>    NumPy is different `2.**300` would ensure the result is a `float64`.
>
>    If a DType does not make use of this, it would get the behaviour
>    of option 2.
>
> 2. The "default" DType option: np.array([1], dtype=bfloat16) + 4. is
>    always the same as `bfloat16 + float64 -> float64`.
>
> 3. Use whatever NumPy considers the "smallest appropriate dtype".
>    This will not always work correctly for unsigned integers, and for
>    floats this would be float16, which doesn't help with bfloat16.
>
> 4. Try to expose the actual value. (I do not want to do this, but it
>    is probably a plausible extension with most other options, since
>    the other options can be the "default".)
>
>
> Within these options, there is one more difficulty. NumPy currently
> applies the same logic for:
>
>     np.array([1], dtype=bfloat16) + np.array(4., dtype=np.float64)
>
> which in my opinion is wrong (the second array is typed). We do have
> the same issue with deciding what to do in the future for NumPy itself.
> Right now I feel that new (user) DTypes should live in the future
> (whatever that future is).
>

I agree. And I have a preference for option 1. Option 2 is too greedy in
upcasting, the value-based casting is problematic in multiple ways (e.g.,
hard for Numba because output dtype cannot be predicted from input dtypes),
and option 4 is hard to understand a rationale for (maybe so the user dtype
itself can implement option 3?).


> I have said previously, that we could distinguish this for universal
> functions.  But calls like `np.asarray(4.)` are common, and they would
> lose the information that `4.` was originally a Python float.
>

Hopefully the future will have way fewer asarray calls in it. Rejecting
scalar input to functions would be nice. This is what most other
array/tensor libraries do.


>
> So, recently, I was considering that a better option may be to limit
> this to math Python operators: +, -, /, **, ...
>

+1

This discussion may be relevant:
https://github.com/data-apis/array-api/issues/14.


> Those are the places where it may make a difference to write:
>
>     arr + 4.         vs.    arr + bfloat16(4.)
>     int8_arr + 1     vs.    int8_arr + np.int8(1)
>     arr += 4.      (in-place may be the most significant use-case)
>
> while:
>
>     np.add(int8_arr, 1)    vs.   np.add(int8_arr, np.int8(1))
>
> is maybe less significant. On the other hand, it would add a subtle
> difference between operators vs. direct ufunc calls...
>
>
> In general, it may not matter: We can choose option 1 (which the
> bfloat16 does not have to use), and modify it if we ever change the
> logic in NumPy itself.  Basically, I will probably pick option 1 for
> now and press on, and we can reconsider later.  And hope that it does
> not make things even more complicated than it is now.
>
> Or maybe better just limit it completely to always use the default for
> user DTypes?
>

I'm not sure I understand why you like option 1 but want to give
user-defined dtypes the choice of opting out of it. Upcasting will rarely
make sense for user-defined dtypes anyway.


>
> But I would be interested if the "limit to Python operators" is
> something we should aim for here.  This does make a small difference,
> because user DTypes could "live" in the future if we have an idea of
> how that future may look like.
>

A future with:
- no array scalars
- 0-D arrays have the same casting rules as >=1-D arrays
- no value-based casting
would be quite nice. For "same kind" casting like
https://data-apis.github.io/array-api/latest/API_specification/type_promotion.html.
Mixed-kind casting isn't specified there, because it's too different
between libraries. The JAX design (
https://jax.readthedocs.io/en/latest/type_promotion.html)  seems sensible
there.

Cheers,
Ralf
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From ralf.gommers at gmail.com  Tue Jan 26 00:11:59 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Tue, 26 Jan 2021 06:11:59 +0100
Subject: [Numpy-discussion] NumPy video content: creating a YouTube
 channel
In-Reply-To: <CAC7J6VZwe-GavuE3t=jOoBw5AM-9H13hHXHc6g_U+xZZt=DUuw@mail.gmail.com>
References: <CAC7J6VZwe-GavuE3t=jOoBw5AM-9H13hHXHc6g_U+xZZt=DUuw@mail.gmail.com>
Message-ID: <CABL7CQjfN4LJ8BWiZJLbf8+xRah4fx5k1v49mjufJh9BGKcvHg@mail.gmail.com>

On Mon, Jan 25, 2021 at 6:45 PM Melissa Mendon?a <melissawm at gmail.com>
wrote:

> Hi all,
>
> The NumPy Documentation Team has been discussing video content as part of
> our outreach and documentation efforts, in part inspired by the excellent
> Spyder IDE channel [1]. At our last meeting, we realized there is already a
> good amount of content about NumPy on YouTube (a few examples [2, 3, 4]).
> We thought about creating a YouTube account for NumPy and listing those
> videos in a playlist, initially. Eventually, we can also add our own videos
> about how to contribute - we're still brainstorming on those.
>
> I'm writing to the mailing list to ask the community for input on creating
> this as an official channel for NumPy. If you have any thoughts or
> questions regarding this, please let us know.
>

Sounds like a great idea to me! There are some more NumPy talk videos
listed on https://numpy.org/learn/.

Cheers,
Ralf


> Cheers,
>
> Melissa
>
> [1] https://www.youtube.com/channel/UCAOyvaOj7dMnavvGUkz9Djg
> [2] https://www.youtube.com/watch?v=dBTJD_FDVjU
> [3] https://www.youtube.com/watch?v=lHJqOE5j6xE
> [4] https://www.youtube.com/watch?v=ZB7BZMhfPgk
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From jh at physics.ucf.edu  Tue Jan 26 00:50:28 2021
From: jh at physics.ucf.edu (Joe Harrington)
Date: Tue, 26 Jan 2021 00:50:28 -0500
Subject: [Numpy-discussion] NumPy video content: creating a YouTube
 channel
In-Reply-To: <mailman.13182.1611637919.7190.numpy-discussion@python.org>
References: <mailman.13182.1611637919.7190.numpy-discussion@python.org>
Message-ID: <2936b918-92d9-e969-b7d1-c4e5a819593a@physics.ucf.edu>

On 1/25/21, 12:44 PM, Melissa Mendon?a <melissawm at gmail.com> wrote:
> The NumPy Documentation Team has been discussing video content as part 
> of our outreach and documentation efforts, in part inspired by the 
> excellent Spyder IDE channel [1]. At our last meeting, we realized 
> there is already a good amount of content about NumPy on YouTube (a 
> few examples [2, 3, 4]). We thought about creating a YouTube account 
> for NumPy and listing those videos in a playlist, initially. 
> Eventually, we can also add our own videos about how to contribute - 
> we're still brainstorming on those.
>
> I'm writing to the mailing list to ask the community for input on 
> creating this as an official channel for NumPy. If you have any 
> thoughts or questions regarding this, please let us know.
>
> Cheers,
>
> Melissa
>
> [1] https://www.youtube.com/channel/UCAOyvaOj7dMnavvGUkz9Djg
> [2] https://www.youtube.com/watch?v=dBTJD_FDVjU
> [3] https://www.youtube.com/watch?v=lHJqOE5j6xE
> [4] https://www.youtube.com/watch?v=ZB7BZMhfPgk

I like the idea of there being such a channel very much! However, 
whether it's formally a project of NumPy or just run by community 
members makes a difference.? If it's formally part of the project, you'd 
expect those to be 100% current and the best content on the topic, or at 
least highly competitive with the best.? They should get updates with 
each significant release.

For example, I think it's safe to say that nobody else has produced a 
reference manual that competes with the reference pages.? They're kept 
up to date and are pretty readable.

It's harder to spot-edit video, though, to keep up with changes.? Unless 
you have a lot of volunteers and are ready to coordinate them all, a 
video project might best be done as a side venture or with a beta label 
until it demonstrates that it can keep its content fresh.? An indexing 
effort for existing, high-quality video might be more valuable in the 
short term than shooting all-new video, too.

--jh--




From ralf.gommers at gmail.com  Tue Jan 26 03:25:17 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Tue, 26 Jan 2021 09:25:17 +0100
Subject: [Numpy-discussion] accepting NEP 23 - backwards compatibility and
 deprecation policy NEP
In-Reply-To: <CABL7CQinr0yVkxKwrRfz5v4QKB1YJtuJN8Mkq0WRS9jqoBOJVQ@mail.gmail.com>
References: <CABL7CQinr0yVkxKwrRfz5v4QKB1YJtuJN8Mkq0WRS9jqoBOJVQ@mail.gmail.com>
Message-ID: <CABL7CQims4Msg7v9azbr=Jfye_f3QX-b3Ar+A8XhBeYYesKePA@mail.gmail.com>

Hi all,

The update PR was merged after a lot more review on GitHub. I propose we
change the status of this NEP to Accepted. We'll merge a PR to do so unless
there are objections within the next five days.

Cheers,
Ralf



On Wed, Dec 30, 2020 at 3:05 PM Ralf Gommers <ralf.gommers at gmail.com> wrote:

