[yt-users] Analyzing SPH data

Alankar Dutta dutta.alankar at gmail.com
Sat Mar 4 12:37:44 PST 2017


Yes I will definitely open up an issue and try to introduce a pull if I can.

Alankar Dutta

On Mar 5, 2017 2:04 AM, "Nathan Goldbaum" <nathan12343 at gmail.com> wrote:

> Not right now, no, although I think it would be straightforward to modify
> yt to be able to do this. We would need to add a way to indicate that you
> don't want to load the full dataset (e.g. as a keyword argument to the
> load() function), and then turn off the machinery that detects if a Gadget
> binary file is part of a multi-file dataset.
>
> Would you mind opening an issue so we don't lose track of this feature
> request?
>
> https://bitbucket.org/yt_analysis/yt/issues/new
>
> I can try to take a stab at this somtime in the next couple weeks. If
> you'd like to try adding the feature yourself we would welcome a pull
> request that implements this.
>
> On Sat, Mar 4, 2017 at 2:27 PM Alankar Dutta <dutta.alankar at gmail.com>
> wrote:
>
>> Is it possible somehow to read only a few of the files from the entire
>> dataset? If so then how?
>>
>> Alankar Dutta
>>
>>
>> Alankar Dutta
>>
>> On Mar 5, 2017 1:51 AM, "Nathan Goldbaum" <nathan12343 at gmail.com> wrote:
>>
>> So unfortunately the current support for SPH data is not able to ingest a
>> dataset as big as yours, at least on server with as much RAM as you have
>> available.
>>
>> In principle we could make it so you could load just one of your files at
>> a time, that would definitely work, but I don't think the current support
>> for particle data will ever be able to scale to load a dataset as big as
>> yours.
>>
>> I'm currently actively working on improving the scaling and peak memory
>> consumption of yt when looking at SPH particle data. Unfortunately this
>> work is not yet ready for anyone besides someone who is ok with some
>> features being broken. I'm actively working on stabilizing this code and it
>> will hopefully be available as part of a stable release of yt in the
>> medium-term future. If you'd like more information about this effort or are
>> interested in helping out, take a look at the yt enhancement proposal
>> describing the work:
>>
>> https://bitbucket.org/yt_analysis/ytep/pull-requests/67
>>
>> I'm sorry that I don't have a nicer answer for you here. Hopefully in the
>> medium-term future yt will be able to easily work with extremely large SPH
>> datasets like yours.
>>
>> -Nathan
>>
>> On Sat, Mar 4, 2017 at 12:51 PM, Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Hello,
>>
>> *I used the following code. This automatically tries to read my entire
>> Gadget Snapshot Dataset (1024 files):*
>>
>> import yt
>>
>> loc = '/media/alankar/Seagate Expansion Drive/mb2/snapshots/snapdir_068/'
>> fname = loc+'snapshot_068.0'
>>
>> ds = yt.load(fname)
>> ds.index
>> ad= ds.all_data()
>>
>> px = yt.ProjectionPlot(ds, 'x', ('gas', 'density'))
>> px.show()
>>
>> *I get the following error message:*
>>
>> Reloaded modules: yt, yt.funcs, yt.extern, yt.extern.six, yt.utilities,
>> yt.utilities.logger, yt.config, yt.utilities.exceptions, yt.extern.tqdm,
>> yt.extern.tqdm._tqdm, yt.extern.tqdm._utils, yt.extern.tqdm._tqdm_gui,
>> yt.extern.tqdm._tqdm_pandas, yt.extern.tqdm._version, yt.units,
>> yt.units.unit_symbols, yt.units.yt_array, yt.units.unit_object,
>> yt.units.dimensions, yt.units.equivalencies, yt.utilities.physical_ratios,
>> yt.units.unit_lookup_table, yt.units.unit_registry, yt.utilities.lru_cache,
>> yt.utilities.on_demand_imports, yt.units.pint_conversions,
