Hello everyone.
I was wondering if anyone has had experience with producing a profile plot
from a 2d projection object (FRB object).
Essentially, what I am trying to do is plot the stellar surface density of
a galaxy as a function of radius.
This is achieved by doing the following from a disk YT object called
cylinder (in which the origional simulation object is called shot)
center = cylinder.get_field_parameter("center")
normal = cylinder.get_field_parameter("normal")
image_width = (100,"kpc")
three_image_width = YTArray((image_width[0], image_width[0],
image_width[0]),image_width[1])
left = center - image_width
right = center + image_width
region = shot.region(center, left, right)
proj =
yt.ProjectionPlot(cylinder.ds,"z",[("deposit","stars_density")],center=center,width=image_width,data_source=region,axes_unit="kpc")
the error arrises here
prof =
yt.create_profile(proj,bin_fields="cylindrical_r",fields=[("deposit","stars_density")],n_bins=128,weight_field=None
)
where I get the error
/gpfs/home/........./profiles.pyc in create_profile(data_source,
bin_fields, fields, n_bins, extrema, logs, units, weight_field,
accumulation, fractional)
1304 else:
1305 raise NotImplementedError
-> 1306 bin_fields = data_source._determine_fields(bin_fields)
1307 fields = data_source._determine_fields(fields)
1308 if units is not None:
AttributeError: 'FixedResolutionBuffer' object has no attribute
'_determine_fields'
Any ideas how to get around this error?
Also some other things to add as a postscript. Since how the projection
works, if I provide weights=None as a keyword argument within the
ProjectionPlot object, I get a surface density (g/cm^2). But also a
"cylindrical_r" in cm^2 as well. I *think* the way to get around this is to
do another projection where weights="ones", get the radius values out of
that profile.. and then in matplotlib, useing the surface density array
from the former profile, and the radius bin array from the latter...
Produce a plot of the surface density as a function of radius from those
two arrays (I might check by hand afterwards to see if this does the
trick). This seems kinda convoluted so I am wondering if there is an easier
way than this.
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Hi all,
I am trying to locally install yt on Blue Waters.
I did a module of swap to PrgEnv-gnu and then bash install_script.sh.
Has anyone run into this error before?
http://paste.yt-project.org/show/5576/
Thanks,
Kenza
Hi,
I want to render a Volume Plot based on data from a FLASH file, which
uses HDF5 file format. I tried the tutorial at
http://yt-project.org/doc/cookbook/simple_plots.html#cookbook-simple-volume… with my file, but I always get this
error:
yt\units\yt_array.py:764: RuntimeWarning: divide by zero encountered in divide
return YTArray(super(YTArray, self).__rdiv__(lo))
yt\data_objects\image_array.py:229: RuntimeWarning: invalid value
encountered in multiply
np.multiply(self[:, :, :3], 1.0/cmax, out[:, :, :3])
This is the complete log:
yt : [INFO ] 2015-05-29 20:51:30,302 integer runtime parameter
checkpointfilenumber overwrites a simulation scalar of the same name
yt : [INFO ] 2015-05-29 20:51:30,302 integer runtime parameter
forcedplotfilenumber overwrites a simulation scalar of the same name
yt : [INFO ] 2015-05-29 20:51:30,302 integer runtime parameter
nbegin overwrites a simulation scalar of the same name
yt : [INFO ] 2015-05-29 20:51:30,302 integer runtime parameter
particlefilenumber overwrites a simulation scalar of the same name
yt : [INFO ] 2015-05-29 20:51:30,302 integer runtime parameter
plotfilenumber overwrites a simulation scalar of the same name
yt : [INFO ] 2015-05-29 20:51:30,331 Parameters: current_time
= 1.10472907814e+17
yt : [INFO ] 2015-05-29 20:51:30,331 Parameters: domain_dimensions
= [16 16 16]
yt : [INFO ] 2015-05-29 20:51:30,332 Parameters: domain_left_edge
= [ -2.20000000e+25 -2.20000000e+25 -2.20000000e+25]
yt : [INFO ] 2015-05-29 20:51:30,332 Parameters: domain_right_edge
= [ 2.20000000e+25 2.20000000e+25 2.20000000e+25]
yt : [INFO ] 2015-05-29 20:51:30,332 Parameters:
cosmological_simulation = 0.0
yt : [INFO ] 2015-05-29 20:51:32,513 Loading field plugins.