> Hi all,
>
> Here is a long overdue update of the draft NEP about backwards
> compatibility and deprecation policy:
> https://github.com/numpy/numpy/pull/18097
>
> - This is NEP 23:
> https://numpy.org/neps/nep-0023-backwards-compatibility.html
> - Link to the previous mailing list discussion:
> https://mail.python.org/pipermail/numpy-discussion/2018-July/078432.html
>
> It would be nice to get this NEP to Accepted status. Main changes are:
>
> - Removed all examples that people objected to
> - Removed all content regarding versioning
> - Restructured sections, and added "Strategies related to deprecations"
> (using suggestions by @njsmith and @shoyer).
> - Added concrete examples of deprecations, and a more thorough description
> of how to go about adding warnings incl. Sphinx directives, using
> `stacklevel`, etc.
>
> As always, feedback here or on the PR is very welcome!
>
> Cheers,
> Ralf
>
>
> Abstract
> --------
>
> In this NEP we describe NumPy's approach to backwards compatibility,
> its deprecation and removal policy, and the trade-offs and decision
> processes for individual cases where breaking backwards compatibility
> is considered.
>
>
> Motivation and Scope
> --------------------
>
> NumPy has a very large user base.  Those users rely on NumPy being stable
> and the code they write that uses NumPy functionality to keep working.
> NumPy is also actively maintained and improved -- and sometimes
> improvements
> require, or are made much easier by, breaking backwards compatibility.
> Finally, there are trade-offs in stability for existing users vs. avoiding
> errors or having a better user experience for new users.  These competing
> needs often give rise to long debates and to delays in accepting or
> rejecting
> contributions.  This NEP tries to address that by providing a policy as
> well
> as examples and rationales for when it is or isn't a good idea to break
> backwards compatibility.
>
> In scope for this NEP are:
>
> - Principles of NumPy's approach to backwards compatibility.
> - How to deprecate functionality, and when to remove already deprecated
>   functionality.
> - Decision making process for deprecations and removals.
>
> Out of scope are:
>
> - Making concrete decisions about deprecations of particular functionality.
> - NumPy's versioning scheme.
>
>
> General principles
> ------------------
>
> When considering proposed changes that are backwards incompatible, the
> main principles the NumPy developers use when making a decision are:
>
> 1. Changes need to benefit users more than they harm them.
> 2. NumPy is widely used so breaking changes should by default be assumed
> to be
>    fairly harmful.
> 3. Decisions should be based on data and actual effects on users and
> downstream
>    packages rather than, e.g., appealing to the docs or for stylistic
> reasons.
> 4. Silently getting a wrong answer is much worse than getting a loud error.
>
> When assessing the costs of proposed changes, keep in mind that most users
> do
> not read the mailing list, do not look at deprecation warnings, and
> sometimes
> wait more than one or two years before upgrading from their old version.
> And
> that NumPy has millions of users, so "no one will do or use this" is very
> likely incorrect.
>
> Benefits include improved functionality, usability and performance, as
> well as
> lower maintenance cost and improved future extensibility.
>
> Fixes for clear bugs are exempt from this backwards compatibility policy.
> However in case of serious impact on users (e.g. a downstream library
> doesn't
> build anymore or would start giving incorrect results), even bug fixes may
> have
> to be delayed for one or more releases.
>
>
> Strategies related to deprecations
> ----------------------------------
>
> Getting hard data on the impact of a deprecation of often difficult.
> Strategies
> that can be used to assess such impact include:
>
> - Use a code search engine ([1]_) or static ([2]_) or dynamic ([3]_) code
>   analysis tools to determine where and how the functionality is used.
> - Testing prominent downstream libraries against a development build of
> NumPy
>   containing the proposed change to get real-world data on its impact.
> - Making a change in master and reverting it, if needed, before a release.
> We
>   do encourage other packages to test against NumPy's master branch, so
> this
>   often turns up issues quickly.
>
> If the impact is unclear or significant, it is often good to consider
> alternatives to deprecations. For example discouraging use in documentation
> only, or moving the documentation for the functionality to a less prominent
> place or even removing it completely. Commenting on open issues related to
> it
> that they are low-prio or labeling them as "wontfix" will also be a signal
> to
> users, and reduce the maintenance effort needing to be spent.
>
>
> Implementing deprecations and removals
> --------------------------------------
>
> Deprecation warnings are necessary in all cases where functionality
> will eventually be removed.  If there is no intent to remove functionality,
> then it should not be deprecated either. A "please don't use this" in the
> documentation or other type of warning should be used instead.
>
> Deprecations:
>
> - shall include the version number of the release in which the
> functionality
>   was deprecated.
> - shall include information on alternatives to the deprecated
> functionality, or a
>   reason for the deprecation if no clear alternative is available.
> - shall use ``VisibleDeprecationWarning`` rather than
> ``DeprecationWarning``
>   for cases of relevance to end users. For cases only relevant to
>   downstream libraries, a regular ``DeprecationWarning`` is fine.
>   *Rationale: regular deprecation warnings are invisible by default;
> library
>   authors should be aware how deprecations work and test for them, but we
> can't
>   expect this from all users.*
> - shall be listed in the release notes of the release where the
> deprecation is
>   first present.
> - shall set a ``stacklevel``, so the warning appears to come from the
> correct
>   place.
> - shall be mentioned in the documentation for the functionality. A
>   ``.. deprecated::`` directive can be used for this.
>
> Examples of good deprecation warnings:
>
> .. code-block:: python
>
>     warnings.warn('np.asscalar(a) is deprecated since NumPy 1.16.0, use '
>                   'a.item() instead', DeprecationWarning, stacklevel=3)
>
>     warnings.warn("Importing from numpy.testing.utils is deprecated "
>                   "since 1.15.0, import from numpy.testing instead.",
>                   DeprecationWarning, stacklevel=2)
>
>     # A change in NumPy 1.14.0 for Python 3 loadtxt/genfromtext, slightly
>     # tweaked in this NEP (original didn't have version number).
>     warnings.warn(
>         "Reading unicode strings without specifying the encoding "
>         "argument is deprecated since NumPy 1.14.0. Set the encoding, "
>         "use None for the system default.",
>         np.VisibleDeprecationWarning, stacklevel=2)
>
> Removal of deprecated functionality:
>
> - shall be done after at least 2 releases (assuming the current 6-monthly
>   release cycle; if that changes, there shall be at least 1 year between
>   deprecation and removal).
> - shall be listed in the release notes of the release where the removal
> happened.
> - can be done in any minor (but not bugfix) release.
>
> For backwards incompatible changes that aren't "deprecate and remove" but
> for
> which code will start behaving differently, a ``FutureWarning`` should be
> used. Release notes, mentioning version number and using ``stacklevel``
> should
> be done in the same way as for deprecation warnings. A ``..
> versionchanged::``
> directive can be used in the documentation to indicate when the behavior
> changed:
>
> .. code-block:: python
>
>     def argsort(self, axis=np._NoValue, ...):
>         """
>         Parameters
>         ----------
>         axis : int, optional
>             Axis along which to sort. If None, the default, the flattened
> array
>             is used.
>
>             ..  versionchanged:: 1.13.0
>                 Previously, the default was documented to be -1, but that
> was
>                 in error. At some future date, the default will change to
> -1, as
>                 originally intended.
>                 Until then, the axis should be given explicitly when
>                 ``arr.ndim > 1``, to avoid a FutureWarning.
>         """
>         ...
>         warnings.warn(
>             "In the future the default for argsort will be axis=-1, not
> the "
>             "current None, to match its documentation and np.argsort. "
>             "Explicitly pass -1 or None to silence this warning.",
>             MaskedArrayFutureWarning, stacklevel=3)
>
>
> Decision making
> ~~~~~~~~~~~~~~~
>
> In concrete cases where this policy needs to be applied, decisions are
> made according
> to the `NumPy governance model
> <https://docs.scipy.org/doc/numpy/dev/governance/index.html>`_.
>
> All deprecations must be proposed on the mailing list, in order to give
> everyone
> with an interest in NumPy development to be able to comment. Removal of
> deprecated functionality does not need discussion on the mailing list.
>
>
> Functionality with more strict deprecation policies
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>
> - ``numpy.random`` has its own backwards compatibility policy,
>   see `NEP 19 <http://www.numpy.org/neps/nep-0019-rng-policy.html>`_.
> - The file format for ``.npy`` and ``.npz`` files must not be changed in a
> backwards
>   incompatible way.
>
>
> Example cases
> -------------
>
> We now discuss a few concrete examples from NumPy's history to illustrate
> typical issues and trade-offs.
>
> **Changing the behavior of a function**
>
> ``np.histogram`` is probably the most infamous example.
> First, a new keyword ``new=False`` was introduced, this was then switched
> over to None one release later, and finally it was removed again.
> Also, it has a ``normed`` keyword that had behavior that could be
> considered
> either suboptimal or broken (depending on ones opinion on the statistics).
> A new keyword ``density`` was introduced to replace it; ``normed`` started
> giving
> ``DeprecationWarning`` only in v.1.15.0.  Evolution of ``histogram``::
>
>     def histogram(a, bins=10, range=None, normed=False):  # v1.0.0
>
>     def histogram(a, bins=10, range=None, normed=False, weights=None,
> new=False):  #v1.1.0
>
>     def histogram(a, bins=10, range=None, normed=False, weights=None,
> new=None):  #v1.2.0
>
>     def histogram(a, bins=10, range=None, normed=False, weights=None):
>  #v1.5.0
>
>     def histogram(a, bins=10, range=None, normed=False, weights=None,
> density=None):  #v1.6.0
>
>     def histogram(a, bins=10, range=None, normed=None, weights=None,
> density=None):  #v1.15.0
>         # v1.15.0 was the first release where `normed` started emitting
>         # DeprecationWarnings
>
> The ``new`` keyword was planned from the start to be temporary.  Such a
> plan
> forces users to change their code more than once, which is almost never the
> right thing to do.  Instead, a better approach here would have been to
> deprecate ``histogram`` and introduce a new function ``hist`` in its place.
>
>
> **Disallowing indexing with floats**
>
> Indexing an array with floats is asking for something ambiguous, and can
> be a
> sign of a bug in user code.  After some discussion, it was deemed a good
> idea
> to deprecate indexing with floats.  This was first tried for the v1.8.0
> release, however in pre-release testing it became clear that this would
> break
> many libraries that depend on NumPy.  Therefore it was reverted before
> release,
> to give those libraries time to fix their code first.  It was finally
> introduced for v1.11.0 and turned into a hard error for v1.12.0.
>
> This change was disruptive, however it did catch real bugs in, e.g., SciPy
> and
> scikit-learn.  Overall the change was worth the cost, and introducing it in
> master first to allow testing, then removing it again before a release, is
> a
> useful strategy.
>
> Similar deprecations that also look like good examples of
> cleanups/improvements:
>
> - removing deprecated boolean indexing (in 2016, see `gh-8312 <
> https://github.com/numpy/numpy/pull/8312>`__)
> - deprecating truth testing on empty arrays (in 2017, see `gh-9718 <
> https://github.com/numpy/numpy/pull/9718>`__)
>
>
> **Removing the financial functions**
>
> The financial functions (e.g. ``np.pmt``) had short non-descriptive names,
> were
> present in the main NumPy namespace, and didn't really fit well within
> NumPy's
> scope.  They were added in 2008 after
> `a discussion <
> https://mail.python.org/pipermail/numpy-discussion/2008-April/032353.html
> >`_
> on the mailing list where opinion was divided (but a majority in favor).
> The financial functions didn't cause a lot of overhead, however there were
> still multiple issues and PRs a year for them which cost maintainer time to
> deal with.  And they cluttered up the ``numpy`` namespace.  Discussion on
> removing them happened in 2013 (gh-2880, rejected) and then again in 2019
> (:ref:`NEP32`, accepted without significant complaints).
>
> Given that they were clearly outside of NumPy's scope, moving them to a
> separate ``numpy-financial`` package and removing them from NumPy after a
> deprecation period made sense.
>
>
> Alternatives
> ------------
>
> **Being more aggressive with deprecations.**
>
> The goal of being more aggressive is to allow NumPy to move forward faster.
> This would avoid others inventing their own solutions (often in multiple
> places), as well as be a benefit to users without a legacy code base.  We
> reject this alternative because of the place NumPy has in the scientific
> Python
> ecosystem - being fairly conservative is required in order to not increase
> the
> extra maintenance for downstream libraries and end users to an unacceptable
> level.
>
>
> Discussion
> ----------
>
> - `Mailing list discussion on the first version of this NEP in 2018 <
> https://mail.python.org/pipermail/numpy-discussion/2018-July/078432.html
> >`__
>
>
> References and Footnotes
> ------------------------
>
> - `Issue requesting semantic versioning <
> https://github.com/numpy/numpy/issues/10156>`__
>
> .. [1] https://searchcode.com/
>
> .. [2] https://github.com/Quansight-Labs/python-api-inspect
>
> .. [3] https://github.com/data-apis/python-record-api
>
>
>
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From ralf.gommers at gmail.com  Tue Jan 26 03:31:31 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Tue, 26 Jan 2021 09:31:31 +0100
Subject: [Numpy-discussion] accepting NEP 46 - sponsorship guidelines
Message-ID: <CABL7CQhQTQJgem9cK+J3LR_OeQ_cwfo2cWq9aGNQBkVtYkhcjQ@mail.gmail.com>

Hi all,

The sponsorship guidelines PR (
https://numpy.org/neps/nep-0046-sponsorship-guidelines.html) was merged as
Draft and everyone seems happy with it. I propose to change its status to
Accepted. We'll merge a PR to do so unless there are objections within the
next five days.