>> yt.utilities.physical_constants, yt.fields, yt.fields.api,
>> yt.fields.field_plugin_registry, yt.fields.angular_momentum,
>> yt.fields.derived_field, yt.fields.field_exceptions,
>> yt.fields.field_detector, yt.fields.vector_operations,
>> yt.utilities.math_utils, yt.utilities.lib, yt.utilities.lib.misc_utilities,
>> yt.utilities.lib.geometry_utils, yt.fields.astro_fields,
>> yt.fields.cosmology_fields, yt.fields.fluid_fields,
>> yt.fields.fluid_vector_fields, yt.fields.magnetic_field,
>> yt.fields.geometric_fields, yt.fields.field_functions,
>> yt.fields.particle_fields, yt.fields.local_fields, yt.fields.field_info_container,
>> yt.fields.my_plugin_fields, yt.fields.xray_emission_fields,
>> yt.utilities.linear_interpolators, yt.utilities.lib.interpolators,
>> yt.utilities.cosmology, yt.data_objects, yt.data_objects.api,
>> yt.data_objects.grid_patch, yt.data_objects.data_containers,
>> yt.data_objects.particle_io, yt.data_objects.field_data, yt.frontends,
>> yt.frontends.ytdata, yt.frontends.ytdata.utilities,
>> yt.utilities.lib.marching_cubes, yt.utilities.parallel_tools,
>> yt.utilities.parallel_tools.parallel_analysis_interface,
>> yt.data_objects.image_array, yt.visualization,
>> yt.visualization.image_writer, yt.visualization.color_maps,
>> yt.visualization._colormap_data, yt.utilities.lib.image_utilities,
>> yt.utilities.png_writer, yt.utilities.lib.quad_tree,
>> yt.utilities.parameter_file_storage, yt.utilities.amr_kdtree,
>> yt.utilities.amr_kdtree.api, yt.utilities.amr_kdtree.amr_kdtree,
>> yt.utilities.amr_kdtree.amr_kdtools, yt.utilities.lib.amr_kdtools,
>> yt.utilities.lib.partitioned_grid, yt.geometry,
>> yt.geometry.grid_geometry_handler, yt.arraytypes,
>> yt.geometry.geometry_handler, yt.utilities.io_handler,
>> yt.utilities.definitions, yt.geometry.grid_container,
>> yt.data_objects.derived_quantities, yt.geometry.selection_routines,
>> yt.data_objects.profiles, yt.utilities.lib.particle_mesh_operations,
>> yt.geometry.particle_deposit, yt.data_objects.octree_subset,
>> yt.geometry.particle_smooth, yt.geometry.particle_oct_container,
>> yt.data_objects.static_output, yt.data_objects.particle_filters,
>> yt.data_objects.particle_unions, yt.data_objects.unions,
>> yt.utilities.minimal_representation, yt.units.unit_systems,
>> yt.data_objects.region_expression, yt.geometry.coordinates,
>> yt.geometry.coordinates.api, yt.geometry.coordinates.coordinate_handler,
>> yt.geometry.coordinates.cartesian_coordinates,
>> yt.utilities.lib.pixelization_routines, yt.data_objects.unstructured_mesh,
>> yt.utilities.lib.mesh_utilities, yt.geometry.coordinates.polar_coordinates,
>> yt.geometry.coordinates.cylindrical_coordinates, yt.geometry.coordinates.spherical_coordinates,
>> yt.geometry.coordinates.geographic_coordinates,
>> yt.geometry.coordinates.spec_cube_coordinates,
>> yt.data_objects.time_series, yt.convenience, yt.utilities.hierarchy_inspection,
>> yt.data_objects.analyzer_objects, yt.data_objects.particle_trajectories,
>> yt.data_objects.construction_data_containers,
>> yt.utilities.grid_data_format, yt.utilities.grid_data_format.conversion,
>> yt.utilities.grid_data_format.conversion.conversion_abc,
>> yt.utilities.grid_data_format.conversion.conversion_athena,
>> yt.utilities.grid_data_format.writer, yt.frontends.stream,
>> yt.frontends.stream.api, yt.frontends.stream.data_structures,
>> yt.geometry.oct_geometry_handler, yt.geometry.particle_geometry_handler,
>> yt.geometry.oct_container, yt.geometry.unstructured_mesh_handler,
>> yt.utilities.decompose, yt.utilities.flagging_methods,