yt : [INFO ] 2015-05-29 20:51:32,513 Loaded angular_momentum (8
new fields)
yt : [INFO ] 2015-05-29 20:51:32,515 Loaded astro (15 new fields)
yt : [INFO ] 2015-05-29 20:51:32,515 Loaded cosmology (22 new fields)
yt : [WARNING ] 2015-05-29 20:51:32,515 Field ('gas',
'number_density') already exists. To override use force_override=True.
yt : [INFO ] 2015-05-29 20:51:32,516 Loaded fluid (63 new fields)
yt : [INFO ] 2015-05-29 20:51:32,516 Loaded fluid_vector (95 new fields)
yt : [INFO ] 2015-05-29 20:51:32,516 Loaded geometric (111 new fields)
yt : [INFO ] 2015-05-29 20:51:32,517 Loaded local (111 new fields)
yt : [INFO ] 2015-05-29 20:51:32,517 Loaded magnetic_field (119
new fields)
yt : [INFO ] 2015-05-29 20:51:32,519 Loaded my_plugins (119 new fields)
yt : [INFO ] 2015-05-29 20:51:32,519 Loaded species (121 new fields)
yt : [INFO ] 2015-05-29 20:51:42,595 Warning: no_ghost is
currently True (default). This may lead to artifacts at grid boundaries.
Ray casting100% ||||||||||||||||||||||||||||||||||||||||||||||| Time: 00:00:01
C:\Anaconda\lib\site-packages\yt\units\yt_array.py:764:
RuntimeWarning: divide by zero encountered in divide
return YTArray(super(YTArray, self).__rdiv__(lo))
C:\Anaconda\lib\site-packages\yt\data_objects\image_array.py:229:
RuntimeWarning: invalid value encountered in multiply
np.multiply(self[:, :, :3], 1.0/cmax, out[:, :, :3])
The image itself is created, but only black, also the rendering
process is instantly finished.
I've tried it with the "Enzo_64/DD0043/data0043" file as used for the
tutorial, this works with errors. Then I've tried using a given FLASH
dataset, the "GalaxyClusterMerger" - same result as my dataset, also
the error.
I'm using Win 8.1 64-bit Anaconda distribution and yt-project 3.1.
Also tried the same thing on Ubuntu 14 with freshly installed
yt-project, same error.
Is there a solution to create a volume render with FLASH files?
Thank you for your attention!
Kilian
Helly yt-crowd.
I am doing some volume rendering in yt and getting some errors when I try to grow the image size. I am trying to write a png image that is 1024 x 1024. I get the following errors:
image_array.py:229: RuntimeWarning: invalid value encountered in multiply
np.multiply(self[:, :, :3], 1.0/cmax, out[:, :, :3])
yt_array.py:764: RuntimeWarning: divide by zero encountered in divide
return YTArray(super(YTArray, self).__rdiv__(lo))
The largest image I can generate is about 800x 800. It is a nice image too I tell ya. Just wish I could do a bigger one to submit for publication.
Attached is the script I am using. Any help would be great.
Thanks,
Dave Semeraro
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Hi, Everybody--
I have a dumb question about temperature in enzo. Where is it? I thought
I rememberd that being a stock derived field, but I don't see it in the
enzo frontends. I can go ahead and make a PR for that if there's not
something obvious I'm missing.
Thanks!
d.
--
-- Sent from a computer.
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Dear users,
This there a simple way to store multiple values at each step using
parallel_objects? I'm doing:
########################################################
yt.enable_parallelism()
num_procs = 4
plot = glob.glob(./plot*)
my_storage = {}
for sto, p in yt.parallel_objects(plots, num_procs, my_storage):
sto.result_id = 'energy' + p
sto.resutl = dd["total_energy"]
sto.result_id = 'Px' + p
sto.result = dd["total_mom_x"]
######################################################
which is just overwriting my energy with the momentum. I also tried to just
set to different dictionaries without passing it to yt.parallel_objects as
storage, but of course each proc as only a local copy then.
Cordially,
Josh
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Hi, Everyone--
I'm trying to get code units from enzo for a cosmology run, but
in_units('code_density')
seems to do nothing.
'code_mass/code_length**3'
seems to work. Is this a bug, or a feature?
>>> ad['density'].in_units('code_mass/code_length**3')
YTArray([ 0.9970247 , 0.99774731, 0.99854185, ..., 0.99993769,
0.99914176, 0.99841755]) code_mass/code_length**3
>>> ad['density'].in_units('code_density')
YTArray([ 1.87321000e-29, 1.87456764e-29, 1.87606042e-29, ...,
1.87868293e-29, 1.87718755e-29, 1.87582689e-29]) code_density
Thanks!
d.
