Mailman 3 May 2013 - yt-users

Porting .ply files to Blender with colors?
by Jill P. Naiman 15 Aug '22

15 Aug '22

Hi All, I was curious if anyone has had any luck porting .ply files generated with yt into Blender with colors? It seems to port in the surfaces just fine, but they are a uniform color. From what I can gather, Blender imports .ply files with face color instead of vertex so I tried the surf.export_ply routine with "face" instead of "vertex" for sample_type, but no luck ("vertex" doesn't work either). Let me know if I can provide any more useful info. Thanks for any help, -J

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Stars on volume rendering
by Elizabeth Harper-Clark 11 Dec '21

11 Dec '21

Hi all, Thanks for all your help over the last couple of days. One more question: - Can I plot particles on a volume rendered image? I have stars and I want to show where they are! Thanks, Libby -- Elizabeth Harper-Clark MA MSci PhD Candidate, Canadian Institute for Theoretical Astrophysics, UofT Sciences and Engineering Coordinator, Teaching Assistants' Training Program, UofT www.astro.utoronto.ca/~h-clark <http://www.astro.utoronto.ca/%7Eh-clark> h-clark(a)cita.utoronto.ca Astronomy office phone: +1-416-978-5759

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Variance in phase/profiles
by david collins 11 Apr '20

11 Apr '20

Hi, Everybody! Does anyone out there have a technique for getting the variance out of a profile object? A profile object is good at getting <X> vs. B, I'd then like to get < (X - <X>)^2 > vs B. Matt and I had spittballed the possibility some time ago, but I was wondering if anyone out there had successfully done it. Thanks, d. -- Sent from my computer.

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yt volume render/AMRKDtree help
by Renyue Cen 25 Aug '13

25 Aug '13

Hi, I did some simple volume rendering with the following script: volume2 = AMRKDTree(pf, fields=["Dark_Matter_Density"], no_ghost=False, tree_type="domain", le=c-0.5*WW, re=c+0.5*WW) cam = pf.h.camera(c, L, W, N, tf, volume=volume2, no_ghost=False, north_vector=L, steady_north=True) cam.snapshot(fn="%s_iso-DMdensity-%3.3d.png" % (filenameTHIS, j)) I got rather strange results in that the pictures look symmetric, which I am pretty sure can not be true. I attach the obtained plot. Note that I am using KD tree and using 32 cores. Your help at your earliest convenience is appreciated. Best, Renyue

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Finding the max density from a checkpoint dump?
by Joseph Smidt 29 May '13

29 May '13

Hey everyone, My Enzo simulation has refined to enough levels that I need to make checkpoint dumps mid-timestep and do YT analysis from there. I can read in the checkpoint dump but when I go to find the max density I get this error: http://pastebin.com/2mNVxNyW Anybody have any idea what is going on and how to fix this? Also, since this dump is in the middle of the W-cycle, I believe the time on the finest grid is different then the root grid. How do I find the time on the finest grid for this checkpoint dump? Thanks. -- ------------------------------------------------------------------------ Joseph Smidt <josephsmidt(a)gmail.com> Theoretical Division P.O. Box 1663, Mail Stop B283 Los Alamos, NM 87545 Office: 505-665-9752 Fax: 505-667-1931

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Chombo data format - Example load?
by Haig, Christina 28 May '13

28 May '13

Can anyone give me an example script to load an hdf file that is written in the Chombo data format? I've been searching the site, but I can't find any comprehensible documentation about the relatively 'new' feature of being able to read Chombo HDF5. Many Thanks, Christina

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plotting just contours in a slice
by Chris Malone 25 May '13

25 May '13

Hi all, I would like to be able to take a slice through a 3D dataset and then plot just the contours of a single variable within that slice. I do not want to overlay the contours with an annotate_countours method. I know one way about this would be to use the FixedResolutionBuffer of some slice plot to reconstruct a mesh-grid and the data, which can then be used within matplotlib directly to create a contour plot. I was curious if there was a more clever method using yt plot objects? Chris