>> yt.frontends.stream.fields, yt.frontends.exodus_ii,
>> yt.frontends.exodus_ii.util, yt.frontends.stream.io,
>> yt.frontends.stream.tests, yt.frontends.stream.sample_data,
>> yt.data_objects.selection_data_containers, yt.utilities.orientation,
>> yt.frontends.api, yt.frontends.art, yt.frontends.art.api,
>> yt.frontends.art.data_structures, yt.frontends.art.definitions,
>> yt.frontends.art.fields, yt.utilities.fortran_utils, yt.frontends.art.io,
>> yt.frontends.art.tests, yt.frontends.artio, yt.frontends.artio.api,
>> yt.frontends.artio.data_structures, yt.frontends.artio._artio_caller,
>> yt.frontends.artio.fields, yt.frontends.artio.io,
>> yt.frontends.artio.tests, yt.frontends.athena, yt.frontends.athena.api,
>> yt.frontends.athena.data_structures, yt.frontends.athena.fields,
>> yt.frontends.athena.io, yt.frontends.athena.tests,
>> yt.frontends.athena_pp, yt.frontends.athena_pp.api,
>> yt.frontends.athena_pp.data_structures, yt.utilities.file_handler,
>> yt.frontends.athena_pp.fields, yt.frontends.athena_pp.io,
>> yt.frontends.athena_pp.tests, yt.frontends.boxlib, yt.frontends.boxlib.api,
>> yt.frontends.boxlib.data_structures, yt.frontends.boxlib.fields,
>> yt.frontends.boxlib.io, yt.frontends.chombo, yt.frontends.chombo.io,
>> yt.frontends.boxlib.tests, yt.frontends.chombo.api,
>> yt.frontends.chombo.data_structures, yt.frontends.chombo.fields,
>> yt.frontends.chombo.tests, yt.frontends.eagle, yt.frontends.eagle.api,
>> yt.frontends.eagle.data_structures, yt.frontends.gadget,
>> yt.frontends.gadget.data_structures, yt.frontends.sph,
>> yt.frontends.sph.data_structures, yt.frontends.gadget.definitions,
>> yt.frontends.gadget.fields, yt.frontends.sph.fields,
>> yt.fields.species_fields, yt.utilities.chemical_formulas,
>> yt.utilities.periodic_table, yt.frontends.owls, yt.frontends.owls.fields,
>> yt.frontends.owls.owls_ion_tables, yt.frontends.eagle.fields,
>> yt.frontends.eagle.definitions, yt.frontends.eagle.io,
>> yt.frontends.owls.io, yt.frontends.gadget.io, yt.frontends.eagle.tests,
>> yt.frontends.enzo, yt.frontends.enzo.api, yt.frontends.enzo.data_structures,
>> yt.utilities.pyparselibconfig, yt.utilities.pyparselibconfig.api,
>> yt.utilities.pyparselibconfig.libconfig, yt.frontends.enzo.fields,
>> yt.frontends.enzo.simulation_handling, yt.frontends.enzo.io,
>> yt.frontends.enzo.tests, yt.frontends.exodus_ii.api,
>> yt.frontends.exodus_ii.data_structures, yt.frontends.exodus_ii.io,
>> yt.frontends.exodus_ii.fields, yt.frontends.exodus_ii.simulation_handling,
>> yt.frontends.exodus_ii.tests, yt.frontends.fits, yt.frontends.fits.api,
>> yt.frontends.fits.data_structures, yt.frontends.fits.fields,
>> yt.frontends.fits.io, yt.frontends.fits.misc, yt.frontends.fits.tests,
>> yt.frontends.flash, yt.frontends.flash.api, yt.frontends.flash.data_structures,
>> yt.frontends.flash.fields, yt.frontends.flash.io,
>> yt.frontends.flash.tests, yt.frontends.gadget.api, yt.frontends.gadget.simulation_handling,
>> yt.frontends.gadget.tests, yt.frontends.gadget_fof,
>> yt.frontends.gadget_fof.api, yt.frontends.gadget_fof.data_structures,
>> yt.frontends.gadget_fof.fields, yt.frontends.gadget_fof.io,
>> yt.frontends.gadget_fof.tests, yt.frontends.gamer, yt.frontends.gamer.api,
>> yt.frontends.gamer.data_structures, yt.frontends.gamer.fields,
>> yt.testing, yt.frontends.gamer.io, yt.frontends.gdf,
>> yt.frontends.gdf.api, yt.frontends.gdf.data_structures,
>> yt.frontends.gdf.fields, yt.frontends.gdf.io, yt.frontends.gdf.tests,
>> yt.frontends.gizmo, yt.frontends.gizmo.api, yt.frontends.gizmo.data_structures,
