[yt-svn] commit/yt: ngoldbaum: Merged in jzuhone/yt/yt-3.0 (pull request #1009)
commits-noreply at bitbucket.org
commits-noreply at bitbucket.org
Tue Jul 15 09:13:02 PDT 2014
1 new commit in yt:
https://bitbucket.org/yt_analysis/yt/commits/7e7ef2aaa715/
Changeset: 7e7ef2aaa715
Branch: yt-3.0
User: ngoldbaum
Date: 2014-07-15 18:12:52
Summary: Merged in jzuhone/yt/yt-3.0 (pull request #1009)
Removing analysis modules as per Trello card
Affected #: 22 files
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/PPVCube.ipynb
--- a/doc/source/analyzing/analysis_modules/PPVCube.ipynb
+++ b/doc/source/analyzing/analysis_modules/PPVCube.ipynb
@@ -1,7 +1,7 @@
{
"metadata": {
"name": "",
- "signature": "sha256:3f810954006851303837edb8fd85ee6583a883122b0f4867903562546c4f19d2"
+ "signature": "sha256:ba8b6a53571695ae1d0c236ad43875823746e979a329a9d35ab0a8b899cebbba"
},
"nbformat": 3,
"nbformat_minor": 0,
@@ -21,7 +21,7 @@
"input": [
"%matplotlib inline\n",
"from yt.mods import *\n",
- "from yt.analysis_modules.api import PPVCube"
+ "from yt.analysis_modules.ppv_cube.api import PPVCube"
],
"language": "python",
"metadata": {},
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/SZ_projections.ipynb
--- a/doc/source/analyzing/analysis_modules/SZ_projections.ipynb
+++ b/doc/source/analyzing/analysis_modules/SZ_projections.ipynb
@@ -1,7 +1,7 @@
{
"metadata": {
"name": "",
- "signature": "sha256:7fc053480ba7896bfa5905bd69f7b3dd326364fbab324975b76f79640f2e0adf"
+ "signature": "sha256:4745a15abb6512547b50280b92c22567f89255189fd968ca706ef7c39d48024f"
},
"nbformat": 3,
"nbformat_minor": 0,
@@ -91,7 +91,7 @@
"input": [
"%matplotlib inline\n",
"from yt.mods import *\n",
- "from yt.analysis_modules.api import SZProjection\n",
+ "from yt.analysis_modules.sunyaev_zeldovich.api import SZProjection\n",
"\n",
"ds = load(\"enzo_tiny_cosmology/DD0046/DD0046\")\n",
"\n",
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/absorption_spectrum.rst
--- a/doc/source/analyzing/analysis_modules/absorption_spectrum.rst
+++ b/doc/source/analyzing/analysis_modules/absorption_spectrum.rst
@@ -35,7 +35,7 @@
.. code-block:: python
- from yt.analysis_modules.api import AbsorptionSpectrum
+ from yt.analysis_modules.absorption_spectrum.api import AbsorptionSpectrum
sp = AbsorptionSpectrum(900.0, 1800.0, 10000)
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/light_ray_generator.rst
--- a/doc/source/analyzing/analysis_modules/light_ray_generator.rst
+++ b/doc/source/analyzing/analysis_modules/light_ray_generator.rst
@@ -26,7 +26,7 @@
.. code-block:: python
- from yt.analysis_modules.api import LightRay
+ from yt.analysis_modules.cosmological_observation.api import LightRay
lr = LightRay("enzo_tiny_cosmology/32Mpc_32.enzo",
'Enzo', 0.0, 0.1)
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/photon_simulator.rst
--- a/doc/source/analyzing/analysis_modules/photon_simulator.rst
+++ b/doc/source/analyzing/analysis_modules/photon_simulator.rst
@@ -386,7 +386,7 @@
from yt.mods import *
from yt.utilities.physical_constants import cm_per_kpc, K_per_keV, mp
from yt.utilities.cosmology import Cosmology
- from yt.analysis_modules.api import *
+ from yt.analysis_modules.photon_simulator.api import *
import aplpy
R = 1000. # in kpc
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 doc/source/analyzing/analysis_modules/planning_cosmology_simulations.rst
--- a/doc/source/analyzing/analysis_modules/planning_cosmology_simulations.rst
+++ b/doc/source/analyzing/analysis_modules/planning_cosmology_simulations.rst
@@ -10,7 +10,7 @@
.. code-block:: python
- from yt.analysis_modules.api import CosmologySplice
+ from yt.analysis_modules.cosmological_observation.api import CosmologySplice
my_splice = CosmologySplice('enzo_tiny_cosmology/32Mpc_32.enzo', 'Enzo')
my_splice.plan_cosmology_splice(0.0, 0.1, filename='redshifts.out')
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/api.py
--- a/yt/analysis_modules/api.py