Cheers,
Ralf
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From stefanv at berkeley.edu  Tue Jan 26 03:43:29 2021
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Tue, 26 Jan 2021 00:43:29 -0800
Subject: [Numpy-discussion] 
 =?utf-8?q?accepting_NEP_23_-_backwards_compat?=
 =?utf-8?q?ibility_and_deprecation_policy_NEP?=
In-Reply-To: <CABL7CQims4Msg7v9azbr=Jfye_f3QX-b3Ar+A8XhBeYYesKePA@mail.gmail.com>
References: <CABL7CQinr0yVkxKwrRfz5v4QKB1YJtuJN8Mkq0WRS9jqoBOJVQ@mail.gmail.com>
 <CABL7CQims4Msg7v9azbr=Jfye_f3QX-b3Ar+A8XhBeYYesKePA@mail.gmail.com>
Message-ID: <9b3c66bc-7318-4c25-8c0d-cc6bc5280a87@www.fastmail.com>

On Tue, Jan 26, 2021, at 00:25, Ralf Gommers wrote:
> The update PR was merged after a lot more review on GitHub. I propose we change the status of this NEP to Accepted. We'll merge a PR to do so unless there are objections within the next five days.

Thanks for the heads-up, Ralf.  I am happy to have the NEP accepted.

St?fan
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From friedrichromstedt at gmail.com  Tue Jan 26 03:48:58 2021
From: friedrichromstedt at gmail.com (Friedrich Romstedt)
Date: Tue, 26 Jan 2021 09:48:58 +0100
Subject: [Numpy-discussion] Unreliable crash when converting using
 numpy.asarray via C buffer interface
Message-ID: <CAN06=CzuKftoPkz8TJmbTfC18dH9-WX6rE4WQxxpQUxVpbtHMQ@mail.gmail.com>

Hi,

This is with Python 3.8.2 64-bit and numpy 1.19.2 on Windows 10.  I'd
like to be able to convert some C++ extension type to a numpy array by
using ``numpy.asarray``.  The extension type implements the Python
buffer interface to support this.

The extension type, called "Image" here, holds some chunk of
``double``, C order, contiguous, 2 dimensions.  It "owns" the buffer;
the buffer is not shared with other objects.  The following Python
code crashes::

    image = <... Image production ...>
    ar = numpy.asarray(image)

However, when I say::

    image = <... Image production ...>
    print("---")
    ar = numpy.asarray(image)

the entire program is executing properly with correct data in the
numpy ndarray produced using the buffer interface.

The extension type permits reading the pixel values by a method;
copying them over by a Python loop works fine.  I am ``Py_INCREF``-ing
the producer in the C++ buffer view creation function properly.  The
shapes and strides of the buffer view are ``delete[]``-ed upon
releasing the buffer; avoiding this does not prevent the crash.  I am
catching ``std::exception`` in the view creation function; no such
exception occurs.  The shapes and strides are allocated by ``new
Py_ssize_t[2]``, so they will survive the view creation function.

I spent some hours trying to figure out what I am doing wrong.  Maybe
someone has an idea about this?  I double-checked each line of code
related to this problem and couldn't find any mistake.  Probabaly I am
not looking at the right aspect.

Best,
Friedrich

From pierre.augier at univ-grenoble-alpes.fr  Tue Jan 26 09:59:33 2021
From: pierre.augier at univ-grenoble-alpes.fr (PIERRE AUGIER)
Date: Tue, 26 Jan 2021 15:59:33 +0100 (CET)
Subject: [Numpy-discussion] Comment published in Nature Astronomy about
 The ecological impact of computing with Python
In-Reply-To: <1941664094.43615172.1606232825156.JavaMail.zimbra@univ-grenoble-alpes.fr>
References: <1941664094.43615172.1606232825156.JavaMail.zimbra@univ-grenoble-alpes.fr>
Message-ID: <488698904.2509842.1611673173691.JavaMail.zimbra@univ-grenoble-alpes.fr>

Hi,

Here are some preliminary results of an experiment on energy consumption measurement at Grid'5000 (https://www.grid5000.fr/w/Energy_consumption_monitoring_tutorial). The goal is to have enough to be able to submit a serious comment to a recent article published in Nature Astronomy (Zwart, 2020) which recommends to stop using and teaching Python because of the ecological impact of computing.

On the attached figure: it represents the CO2 production as a function of elapsed time for different implementations (https://github.com/paugier/nbabel). It can be compared with https://raw.githubusercontent.com/paugier/nbabel/master/py/fig/fig_ecolo_impact_transonic.png taken from Zwart (2020).

The implementations labeled "nbabel.org" have been found on https://www.nbabel.org/ and have recently been used in the article by Zwart (2020). Note that these C++, Fortran and Julia implementations are not well optimized. However, I think they are representative of many C++, Fortran and Julia codes written by scientists.

There is one simple Pythran implementation which is really fast (slightly slower than the fastest implementation in Julia but it is not a big deal).

Note that of course these results do not show that Python is faster that C++!! We just show here that it's easy to write in Python **very** efficient implementations of numerically intensive problems.

I think soon I'm going to have enough materials to contact the editors to ask how we can publicly answer to this comment published in their journal. With this work https://github.com/paugier/nbabel (proper energy consumption measurements), I clearly demonstrate that the basis of Zwart's comment is factually wrong (its benchmark and Figure 3), so that most of its conclusions are also wrong.

I'd like to know if some people involved in the community are willing to be co-authors of this potential reply.

Cheers,
Pierre

--
Pierre Augier - CR CNRS                 http://www.legi.grenoble-inp.fr
LEGI (UMR 5519) Laboratoire des Ecoulements Geophysiques et Industriels
BP53, 38041 Grenoble Cedex, France                tel:+33.4.56.52.86.16

----- Mail original -----
> De: "PIERRE AUGIER" <pierre.augier at univ-grenoble-alpes.fr>
> ?: "numpy-discussion" <numpy-discussion at python.org>
> Envoy?: Mardi 24 Novembre 2020 16:47:05
> Objet: [Numpy-discussion] Comment published in Nature Astronomy about The ecological impact of computing with Python

> Hi,
> 
> I recently took a bit of time to study the comment "The ecological impact of
> high-performance computing in astrophysics" published in Nature Astronomy
> (Zwart, 2020, https://www.nature.com/articles/s41550-020-1208-y,
> https://arxiv.org/pdf/2009.11295.pdf), where it is stated that "Best however,
> for the environment is to abandon Python for a more environmentally friendly
> (compiled) programming language.".
> 
> I wrote a simple Python-Numpy implementation of the problem used for this study
> (https://www.nbabel.org) and, accelerated by Transonic-Pythran, it's very
> efficient. Here are some numbers (elapsed times in s, smaller is better):
> 
>| # particles |  Py | C++ | Fortran | Julia |
>|-------------|-----|-----|---------|-------|
>|     1024    |  29 |  55 |   41    |   45  |
>|     2048    | 123 | 231 |  166    |  173  |
> 
> The code and a modified figure are here: https://github.com/paugier/nbabel
> (There is no check on the results for https://www.nbabel.org, so one still has
> to be very careful.)
> 
> I think that the Numpy community should spend a bit of energy to show what can
> be done with the existing tools to get very high performance (and low CO2
> production) with Python. This work could be the basis of a serious reply to the
> comment by Zwart (2020).
> 
> Unfortunately the Python solution in https://www.nbabel.org is very bad in terms
> of performance (and therefore CO2 production). It is also true for most of the
> Python solutions for the Computer Language Benchmarks Game in
> https://benchmarksgame-team.pages.debian.net/benchmarksgame/ (codes here
> https://salsa.debian.org/benchmarksgame-team/benchmarksgame#what-else).
> 
> We could try to fix this so that people see that in many cases, it is not
> necessary to "abandon Python for a more environmentally friendly (compiled)
> programming language". One of the longest and hardest task would be to
> implement the different cases of the Computer Language Benchmarks Game in
> standard and modern Python-Numpy. Then, optimizing and accelerating such code
> should be doable and we should be able to get very good performance at least
> for some cases. Good news for this project, (i) the first point can be done by
> anyone with good knowledge in Python-Numpy (many potential workers), (ii) for
> some cases, there are already good Python implementations and (iii) the work
> can easily be parallelized.
> 
> It is not a criticism, but the (beautiful and very nice) new Numpy website
> https://numpy.org/ is not very convincing in terms of performance. It's written
> "Performant The core of NumPy is well-optimized C code. Enjoy the flexibility
> of Python with the speed of compiled code." It's true that the core of Numpy is
> well-optimized C code but to seriously compete with C++, Fortran or Julia in
> terms of numerical performance, one needs to use other tools to move the
> compiled-interpreted boundary outside the hot loops. So it could be reasonable
> to mention such tools (in particular Numba, Pythran, Cython and Transonic).
> 
> Is there already something planned to answer to Zwart (2020)?
> 
> Any opinions or suggestions on this potential project?
> 
> Pierre
> 
> PS: Of course, alternative Python interpreters (PyPy, GraalPython, Pyjion,
> Pyston, etc.) could also be used, especially if HPy
> (https://github.com/hpyproject/hpy) is successful (C core of Numpy written in
> HPy, Cython able to produce HPy code, etc.). However, I tend to be a bit
> skeptical in the ability of such technologies to reach very high performance
> for low-level Numpy code (performance that can be reached by replacing whole
> Python functions with optimized compiled code). Of course, I hope I'm wrong!
> IMHO, it does not remove the need for a successful HPy!
> 
> --
> Pierre Augier - CR CNRS                 http://www.legi.grenoble-inp.fr
> LEGI (UMR 5519) Laboratoire des Ecoulements Geophysiques et Industriels
> BP53, 38041 Grenoble Cedex, France                tel:+33.4.56.52.86.16
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
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From shoyer at gmail.com  Tue Jan 26 12:23:45 2021
From: shoyer at gmail.com (Stephan Hoyer)
Date: Tue, 26 Jan 2021 09:23:45 -0800
Subject: [Numpy-discussion] accepting NEP 23 - backwards compatibility
 and deprecation policy NEP
In-Reply-To: <9b3c66bc-7318-4c25-8c0d-cc6bc5280a87@www.fastmail.com>
References: <CABL7CQinr0yVkxKwrRfz5v4QKB1YJtuJN8Mkq0WRS9jqoBOJVQ@mail.gmail.com>
 <CABL7CQims4Msg7v9azbr=Jfye_f3QX-b3Ar+A8XhBeYYesKePA@mail.gmail.com>
 <9b3c66bc-7318-4c25-8c0d-cc6bc5280a87@www.fastmail.com>
Message-ID: <CAEQ_Tvf5iqdujzBxCvvy76Bti6B1WB+y8mH7WMxoOmQf8Hz-Ew@mail.gmail.com>

On Tue, Jan 26, 2021 at 12:45 AM Stefan van der Walt <stefanv at berkeley.edu>
wrote:

> On Tue, Jan 26, 2021, at 00:25, Ralf Gommers wrote:
>
> The update PR was merged after a lot more review on GitHub. I propose we
> change the status of this NEP to Accepted. We'll merge a PR to do so unless
> there are objections within the next five days.
>
>
> Thanks for the heads-up, Ralf.  I am happy to have the NEP accepted.
>
> St?fan
>


Thank you, Ralf!



