yt-users June 2019

yt-users@python.org

13 participants
10 discussions

Ytini installation for Houdini on Windows

by uran san

Hi guys, I am very new to Ytini's mailing list, mailing lists as well as Houdini. So please bear with me while I pick up the etiquette around this medium. With that out of the way here's my first question: After having succeeded installing Ytini for Houdini on a Mac OS X 10.14 I would now like to achieve the same with my Houdini install on a Windows 10 OS. I have tried to somewhat reproduce all steps described here http://www.ytini.com/getstarted.html#collapseTwoOut (Houdini 17.5 Tested on Mac OS X) on my Windows machine but wasn't surprised to learn that of course Houdini could not find the ytini module when I tried to import it in the python shell. Is there somebody, that could point me . in the right direction of how to install Ytini for Houdini on a Windows 10 OS environment? Not afraid of reading so even hints a re more than welcome. Many Thanks in advance Ur4n

3 months, 2 weeks

Covering grid dimensions

by andrea.husseiniova＠gmail.com

I'm working with a dataset from a particle-based simulation with 64^3 particles and am trying to create a covering grid so that I can create a 3D visualization (using volume rendering). I have a problem with the dimensions of that covering grid. A ProjectionPlot from the covering grid dataset only produces a 2x2x2 pixel plot even though the original dataset ProjectionPlot is a 64x64x64 plot. I tried defining the dimensions of the covering grid to be [64,64,64], which results in a 64 pixel wide plot however data is only present in the first 2x2x2 pixels and the rest of the plot is blank. The way I define my covering grid is shown below. Could someone please suggest a solution to this problem? cov_grid = ds.covering_grid(level=0, left_edge=[-1,-1,-1], dims=ds.domain_dimensions, fields=('deposit','PartType1_density')) #alternate version cov_grid = ds.covering_grid(level=32, left_edge=[-1,-1,-1], dims=[64,64,64], fields=('deposit','PartType1_density')) ds_new = cov_grid.save_as_dataset() grid_ds = yt.load(ds_new)

9 months, 1 week

mass flux of gas in different temperature bins

by Stephanie Tonnesen

Hi all, I am having some trouble figuring out how to calculate the mass flux as a function of z-position in a wind-tunnel simulation. I am running Enzo with 5 AMR levels. If I trying and make a 1d-profile with create_profile, I would have to make my bin sizes as small as the highest level of refinement, which means I have plenty of z values with zeros. I tried to make a covering_grid, thinking I could just deal with everything as arrays, but as I expected I run out of memory if I make a covering grid of the whole domain at max resolution. When I create a YTdisk region, I get an error when trying to make a covering_grid: AttributeError: 'YTDisk' object has no attribute 'covering_grid' I then tried to use the surface and calculate_flux commands: surf3 = ds.disk([0.5,0.5,0.5],[0., 0., 1.],(30,'kpc'),(100,'kpc')) surfu = ds.surface(surf3,"z",(54,"kpc")) fluxu = surfu.calculate_flux("x-velocity","y-velocity","z-velocity","density") at which point I get this error: ____________________________________________________ Traceback (most recent call last): File "yt_surface_flux.py", line 85, in <module> fluxu = surfu.calculate_flux("x-velocity","y-velocity","z-velocity","density") File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 1269, in calculate_flux field_x, field_y, field_z, fluxing_field) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 1280, in _calculate_flux_in_grid vc_data = grid.get_vertex_centered_data(vc_fields) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/grid_patch.py", line 310, in get_vertex_centered_data cg = self.retrieve_ghost_zones(1, fields, smoothed=smoothed) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/grid_patch.py", line 272, in retrieve_ghost_zones **kwargs) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 927, in __init__ YTCoveringGrid.__init__(self, *args, **kwargs) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 555, in __init__ self.get_data(fields) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 642, in get_data if len(fill) > 0: self._fill_fields(fill) File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/construction_data_containers.py", line 1003, in _fill_fields for chunk in ls.data_source.chunks(fields, "io"): File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/data_containers.py", line 1263, in chunks self.get_data() # Ensure we have built ourselves File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/data_containers.py", line 1306, in get_data self.index._identify_base_chunk(self) File "/mnt/home/stonnesen/yt-conda/yt/yt/geometry/grid_geometry_handler.py", line 289, in _identify_base_chunk gi = dobj.selector.select_grids(self.grid_left_edge, File "/mnt/home/stonnesen/yt-conda/yt/yt/data_objects/data_containers.py", line 1258, in selector self._selector = sclass(self) File "yt/geometry/selection_routines.pyx", line 860, in yt.geometry.selection_routines.RegionSelector.__init__ RuntimeError: Error: yt attempted to read outside the boundaries of a non-periodic domain along dimension 0. Region left edge = -0.0078125 code_length, Region right edge = 1.0078125 code_length Dataset left edge = 0.0 code_length, Dataset right edge = 1.0 code_length This commonly happens when trying to compute ghost cells up to the domain boundary. Two possible solutions are to load a smaller regi on that does not border the edge or override the periodicity for this dataset. ___________________________________________ However, my simulated region is 300 kpc across, so I am not at the edge in any axis. I suppose I have 2 questions: can I make a covering_grid of a region of a simulation, or can I have some guidance on making the calculate_flux command work? Thanks in advance!! Best, Stephanie -- Dr. Stephanie Tonnesen Associate Research Scientist CCA, Flatiron Institute New York, NY stonnes(a)gmail.com