+++ /dev/null
@@ -1,117 +0,0 @@
-"""
-API for yt.analysis_modules
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-from .absorption_spectrum.api import \
- AbsorptionSpectrum
-
-from .coordinate_transformation.api import \
- spherical_regrid
-
-from .cosmological_observation.api import \
- CosmologySplice, \
- LightCone, \
- find_unique_solutions, \
- project_unique_light_cones, \
- LightRay
-
-from .halo_finding.api import \
- Halo, \
- HOPHalo, \
- parallelHOPHalo, \
- LoadedHalo, \
- FOFHalo, \
- HaloList, \
- HOPHaloList, \
- FOFHaloList, \
- parallelHOPHaloList, \
- LoadedHaloList, \
- GenericHaloFinder, \
- parallelHF, \
- HOPHaloFinder, \
- FOFHaloFinder, \
- HaloFinder, \
- LoadHaloes
-
-from .halo_mass_function.api import \
- HaloMassFcn, \
- TransferFunction, \
- integrate_inf
-
-from .halo_merger_tree.api import \
- DatabaseFunctions, \
- MergerTree, \
- MergerTreeConnect, \
- Node, \
- Link, \
- MergerTreeDotOutput, \
- MergerTreeTextOutput
-
-from .halo_profiler.api import \
- VirialFilter, \
- HaloProfiler, \
- FakeProfile
-
-from .level_sets.api import \
- identify_contours, \
- Clump, \
- find_clumps, \
- get_lowest_clumps, \
- write_clump_index, \
- write_clumps, \
- write_old_clump_index, \
- write_old_clumps, \
- write_old_clump_info, \
- _DistanceToMainClump, \
- recursive_all_clumps, \
- return_all_clumps, \
- return_bottom_clumps, \
- recursive_bottom_clumps, \
- clump_list_sort
-
-from .radial_column_density.api import \
- RadialColumnDensity
-
-from .spectral_integrator.api import \
- add_xray_emissivity_field
-
-from .star_analysis.api import \
- StarFormationRate, \
- SpectrumBuilder
-
-from .two_point_functions.api import \
- TwoPointFunctions, \
- FcnSet
-
-from .sunyaev_zeldovich.api import SZProjection
-
-from .radmc3d_export.api import \
- RadMC3DWriter
-
-from .particle_trajectories.api import \
- ParticleTrajectories
-
-from .photon_simulator.api import \
- PhotonList, \
- EventList, \
- SpectralModel, \
- XSpecThermalModel, \
- XSpecAbsorbModel, \
- TableApecModel, \
- TableAbsorbModel, \
- PhotonModel, \
- ThermalPhotonModel
-
-from .ppv_cube.api import \
- PPVCube
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/coordinate_transformation/api.py
--- a/yt/analysis_modules/coordinate_transformation/api.py
+++ /dev/null
@@ -1,17 +0,0 @@
-"""
-API for coordinate_transformation
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-from .transforms import \
- spherical_regrid
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/coordinate_transformation/setup.py
--- a/yt/analysis_modules/coordinate_transformation/setup.py
+++ /dev/null
@@ -1,16 +0,0 @@
-#!/usr/bin/env python
-import setuptools
-import os
-import sys
-import os.path
-
-import os.path
-
-
-def configuration(parent_package='', top_path=None):
- from numpy.distutils.misc_util import Configuration
- config = Configuration('coordinate_transformation',
- parent_package, top_path)
- config.make_config_py() # installs __config__.py
- #config.make_svn_version_py()
- return config
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/coordinate_transformation/transforms.py
--- a/yt/analysis_modules/coordinate_transformation/transforms.py
+++ /dev/null
@@ -1,117 +0,0 @@
-"""
-Transformations between coordinate systems
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-import numpy as np
-from yt.funcs import *
-
-from yt.utilities.linear_interpolators import \
- TrilinearFieldInterpolator
-
-def spherical_regrid(pf, nr, ntheta, nphi, rmax, fields,
- center=None, smoothed=True):
- """
- This function takes a parameter file (*pf*) along with the *nr*, *ntheta*
- and *nphi* points to generate out to *rmax*, and it grids *fields* onto
- those points and returns a dict. *center* if supplied will be the center,
- otherwise the most dense point will be chosen. *smoothed* governs whether
- regular covering grids or smoothed covering grids will be used.