>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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From sebastian at sipsolutions.net  Tue Jan 26 16:15:37 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Tue, 26 Jan 2021 15:15:37 -0600
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
 <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
Message-ID: <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>

On Tue, 2021-01-26 at 06:11 +0100, Ralf Gommers wrote:
> On Tue, Jan 26, 2021 at 2:01 AM Sebastian Berg <  
> sebastian at sipsolutions.net>
> wrote:
> 
> > Hi all,
> > 
> > does anyone have a thought about how user DTypes (i.e. DTypes not
> > currently part of NumPy) should interact with the "value based
> > promotion" logic we currently have?
> > For now I can just do anything, and we will find out later.? And I
> > will
> > have to do something for now, basically with the hope that it all
> > turns
> > out all-right.
> > 
> > But there are multiple options for both what to offer to user
> > DTypes
> > and where we want to move (I am using `bfloat16` as a potential
> > DType
> > here).
> > 
> > 1. The "weak" dtype option (this is what JAX does), where:
> > 
> > ?????? np.array([1], dtype=bfloat16) + 4.
> > 
> > ?? returns a bfloat16, because 4. is "lower" than all floating
> > ?? point types.
> > ?? In this scheme the user defined `bfloat16` knows that the input
> > ?? is a Python float, but it does not know its value (if an
> > ?? overflow occurs during conversion, it could warn or error but
> > ?? not upcast).? For example `np.array([1], dtype=uint4) + 2**5`
> > ?? will try `uint4(2**5)` assuming it works.
> > ?? NumPy is different `2.**300` would ensure the result is a
> > `float64`.
> > 
> > ?? If a DType does not make use of this, it would get the behaviour
> > ?? of option 2.
> > 
> > 2. The "default" DType option: np.array([1], dtype=bfloat16) + 4.
> > is
> > ?? always the same as `bfloat16 + float64 -> float64`.
> > 
> > 3. Use whatever NumPy considers the "smallest appropriate dtype".
> > ?? This will not always work correctly for unsigned integers, and
> > for
> > ?? floats this would be float16, which doesn't help with bfloat16.
> > 
> > 4. Try to expose the actual value. (I do not want to do this, but
> > it
> > ?? is probably a plausible extension with most other options, since
> > ?? the other options can be the "default".)
> > 
> > 
> > Within these options, there is one more difficulty. NumPy currently
> > applies the same logic for:
> > 
> > ??? np.array([1], dtype=bfloat16) + np.array(4., dtype=np.float64)
> > 
> > which in my opinion is wrong (the second array is typed). We do
> > have
> > the same issue with deciding what to do in the future for NumPy
> > itself.
> > Right now I feel that new (user) DTypes should live in the future
> > (whatever that future is).
> > 
> 
> I agree. And I have a preference for option 1. Option 2 is too greedy
> in
> upcasting, the value-based casting is problematic in multiple ways
> (e.g.,
> hard for Numba because output dtype cannot be predicted from input
> dtypes),
> and option 4 is hard to understand a rationale for (maybe so the user
> dtype
> itself can implement option 3?).

Yes, well, the "rational" for option 4 is that you expose everything
that NumPy currently needs (assuming we make no changes). That would be
the only way that allows a `bfloat16` to work exactly comparable to a
`float16` as currently defined in NumPy.

To be clear: It horrifies me, but defining a "better" way is much
easier than trying to keep everything as (at least for now) while also
thinking about how it should look like in the future (and making sure
that user DTypes are ready for that future).

My guess is, we can agree on aiming for Option 1 and trying to limit it
to Python operators.  Unfortunately, only time will tell how feasible
that will actually be.

> 
> 
> > I have said previously, that we could distinguish this for
> > universal
> > functions.? But calls like `np.asarray(4.)` are common, and they
> > would
> > lose the information that `4.` was originally a Python float.
> > 
> 
> Hopefully the future will have way fewer asarray calls in it.
> Rejecting
> scalar input to functions would be nice. This is what most other
> array/tensor libraries do.
> 

Well, right now NumPy has scalars (both ours and Python), and I would
expect that changing that may well be more disruptive than changing the
value based promotion (assuming we can add good FutureWarnings).

I would probabaly need a bit convincing that forbidding `np.add(array,
2)` is worth the trouble, but luckily that is probably an orthogonal
question.  (The fact that we even accept 0-D arrays as "value based" is
probably the biggest difficulty.)

> 
> > 
> > So, recently, I was considering that a better option may be to
> > limit
> > this to math Python operators: +, -, /, **, ...
> > 
> 
> +1
> 
> This discussion may be relevant:
> https://github.com/data-apis/array-api/issues/14.
> 

I have browsed through it, I guess you also were thinking of limiting
scalars to operators (although possibly even more broadly rather than
just for promotion purposes).  I am not sure I understand this:

    Non-array ("scalar") operands are not permitted to participate in
type promotion.

Since they do participate also in JAX and in what I wrote here. They
just participate in an abstract way. I.e. as `Floating` or `Integer`,
but not like a specific float or integer.

> 
> > Those are the places where it may make a difference to write:
> > 
> > ??? arr + 4.???????? vs.??? arr + bfloat16(4.)
> > ??? int8_arr + 1???? vs.??? int8_arr + np.int8(1)
> > ??? arr += 4.????? (in-place may be the most significant use-case)
> > 
> > while:
> > 
> > ??? np.add(int8_arr, 1)??? vs.?? np.add(int8_arr, np.int8(1))
> > 
> > is maybe less significant. On the other hand, it would add a subtle
> > difference between operators vs. direct ufunc calls...
> > 
> > 
> > In general, it may not matter: We can choose option 1 (which the
> > bfloat16 does not have to use), and modify it if we ever change the
> > logic in NumPy itself.? Basically, I will probably pick option 1
> > for
> > now and press on, and we can reconsider later.? And hope that it
> > does
> > not make things even more complicated than it is now.
> > 
> > Or maybe better just limit it completely to always use the default
> > for
> > user DTypes?
> > 
> 
> I'm not sure I understand why you like option 1 but want to give
> user-defined dtypes the choice of opting out of it. Upcasting will
> rarely
> make sense for user-defined dtypes anyway.
> 

I never meant this as an opt-out, the question is what you do if the
user DType does not opt-in/define the operation.

Basically, the we would promote with `Floating` here (or `PyFloating`,
but there should be no difference; for now I will do PyFloating, but it
should probably be changed later). I was hinting at provide a default
fallback, so that if:

    UserDtype + Floating -> Undefined/Error

we automatically try the "default", e.g.:

    UserDType + Float64 -> Something

That would mean users don't have to worry about `Floating` itself.

But I am not opinionated here, a user DType author should be able to
quickly deal with either issue (that Float64 is undesired or that the
Error is undesired if no "default" exists).  Maybe the error is more
conservative/constructive though.

> 
> > 
> > But I would be interested if the "limit to Python operators" is
> > something we should aim for here.? This does make a small
> > difference,
> > because user DTypes could "live" in the future if we have an idea
> > of
> > how that future may look like.
> > 
> 
> A future with:
> - no array scalars
> - 0-D arrays have the same casting rules as >=1-D arrays
> - no value-based casting
> would be quite nice. For "same kind" casting like
> 

I don't think array-scalars really matter here, since they are typed
and behave identical to 0-D arrays anyway.  We can have long opinion
pieces on whether they should exist :).

>   
> https://data-apis.github.io/array-api/latest/API_specification/type_promotion.html
> .
> Mixed-kind casting isn't specified there, because it's too different
> between libraries. The JAX design (
> https://jax.readthedocs.io/en/latest/type_promotion.html)? seems
> sensible
> there.

The JAX design is the "weak DType" design (when it comes to Python
numbers). Although, the fact that a "weak" `complex` is sorted above
all floats, means that `bfloat16_arr + 1j` will go to the default
complex dtype as well.
But yes, I like the "weak" approach, just think also JAX has some
wrinkles to smoothen.


There is a good deal more to this if you get user DTypes and I add one
more important constraint that:

    from my_extension_module import uint24

must not change any existing code that does not explicitly use
`uint24`.

Then my current approach guarantees:

    np.result_type(uint24, int48, int64) -> Error

If `uint24` and `int48` do not know each other (`int64` is obviously
right here, but it is tricky to be quite certain).

The other tricky example I have was:

  The following becomes problematic (order does not matter):
          uint24 +      int16  +           uint32  -> int64
     <==      (uint24 + int16) + (uint24 + uint32) -> int64
     <==                int32  +           uint32  -> int64

With the addition that `uint24 + int32 -> int48` is defined the first
could be expected to return `int48`, but actually getting there is
tricky (and my current code will not).

If promotion result of a user DType with a builtin one, can be a
builtin one, then "ammending" the promotion with things like `uint24 +
int32 -> int48` can lead to slightly surprising promotion results. 
This happens if the result of a promotion with another "category"
(builtin) can be both a larger category or a lower one.

- Sebastian


> 
> Cheers,
> Ralf
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From sebastian at sipsolutions.net  Wed Jan 27 01:00:49 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Wed, 27 Jan 2021 00:00:49 -0600
Subject: [Numpy-discussion] NumPy Development Meeting Wednesday - Triage
 Focus
Message-ID: <0d0409c2274de506d0220cbb4e8c1d7242da248d.camel@sipsolutions.net>

Hi all,

Our bi-weekly triage-focused NumPy development meeting is Wednesday,
Jan 27th at 11 am Pacific Time (19:00 UTC).
Everyone is invited to join in and edit the work-in-progress meeting
topics and notes:
https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg

I encourage everyone to notify us of issues or PRs that you feel should
be prioritized, discussed, or reviewed.

Best regards

Sebastian

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From blkzol001 at myuct.ac.za  Wed Jan 27 03:53:55 2021
From: blkzol001 at myuct.ac.za (zoj613)
Date: Wed, 27 Jan 2021 01:53:55 -0700 (MST)
Subject: [Numpy-discussion] Addition of new distributions: Polya-gamma
In-Reply-To: <1609421194605-0.post@n7.nabble.com>
References: <AM6PR03MB58635C911061133F1F83792DB8DA0@AM6PR03MB5863.eurprd03.prod.outlook.com>
 <CAF6FJivqpLsXqvyUQcAUL67VHQw0viQWTry1+L1pq4GipfDdhw@mail.gmail.com>
 <1609421194605-0.post@n7.nabble.com>
Message-ID: <1611737635288-0.post@n7.nabble.com>

As a follow-up to my last post here and comments from Robert Kern. I have
just released version 1.0.0 of the sampler on PyPI. The work is pretty much
done (I hope). Feedback would be very much appreciated.