>> yt.frontends.gizmo.fields, yt.frontends.halo_catalog,
>> yt.frontends.halo_catalog.api, yt.frontends.halo_catalog.data_structures,
>> yt.frontends.halo_catalog.fields, yt.frontends.ytdata.data_structures,
>> yt.frontends.ytdata.fields, yt.utilities.tree_container,
>> yt.frontends.halo_catalog.io, yt.frontends.http_stream,
>> yt.frontends.http_stream.api, yt.frontends.http_stream.data_structures,
>> yt.frontends.http_stream.io, yt.frontends.moab, yt.frontends.moab.api,
>> yt.frontends.moab.data_structures, yt.frontends.moab.fields,
>> yt.frontends.moab.io, yt.frontends.moab.tests, yt.frontends.open_pmd,
>> yt.frontends.open_pmd.api, yt.frontends.open_pmd.data_structures,
>> yt.frontends.open_pmd.fields, yt.frontends.open_pmd.misc,
>> yt.frontends.open_pmd.io, yt.frontends.open_pmd.tests,
>> yt.frontends.owls.api, yt.frontends.owls.data_structures,
>> yt.frontends.owls.simulation_handling, yt.frontends.owls.tests,
>> yt.frontends.owls_subfind, yt.frontends.owls_subfind.api,
>> yt.frontends.owls_subfind.data_structures, yt.frontends.owls_subfind.fields,
>> yt.frontends.owls_subfind.io, yt.frontends.owls_subfind.tests,
>> yt.frontends.ramses, yt.frontends.ramses.api, yt.frontends.ramses.data_structures,
>> yt.frontends.ramses.definitions, yt.frontends.ramses.fields,
>> yt.utilities.lib.cosmology_time, yt.frontends.ramses.io,
>> yt.frontends.ramses.tests, yt.frontends.rockstar,
>> yt.frontends.rockstar.api, yt.frontends.rockstar.data_structures,
>> yt.frontends.rockstar.fields, yt.frontends.rockstar.definitions,
>> yt.frontends.rockstar.io, yt.frontends.rockstar.tests, yt.frontends.sdf,
>> yt.frontends.sdf.api, yt.frontends.sdf.data_structures,
>> yt.frontends.sdf.fields, yt.utilities.sdf, yt.frontends.sdf.io,
>> yt.frontends.tipsy, yt.frontends.tipsy.api, yt.frontends.tipsy.data_structures,
>> yt.frontends.tipsy.fields, yt.frontends.tipsy.io,
>> yt.frontends.tipsy.tests, yt.frontends.ytdata.api, yt.frontends.ytdata.io,
>> yt.visualization.api, yt.visualization.particle_plots,
>> yt.visualization.fixed_resolution, yt.visualization.volume_rendering,
>> yt.visualization.volume_rendering.api, yt.visualization.volume_rendering.transfer_functions,
>> yt.visualization.volume_rendering.image_handling,
>> yt.visualization.volume_rendering.camera, yt.visualization.volume_rendering.utils,
>> yt.utilities.lib.bounding_volume_hierarchy, yt.utilities.lib.image_samplers,
>> yt.visualization.volume_rendering.lens, yt.utilities.lib.grid_traversal,
>> yt.visualization.volume_rendering.transfer_function_helper,
>> yt.visualization.volume_rendering.volume_rendering,
>> yt.visualization.volume_rendering.scene, yt.visualization.volume_rendering.render_source,
>> yt.visualization.volume_rendering.zbuffer_array, yt.visualization.volume_rendering.off_axis_projection,
>> yt.visualization.volume_rendering.interactive_vr_helpers,
>> yt.visualization.fixed_resolution_filters, yt.utilities.lib.api,
>> yt.utilities.lib.depth_first_octree, yt.utilities.lib.fortran_reader,
>> yt.utilities.lib.basic_octree, yt.utilities.lib.points_in_volume,
>> yt.utilities.lib.ray_integrators, yt.utilities.lib.write_array,
>> yt.utilities.lib.contour_finding, yt.utilities.lib.line_integral_convolution,
>> yt.visualization.plot_window, yt.visualization.base_plot_types,
>> yt.visualization.plot_modifications, yt.analysis_modules,
>> yt.analysis_modules.cosmological_observation, yt.analysis_modules.
>> cosmological_observation.light_ray, yt.analysis_modules.
>> cosmological_observation.light_ray.light_ray, yt.analysis_modules.