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PlotCollection questions
by Francia Riesco 22 May '13

22 May '13

Hello Everybody, first I want to thank for every time I got an answer when I write here, I really appreciate it. Now I am writing because I am using PlotCollection (As you can see my code) and I have some questions 1) the plot is coming in cm^3 and I want to change it to kpc^3 is there a way to change it? 2) I am attaching the plot can I change to dot or any different symbol and color? 3) why some plot come "empty"? and also I get this error message /Data has no positive values, and therefore can not be log-scaled./ ----- sphere = pf.h.sphere(c, (250., 'kpc')) # 250. levels = 8 #8 mi, ma = sphere.quantities["Extrema"]("Density")[0] contour_values, connected_sets = sphere.extract_connected_sets("Density", levels, mi, ma) for i in connected_sets: eb = connected_sets[i] print "level " + str(i) + " clmsp# " + str(len(eb)) for j in eb: obj = eb[j] com = obj.quantities["CenterOfMass"]() print com pc = PlotCollection(pf, com) pc.add_profile_object(obj, ["Density", "Temperature"],weight="CellMassMsun") # average T(rho) pc.add_profile_object(obj, ["Density", "CellVolume"], weight=None) # pc.add_profile_object(obj, ["Density", "CellMassMsun"], weight=None) # try: pc.save("sliceplot_300_"+str(i)+"_" +str(j)) except Exception, e: print e continue ----- Thank you in advance!!

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Matplotlib installation failure on OS X
by Paul La Plante 21 May '13

21 May '13

Hi, I am having trouble installing yt on my personal machine using the install script. I downloaded the script from the suggested website (http://hg.yt-project.org/yt/raw/stable/doc/install_script.sh) and attempted to execute it with `bash install_script.sh.' I have tried a few different combinations of install options, but it always seems to fail while building matplotlib. My system is OS X 10.8.3, and gcc version 4.8.0 (installed from MacPorts). I have attached my yt_install.log. Thanks in advance for any help! Best regards, Paul

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Clumps, contours, n_contours
by david collins 21 May '13

21 May '13

Hi, all-- I'm seeing a glitch in the matplotlib countor function, as employed by annotate_clumps. As is, I'm seeing some clumps that are not plotted by the countour plotter unless I bump the number of contours-- I get all the plots if I change the contour line to: self.rv = plot._axes.contour(buff, len(self.clumps)+5, extent=extent,**self.plot_args) instead of self.rv = plot._axes.contour(buff, len(self.clumps)+1, extent=extent,**self.plot_args) Is this a glitch that anyone is aware of? Is there a more general fix? The clump contour is not the only time I've run into this glitch. It seems to happen on large contours, for what that's worth. Thanks! d.

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Re: [yt-users] yt-users Digest, Vol 63, Issue 10
by Wolfram Schmidt 20 May '13

20 May '13

Hi Sam, thanks for your response. The most recent code version I used is e6227ef4338b (stable) Would you suggest to alterntively use the simple volume rendering script? Cheers, Wolfram On Fri, 17 May 2013, yt-users-request(a)lists.spacepope.org wrote: > Send yt-users mailing list submissions to > yt-users(a)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(a)lists.spacepope.org > > You can reach the person managing the list at > yt-users-owner(a)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: volume rendering of other fields than the density > (Sam Skillman) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 16 May 2013 14:08:53 -0600 > From: Sam Skillman <samskillman(a)gmail.com> > To: Discussion of the yt analysis package > <yt-users(a)lists.spacepope.org> > Subject: Re: [yt-users] volume rendering of other fields than the > density > Message-ID: > <CAB4=1s3vHjqFtEjH8EwGGBR71rw5LhQo=-Zp6F1ugRd9dwAy5A(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > Hi Wolfram, > > Sorry for the trouble -- the adaptive healpix rendering is fairly beta, as > noted in that example, and I fear it may have gotten left behind in some of > the recent developments. Could you let me know what version of yt you are > using? You can check this with: > > yt instinfo > > It should spit out something like (in addition to other things): > The current version of the code is: > > --- > 1158e48daef2 > --- > > Thanks, > Sam > >