--
Sent from: http://numpy-discussion.10968.n7.nabble.com/

From ralf.gommers at gmail.com  Wed Jan 27 04:33:06 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Wed, 27 Jan 2021 10:33:06 +0100
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
 <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
 <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>
Message-ID: <CABL7CQgqFGjt=d4hM7aHvqcqA0zt4gJUeGCCEekh0jp8Dk1FPA@mail.gmail.com>

On Tue, Jan 26, 2021 at 10:21 PM Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> On Tue, 2021-01-26 at 06:11 +0100, Ralf Gommers wrote:
> > On Tue, Jan 26, 2021 at 2:01 AM Sebastian Berg <
> > sebastian at sipsolutions.net>
> > wrote:
> >
> > > Hi all,
> > >
> > > does anyone have a thought about how user DTypes (i.e. DTypes not
> > > currently part of NumPy) should interact with the "value based
> > > promotion" logic we currently have?
> > > For now I can just do anything, and we will find out later.  And I
> > > will
> > > have to do something for now, basically with the hope that it all
> > > turns
> > > out all-right.
> > >
> > > But there are multiple options for both what to offer to user
> > > DTypes
> > > and where we want to move (I am using `bfloat16` as a potential
> > > DType
> > > here).
> > >
> > > 1. The "weak" dtype option (this is what JAX does), where:
> > >
> > >        np.array([1], dtype=bfloat16) + 4.
> > >
> > >    returns a bfloat16, because 4. is "lower" than all floating
> > >    point types.
> > >    In this scheme the user defined `bfloat16` knows that the input
> > >    is a Python float, but it does not know its value (if an
> > >    overflow occurs during conversion, it could warn or error but
> > >    not upcast).  For example `np.array([1], dtype=uint4) + 2**5`
> > >    will try `uint4(2**5)` assuming it works.
> > >    NumPy is different `2.**300` would ensure the result is a
> > > `float64`.
> > >
> > >    If a DType does not make use of this, it would get the behaviour
> > >    of option 2.
> > >
> > > 2. The "default" DType option: np.array([1], dtype=bfloat16) + 4.
> > > is
> > >    always the same as `bfloat16 + float64 -> float64`.
> > >
> > > 3. Use whatever NumPy considers the "smallest appropriate dtype".
> > >    This will not always work correctly for unsigned integers, and
> > > for
> > >    floats this would be float16, which doesn't help with bfloat16.
> > >
> > > 4. Try to expose the actual value. (I do not want to do this, but
> > > it
> > >    is probably a plausible extension with most other options, since
> > >    the other options can be the "default".)
> > >
> > >
> > > Within these options, there is one more difficulty. NumPy currently
> > > applies the same logic for:
> > >
> > >     np.array([1], dtype=bfloat16) + np.array(4., dtype=np.float64)
> > >
> > > which in my opinion is wrong (the second array is typed). We do
> > > have
> > > the same issue with deciding what to do in the future for NumPy
> > > itself.
> > > Right now I feel that new (user) DTypes should live in the future
> > > (whatever that future is).
> > >
> >
> > I agree. And I have a preference for option 1. Option 2 is too greedy
> > in
> > upcasting, the value-based casting is problematic in multiple ways
> > (e.g.,
> > hard for Numba because output dtype cannot be predicted from input
> > dtypes),
> > and option 4 is hard to understand a rationale for (maybe so the user
> > dtype
> > itself can implement option 3?).
>
> Yes, well, the "rational" for option 4 is that you expose everything
> that NumPy currently needs (assuming we make no changes). That would be
> the only way that allows a `bfloat16` to work exactly comparable to a
> `float16` as currently defined in NumPy.
>
> To be clear: It horrifies me, but defining a "better" way is much
> easier than trying to keep everything as (at least for now) while also
> thinking about how it should look like in the future (and making sure
> that user DTypes are ready for that future).
>
> My guess is, we can agree on aiming for Option 1 and trying to limit it
> to Python operators.  Unfortunately, only time will tell how feasible
> that will actually be.
>

That sounds good.

> > I have said previously, that we could distinguish this for
> > > universal
> > > functions.  But calls like `np.asarray(4.)` are common, and they
> > > would
> > > lose the information that `4.` was originally a Python float.
> > >
> >
> > Hopefully the future will have way fewer asarray calls in it.
> > Rejecting
> > scalar input to functions would be nice. This is what most other
> > array/tensor libraries do.
> >
>
> Well, right now NumPy has scalars (both ours and Python), and I would
> expect that changing that may well be more disruptive than changing the
> value based promotion (assuming we can add good FutureWarnings).
>
> I would probabaly need a bit convincing that forbidding `np.add(array,
> 2)` is worth the trouble, but luckily that is probably an orthogonal
> question.  (The fact that we even accept 0-D arrays as "value based" is
> probably the biggest difficulty.)
>

It probably isn't worth going through trouble for indeed. And yes, the "0-D
arrays are special" is the more important issue.


> >
> > >
> > > So, recently, I was considering that a better option may be to
> > > limit
> > > this to math Python operators: +, -, /, **, ...
> > >
> >
> > +1
> >
> > This discussion may be relevant:
> > https://github.com/data-apis/array-api/issues/14.
> >
>
> I have browsed through it, I guess you also were thinking of limiting
> scalars to operators (although possibly even more broadly rather than
> just for promotion purposes).


Indeed. `x + 1` must work, that's extremely common. `np.somefunc(x, 1)` is
not common, and there's little downside (and lots of upside) in not
supporting it if you'd design a new numpy-like library.

  I am not sure I understand this:
>
>     Non-array ("scalar") operands are not permitted to participate in
> type promotion.
>
> Since they do participate also in JAX and in what I wrote here. They
> just participate in an abstract way. I.e. as `Floating` or `Integer`,
> but not like a specific float or integer.
>

You're right, that sentence could use a tweak. I think the intent was to
say that doing this in a multi-step way like
- cast scalar to array with some dtype (e.g. Python float becomes numpy
float64)
- then apply the `array <op> array` casting rules to that resulting dtype
should not be done.


> > > Those are the places where it may make a difference to write:
> > >
> > >     arr + 4.         vs.    arr + bfloat16(4.)
> > >     int8_arr + 1     vs.    int8_arr + np.int8(1)
> > >     arr += 4.      (in-place may be the most significant use-case)
> > >
> > > while:
> > >
> > >     np.add(int8_arr, 1)    vs.   np.add(int8_arr, np.int8(1))
> > >
> > > is maybe less significant. On the other hand, it would add a subtle
> > > difference between operators vs. direct ufunc calls...
> > >
> > >
> > > In general, it may not matter: We can choose option 1 (which the
> > > bfloat16 does not have to use), and modify it if we ever change the
> > > logic in NumPy itself.  Basically, I will probably pick option 1
> > > for
> > > now and press on, and we can reconsider later.  And hope that it
> > > does
> > > not make things even more complicated than it is now.
> > >
> > > Or maybe better just limit it completely to always use the default
> > > for
> > > user DTypes?
> > >
> >
> > I'm not sure I understand why you like option 1 but want to give
> > user-defined dtypes the choice of opting out of it. Upcasting will
> > rarely
> > make sense for user-defined dtypes anyway.
> >
>
> I never meant this as an opt-out, the question is what you do if the
> user DType does not opt-in/define the operation.
>
> Basically, the we would promote with `Floating` here (or `PyFloating`,
> but there should be no difference; for now I will do PyFloating, but it
> should probably be changed later). I was hinting at provide a default
> fallback, so that if:
>
>     UserDtype + Floating -> Undefined/Error
>
> we automatically try the "default", e.g.:
>
>     UserDType + Float64 -> Something
>
> That would mean users don't have to worry about `Floating` itself.
>
> But I am not opinionated here, a user DType author should be able to
> quickly deal with either issue (that Float64 is undesired or that the
> Error is undesired if no "default" exists).  Maybe the error is more
> conservative/constructive though.
>

I'd start with the error, and reconsider only if there's a practical
problem with it. Going from error to fallback later is much easier than the
other way around.


> > > But I would be interested if the "limit to Python operators" is
> > > something we should aim for here.  This does make a small
> > > difference,
> > > because user DTypes could "live" in the future if we have an idea
> > > of
> > > how that future may look like.
> > >
> >
> > A future with:
> > - no array scalars
> > - 0-D arrays have the same casting rules as >=1-D arrays
> > - no value-based casting
> > would be quite nice. For "same kind" casting like
> >
>
> I don't think array-scalars really matter here, since they are typed
> and behave identical to 0-D arrays anyway.  We can have long opinion
> pieces on whether they should exist :).
>

Let's not do that:) My summary would be: Travis regrets adding them, all
other numpy-like libraries I know of decided not to have them, and that all
worked out fine. Don't want to think about touching them in NumPy now.


> >
> https://data-apis.github.io/array-api/latest/API_specification/type_promotion.html
> > .
> > Mixed-kind casting isn't specified there, because it's too different
> > between libraries. The JAX design (
> > https://jax.readthedocs.io/en/latest/type_promotion.html)  seems
> > sensible
> > there.
>
> The JAX design is the "weak DType" design (when it comes to Python
> numbers). Although, the fact that a "weak" `complex` is sorted above
> all floats, means that `bfloat16_arr + 1j` will go to the default
> complex dtype as well.
> But yes, I like the "weak" approach, just think also JAX has some
> wrinkles to smoothen.
>
>
> There is a good deal more to this if you get user DTypes and I add one
> more important constraint that:
>
>     from my_extension_module import uint24
>
> must not change any existing code that does not explicitly use
> `uint24`.
>
> Then my current approach guarantees:
>
>     np.result_type(uint24, int48, int64) -> Error
>
> If `uint24` and `int48` do not know each other (`int64` is obviously
> right here, but it is tricky to be quite certain).
>

That makes sense. I'd expect that to be extremely rare anyway. User-defined
dtypes need to interact with Python types and NumPy dtypes, anything
unknown should indeed just error.


> The other tricky example I have was:
>
>   The following becomes problematic (order does not matter):
>           uint24 +      int16  +           uint32  -> int64
>      <==      (uint24 + int16) + (uint24 + uint32) -> int64
>      <==                int32  +           uint32  -> int64
>
> With the addition that `uint24 + int32 -> int48` is defined the first
> could be expected to return `int48`, but actually getting there is
> tricky (and my current code will not).
>
> If promotion result of a user DType with a builtin one, can be a
> builtin one, then "ammending" the promotion with things like `uint24 +
> int32 -> int48` can lead to slightly surprising promotion results.
> This happens if the result of a promotion with another "category"
> (builtin) can be both a larger category or a lower one.
>

I'm not sure I follow this. If uint24 and int48 both come from the same
third-party package, there is still a problem here?