- """
- mylog.warning("This code may produce some artifacts of interpolation")
- mylog.warning("See yt/extensions/coordinate_transforms.py for plotting information")
- if center is None: center = pf.h.find_max("Density")[1]
- fields = ensure_list(fields)
- r,theta,phi = np.mgrid[0:rmax:nr*1j,
- 0:np.pi:ntheta*1j,
- 0:2*np.pi:nphi*1j]
- new_grid = dict(r=r, theta=theta, phi=phi)
- new_grid['x'] = r*np.sin(theta)*np.cos(phi) + center[0]
- new_grid['y'] = r*np.sin(theta)*np.sin(phi) + center[1]
- new_grid['z'] = r*np.cos(theta) + center[2]
- sphere = pf.sphere(center, rmax)
- return arbitrary_regrid(new_grid, sphere, fields, smoothed)
-
-def arbitrary_regrid(new_grid, data_source, fields, smoothed=True):
- """
- This function accepts a dict of points 'x', 'y' and 'z' and a data source
- from which to interpolate new points, along with a list of fields it needs
- to regrid onto those xyz points. It then returns interpolated points.
- This has not been well-tested other than for regular spherical regridding.
- """
- fields = ensure_list(fields)
- new_grid['handled'] = np.zeros(new_grid['x'].shape, dtype='bool')
- for field in fields:
- new_grid[field] = np.zeros(new_grid['x'].shape, dtype='float64')
- grid_order = np.argsort(data_source.grid_levels[:,0])
- ng = len(data_source._grids)
-
- for i,grid in enumerate(data_source._grids[grid_order][::-1]):
- mylog.info("Regridding grid % 4i / % 4i (%s - %s)", i, ng, grid.id, grid.Level)
- cg = grid.retrieve_ghost_zones(1, fields, smoothed=smoothed)
-
- # makes x0,x1,y0,y1,z0,z1
- bounds = np.concatenate(zip(cg.left_edge, cg.right_edge))
-
-
- # Now we figure out which of our points are inside this grid
- # Note that we're only looking at the grid, not the grid-with-ghost-zones
- point_ind = np.ones(new_grid['handled'].shape, dtype='bool') # everything at first
- for i,ax in enumerate('xyz'): # i = 0,1,2 ; ax = x, y, z
- # &= does a logical_and on the array
- point_ind &= ( ( grid.LeftEdge[i] <= new_grid[ax] )
- & ( new_grid[ax] <= grid.RightEdge[i] ) )
- point_ind &= (new_grid['handled'] == False) # only want unhandled points
-
- # If we don't have any, we can just leave
- if point_ind.sum() == 0: continue
-
- # because of the funky way the interpolator takes points, we have to make a
- # new dict of just the points inside this grid
- point_grid = {'x' : new_grid['x'][point_ind],
- 'y' : new_grid['y'][point_ind],
- 'z' : new_grid['z'][point_ind]}
-
- # Now we know which of the points in new_grid are inside this grid
- for field in fields:
- interpolator = TrilinearFieldInterpolator(
- cg[field],bounds,['x','y','z'])
- new_grid[field][point_ind] = interpolator(point_grid)
-
- new_grid['handled'][point_ind] = True
-
- mylog.info("Finished with %s dangling points",
- new_grid['handled'].size - new_grid['handled'].sum())
-
- return new_grid
-
-"""
-# The following will work to plot through different slices:
-
-import pylab
-for i in range(n_theta):
- print "Doing % 3i / % 3i" % (i, n_theta)
- pylab.clf()
- ax=pylab.subplot(1,1,1, projection="polar", aspect=1.)