>> cosmological_observation.cosmology_splice, yt.utilities.lib.mesh_triangulation,
>> yt.visualization.plot_container, yt.visualization.tick_locators,
>> yt.visualization.profile_plotter, yt.visualization.streamlines,
>> yt.visualization.fits_image, yt.analysis_modules.list_modules
>> yt : [INFO     ] 2017-03-05 00:12:08,986 Calculating time from 5.000e-01
>> to be 1.881e+17 seconds
>> yt : [INFO     ] 2017-03-05 00:12:08,986 Calculating time from 5.000e-01
>> to be 1.881e+17 seconds
>> yt : [INFO     ] 2017-03-05 00:12:08,986 Calculating time from 5.000e-01
>> to be 1.881e+17 seconds
>> yt : [INFO     ] 2017-03-05 00:12:08,986 Calculating time from 5.000e-01
>> to be 1.881e+17 seconds
>> yt : [INFO     ] 2017-03-05 00:12:08,986 Calculating time from 5.000e-01
>> to be 1.881e+17 seconds
>> yt : [INFO     ] 2017-03-05 00:12:09,002 Assuming length units are in
>> kpc/h (comoving)
>> yt : [INFO     ] 2017-03-05 00:12:09,002 Assuming length units are in
>> kpc/h (comoving)
>> yt : [INFO     ] 2017-03-05 00:12:09,002 Assuming length units are in
>> kpc/h (comoving)
>> yt : [INFO     ] 2017-03-05 00:12:09,002 Assuming length units are in
>> kpc/h (comoving)
>> yt : [INFO     ] 2017-03-05 00:12:09,002 Assuming length units are in
>> kpc/h (comoving)
>> yt : [INFO     ] 2017-03-05 00:12:09,027 Parameters:
>> current_time              = 1.8806506178595517e+17 s
>> yt : [INFO     ] 2017-03-05 00:12:09,027 Parameters:
>> current_time              = 1.8806506178595517e+17 s
>> yt : [INFO     ] 2017-03-05 00:12:09,027 Parameters:
>> current_time              = 1.8806506178595517e+17 s
>> yt : [INFO     ] 2017-03-05 00:12:09,027 Parameters:
>> current_time              = 1.8806506178595517e+17 s
>> yt : [INFO     ] 2017-03-05 00:12:09,027 Parameters:
>> current_time              = 1.8806506178595517e+17 s
>> yt : [INFO     ] 2017-03-05 00:12:09,044 Parameters:
>> domain_dimensions         = [2 2 2]
>> yt : [INFO     ] 2017-03-05 00:12:09,044 Parameters:
>> domain_dimensions         = [2 2 2]
>> yt : [INFO     ] 2017-03-05 00:12:09,044 Parameters:
>> domain_dimensions         = [2 2 2]
>> yt : [INFO     ] 2017-03-05 00:12:09,044 Parameters:
>> domain_dimensions         = [2 2 2]
>> yt : [INFO     ] 2017-03-05 00:12:09,044 Parameters:
>> domain_dimensions         = [2 2 2]
>> yt : [INFO     ] 2017-03-05 00:12:09,064 Parameters:
>> domain_left_edge          = [ 0.  0.  0.]
>> yt : [INFO     ] 2017-03-05 00:12:09,064 Parameters:
>> domain_left_edge          = [ 0.  0.  0.]
>> yt : [INFO     ] 2017-03-05 00:12:09,064 Parameters:
>> domain_left_edge          = [ 0.  0.  0.]
>> yt : [INFO     ] 2017-03-05 00:12:09,064 Parameters:
>> domain_left_edge          = [ 0.  0.  0.]
>> yt : [INFO     ] 2017-03-05 00:12:09,064 Parameters:
>> domain_left_edge          = [ 0.  0.  0.]
>> yt : [INFO     ] 2017-03-05 00:12:09,081 Parameters:
>> domain_right_edge         = [ 100000.  100000.  100000.]
>> yt : [INFO     ] 2017-03-05 00:12:09,081 Parameters:
>> domain_right_edge         = [ 100000.  100000.  100000.]
>> yt : [INFO     ] 2017-03-05 00:12:09,081 Parameters:
>> domain_right_edge         = [ 100000.  100000.  100000.]
>> yt : [INFO     ] 2017-03-05 00:12:09,081 Parameters:
>> domain_right_edge         = [ 100000.  100000.  100000.]
>> yt : [INFO     ] 2017-03-05 00:12:09,081 Parameters:
>> domain_right_edge         = [ 100000.  100000.  100000.]