Cheers,
Ralf
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From einstein.edison at gmail.com  Wed Jan 27 04:50:12 2021
From: einstein.edison at gmail.com (Hameer Abbasi)
Date: Wed, 27 Jan 2021 10:50:12 +0100
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
Message-ID: <dcd43fa2-a608-4ff6-b76a-10d4b3466fee@Canary>

Hi, Sebastian, all

Please find my answers inlined below.

--
Sent from Canary (https://canarymail.io)

> On Dienstag, Jan. 26, 2021 at 2:01 AM, Sebastian Berg <sebastian at sipsolutions.net (mailto:sebastian at sipsolutions.net)> wrote:
> Hi all,
>
> does anyone have a thought about how user DTypes (i.e. DTypes not
> currently part of NumPy) should interact with the "value based
> promotion" logic we currently have?
> For now I can just do anything, and we will find out later. And I will
> have to do something for now, basically with the hope that it all turns
> out all-right.
>
> But there are multiple options for both what to offer to user DTypes
> and where we want to move (I am using `bfloat16` as a potential DType
> here).
>
> 1. The "weak" dtype option (this is what JAX does), where:
>
> np.array([1], dtype=bfloat16) + 4.
>
> returns a bfloat16, because 4. is "lower" than all floating
> point types.
> In this scheme the user defined `bfloat16` knows that the input
> is a Python float, but it does not know its value (if an
> overflow occurs during conversion, it could warn or error but
> not upcast). For example `np.array([1], dtype=uint4) + 2**5`
> will try `uint4(2**5)` assuming it works.
> NumPy is different `2.**300` would ensure the result is a `float64`.
>

This is what I would strongly consider the ?correct? behaviour, and would strongly prefer. All new features/user dtypes should NOT have value-based casting (or undesirable things like this in general).
If we need to have a shim for internal dtypes to preserve old behaviour, so be it, but we should aim to deprecate that at some point in the future and get rid of the shim. It should be clearly marked in the
code as a hack.

>
> If a DType does not make use of this, it would get the behaviour
> of option 2.
>
> 2. The "default" DType option: np.array([1], dtype=bfloat16) + 4. is
> always the same as `bfloat16 + float64 -> float64`.
>
> 3. Use whatever NumPy considers the "smallest appropriate dtype".
> This will not always work correctly for unsigned integers, and for
> floats this would be float16, which doesn't help with bfloat16.
>
> 4. Try to expose the actual value. (I do not want to do this, but it
> is probably a plausible extension with most other options, since
> the other options can be the "default".)
>
>
> Within these options, there is one more difficulty. NumPy currently
> applies the same logic for:
>
> np.array([1], dtype=bfloat16) + np.array(4., dtype=np.float64)
>
> which in my opinion is wrong (the second array is typed). We do have
> the same issue with deciding what to do in the future for NumPy itself.
> Right now I feel that new (user) DTypes should live in the future
> (whatever that future is).
>
> I have said previously, that we could distinguish this for universal
> functions. But calls like `np.asarray(4.)` are common, and they would
> lose the information that `4.` was originally a Python float.
>
>
> So, recently, I was considering that a better option may be to limit
> this to math Python operators: +, -, /, **, ?
>

I would strongly oppose any divergence between ufuncs and operators. I?m not a fan of special cases, and I hate divergence between behaviour that should be equivalent in the user?s eye. This would equate to adding more special cases, and would only cause confusion for users and library authors alike, unless they dig up a NEP or a mailing list discussion and go through all of it. Plus, it would be basically impossible to get rid of.

Unless what you mean is limiting value-based casting to Python operators and taking the logic out of ufuncs themselves? In which case, my answer is ?yes, but??:

We should aim to get rid of ?implicit? casting in most cases. My ideal world would be ufunc(NumPy array/scalar, python scalar) raises a TypeError. All asarray calls need a dtype, but that?s going to take a LONG time, if it?s ever going to happen. So I?m willing to settle for the above.

>
> Those are the places where it may make a difference to write:
>
> arr + 4. vs. arr + bfloat16(4.)
> int8_arr + 1 vs. int8_arr + np.int8(1)
> arr += 4. (in-place may be the most significant use-case)
>
> while:
>
> np.add(int8_arr, 1) vs. np.add(int8_arr, np.int8(1))
>
> is maybe less significant. On the other hand, it would add a subtle
> difference between operators vs. direct ufunc calls...
>
>
> In general, it may not matter: We can choose option 1 (which the
> bfloat16 does not have to use), and modify it if we ever change the
> logic in NumPy itself. Basically, I will probably pick option 1 for
> now and press on, and we can reconsider later. And hope that it does
> not make things even more complicated than it is now.
>

This seems like the right thing to do. If things break, users need to be a bit more careful about choosing types. Which is nice. It eliminates whole classes of bugs.
>
> Or maybe better just limit it completely to always use the default for
> user DTypes?
>
>
> But I would be interested if the "limit to Python operators" is
> something we should aim for here. This does make a small difference,
> because user DTypes could "live" in the future if we have an idea of
> how that future may look like.
>
> Cheers,
>
> Sebastian
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
Best regards,
Hameer Abbasi
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From swan.bosc at pm.me  Wed Jan 27 07:24:54 2021
From: swan.bosc at pm.me (Swan BOSC)
Date: Wed, 27 Jan 2021 12:24:54 +0000
Subject: [Numpy-discussion] On the use of adding an expfit class in or next
 to the polynomial module
Message-ID: <PfSkdQY_PQMpJtcLZJhfYHloxSH54aXrjQOyY95rLaebJS7gZYBAmSdcEdC_MG-O3FF_cGKvuJYVPK2oQQ048HjddUWEN9PT9dE-7A21bXM=@pm.me>

Hello people !
First-of-all, thank you for your great service to the Python community.

I'm working for a project on porting some Octave code base towards Python. As you can imagine, it is a lot of fun, but I sometimes come across functions that are not (yet ?) available in the mighty NumPy package.

Namely, the expfit function, as presented [here](https://octave.sourceforge.io/optim/function/expfit.html) (https://octave.sourceforge.io/optim/function/expfit.html) doesn't seem to exist. I'm currently building a replacement for it in my words (keywords I mean ;) ) but maybe a better solution would be to contribute some code into NumPy.

AFAIK, the preferred way to fit a Polynomial nowadays is to call numpy.polynomial.polynomial.Polynomial.
Do you think that a class for `Exponential` based on that one would be an interesting addition to NumPy ?

Thanks in advance,

Swan BOSC.
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From melissawm at gmail.com  Wed Jan 27 10:24:30 2021
From: melissawm at gmail.com (=?UTF-8?Q?Melissa_Mendon=C3=A7a?=)
Date: Wed, 27 Jan 2021 12:24:30 -0300
Subject: [Numpy-discussion] NumPy video content: creating a YouTube
 channel
In-Reply-To: <2936b918-92d9-e969-b7d1-c4e5a819593a@physics.ucf.edu>
References: <mailman.13182.1611637919.7190.numpy-discussion@python.org>
 <2936b918-92d9-e969-b7d1-c4e5a819593a@physics.ucf.edu>
Message-ID: <CAC7J6VY70_+d2gu3EQtQj0G3+uc4ui0J5SRn7=go3UeZb6nhjw@mail.gmail.com>

On Tue, Jan 26, 2021 at 3:10 AM Joe Harrington <jh at physics.ucf.edu> wrote:

>
> I like the idea of there being such a channel very much! However,
> whether it's formally a project of NumPy or just run by community
> members makes a difference.  If it's formally part of the project, you'd
> expect those to be 100% current and the best content on the topic, or at
> least highly competitive with the best.  They should get updates with
> each significant release.
>
> For example, I think it's safe to say that nobody else has produced a
> reference manual that competes with the reference pages.  They're kept
> up to date and are pretty readable.
>
> It's harder to spot-edit video, though, to keep up with changes.  Unless
> you have a lot of volunteers and are ready to coordinate them all, a
> video project might best be done as a side venture or with a beta label
> until it demonstrates that it can keep its content fresh.  An indexing
> effort for existing, high-quality video might be more valuable in the
> short term than shooting all-new video, too.
>
> --jh--
>
>
Thanks, Joe. I think that all makes sense and is a valid concern that we
also share. For now, we might experiment with indexing talks that are
already online, and if we do build up enough contributors to generate
original video content, we can go ahead with this idea.

Cheers,

Melissa
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From sebastian at sipsolutions.net  Wed Jan 27 11:38:58 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Wed, 27 Jan 2021 10:38:58 -0600
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <CABL7CQgqFGjt=d4hM7aHvqcqA0zt4gJUeGCCEekh0jp8Dk1FPA@mail.gmail.com>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
 <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
 <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>
 <CABL7CQgqFGjt=d4hM7aHvqcqA0zt4gJUeGCCEekh0jp8Dk1FPA@mail.gmail.com>
Message-ID: <3157cebbc8ea8839e68cbf3eb53a43516891e7b7.camel@sipsolutions.net>

On Wed, 2021-01-27 at 10:33 +0100, Ralf Gommers wrote:
> On Tue, Jan 26, 2021 at 10:21 PM Sebastian Berg <
> sebastian at sipsolutions.net>
> wrote:
> 
<snip>

Thanks for all the other comments, they are helpful. I am considering
writing a (hopefully short) NEP, to define the direction of thinking
here (and clarify what user DTypes can expect).  I don't like doing
that, but the issue turns out to have a lot of traps and confusing
points. (Our current logic alone is confusing enough...)

> 
> > The other tricky example I have was:
> > 
> > ? The following becomes problematic (order does not matter):
> > ????????? uint24 +????? int16? +?????????? uint32? -> int64
> > ???? <==????? (uint24 + int16) + (uint24 + uint32) -> int64
> > ???? <==??????????????? int32? +?????????? uint32? -> int64
> > 
> > With the addition that `uint24 + int32 -> int48` is defined the
> > first
> > could be expected to return `int48`, but actually getting there is
> > tricky (and my current code will not).
> > 
> > If promotion result of a user DType with a builtin one, can be a
> > builtin one, then "ammending" the promotion with things like
> > `uint24 +
> > int32 -> int48` can lead to slightly surprising promotion results.
> > This happens if the result of a promotion with another "category"
> > (builtin) can be both a larger category or a lower one.
> > 
> 
> I'm not sure I follow this. If uint24 and int48 both come from the
> same
> third-party package, there is still a problem here?
> 

Yes, at least unless you ask `uint24` to take over all of the work
(i.e. pass in all DTypes at once).
So with a binary operator design it is "problematic" (in the sense that
you have to live with the above result). Of course a binary operator
base does probably not preclude a more complex design.
I like a binary operator (it seems much easier to reason about and is a
common design pattern).  But it would be plausible to have an n-ary
design where you pass all dtypes to each and ask them to handle it
(similar to `__array_ufunc__`).
We could even have both (the binary version for most things, but the
ability to hook into the n-ary "reduction").

