Re: [yt-users] Error with annotate_marker: Unknown property

2 Aug 2013

      Hey Chao,

Sorry for not saying how I determined that.  If you look at the traceback
you posted, you'll see that the execution left yt and entered matplotlib on
line 777 of $YT_HG/yt/visualization/plot_window.py with a call to
axes.scatter().  I happened to know that axes in this context refers to a
matplotlib axes.Axes object, so that was what led me to the proper page in
the matplotlib documentation.

Whenever you see an error like that, it really pays to closely look at the
traceback to try and figure out exactly what broke.  One of the advantages
of using open source python tools like yt and matplotlib is that the source
code is on your computer and you can always take a look at it to get some
context for the traceback, even if you're unfamiliar with the codebase.
 Even better, you can modify the code, and, for example, insert calls to
debuggers like pdb to interactively figure out exactly what's happening.
 No matter how confusing a package's documentation, you can always be
certain that the most up do date and accurate documentation for a project
will be the source code its self.

Hope that was useful rather than just a mini-rant ;)

-Nathan

On Thu, Aug 1, 2013 at 8:04 PM, Chao Shi  wrote:
...
On Thu, Aug 1, 2013 at 10:49 PM, wrote:
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Today's Topics:
1. Re: Error with annotate_marker: Unknown property (Nathan Goldbaum)
   2. ANN: matplotlib 1.3.0 released (Nathan Goldbaum)
   3. Re: MultiVariate volume rendering difficulties (Cameron Hummels)
----------------------------------------------------------------------
Hi Nathan,
Thanks. That's very informative. Would you mind tell me how you found
that? I also tried to
search for the allowed keywords for that callback but didn't find any
useful information. Just in case
next time I run into such kind of problems.
Thank you very much.
Chao
...
Message: 1
Date: Thu, 1 Aug 2013 16:35:55 -0700
From: Nathan Goldbaum 
To: Discussion of the yt analysis package

Subject: Re: [yt-users] Error with annotate_marker: Unknown property
Message-ID:

Content-Type: text/plain; charset="iso-8859-1"
Hi Chao,
For that callback, you're only allowed to specify keyword arguments
accepted by matplotlib.axes.Axes.scatter:
http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.scatter
or Collection properties:
http://matplotlib.org/api/collections_api.html#matplotlib.collections.Collec...
I'd have to look closer to figure out which keyword corresponds to what
you're looking for, but hopefully that leaves you enough information to
figure out how to do what you're trying to do.
-Nathan
On Thu, Aug 1, 2013 at 3:53 PM, Chao Shi  wrote:
...
Hi all,
I'm trying to mark some positions with circle on slice and projection
plot. But it can't recognize arguments used for specifying the property
of
the marker. For example:
...
...
...
p = SlicePlot(pf,'x','Density')
...
...
...
p.annotate_marker([0.5]*3,marker='o', plot_args={'color': 'red',
'mew': 5})
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File
"/home/cshi31/yt-x86_64/src/yt-hg/yt/visualization/plot_window.py",
line 100, in newfunc
    args[0]._setup_plots()
  File
"/home/cshi31/yt-x86_64/src/yt-hg/yt/visualization/plot_window.py",
line 886, in _setup_plots
    self.run_callbacks(f)
  File
"/home/cshi31/yt-x86_64/src/yt-hg/yt/visualization/plot_window.py",
line 896, in run_callbacks
    callback(cbw)
  File
"/home/cshi31/yt-x86_64/src/yt-hg/yt/visualization/plot_modifications.py",
...
line 777, in __call__
    plot._axes.scatter(x,y, marker = self.marker, **self.plot_args)
  File
"/home/cshi31/yt-x86_64/lib/python2.7/site-packages/matplotlib/axes.py",
line 6123, in scatter
    collection.update(kwargs)
   File
"/home/cshi31/yt-x86_64/lib/python2.7/site-packages/matplotlib/artist.py",
...
line 670, in update
    raise AttributeError('Unknown property %s' % k)
AttributeError: Unknown property mew
mew is an alias for markeredgewidth. I also tried with 'markeredgewidth'
but it gave the same error.
Besides, 'mec', 'ms' also can't be recognized. Only 'color' works.
Does anyone have a clue about this?
Thanks very much.
Chao
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Message: 2
Date: Thu, 1 Aug 2013 18:24:41 -0700
From: Nathan Goldbaum 
To: Discussion of the yt analysis package