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clump to field?
by david collins 17 May '13

17 May '13

Hi, all-- I have a clump that I've gotten with the clump finder. I'd like to paint those zones of that clump with a flag, so I can exclude that region from other analysis. I'm a little stuck on how to get this done-- I feel like it needs to involve clump.data._flush_data_to_grids and a cut_mask, but I'm a little stuck on how to define the field that I flush_to_grids. Specifically, how to get the cut_mask information to the field, and how to avoid clobbering the paint from one clump with another (or, from one grid with another) I'm trying to do something like: <code> for grid in clump.data._grids: cut_mask = clump.data._get_cut_mask(grid) def masked_region(field,data): cut_mask = data.get_field_parameter('cut_mask', None) try: base = data['masked_region'] except: base = na.zeros(data['Density'].shape) if cut_mask is not None: base = na.maximum(base,cut_mask) return base add_field('masked_region',function=masked_region,validators=[ValidateGridType()], not_in_all=True) grid.set_field_parameter('cut_mask',cut_mask) print grid, cut_mask.sum(), grid['masked_region'].sum() clump.data._flush_to_grids('masked_region',0) </code> but clump['masked_region'].sum() only returns the flagged zones in the first of the grids. I feel like this is something I've done before, but can't find any reference to it in my email or old scripts. Apologies if this has been answered elsewhere, or it's obvious and I'm being thick. Thanks! d.

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volume rendering of other fields than the density
by Wolfram Schmidt 17 May '13

17 May '13

Hi all, I used the example script from the Tutorial section of the Volume Rendering page: http://yt-project.org/doc/visualizing/volume_rendering.html#adaptive-healpi… It works fine for the density, but for any other field (e.g. temperature) the output is just blank. I don't see why I wouldn't work for other fields, as the script appears to be written for arbitrary fields. Changing level bounds, use_log, etc. doesn't help. Does anyone how to fix this? Cheers, Wolfram

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Arbitrary Angle Projections
by Haig, Christina 16 May '13

16 May '13

This is a question of capability / feature suggestion if it doesn't exist. I see that yt can make projection plots along the cartesian axes, and can also do a light-ray through a particular line of sight. My question is: Can yt make a projection plot along an arbitrary axis, specified by some rotation angle? Many Thanks, Christina Haig

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star particles count
by Latif 14 May '13

14 May '13

Hi all, I have star particles in enzo simulations. Counting the particles by creation time and type gave different results. Is it a problem with Yt or comes from simulation? Any ideas? star_particles = dd["creation_time"] > 0.0 print "Number of star particles by creation time", star_particles.sum() star_particles = dd["particle_type"] == 2 print "Number of star particles by type", star_particles.sum() Number of star particles by creation time 3818 Number of star particles by type 0 thanks in advance, Cheers Latif

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strange particle field behavior
by Britton Smith 10 May '13

10 May '13

Hi all, I am seeing something odd with a field called "IsStarParticle". This is an Enzo field defined in the following way: def _IsStarParticle(field, data): is_star = (data['creation_time'] > 0).astype('float64') return is_star When I do the following: print pf.h.grids[0]['IsStarParticle'] I get the expected field of 1s and 0s. When I do this: all_data = pf.h.all_data() print all_data['IsStarParticle'] I get the values that correspond to the creation_time field. It does not matter in what order I do this. Whenever I try to access the field from a geometric object, I get the actual creation time and not the field I expect. Whenever I access it from a grid object, I get the right thing. Does anyone know what's going on here? Britton

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plot with source region and field parameters
by david collins 09 May '13