Cheers,

Sebastian


> Cheers,
> Ralf
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From ralf.gommers at gmail.com  Wed Jan 27 12:16:37 2021
From: ralf.gommers at gmail.com (Ralf Gommers)
Date: Wed, 27 Jan 2021 18:16:37 +0100
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <3157cebbc8ea8839e68cbf3eb53a43516891e7b7.camel@sipsolutions.net>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
 <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
 <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>
 <CABL7CQgqFGjt=d4hM7aHvqcqA0zt4gJUeGCCEekh0jp8Dk1FPA@mail.gmail.com>
 <3157cebbc8ea8839e68cbf3eb53a43516891e7b7.camel@sipsolutions.net>
Message-ID: <CABL7CQiQNqgBVFZPwyj+27W7M=e31pLPdW+U_cX+7At3H8kcxg@mail.gmail.com>

On Wed, Jan 27, 2021 at 5:44 PM Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> On Wed, 2021-01-27 at 10:33 +0100, Ralf Gommers wrote:
> > On Tue, Jan 26, 2021 at 10:21 PM Sebastian Berg <
> > sebastian at sipsolutions.net>
> > wrote:
> >
> <snip>
>
> Thanks for all the other comments, they are helpful. I am considering
> writing a (hopefully short) NEP, to define the direction of thinking
> here (and clarify what user DTypes can expect).  I don't like doing
> that, but the issue turns out to have a lot of traps and confusing
> points. (Our current logic alone is confusing enough...)
>

Sounds good, thanks.


> >
> > > The other tricky example I have was:
> > >
> > >   The following becomes problematic (order does not matter):
> > >           uint24 +      int16  +           uint32  -> int64
> > >      <==      (uint24 + int16) + (uint24 + uint32) -> int64
> > >      <==                int32  +           uint32  -> int64
> > >
> > > With the addition that `uint24 + int32 -> int48` is defined the
> > > first
> > > could be expected to return `int48`, but actually getting there is
> > > tricky (and my current code will not).
> > >
> > > If promotion result of a user DType with a builtin one, can be a
> > > builtin one, then "ammending" the promotion with things like
> > > `uint24 +
> > > int32 -> int48` can lead to slightly surprising promotion results.
> > > This happens if the result of a promotion with another "category"
> > > (builtin) can be both a larger category or a lower one.
> > >
> >
> > I'm not sure I follow this. If uint24 and int48 both come from the
> > same
> > third-party package, there is still a problem here?
> >
>
> Yes, at least unless you ask `uint24` to take over all of the work
> (i.e. pass in all DTypes at once).
> So with a binary operator design it is "problematic" (in the sense that
> you have to live with the above result). Of course a binary operator
> base does probably not preclude a more complex design.
> I like a binary operator (it seems much easier to reason about and is a
> common design pattern).  But it would be plausible to have an n-ary
> design where you pass all dtypes to each and ask them to handle it
> (similar to `__array_ufunc__`).
> We could even have both (the binary version for most things, but the
> ability to hook into the n-ary "reduction").
>

I'd say just document it and recommend that if >1 custom dtypes are used,
then the user should (if they really care about the issue you bring up)
determine the output dtype you want via some use of result_type and then
explicitly cast.

Cheers,
Ralf
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From sebastian at sipsolutions.net  Wed Jan 27 13:18:09 2021
From: sebastian at sipsolutions.net (Sebastian Berg)
Date: Wed, 27 Jan 2021 12:18:09 -0600
Subject: [Numpy-discussion] Value based promotion and user DTypes
In-Reply-To: <CABL7CQiQNqgBVFZPwyj+27W7M=e31pLPdW+U_cX+7At3H8kcxg@mail.gmail.com>
References: <ad9a84fec522035395701f7b2328dfdce519d43b.camel@sipsolutions.net>
 <CABL7CQiqhyF4OcBjBWbNNqV8GNp7NW62aw-ftepTP-4_ruWkLA@mail.gmail.com>
 <e01db20635444cf4f9fe2286e31ef78f4e7aef4e.camel@sipsolutions.net>
 <CABL7CQgqFGjt=d4hM7aHvqcqA0zt4gJUeGCCEekh0jp8Dk1FPA@mail.gmail.com>
 <3157cebbc8ea8839e68cbf3eb53a43516891e7b7.camel@sipsolutions.net>
 <CABL7CQiQNqgBVFZPwyj+27W7M=e31pLPdW+U_cX+7At3H8kcxg@mail.gmail.com>
Message-ID: <0b078f017c45e33a0f2a77d7d4676dcaaa9f899f.camel@sipsolutions.net>

On Wed, 2021-01-27 at 18:16 +0100, Ralf Gommers wrote:
> On Wed, Jan 27, 2021 at 5:44 PM Sebastian Berg <
> sebastian at sipsolutions.net>
> wrote:
> 
> > On Wed, 2021-01-27 at 10:33 +0100, Ralf Gommers wrote:
> > > On Tue, Jan 26, 2021 at 10:21 PM Sebastian Berg <
> > > sebastian at sipsolutions.net>
> > > wrote:
> > > 
> > <snip>
> > 
> > Thanks for all the other comments, they are helpful. I am
> > considering
> > writing a (hopefully short) NEP, to define the direction of
> > thinking
> > here (and clarify what user DTypes can expect).? I don't like doing
> > that, but the issue turns out to have a lot of traps and confusing
> > points. (Our current logic alone is confusing enough...)
> > 
> 
> Sounds good, thanks.
> 
> 
> > > 
> > > > The other tricky example I have was:
> > > > 
> > > > ? The following becomes problematic (order does not matter):
> > > > ????????? uint24 +????? int16? +?????????? uint32? -> int64
> > > > ???? <==????? (uint24 + int16) + (uint24 + uint32) -> int64
> > > > ???? <==??????????????? int32? +?????????? uint32? -> int64
> > > > 
> > > > With the addition that `uint24 + int32 -> int48` is defined the
> > > > first
> > > > could be expected to return `int48`, but actually getting there
> > > > is
> > > > tricky (and my current code will not).
> > > > 
> > > > If promotion result of a user DType with a builtin one, can be
> > > > a
> > > > builtin one, then "ammending" the promotion with things like
> > > > `uint24 +
> > > > int32 -> int48` can lead to slightly surprising promotion
> > > > results.
> > > > This happens if the result of a promotion with another
> > > > "category"
> > > > (builtin) can be both a larger category or a lower one.
> > > > 
> > > 
> > > I'm not sure I follow this. If uint24 and int48 both come from
> > > the
> > > same
> > > third-party package, there is still a problem here?
> > > 
> > 
> > Yes, at least unless you ask `uint24` to take over all of the work
> > (i.e. pass in all DTypes at once).
> > So with a binary operator design it is "problematic" (in the sense
> > that
> > you have to live with the above result). Of course a binary
> > operator
> > base does probably not preclude a more complex design.
> > I like a binary operator (it seems much easier to reason about and
> > is a
> > common design pattern).? But it would be plausible to have an n-ary
> > design where you pass all dtypes to each and ask them to handle it
> > (similar to `__array_ufunc__`).
> > We could even have both (the binary version for most things, but
> > the
> > ability to hook into the n-ary "reduction").
> > 
> 
> I'd say just document it and recommend that if >1 custom dtypes are
> used,
> then the user should (if they really care about the issue you bring
> up)
> determine the output dtype you want via some use of result_type and
> then
> explicitly cast.
> 

Right, this is a problem that keeps giving...  Maybe a point of how
tricky Units are, but similar things will also apply to other
"families" of dtypes.
If you have Units (that can be based off any other NumPy numerical
type), you can break my scheme to work around the associativity issue
in the same way:

    Unit[int16] + uint16 + float16

has no clear hierarchy between them (Unit is the highest, but `float16`
dictates the precision).

So, probably we just shouldn't care too much about this (for now), but
if we want the above to return `Unit[float16]`, we must have additional
logic, to do reasonably... (aside from a binary operation)

I agree that these are all "insignificant" issues in many ways, since
most users will never even notice about the subtleties. So in some ways
my meandering towards binary-op only is that it feels at least small
enough in complexity that it hopefully doesn't make solutions for the
above much more complicated.

Cheers,

Sebastian



> Cheers,
> Ralf
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion

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From stefanv at berkeley.edu  Wed Jan 27 21:21:04 2021
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Wed, 27 Jan 2021 18:21:04 -0800
Subject: [Numpy-discussion] PSF Scientific WG grants
Message-ID: <82c3d251-72f8-48b7-b969-e65237b30f26@www.fastmail.com>

Hi all,

I'd like to make you aware of this call for funding from the PSF:

https://pyfound.blogspot.com/2020/12/psf-scientific-working-group-announces.html

Funding is for up to 4000 USD.

The deadline has been extended (the blog post will soon be updated accordingly); I recommend submitting requests within the next two weeks.

St?fan

From stefanv at berkeley.edu  Fri Jan 29 01:49:00 2021
From: stefanv at berkeley.edu (Stefan van der Walt)
Date: Thu, 28 Jan 2021 22:49:00 -0800
Subject: [Numpy-discussion] 
 =?utf-8?q?On_the_use_of_adding_an_expfit_clas?=
 =?utf-8?q?s_in_or_next_to_the_polynomial_module?=
In-Reply-To: <PfSkdQY_PQMpJtcLZJhfYHloxSH54aXrjQOyY95rLaebJS7gZYBAmSdcEdC_MG-O3FF_cGKvuJYVPK2oQQ048HjddUWEN9PT9dE-7A21bXM=@pm.me>
References: <PfSkdQY_PQMpJtcLZJhfYHloxSH54aXrjQOyY95rLaebJS7gZYBAmSdcEdC_MG-O3FF_cGKvuJYVPK2oQQ048HjddUWEN9PT9dE-7A21bXM=@pm.me>
Message-ID: <03b6f877-1ed4-4c8e-b323-9d608d78392e@www.fastmail.com>

Hi there,

Thanks for reaching out.

On Wed, Jan 27, 2021, at 04:24, Swan BOSC wrote:
> Namely, the expfit function, as presented here <https://octave.sourceforge.io/optim/function/expfit.html> (https://octave.sourceforge.io/optim/function/expfit.html) doesn't seem to exist. I'm currently building a replacement for it in my words (keywords I mean ;) ) but maybe a better solution would be to contribute some code into NumPy.
> 
> AFAIK, the preferred way to fit a Polynomial nowadays is to call `numpy.polynomial.polynomial.``Polynomial.` 
> Do you think that a class for `Exponential` based on that one would be an interesting addition to NumPy ?

I think Prony's method would probably be a better fit for `scipy.signal`.  Please be mindful not to translate this from existing GPL code, but to implement it afresh.

