Dear yt
How do I label the axis of a plot in normalized values?
On my plot I want to label my x and y axis in terms of the vertical line.
Do I use convert_to_plot under streamlines?
Link to the plot and script is below
https://drive.google.com/open?id=0B4g8shg4DL7oak5PLWVVdG5UMHc
Thanks in advance
On Thu, Jun 8, 2017 at 1:01 PM,
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Today's Topics:
1. Re: selecting data by refinement level (Klaus Weide) 2. Re: selecting data by refinement level (Matthew Turk) 3. Re: selecting data by refinement level (Nathan Goldbaum) 4. Re: selecting data by refinement level (Klaus Weide)
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Message: 1 Date: Wed, 7 Jun 2017 13:53:49 -0500 (CDT) From: Klaus Weide
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: TEXT/PLAIN; charset=US-ASCII On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet, but the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus
------------------------------
Message: 2 Date: Wed, 7 Jun 2017 13:56:51 -0500 From: Matthew Turk
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: text/plain; charset="UTF-8" Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`. The YTArray it returns is a subclass of ndarray, so should in general be usable in both ways; as you probably figured out, if you do any manipulation of individual elements it adds overhead and (often frustrating, but hopefully ultimately helpful), restrictions on combining incorrect units unless you look at it as a strict ndarray.
On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide
wrote: On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet, but the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus _______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
------------------------------
Message: 3 Date: Wed, 7 Jun 2017 12:00:44 -0700 From: Nathan Goldbaum
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: text/plain; charset="utf-8" On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk
wrote: Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`. The YTArray it returns is a subclass of ndarray, so should in general be usable in both ways; as you probably figured out, if you do any manipulation of individual elements it adds overhead and (often frustrating, but hopefully ultimately helpful), restrictions on combining incorrect units unless you look at it as a strict ndarray.
One tiny note:
YTArray.d is short for YTArray.ndarray_view(), which returns a view onto the array. This doesn't copy the underlying data.
YTArray.to_ndarray() is equivalend to YTArray.value or YTArray.v, whcih returns an ndarray containing a copy of the underlying array data. Getting a copy sometimes adds overhead.
Choosing whether or now you want a copy comes down to what exactly you are doing, since copying adds overhead, but it also prevents silently overwriting data in an unexpected, nonlocal fashion.
On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide
wrote: On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet,
but
the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus _______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
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Message: 4 Date: Wed, 7 Jun 2017 14:45:52 -0500 (CDT) From: Klaus Weide
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: TEXT/PLAIN; charset=US-ASCII On Wed, 7 Jun 2017, Nathan Goldbaum wrote:
On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk
wrote: Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`.
One tiny note:
YTArray.d is short for YTArray.ndarray_view(), which returns a view onto the array. This doesn't copy the underlying data.
Matt and Nathan,
Thanks for the additional info, I think it's very useful to know.
Klaus
------------------------------
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-- *SK2* *"**Claiming that something can move faster than light is a good conversation-stopper in physics. People edge away from you in cocktail parties; friends never return phone calls. You just don’t mess with Albert Einstein.**"*
Try to use plot.set_axes_unit("unitary").
On Fri, Jun 9, 2017 at 9:08 AM Sushilkumar
Dear yt
How do I label the axis of a plot in normalized values?
On my plot I want to label my x and y axis in terms of the vertical line.
Do I use convert_to_plot under streamlines?
Link to the plot and script is below
https://drive.google.com/open?id=0B4g8shg4DL7oak5PLWVVdG5UMHc
Thanks in advance
On Thu, Jun 8, 2017 at 1:01 PM,
wrote: Send yt-users mailing list submissions to yt-users@lists.spacepope.org
To subscribe or unsubscribe via the World Wide Web, visit http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org or, via email, send a message with subject or body 'help' to yt-users-request@lists.spacepope.org
You can reach the person managing the list at yt-users-owner@lists.spacepope.org
When replying, please edit your Subject line so it is more specific than "Re: Contents of yt-users digest..."