09 May '13

Hi, Everybody-- I have a field that I have defined that uses a field_parameter, but I don't seem to be able to get it to work with a projection. >>> region AMRRegion (time0050): center=[ 0.5 0.03369141 0.68457031], left_edge=[ 0. 0.00195312 0.63378906], right_edge=[ 1. 0.06542969 0.73535156] def linewidth(field,data): avg_vx = data.get_field_parameter('avg_vx') return (data['x-velocity']-avg_vx)**2 add_field('linewidth',function=linewidth, validators=[ValidateParameter('avg_vx')]) avg_vx = 7 region.set_field_parameter('avg_vx',avg_vx) print region['linewidth'].min() print region.get_field_parameter('avg_vx') which yields expected output, 1.15751883639e-07 7 But trying to make a projection of that source gives the error below. Is it obvious what I'm doing wrong? I can plot 'Density' just fine. Thanks! >>> proj = oober.pf.h.proj(2,'linewidth',source=region) Initializing tree 0 / 4100% |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Time: 00:00:00 Traceback (most recent call last): | ETA: --:--:-- File "<stdin>", line 1, in <module> File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 1758, in __init__ self._refresh_data() File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 318, in _refresh_data self.get_data() File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 1859, in get_data self._add_level_to_tree(tree, level, fields) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 1981, in _add_level_to_tree self._add_grid_to_tree(tree, grid, fields, zero_out, dls) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 1925, in _add_grid_to_tree for fd in self._get_data_from_grid(grid, fields)] File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 93, in save_state tr = func(self, grid, field, *args, **kwargs) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/data_containers.py", line 2003, in _get_data_from_grid return [grid[field] * bad_points for field in fields] File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/grid_patch.py", line 157, in __getitem__ self.get_data(key) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/grid_patch.py", line 200, in get_data self._generate_field(field) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/grid_patch.py", line 132, in _generate_field self.pf.field_info[field].check_available(self) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/field_info_container.py", line 364, in check_available validator(data) File "/nics/b/home/collins/local_2013_03_12/src/yt-hg/yt/data_objects/field_info_container.py", line 440, in __call__ raise NeedsParameter(doesnt_have) yt.data_objects.field_info_container.NeedsParameter: (['avg_vx'])

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TotalMass for ORION data
by Mark Krumholz 07 May '13