9 months, 2 weeks

Binning with create_profile

by Sam Patrick

Hello, I'm trying to create a radial profile of the gas density using the create_profile function. Even with the extrema explicitly specified the binning does not take these values. I was wondering whether there was a simple way to work around this? My script and output are bellow: ds = yt.load("DD0077/output_0077") val, loc = ds.find_max('density') sp = ds.sphere(loc, (10.0, 'pc')) rp = yt.create_profile(sp, 'radius', ('gas', 'density'), n_bins= 10, extrema= {'radius':((1e-2, 'pc'), (10.0, 'pc'))}, logs= {'radius':True}) rp.x.in_units('pc') >>>YTArray([0.01497631, 0.02988167, 0.05962177, 0.11896107, 0.23735854, 0.47359256, 0.94494138, 1.88540592, 3.76187938, 7.50593617]) pc (where 0.01 and 10 are expected to be the first and last values) Many thanks, Sam Patrick

9 months, 2 weeks

Problem with projection / YTQuantity values must be numeric

by José Mauricio Utreras

Hi all, Recently I have seen this error more often: >> raise RuntimeError("YTQuantity values must be numeric”) I have been able to solve most of the problems which were related with units (some packages behave differently if I do units*array or array*unit). However, I’m getting an error when I’m trying to project a field, and I don’t know how to solve that Code: . . def _Disk_H(field, data): center = data.get_field_parameter('center') z = data["z"] - center[2] return np.abs(z) yt.add_field("Disk_H", function=_Disk_H, units="pc", take_log=False, validators=[ValidateParameter('center')]) . . . disk_dd = dd.cut_region(["obj['Disk_H'].in_units('pc') < 1.0e3"]) proj = ds.proj('density', 2,data_source=disk_dd,weight_field='density’) Saludos! José Utreras Error: proj = ds.proj('density', 2,data_source=disk_dd,weight_field='density') File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/construction_data_containers.py", line 262, in __init__ self.get_data(field) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/construction_data_containers.py", line 336, in get_data self._handle_chunk(chunk, fields, tree) File "/home/jutreras/miniconda3/lib/python3.5/contextlib.py", line 77, in __exit__ self.gen.throw(type, value, traceback) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/data_containers.py", line 960, in _field_parameter_state yield File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/construction_data_containers.py", line 330, in get_data [], "io", local_only = True)): File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/utilities/parallel_tools/parallel_analysis_interface.py", line 508, in parallel_objects for result_id, obj in oiter: File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 800, in chunks yield self File "/home/jutreras/miniconda3/lib/python3.5/contextlib.py", line 77, in __exit__ self.gen.throw(type, value, traceback) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/data_containers.py", line 1265, in _chunked_read yield File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 800, in chunks yield self File "/home/jutreras/miniconda3/lib/python3.5/contextlib.py", line 77, in __exit__ self.gen.throw(type, value, traceback) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/data_containers.py", line 1265, in _chunked_read yield File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 799, in chunks self.get_data(fields) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 805, in get_data ind = self._cond_ind File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 837, in _cond_ind np.logical_and(res, ind, ind) File "/home/jutreras/miniconda3/lib/python3.5/contextlib.py", line 77, in __exit__ self.gen.throw(type, value, traceback) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/data_containers.py", line 960, in _field_parameter_state yield File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/data_objects/selection_data_containers.py", line 833, in _cond_ind res = eval(cond) File "<string>", line 1, in <module> File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/units/yt_array.py", line 1094, in __lt__ return super(YTArray, self).__lt__(oth) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/units/yt_array.py", line 1215, in __array_wrap__ any_nonzero = [np.any(oper1), np.any(oper2)] File "/home/jutreras/miniconda3/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 2164, in any return _wrapreduction(a, np.logical_or, 'any', axis, None, out, keepdims=keepdims) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/numpy/core/fromnumeric.py", line 84, in _wrapreduction return reduction(axis=axis, out=out, **passkwargs) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/numpy/core/_methods.py", line 43, in _any return umr_any(a, axis, dtype, out, keepdims) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/units/yt_array.py", line 1175, in __array_wrap__ return ret[()] File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/units/yt_array.py", line 1165, in __getitem__ return YTQuantity(ret, self.units, bypass_validation=True) File "/home/jutreras/miniconda3/lib/python3.5/site-packages/yt/units/yt_array.py", line 1353, in __new__ raise RuntimeError("YTQuantity values must be numeric") RuntimeError: YTQuantity values must be numeric