Best regards,
St?fan
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From melissawm at gmail.com  Fri Jan 29 12:47:06 2021
From: melissawm at gmail.com (=?UTF-8?Q?Melissa_Mendon=C3=A7a?=)
Date: Fri, 29 Jan 2021 14:47:06 -0300
Subject: [Numpy-discussion] Documentation Team meeting - Monday February 1
In-Reply-To: <CAC7J6Vb5uGp-gEMudbbiWSBKo1gyMsq03M4hz9mnNYir9GcqXw@mail.gmail.com>
References: <CAC7J6Vbkch+=wQcEbJgELAphM2d2552Ywr2txrbinUR-khTR=g@mail.gmail.com>
 <CAC7J6VY9k_EGL-adWpeHLvFOEG6EBy3wauhD8cZ5vmL-JDxA0Q@mail.gmail.com>
 <CAC7J6VaNwZDbtt4FP6mX_-+iD_d=_4VVcjdGiaJj=q7eWCHewA@mail.gmail.com>
 <CAC7J6VZ2D8q0s7+rpKv7HYh9oBqwOQnUP_HjwKCjMtAnfi60Og@mail.gmail.com>
 <CAC7J6VY=vgKXySL1Euy30ZNzqkqvcr4Za1L04JZv-GCk87c1AQ@mail.gmail.com>
 <CAC7J6Vbq0vtd5JH6MXvcSj4A4aZjg+x=QdHvPyQGeGcmpp8JYg@mail.gmail.com>
 <CAC7J6VZ_+uh967zGc7qA6+KWKsP=gZ8bZecrJ9Hq9oG0JTzsOg@mail.gmail.com>
 <CAC7J6VZkder9wiEmE+Cm5Lxg0zt0t_a-KwfuvcCXZG91Wk+7kA@mail.gmail.com>
 <CAC7J6VYyt4c2qcp92iE8_BMF70cUC3-ZX5E5mqNa0zVAFryvmQ@mail.gmail.com>
 <CAC7J6VZq1DLDk--F+S6F50DHMMXOaWo6cbpSau7APHe22X_c9w@mail.gmail.com>
 <CAC7J6VaegMEY9dvMeRSe2YY=AUEJYkXNNF-KTy89zyE6LgHo5A@mail.gmail.com>
 <CAC7J6VY4_X-MyXajy0KryML03KoryKR9n5dsf5bupgv7noukUg@mail.gmail.com>
 <CAC7J6Va3n9Hdym+RmscOkDyf1ukH+DDtCv7N9D8y0cX1a+uC-A@mail.gmail.com>
 <CAC7J6VZX57n+_nWL-dKe4YzqY=Nc1=LYRXkNv8+JcP=q3Vyqog@mail.gmail.com>
 <CAC7J6Vb5uGp-gEMudbbiWSBKo1gyMsq03M4hz9mnNYir9GcqXw@mail.gmail.com>
Message-ID: <CAC7J6Va3g7Pqrs=Hxtgg6GKHhZwErz4PPiKLw0YL-R2HUkWprQ@mail.gmail.com>

Hi all!

Our next Documentation Team meeting will be on *Monday, February 1* at ***4PM
UTC***. All are welcome - you don't need to already be a contributor to
join. If you have questions or are curious about what we're doing, we'll be
happy to meet you!

If you wish to join on Zoom, use this link:

https://zoom.us/j/96219574921?pwd=VTRNeGwwOUlrYVNYSENpVVBRRjlkZz09#success

Here's the permanent hackmd document with the meeting notes (still being
updated in the next few days!):

https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg
<https://www.google.com/url?q=https%3A%2F%2Fhackmd.io%2FoB_boakvRqKR-_2jRV-Qjg&sa=D&usd=2&usg=AFQjCNGIOzVwlfDFd6YAgBwVUjmjQKWRSw>

Hope to see you around!

** You can click this link to get the correct time at your timezone:
https://www.timeanddate.com/worldclock/fixedtime.html?msg=NumPy+Documentation+Team+Meeting&iso=20210201T16&p1=1440&ah=1


- Melissa
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From charlesr.harris at gmail.com  Sat Jan 30 15:41:20 2021
From: charlesr.harris at gmail.com (Charles R Harris)
Date: Sat, 30 Jan 2021 13:41:20 -0700
Subject: [Numpy-discussion] NumPy 1.20.0 released
Message-ID: <CAB6mnxKQskReueBq2wmqNbWYUUhp80xPSEyH3mJLaCdoefyP6g@mail.gmail.com>

Hi All,

On behalf of the NumPy team I am pleased to announce the release of NumPy
1.20.0rc2. This NumPy release is the largest to date, containing some 684
merged pull requests contributed by 184 people. See the list of highlights
below. The Python versions supported for this release are 3.7-3.9, support
for Python 3.6 has been dropped. Wheels can be downloaded from PyPI
<https://pypi.org/project/numpy/1.20.0/>; source archives, release notes,
and wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v1.20.0>. Linux users will
need pip >= 0.19.3 in order to install manylinux2010 and manylinux2014
wheels.

*Highlights*

   - Annotations for NumPy functions. This work is ongoing and improvements
   can be expected pending feedback from users.
   - Wider use of SIMD to increase execution speed of ufuncs. Much work has
   been done in introducing universal functions that will ease use of modern
   features across different hardware platforms. This work is ongoing.
   - Preliminary work in changing the dtype and casting implementations in
   order to provide an easier path to extending dtypes. This work is ongoing
   but enough has been done to allow experimentation and feedback.
   - Extensive documentation improvements comprising some 185 PR merges.
   This work is ongoing and part of the larger project to improve NumPy's
   online presence and usefulness to new users.
   - Further cleanups related to removing Python 2.7. This improves code
   readability and removes technical debt.
   - Preliminary support for the upcoming Cython 3.0.

*Contributors*

A total of 184 people contributed to this release.  People with a "+" by
their
names contributed a patch for the first time.

* Aaron Meurer +
* Abhilash Barigidad +
* Abhinav Reddy +
* Abhishek Singh +
* Al-Baraa El-Hag +
* Albert Villanova del Moral +
* Alex Leontiev +
* Alex Rockhill +
* Alex Rogozhnikov
* Alexander Belopolsky
* Alexander Kuhn-Regnier +
* Allen Downey +
* Andras Deak
* Andrea Olivo +
* Andrew Eckart +
* Anirudh Subramanian
* Anthony Byuraev +
* Antonio Larrosa +
* Ashutosh Singh +
* Bangcheng Yang +
* Bas van Beek +
* Ben Derrett +
* Ben Elliston +
* Ben Nathanson +
* Bernie Gray +
* Bharat Medasani +
* Bharat Raghunathan
* Bijesh Mohan +
* Bradley Dice +
* Brandon David +
* Brandt Bucher
* Brian Soto +
* Brigitta Sipocz
* Cameron Blocker +
* Carl Leake +
* Charles Harris
* Chris Brown +
* Chris Vavaliaris +
* Christoph Gohlke
* Chunlin Fang
* CloseChoice +
* Daniel G. A. Smith +
* Daniel Hrisca
* Daniel Vanzo +
* David Pitchford +
* Davide Dal Bosco +
* Derek Homeier
* Dima Kogan +
* Dmitry Kutlenkov +
* Douglas Fenstermacher +
* Dustin Spicuzza +
* E. Madison Bray +
* Elia Franzella +
* Enrique Mat?as S?nchez +
* Erfan Nariman | Veneficus +
* Eric Larson
* Eric Moore
* Eric Wieser
* Erik M. Bray
* EthanCJ-git +
* Etienne Guesnet +
* FX Coudert +
* Felix Divo
* Frankie Robertson +
* Ganesh Kathiresan
* Gengxin Xie
* Gerry Manoim +
* Guilherme Leobas
* Hassan Kibirige
* Hugo Mendes +
* Hugo van Kemenade
* Ian Thomas +
* InessaPawson +
* Isabela Presedo-Floyd +
* Isuru Fernando
* Jakob Jakobson +
* Jakub Wilk
* James Myatt +
* Jesse Li +
* John Hagen +
* John Zwinck
* Joseph Fox-Rabinovitz
* Josh Wilson
* Jovial Joe Jayarson +
* Julia Signell +
* Jun Kudo +
* Karan Dhir +
* Kaspar Thommen +
* Kerem Halla?
* Kevin Moore +
* Kevin Sheppard
* Klaus Zimmermann +
* LSchroefl +
* Laurie +
* Laurie Stephey +
* Levi Stovall +
* Lisa Schwetlick +
* Lukas Geiger +
* Madhulika Jain Chambers +
* Matthias Bussonnier
* Matti Picus
* Melissa Weber Mendon?a
* Michael Hirsch
* Nick R. Papior
* Nikola Forr?
* Noman Arshad +
* Paul YS Lee +
* Pauli Virtanen
* Pawe? Redzy?ski +
* Peter Andreas Entschev
* Peter Bell
* Philippe Ombredanne +
* Phoenix Meadowlark +
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Cheers,

Charles Harris
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From swan.bosc at pm.me  Sat Jan 30 19:03:31 2021
From: swan.bosc at pm.me (Swan BOSC)
Date: Sun, 31 Jan 2021 00:03:31 +0000
Subject: [Numpy-discussion] On the use of adding an expfit class in or
 next to the polynomial module
In-Reply-To: <03b6f877-1ed4-4c8e-b323-9d608d78392e@www.fastmail.com>
References: <PfSkdQY_PQMpJtcLZJhfYHloxSH54aXrjQOyY95rLaebJS7gZYBAmSdcEdC_MG-O3FF_cGKvuJYVPK2oQQ048HjddUWEN9PT9dE-7A21bXM=@pm.me>
 <03b6f877-1ed4-4c8e-b323-9d608d78392e@www.fastmail.com>
Message-ID: <ExNbguyRPGgpqoxms9vwCA161Nq1j9a_XUH9mwMfk78Mt4nEpqFpvb4LLhosYoTI-yU0D0DEZj_QwBzBq16eHwUCWg8JZ1BqYhMC2o1_7bw=@pm.me>

Hi Stefan,

Thanks for the advice and for the redirection to scipy !
I will create an implementation of it there

Swan BOSC.

??????? Original Message ???????
On Friday, January 29th, 2021 at 07:49, Stefan van der Walt <stefanv at berkeley.edu> wrote:

> Hi there,
>
> Thanks for reaching out.
>
> On Wed, Jan 27, 2021, at 04:24, Swan BOSC wrote:
>
>> Namely, the expfit function, as presented [here](https://octave.sourceforge.io/optim/function/expfit.html) (https://octave.sourceforge.io/optim/function/expfit.html) doesn't seem to exist. I'm currently building a replacement for it in my words (keywords I mean ;) ) but maybe a better solution would be to contribute some code into NumPy.
>>
>> AFAIK, the preferred way to fit a Polynomial nowadays is to call numpy.polynomial.polynomial.Polynomial.
>> Do you think that a class for `Exponential` based on that one would be an interesting addition to NumPy ?
>
> I think Prony's method would probably be a better fit for `scipy.signal`. Please be mindful not to translate this from existing GPL code, but to implement it afresh.
>
> Best regards,
> St?fan
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