07 May '13

Hi All, I just updated to the latest version of yt, hoping that this would be fixed, but it seems not to be: the "TotalMass" function is broken for Orion data, and, from what I can tell, for any data set that doesn't contain dark matter particles. Here's what I get when I try to use it: In [1]: pf=load('data.0030.3d.hdf5') yt : [WARNING ] 2013-05-06 16:43:36,339 Setting 1.0 in code units to be 1.0 cm yt : [WARNING ] 2013-05-06 16:43:36,339 No time units. Setting 1.0 = 1 second. yt : [INFO ] 2013-05-06 16:43:36,340 Parameters: current_time = 6.78585436617e+13 yt : [INFO ] 2013-05-06 16:43:36,340 Parameters: domain_dimensions = [256 256 256] yt : [INFO ] 2013-05-06 16:43:36,341 Parameters: domain_left_edge = [ -1.68000000e+18 -1.68000000e+18 -1.68000000e+18] yt : [INFO ] 2013-05-06 16:43:36,341 Parameters: domain_right_edge = [ 1.68000000e+18 1.68000000e+18 1.68000000e+18] In [2]: dd=pf.h.all_data() ^[[Ayt : [INFO ] 2013-05-06 16:43:53,804 Adding unknown field gravitational-potential to list of fields In [3]: dd.quantities["TotalMass"]() --------------------------------------------------------------------------- KeyError Traceback (most recent call last) /home3/mkrumhol/yt-x86_64/src/yt-hg/scripts/iyt in <module>() ----> 1 dd.quantities["TotalMass"]() /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/derived_quantities.pyc in __call__(self, *args, **kwargs) 90 self._data_source.pf.h.io) 91 if lazy_reader and not self.force_unlazy: ---> 92 return self._call_func_lazy(args, kwargs) 93 else: 94 return self._call_func_unlazy(args, kwargs) /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/derived_quantities.pyc in _call_func_lazy(self, args, kwargs) 97 self.retvals = [ [] for i in range(self.n_ret)] 98 for gi,g in enumerate(self._get_grids()): ---> 99 rv = self.func(GridChildMaskWrapper(g, self._data_source), *args, **kwargs) 100 if not iterable(rv): rv = (rv,) 101 for i in range(self.n_ret): self.retvals[i].append(rv[i]) /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/derived_quantities.pyc in _TotalMass(data) 152 """ 153 baryon_mass = data["CellMassMsun"].sum() --> 154 particle_mass = data["ParticleMassMsun"].sum() 155 return [baryon_mass + particle_mass] 156 def _combTotalMass(data, total_mass): /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/derived_quantities.pyc in __getitem__(self, item) 58 def __getitem__(self, item): 59 if item not in self.local_cache: ---> 60 data = self.data_source._get_data_from_grid(self.grid, item) 61 self.local_cache[item] = data 62 return self.local_cache[item] /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/data_containers.pyc in save_state(self, grid, field, *args, **kwargs) 93 old_keys = grid.field_data.keys() 94 grid.field_parameters = self.field_parameters ---> 95 tr = func(self, grid, field, *args, **kwargs) 96 grid.field_parameters = old_params 97 grid.field_data = YTFieldData( [(k, grid.field_data[k]) for k in old_keys] ) /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/data_containers.pyc in _get_data_from_grid(self, grid, field) 2643 return np.array([f[i,:][pointI] for i in range(3)]) 2644 else: -> 2645 tr = grid[field] 2646 if tr.size == 1: # dx, dy, dz, cellvolume 2647 tr = tr * np.ones(grid.ActiveDimensions, dtype='float64') /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/grid_patch.pyc in __getitem__(self, key) 155 """ 156 if key not in self.field_data: --> 157 self.get_data(key) 158 return self.field_data[key] 159 /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/grid_patch.pyc in get_data(self, field, convert) 198 else: raise 199 else: --> 200 self._generate_field(field) 201 return self.field_data[field] 202 /home3/mkrumhol/yt-x86_64/src/yt-hg/yt/data_objects/grid_patch.pyc in _generate_field(self, field) 145 self[field] = self.pf.field_info[field](self) 146 else: # Can't find the field, try as it might --> 147 raise exceptions.KeyError(field) 148 149 def has_key(self, key): KeyError: 'ParticleMassMsun' This isn't a huge deal, because I can use "TotalQuantity" on "Density" as a workaround, but I thought I would report it. -- Mark Krumholz krumholz(a)ucolick.org

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question about interpolation to a point
by Brian O'Shea 04 May '13

04 May '13

Hi folks, I have been looking around the yt docs in hopes of finding a routine that does a trilinear interpolation of a grid quantity to an arbitrary point in space. Does such a thing exist, and I simply can't come up with the right search string? Thanks! --Brian

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Release of yt-2.5.2
by Matthew Turk 01 May '13

01 May '13

Hi all, We're proud to release yt version 2.5.2. This is a scheduled point release that includes all bug fixes identified and fixed since the release of 2.5.1 on April 1. Changes and bug fixes include: * Upgrades to most of the dependencies in the install script * Speed improvements to ellipsoidal particle detection * Updates to FLASH fields * CASTRO frontend bug fixes * Fisheye camera bug fixes * ProjectionPlot now accepts a data_source keyword argument * Answer testing now includes plot window answer testing * Athena data serialization If you are using the stable branch of yt from an installation script, you can upgrade using "yt update" or "yt update --all" to upgrade your full dependency stack. If you are using the development branch, you may already have these fixes. A tarball of this release has been uploaded to the Python Package Index (PyPI), although due to user error (me) it includes the Cython sources instead of the C sources for the generated code. Oops. Thanks very much, Matt, on behalf of the yt development team

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