Subject: [yt-users] ANN: matplotlib 1.3.0 released
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Hi all,
Please see the matplotlib mailing list archives for the release notes and
official announcement e-mail:
http://matplotlib.1069221.n5.nabble.com/ANN-matplotlib-1-3-0-released-td4167...
This big new feature for this version is the WebAGG backend, which is a
new
plotting interface specially made for the IPython notebook.  It also
includes a convenience function that alters the plotting settings to
generate xkcd-style plots.
There may be some incompatibilities with yt - if anyone notices any issues
please report it on the issue tracker.
Cheers,
Nathan
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Message: 3
Date: Thu, 1 Aug 2013 19:39:02 -0700
From: Cameron Hummels 
To: Discussion of the yt analysis package

Subject: Re: [yt-users] MultiVariate volume rendering difficulties
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I agree with Stella's solution, as that's what I've done in the past.
 Obviously you can get some blending between the two CTFs, but that's the
point right?
Cameron
On Thu, Aug 1, 2013 at 2:31 PM, Nathan Goldbaum 
...
wrote:
...
Wow Noel, keep up the awesome work!
I'm sure this will be helpful for Sam when he looks at this stuff next
week.
On Thu, Aug 1, 2013 at 1:53 PM, Noel Scudder <
noel.scudder@stonybrook.edu>wrote:
...
Hi all,
Over the past few days I've been investigating the
MultiVariateTransferFunction and receiving feedback from Matt. Since it
needs some updating and the documentation is so vague, I thought I'd
try to
outline the basic flow and idea of an MVTF (thanks to Matt for his
outline), address a couple problems that have been noticed, and give an
example script with images. Please feel free to correct my mistakes,
ask
questions, and add your own knowledge!
The code for the MVTF is
in yt/visualization/volume_rendering/transfer_functions.py . It's also
useful to check out the Planck and Color Transfer Functions in the same
file.
With a CTF, you are limited to one field, which is linked identically
to
each of the RGB color channels and an alpha channel. However, an MVTF
allows you to set up different fields that control each channel and
each
channel's opacity through the use of standard Transfer Functions. For
instance, I could link the red color channel and the red alpha channel
to
Density, the blue and blue alpha channels to Temperature, and the
green and
green alpha channels to Kinetic Energy.
It is important to note that only *one* field (and associated transfer
function) may be linked to any channel. This limits the number of
variables
one can conceivably include to three.
When an MVTF is created, it sets up a few variables:
n_field_tables
tables
field_ids
weight_field_ids
field_table_ids
weight_table_ids
grad_field
light_source_v
The important ones here are tables, field_ids, weight_field_ids,
field_table_ids, and weight_table_ids.
After creating your MVTF, the first thing you must do is create a
TransferFunction, which has some range and number of bins. This can
then be
added as a "table" to your MVTF using add_field_table, which accepts
the
table, the field_id used for interpolating on the x-axis of this
table, a
weight_field_id, and/or a weight_table id.
The field_id is *not* the field index you get from pf.h.field_indexes .
Here, the field_id actually specifies the index of a certain field in
the
field list you supply to the camera object. For instance, if I gave the
camera
fields=['density', 'Temp']
I would have previously called add_field_table using a field_id of 0
for
the TransferFunctions I wanted for density, and using a field_id of 1
for
the TransferFunctions I wanted for temperature.
The same specification with the field_id goes for weight_field_id,
which
is used if the field itself should be a weighting factor for the
emission/absorption (although this does not do scaling, so you will
likely
need to supply a pre-scaled field).
By supplying a weight_table_id, you are taking the results of
interpolation along the x-axis to get a y value from *another* field
table
and using that as a weight.
*Apparently density is typically logged by default. If you want to use
it
as a weight, you probably want it un-logged.
At this point you have added all of your field tables. The second step
is
to link the field tables to the channels you want. Right now, all you
have
is a set of "tables," TransferFunctions that describe how to get a
value
out as a combination of:
1) The y-value interpolated along the x-axis defined by the table
2) The weighting from a given field
3) The weighting from a given field_table (i.e., if you had some
scaling
that was a function of temperature)
On its own, a table will do nothing--you must link it to a channel.
These
are, in order, RGB and aR, aG, aB. You use the link_channels function
for
this purpose, for instance linking table 0 to channel 0 (R). When
linking
channels, there are a couple things to keep in mind. The two arguments
you
supply are the  table_id and the channel, both *integers *(seems like a
common theme for MVTF stuff :-) ). The channel can be integers 0-5,
assigned in the order above. The table_id is a bit more nebulous: a