>> yt : [INFO     ] 2017-03-05 00:12:09,098 Parameters:
>> cosmological_simulation   = 1
>> yt : [INFO     ] 2017-03-05 00:12:09,098 Parameters:
>> cosmological_simulation   = 1
>> yt : [INFO     ] 2017-03-05 00:12:09,098 Parameters:
>> cosmological_simulation   = 1
>> yt : [INFO     ] 2017-03-05 00:12:09,098 Parameters:
>> cosmological_simulation   = 1
>> yt : [INFO     ] 2017-03-05 00:12:09,098 Parameters:
>> cosmological_simulation   = 1
>> yt : [INFO     ] 2017-03-05 00:12:09,114 Parameters:
>> current_redshift          = 1.0000000010567627
>> yt : [INFO     ] 2017-03-05 00:12:09,114 Parameters:
>> current_redshift          = 1.0000000010567627
>> yt : [INFO     ] 2017-03-05 00:12:09,114 Parameters:
>> current_redshift          = 1.0000000010567627
>> yt : [INFO     ] 2017-03-05 00:12:09,114 Parameters:
>> current_redshift          = 1.0000000010567627
>> yt : [INFO     ] 2017-03-05 00:12:09,114 Parameters:
>> current_redshift          = 1.0000000010567627
>> yt : [INFO     ] 2017-03-05 00:12:09,131 Parameters:
>> omega_lambda              = 0.725
>> yt : [INFO     ] 2017-03-05 00:12:09,131 Parameters:
>> omega_lambda              = 0.725
>> yt : [INFO     ] 2017-03-05 00:12:09,131 Parameters:
>> omega_lambda              = 0.725
>> yt : [INFO     ] 2017-03-05 00:12:09,131 Parameters:
>> omega_lambda              = 0.725
>> yt : [INFO     ] 2017-03-05 00:12:09,131 Parameters:
>> omega_lambda              = 0.725
>> yt : [INFO     ] 2017-03-05 00:12:09,145 Parameters:
>> omega_matter              = 0.275
>> yt : [INFO     ] 2017-03-05 00:12:09,145 Parameters:
>> omega_matter              = 0.275
>> yt : [INFO     ] 2017-03-05 00:12:09,145 Parameters:
>> omega_matter              = 0.275
>> yt : [INFO     ] 2017-03-05 00:12:09,145 Parameters:
>> omega_matter              = 0.275
>> yt : [INFO     ] 2017-03-05 00:12:09,145 Parameters:
>> omega_matter              = 0.275
>> yt : [INFO     ] 2017-03-05 00:12:09,160 Parameters:
>> hubble_constant           = 0.702
>> yt : [INFO     ] 2017-03-05 00:12:09,160 Parameters:
>> hubble_constant           = 0.702
>> yt : [INFO     ] 2017-03-05 00:12:09,160 Parameters:
>> hubble_constant           = 0.702
>> yt : [INFO     ] 2017-03-05 00:12:09,160 Parameters:
>> hubble_constant           = 0.702
>> yt : [INFO     ] 2017-03-05 00:12:09,160 Parameters:
>> hubble_constant           = 0.702
>> yt : [INFO     ] 2017-03-05 00:12:25,556 Allocating for 1.190e+10
>> particles (index particle type 'all')
>> yt : [INFO     ] 2017-03-05 00:12:25,556 Allocating for 1.190e+10
>> particles (index particle type 'all')
>> yt : [INFO     ] 2017-03-05 00:12:25,556 Allocating for 1.190e+10
>> particles (index particle type 'all')
>> yt : [INFO     ] 2017-03-05 00:12:25,556 Allocating for 1.190e+10
>> particles (index particle type 'all')
>> yt : [INFO     ] 2017-03-05 00:12:25,556 Allocating for 1.190e+10
>> particles (index particle type 'all')
>> Traceback (most recent call last):
>>
>>   File "<ipython-input-5-0d0fb587bd5e>", line 1, in <module>
>>     runfile('/home/alankar/Documents/X ray map/dev.py',
>> wdir='/home/alankar/Documents/X ray map')
>>
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/
>> spyder/utils/site/sitecustomize.py", line 866, in runfile
>>     execfile(filename, namespace)
>>
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/
>> spyder/utils/site/sitecustomize.py", line 102, in execfile
>>     exec(compile(f.read(), filename, 'exec'), namespace)
>>
>>   File "/home/alankar/Documents/X ray map/dev.py", line 23, in <module>
>>     ds.index
>>
>>   File "/home/alankar/Documents/yt/yt/data_objects/static_output.py",
>> line 501, in index
>>     self, dataset_type=self.dataset_type)
>>
>>   File "/home/alankar/Documents/yt/yt/geometry/particle_geometry_handler.py",
>> line 39, in __init__
>>     super(ParticleIndex, self).__init__(ds, dataset_type)
>>
>>   File "/home/alankar/Documents/yt/yt/geometry/geometry_handler.py",
>> line 50, in __init__