9 months, 2 weeks

Bin error in phase plot

by Sam Patrick

Hi all, I'm trying to write a simple piece of code which produces a phase plot of the entire dataset. I'm currently using yt version 3.5.0 and Python version 3.7.1. Essentially what I have is: val, loc = ds.find_max('density') ad = ds.all_data() plot = yt.PhasePlot(ad, "density", "temperature", "cell_mass", weight_field=None) plot.set_unit('cell_mass', 'Msun') filename = "phase_plot_z={:.2f}.png".format(ds.current_redshift) plot.save(filename) However when I try running the code I get the following error: Traceback (most recent call last): File "phase_plot.py", line 14, in <module> plot = yt.PhasePlot(ad, "density", "temperature", "cell_mass", weight_field=None) File "/opt/apps/yt/jan19/lib/python3.7/site-packages/yt/visualization/profile_plotter.py", line 931, in __init__ fractional=fractional) File "/opt/apps/yt/jan19/lib/python3.7/site-packages/yt/data_objects/profiles.py", line 1207, in create_profile obj.add_fields([field for field in fields]) File "/opt/apps/yt/jan19/lib/python3.7/site-packages/yt/data_objects/profiles.py", line 129, in add_fields self._bin_chunk(chunk, fields, temp_storage) File "/opt/apps/yt/jan19/lib/python3.7/site-packages/yt/data_objects/profiles.py", line 627, in _bin_chunk bin_ind_y = np.digitize(bf_y, self.y_bins) - 1 ValueError: bins must be monotonically increasing or decreasing I'm not entirely sure what's happening since there's no part of the code which is interfacing with binning directly. Any light shed on this issue would be much appreciated. Many thanks, Sam Patrick

9 months, 3 weeks

Help

by Mitali Mitali Damle Damle

Hello, I have recently subscribed to the yt mailing list. However, I am having problems signing into my account. Below are my account details: E-mail address: damle(a)uni-potsdam.de Username: Mitali I would be very helpful if you could kindly look into this matter. Regards, Mitali Damle, MSc Astrophysics, University of Potsdam

9 months, 3 weeks

Halo finder on baryon field

by Sina Hooshangi

Hello, I have an enzo cosmology simulation which consists only baryonic matter and no dark matter and I'm trying to find halos on this baryonic field. but the HaloCatalog requests particle_mass and probably all other particle fields. is there any way to run HaloCatalog on baryonic fields without defining particle fields? if not, is there any well-defined way to turn gas fields in particle fields in yt? Thanks.

9 months, 4 weeks

3-D Mass power spectra

by 梁家豪

Dear yt Can current yt calculate 3-D Mass power spectra? I checked the website but I didn't find any information. I think calculating 3-D Mass power spectra is a very useful for cosmological simulations. So I guess maybe yt supports this function now....? Thanks in advance

10 months

Only a few days left to submit! -- 2019 John Hunter Excellence in Plotting Contest

by Madicken Munk

Hi everybody, There are only a few days left to submit to the 2019 John Hunter Excellence in Plotting Contest! If you're interested in participating, note that you have until June 8th to prepare your submission. In memory of John Hunter, we are pleased to be reviving the SciPy John Hunter Excellence in Plotting Competition for 2019. This open competition aims to highlight the importance of data visualization to scientific progress and showcase the capabilities of open source software. Participants are invited to submit scientific plots to be judged by a panel. The winning entries will be announced and displayed at the conference. John Hunter’s family and NumFocus are graciously sponsoring cash prizes for the winners in the following amounts: - 1st prize: $1000 - 2nd prize: $750 - 3rd prize: $500 - Entries must be submitted by June, 8th to the form at https://goo.gl/forms/cFTB3FUBrMPfQ7Vz1 - Winners will be announced at Scipy 2019 in Austin, TX. - Participants do not need to attend the Scipy conference. - Entries may take the definition of “visualization” rather broadly. Entries may be, for example, a traditional printed plot, an interactive visualization for the web, or an animation. - Source code for the plot must be provided, in the form of Python code and/or a Jupyter notebook, along with a rendering of the plot in a widely used format. This may be, for example, PDF for print, standalone HTML and Javascript for an interactive plot, or MPEG-4 for a video. If the original data can not be shared for reasons of size or licensing, "fake" data may be substituted, along with an image of the plot using real data. - Each entry must include a 300-500 word abstract describing the plot and its importance for a general scientific audience. - Entries will be judged on their clarity, innovation and aesthetics, but most importantly for their effectiveness in communicating a real-world problem. Entrants are encouraged to submit plots that were used during the course of research or work, rather than merely being hypothetical. - SciPy reserves the right to display any and all entries, whether prize-winning or not, at the conference, use in any materials or on its website, with attribution to the original author(s). SciPy John Hunter Excellence in Plotting Competition Co-Chairs Hannah Aizenman Thomas Caswell Madicken Munk Nelle Varoquaux

10 months

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yt-users June 2019