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Hi Jonah,
That's right -- the volume rendering won't work, but slices will. The
VR should be working relatively soon, though.
-Matt
On Sun, May 24, 2015 at 8:47 PM, Jonah Miller
<jonah.maxwell.miller(a)gmail.com> wrote:
> Oh, I should add that I don't think 3D visualization is possible with
> hexahedral meshes at the moment. The pixelizer doesn't support them yet...
> At least that's my understanding. If you really need a 3D visualization, you
> might want to try transforming your data into a regularly spaced grid (using
> another tool) and then loading uniformly spaced data as in this example:
> http://yt-project.org/docs/dev/examining/spherical_data.html
>
> Best,
> Jonah
>
>
> On 15-05-24 09:41 PM, Jonah Miller wrote:
>
> Hi Katharina, Andrew,
>
> There is a convenience function to create the coordinates and connectivity
> arguments: hexahedral_connectivity. This function takes three 1D arrays,
> which are the projections of your grid points onto your coordinate axes,
> here called x,y, and z. The function then returns the connectivity and
> coordinates arrays.
>
> Here's an example:
> http://yt-project.org/docs/dev/examining/loading_data.html#semi-structured-…
>
> Best,
> Jonah
>
> On 15-05-24 09:35 PM, Andrew Myers wrote:
>
> Hi Katharina,
>
> I don't have an example handy, but the "coordinates" and "connectivity"
> arguments are arrays you construct that describe the vertices and zones of
> the hexahedral mesh you want. The "coordinates" argument is supposed to be a
> (N_vertices, 3) - shaped array of floats that has the x, y, and z positions
> of all the vertices in the hexahedral mesh. The "connectivity" argument is a
> (N_zone, 8) - shaped array of ints that gives, for each zone, the indices of
> the 8 vertices that surround it. So for example, if connectivity[0][2] is
> '12', then coordinates[12] would give the position coordinate of the third
> vertex surrounding the first zone, if that makes sense.
>
> Once you've constructed those arrays from the information in your dataset
> and fed them into "load_hexadral_mesh", yt shouldn't care whether the data
> came from an HDF5 file or not.
>
> -Andrew
>
> On Sun, May 24, 2015 at 11:46 AM, Katharina Wollenberg
> <kwollenberg89(a)gmail.com> wrote:
>>
>> Hello together,
>>
>> for visualising a 3D disk from ZEUS-MP HDF5 data in yt, I need to load a
>> single spherical polar coordinate grid where x1,x2,x3 are R,T,P and R has
>> ratioed zones. For that I want to use the command
>> yt.load_hexahedral_mesh(data, connectivity, coordinates, length_unit=None,
>> ...) . However, since I am new to yt, I am a little bit stuck right now…
>> I am not quite sure what is meant in detail by the arguments connectivity
>> and coordinates and how to formulate them in the load_hexahedral_mesh
>> command.
>>
>> Furthermore, do I need to pay particular attention on some commands
>> because of using HDF5 data?
>>
>> If anyone has an example for me, that’d be very helpful!
>>
>> Thanks a lot!
>>
>> Katharina Wollenberg
>>
>>
>>
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>>
>
>
>
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>
>
>
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Hello together,
for visualising a 3D disk from ZEUS-MP HDF5 data in yt, I need to load a single spherical polar coordinate grid where x1,x2,x3 are R,T,P and R has ratioed zones. For that I want to use the command yt.load_hexahedral_mesh(data, connectivity, coordinates, length_unit=None, ...) . However, since I am new to yt, I am a little bit stuck right now…
I am not quite sure what is meant in detail by the arguments connectivity and coordinates and how to formulate them in the load_hexahedral_mesh command.
Furthermore, do I need to pay particular attention on some commands because of using HDF5 data?
If anyone has an example for me, that’d be very helpful!
Thanks a lot!
Katharina Wollenberg
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Hi all,
Is there a convenient way to rotate a slice or projection plot (with
associated axis labels and tick marks) in yt? My simulation domain is long
and skinny, and yt automatically plots it with the long edge aligned
horizontally; I'd like to rotate these 2D plots by 90 degrees.
I've combed through the docs and the only way I can think to do it would be
to create a fixed resolution buffer and then manipulate it via matplotlib
functions. The camera seems only applicable for 3D (and doesn't paint the
axes, so far as I can tell).
Any ideas or pointers to docs?
Thanks,
Jason
----
Jason Galyardt
jeg(a)uga.edu
Department of Physics and Astronomy
University of Georgia
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