>>     self._setup_geometry()
>>
>>   File "/home/alankar/Documents/yt/yt/geometry/particle_geometry_handler.py",
>> line 50, in _setup_geometry
>>     self._initialize_particle_handler()
>>
>>   File "/home/alankar/Documents/yt/yt/geometry/particle_geometry_handler.py",
>> line 99, in _initialize_particle_handler
>>     self._initialize_indices()
>>
>>   File "/home/alankar/Documents/yt/yt/geometry/particle_geometry_handler.py",
>> line 121, in _initialize_indices
>>     morton = np.empty(self.total_particles, dtype="uint64")
>>
>> MemoryError
>>
>>
>> Alankar Dutta
>>
>>
>>
>> On Sat, Mar 4, 2017 at 11:56 PM, Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Thanks Nathan that works. Can you please suggest me a way to share with
>> you my entire 960 GB snapshot containing 1024 files? Then you can have a
>> look at them if you are interested in adding further support.
>>
>> Alankar Dutta
>>
>> On Sat, Mar 4, 2017 at 11:11 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>> wrote:
>>
>> Oops, typo, should be https://bitbucket.org/ngoldbaum/yt
>>
>>
>> On Sat, Mar 4, 2017 at 11:40 AM Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Hello,
>>
>>
>> $ hg pull -r f4c5c13 https://bitbucket.org/yt_analysis/yt
>> This is giving the following error:
>> pulling from https://bitbucket.org/yt_analysis/yt
>> abort: unknown revision 'f4c5c13'!
>>
>> Alankar Dutta
>>
>>
>> On Sat, Mar 4, 2017 at 10:46 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>> wrote:
>>
>> To test my pull request you're going to want to build yt from a clone of
>> the mercurial repository after pulling in my changes.
>>
>> $ conda uninstall yt
>> $ hg clone https://bitbucket.org/yt_analysis/yt
>> $ cd yt
>> $ hg pull -r f4c5c13 https://bitbucket.org/yt_analysis/yt
>> $ hg update f4c5c13
>> $ python setup.py develop
>>
>> You'll need a compilation environment set up for that to succeed. If you
>> don't have compilers installed it will be less straightforward to test
>> this. I'd urge you *not* to hand-edit your installed version of yt from
>> conda, as that will create more headaches for you if you make a mistake and
>> forget to correct it.
>>
>>
>> On Sat, Mar 4, 2017 at 10:34 AM Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Hello,
>>
>> I have modified the yt files as given in the pull request. I get the
>> following error code:
>>
>> Traceback (most recent call last):
>>   File "dev.py", line 9, in <module>
>>     import yt
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/yt/__init__.py",
>> line 133, in <module>
>>     frontends = _frontend_container()
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/yt/frontends/api.py",
>> line 52, in __init__
>>     setattr(self, frontend, importlib.import_module(_mod))
>>   File "/home/alankar/anaconda3/lib/python3.6/importlib/__init__.py",
>> line 126, in import_module
>>     return _bootstrap._gcd_import(name[level:], package, level)
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/yt/frontends/eagle/api.py",
>> line 17, in <module>
>>     from .data_structures import \
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/yt/
>> frontends/eagle/data_structures.py", line 21, in <module>
>>     from yt.frontends.gadget.data_structures import \
>>   File "/home/alankar/anaconda3/lib/python3.6/site-packages/yt/
>> frontends/gadget/data_structures.py", line 28, in <module>
>>     from yt.frontends.sph.data_structures import \
>> ImportError: cannot import name 'SPHDataset'
>>
>> The following is my code:
>> import yt
>> ds = yt.load("snapshot_068.0")
>>
>> Alankar Dutta
>>
>> On Sat, Mar 4, 2017 at 3:13 PM, Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Oh I missed telling that the full dataset is around 950 GB
>>
>> On Sat, Mar 4, 2017 at 1:02 PM, Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Hello,
>>
>> This is only one part of the multipart snapshot of the simulation. I am
>> sending you the header information from the snapshot file:
>>
