[yt-users] Error with annotate_marker: Unknown property
Chao Shi
shichao116 at gmail.com
Thu Aug 1 20:04:37 PDT 2013
On Thu, Aug 1, 2013 at 10:49 PM, <yt-users-request at lists.spacepope.org>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 <nathan12343 at gmail.com>
> To: Discussion of the yt analysis package
> <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] Error with annotate_marker: Unknown property
> Message-ID:
> <CAJXewO=
> bQbfRxAFjwR-2Q3Wsb5ZvGJPxwtRsk_Kfqc0zVa1cCg at mail.gmail.com>
> 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.Collection
>
> 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 <shichao116 at gmail.com> 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
> >
> >
> > _______________________________________________
> > yt-users mailing list
> > yt-users at lists.spacepope.org
> > http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
> >
> >
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> ------------------------------
>
> Message: 2
> Date: Thu, 1 Aug 2013 18:24:41 -0700
> From: Nathan Goldbaum <nathan12343 at gmail.com>
> To: Discussion of the yt analysis package
> <yt-users at lists.spacepope.org>
> 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-td41670.html
>
> 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 <chummels at gmail.com>
> To: Discussion of the yt analysis package
> <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] MultiVariate volume rendering difficulties
> Message-ID:
> <
> CACyTu7ERKuNSgCY3HMQGPXL3UPhRspyUG_r3V8L1-rzxTaPNeQ at mail.gmail.com>
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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 <nathan12343 at gmail.com
> >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 at 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 <samskillman at gmail.com
> >wrote:
> >>
> >>> 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" <nathan12343 at gmail.com>
> >>> 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 a
> star
> >>>>> and then get temperature overlayed to show hotspots. I found the
> >>>>> MultiVariateTransferFunction, but it is unfortunately not
> 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
> >>>>>
> >>>>
> >>>> _______________________________________________
> >>>> yt-users mailing list
> >>>> yt-users at lists.spacepope.org
> >>>> http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
> >>>>
> >>>>
> >>> _______________________________________________
> >>> yt-users mailing list
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> >>>
> >>>
> >>
> >> _______________________________________________
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> >>
> >>
> >
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>
>
> --
> Cameron Hummels
> Postdoctoral Researcher
> Steward Observatory
> University of Arizona
> http://chummels.org
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