table_id is assigned to a table when it is created, meaning that the
first
table you create using add_field_table will have a table_id of 0, the
next
will have a table_id of 1, and so on. Although you cannot link more
than
one table to a channel, you can have more than one channel linked to a
single table--simply supply a list in place of an integer for the
channel
argument.
Finally, don't leave your TransferFunctions empty! Add some gaussians,
keeping in mind the channel and field each TF uses. After that your
MVTF
will be ready, and you can supply it to the camera object like any
other
transfer function and take a snapshot.
Here's a example script: http://pastebin.com/NC4pHPR7
Which creates this image: http://i.imgur.com/EKv943G.png
The main problem I've been noticing is with the grey_opacity, which was
already discussed--apparently the MVTF was never updated after opaque
volume rendering was implemented. Although by default an MVTF doesn't
have
a grey_opacity attribute and yt will complain about this, you can
placate
the beast by supplying
mv.grey_opacity=False
anyway. If you set grey_opacity to True, however, odd things will
happen,
which I suspect is simply due to the MVTF not having been updated for
opaque rendering yet: http://i.imgur.com/rrOnbgy.png
I think that about sums up my two cents on the MVTF.
Finally, my original desire was to have two different
ColorTransferFunctions with two different fields rendered by one
camera at
once. In other words, simultaneously render two different colormaps
applied
to two different fields. Right now this isn't possible in yt (although
Matt
thinks it may be somewhat straightforward to implement), so I came up
with
a makeshift way, where I render one TF for the first field without a
background and the second TF for the second field *with* a background,
and then overlay them using ImageMagick:
im.write_png('transparent_temp.png', background=None)
...
im2.write_png('dens_and_background.png')
os.system('composite transparent_temp.png dens_and_background.png
multi.png')
However, it's expensive, and it goes outside yt. Does anyone know if
there's a way to combine these images without leaving yt?
Thanks for reading!
-Noel
On Tue, Jul 30, 2013 at 1:03 PM, Sam Skillman 
...
Hi all,
The multivariate tf could use both some updating and documentation.
I'm
offline for the next few days but if it hasn't been fixed by next
week I
can take a look.
Sam
On Jul 30, 2013 8:40 AM, "Nathan Goldbaum" 
wrote:
...
Hi Noel,
I believe this is a bug that needs to be fixed.  It seems
MultiVariateTransferFunction was never updated after opaque volume
rendering was added.
Can you please open a new issue about this?
Nathan
...
...
...
...
On Tuesday, July 30, 2013, Noel Scudder wrote:
> Hi all,
>
> I'm attempting to visualize multiple variables in the same volume
> rendering. For instance, I'd like to show some density surfaces of
...
> and then get temperature overlayed to show hotspots. I found the
> MultiVariateTransferFunction, but it is unfortunately not
a star
particularly well
...
> documented yet, and I'm being repeatedly thwarted. I'm not sure if
I've set
> it up correctly, or how to go from the transfer function to an
image.
> Here's my current script, using just one variable for now:
>
> #----------------------------------
> from yt.mods import *
> pf = load('plt00100')
>
> #<some constants>
>
> pf.h
> pf.field_info['density'].take_log=True
>
> mv = MultiVariateTransferFunction()
>
> tf = TransferFunction((mi-1, ma+1), nbins=1.0e6)
> tf.add_gaussian(np.log10(9.0e5), 0.01, 1.0)
>
> mv.add_field_table(tf, 0)
> mv.link_channels(0, [0,1,2,3])
>
> c = [5.0e9, 5.0e9, 5.0e9]
> L = [0.15, 1.0, 0.40]
> W = wi*0.7
> Nvec = 1024
>
> cam = pf.h.camera(c, L, W, (Nvec,Nvec), transfer_function = mv,
>                              fields=['density'], pf=pf,
no_ghost=True)
>
> im = cam.snapshot(num_threads=4)
>
> im.write_png('plt00100.png' )
> #----------------------------------
>
> I checked to make sure density is indeed my 0-index field. I get the
> following error after ray casting:
...
...
...
...
>
> Traceback (most recent call last):
>   File "<stdin>", line 1, in <module>
>   File "multivol.py", line 153, in <module>
>     im = cam.snapshot(num_threads=4)
>   File
>
"/home/noel/shocks/yt-x86_64/src/yt-hg/yt/visualization/volume_rendering/camera.py",
> line 742, in snapshot
>     image, sampler),
>   File
>
"/home/noel/shocks/yt-x86_64/src/yt-hg/yt/visualization/volume_rendering/camera.py",
> line 632, in _render
>     image = self.finalize_image(image)
>   File
>
"/home/noel/shocks/yt-x86_64/src/yt-hg/yt/visualization/volume_rendering/camera.py",
> line 611, in finalize_image
>     if self.transfer_function.grey_opacity is False:
> AttributeError: 'MultiVariateTransferFunction' object has no
attribute
> 'grey_opacity'
>
>
> Can I not use snapshot in this case, or is something else the matter
> entirely?
>
> Thanks,
> Noel Scudder
...
...
...
...
>
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--
Cameron Hummels
Postdoctoral Researcher
Steward Observatory
University of Arizona
http://chummels.org
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