Today's Topics:
1. Re: selecting data by refinement level (Klaus Weide) 2. Re: selecting data by refinement level (Matthew Turk) 3. Re: selecting data by refinement level (Nathan Goldbaum) 4. Re: selecting data by refinement level (Klaus Weide)
----------------------------------------------------------------------
Message: 1 Date: Wed, 7 Jun 2017 13:53:49 -0500 (CDT) From: Klaus Weide
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: TEXT/PLAIN; charset=US-ASCII On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet, but the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus
------------------------------
Message: 2 Date: Wed, 7 Jun 2017 13:56:51 -0500 From: Matthew Turk
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: text/plain; charset="UTF-8" Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`. The YTArray it returns is a subclass of ndarray, so should in general be usable in both ways; as you probably figured out, if you do any manipulation of individual elements it adds overhead and (often frustrating, but hopefully ultimately helpful), restrictions on combining incorrect units unless you look at it as a strict ndarray.
On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide
wrote: On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet, but the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus _______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
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Message: 3 Date: Wed, 7 Jun 2017 12:00:44 -0700 From: Nathan Goldbaum
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: text/plain; charset="utf-8" On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk
wrote: Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`. The YTArray it returns is a subclass of ndarray, so should in general be usable in both ways; as you probably figured out, if you do any manipulation of individual elements it adds overhead and (often frustrating, but hopefully ultimately helpful), restrictions on combining incorrect units unless you look at it as a strict ndarray.
One tiny note:
YTArray.d is short for YTArray.ndarray_view(), which returns a view onto the array. This doesn't copy the underlying data.
YTArray.to_ndarray() is equivalend to YTArray.value or YTArray.v, whcih returns an ndarray containing a copy of the underlying array data. Getting a copy sometimes adds overhead.
Choosing whether or now you want a copy comes down to what exactly you are doing, since copying adds overhead, but it also prevents silently overwriting data in an unexpected, nonlocal fashion.
On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide
wrote: On Wed, 7 Jun 2017, Matthew Turk wrote:
Hi Klaus,
Whoops, I said "grid_collection" but I meant "data_collection".
Thanks Matt. I have not tried the 'collection of grids' approach yet,
but
the following does what I want:
ds = yt.load(dump_path)
ad = ds.all_data() if fine_only: maxreflevel = ad.index.grid_levels.max() print '*** Filtering data so that only FLASH refinement level {} cells are used'.format(maxreflevel+1) ad.min_level = maxreflevel ad.max_level = maxreflevel print 'These cover a volume of %s' % ad['cell_volume'].sum() # ..... data = {} data['dens'] = ad['dens'].to_ndarray() # .....
Klaus _______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
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Message: 4 Date: Wed, 7 Jun 2017 14:45:52 -0500 (CDT) From: Klaus Weide
To: Discussion of the yt analysis package Subject: Re: [yt-users] selecting data by refinement level Message-ID: Content-Type: TEXT/PLAIN; charset=US-ASCII On Wed, 7 Jun 2017, Nathan Goldbaum wrote:
On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk
wrote: Great! As a quick note, you can use `.d` as shorthand for `to_ndarray()`.
One tiny note:
YTArray.d is short for YTArray.ndarray_view(), which returns a view onto the array. This doesn't copy the underlying data.
Matt and Nathan,
Thanks for the additional info, I think it's very useful to know.
Klaus
------------------------------
Subject: Digest Footer
_______________________________________________ yt-users mailing list yt-users@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
------------------------------
End of yt-users Digest, Vol 112, Issue 5 ****************************************
-- *SK2*
*"**Claiming that something can move faster than light is a good conversation-stopper in physics. People edge away from you in cocktail parties; friends never return phone calls. You just don’t mess with Albert Einstein.**"*
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participants (2)
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Nathan Goldbaum
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Sushilkumar