>> {'O0': 0.27500000000000002,
>>  'Ol': 0.72499999999999998,
>>  'boxsize': 100000.0,
>>  'flag_age': 1,
>>  'flag_cooling': 1,
>>  'flag_delaytime': 0,
>>  'flag_fb': 1,
>>  'flag_fh2': 0,
>>  'flag_metals': 1,
>>  'flag_potential': 3,
>>  'flag_sfr': 1,
>>  'flag_tmax': 0,
>>  'h': 0.70199999999999996,
>>  'massTable': array([ 0.        ,  0.00110449,  0.        ,  0.        ,  0.        ,  0.        ]),
>>  'nbndry': 76247,
>>  'nbulge': 0,
>>  'ndisk': 0,
>>  'ndm': 1459617792,
>>  'nfiles': 1024,
>>  'ngas': 1343721867,
>>  'npartThisFile': array([10045237, 10239661,        0,        0,   451148,       67], dtype=uint32),
>>  'npartTotal': array([1343721867, 1459617792,          0,          0,  503500456,
>>              76247], dtype=uint32),
>>  'npartTotalHW': array([1, 1, 0, 0, 0, 0], dtype=uint32),
>>  'nstar': 503500456,
>>  'redshift': 1.0000000010567627,
>>  'rhocrit': 2.707660428120944e-29,
>>  'time': 0.49999999973580939}
>>
>>
>>
>> I extracted this information using a different python program.
>>
>> Alankar Dutta
>>
>> On Sat, Mar 4, 2017 at 12:45 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>> wrote:
>>
>>
>>
>> On Sat, Mar 4, 2017 at 12:25 AM, Nathan Goldbaum <nathan12343 at gmail.com>
>> wrote:
>>
>>
>>
>> On Sat, Mar 4, 2017 at 12:13 AM, Alankar Dutta <dutta.alankar at gmail.com>
>> wrote:
>>
>> Hello,
>>
>> Modifying the GADGET simulation isn't possible the moment because it has
>> already been developed by someone else who has a paper  published  on this
>> simulation and I want to use that simulation  snapshots to make mock xray
>> map from it.
>>
>>
>> I'm talking about modifying yt, not Gadget.
>>
>> Is the file you attached to your other e-mail just a single file in a
>> multi-file dataset? How large is the full dataset? Do you not have a way to
>> produce a full dataset in this output format that's not prohibitively large?
>>
>>
>> I've opened a pull request that allows me to do IO on the data you
>> attached: https://bitbucket.org/yt_analysis/yt/pull-requests/2537
>>
>> This allows me to read your data in, getting sensible values for e.g.
>> position. I suspect we're not using the correct field specification because
>> I see this warning:
>>
>> yt : [WARNING  ] 2017-03-04 01:06:09,109 Your Gadget-2 file may have
>> extra columns or different precision! (1814947576 file vs 1486279952
>> computed)
>>
>> yt supports a number of field specifications out of the box, see:
>>
>> https://bitbucket.org/yt_analysis/yt/src/3eca2ae80ab14a48b643d3055d7d3c
>> 0933fa77ae/yt/frontends/gadget/definitions.py?at=yt&
>> fileviewer=file-view-default#definitions.py-50
>>
>> Do you happen to know which fields are in your output file?
>>
>>
>>
>>
>>
>>
>> Alankar Dutta
>>
>> On Mar 4, 2017 11:38 AM, "Nathan Goldbaum" <nathan12343 at gmail.com> wrote:
>>
>> I think the most straightforward thing to do here is to fix the Gadget
>> frontend so it properly reads in gadget binary data with positions written
>> in double precision.
>>
>> Is there any chance you can generate a smallish test dataset in your
>> Gadget output format that we can use for debugging purposes? With that
>> available it should be straightforward to add support. You can share the
>> dataset using the yt curldrop (https://docs.hub.yt/services.html#curldrop)
>> or a cloud filesharing service like dropbox or google drive.
>>
>> Unfortunately there isn't a way to load SPH data without a full-fledged
>> frontend right now.
>>
>> We do have a load_particles function which allows creating a dataset from
>> particle data loaded as numpy arrays, but it's currently not possible to
>> use it to load SPH data.
>>
>> I'm currently actively working on improving support for SPH data in yt
>> and adding the ability to load SPH data with load_particles is one of the
>> things I've added in that branch of the code. Hopefully this work will be
>> stabilized sometime in the next few months.
>>
>>
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