- ax.pcolormesh(phi[:,i,:], r[:,i,:],
- np.log10(sph_grid[field][:,i,:]))
- pylab.savefig("polar/latitude_%03i.png" % i)
-
-for i in range(n_phi):
- print "Doing % 3i / % 3i" % (i, n_phi)
- pylab.clf()
- ax=pylab.subplot(1,1,1, projection="polar", aspect=1.)
- ax.pcolormesh(theta[:,:,i], r[:,:,i],
- np.log10(sph_grid[field][:,:,i]))
- pylab.savefig("polar/longitude_%03i.png" % i)
-"""
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/halo_profiler/api.py
--- a/yt/analysis_modules/halo_profiler/api.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""
-API for halo_profiler
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-from .halo_filters import \
- VirialFilter
-
-from .multi_halo_profiler import \
- HaloProfiler, \
- FakeProfile, \
- standard_fields
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/halo_profiler/centering_methods.py
--- a/yt/analysis_modules/halo_profiler/centering_methods.py
+++ /dev/null
@@ -1,107 +0,0 @@
-"""
-HaloProfiler re-centering functions.
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-import numpy as np
-
-from yt.funcs import *
-
-from yt.fields.local_fields import \
- add_field
-
-centering_registry = {}
-
-def add_function(name):
- def wrapper(func):
- centering_registry[name] = func
- return func
- return wrapper
-
-#### Dark Matter Density ####
-
- at add_function("Min_Dark_Matter_Density")
-def find_minimum_dm_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MinLocation']('Dark_Matter_Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("Max_Dark_Matter_Density")
-def find_maximum_dm_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MaxLocation']('Dark_Matter_Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("CoM_Dark_Matter_Density")
-def find_CoM_dm_density(data):
- dc_x, dc_y, dc_z = data.quantities['CenterOfMass'](use_cells=False,
- use_particles=True,
- preload=False)
- return (dc_x, dc_y, dc_z)
-
-#### Gas Density ####
-
- at add_function("Min_Gas_Density")
-def find_minimum_gas_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MinLocation']('Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("Max_Gas_Density")
-def find_maximum_gas_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MaxLocation']('Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("CoM_Gas_Density")
-def find_CoM_gas_density(data):
- dc_x, dc_y, dc_z = data.quantities['CenterOfMass'](use_cells=True,
- use_particles=False,
- preload=False)
- return (dc_x, dc_y, dc_z)
-
-#### Total Density ####
-
- at add_function("Min_Total_Density")
-def find_minimum_total_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MinLocation']('Matter_Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("Max_Total_Density")
-def find_maximum_total_density(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MaxLocation']('Matter_Density',
- preload=False)
- return (mx, my, mz)
-
- at add_function("CoM_Total_Density")
-def find_CoM_total_density(data):
- dc_x, dc_y, dc_z = data.quantities['CenterOfMass'](use_cells=True,
- use_particles=True,
- preload=False)
- return (dc_x, dc_y, dc_z)
-
-#### Temperature ####
-
- at add_function("Min_Temperature")
-def find_minimum_temperature(data):
- ma, mini, mx, my, mz, mg = data.quantities['MinLocation']('Temperature',
- preload=False)
- return (mx, my, mz)
-
- at add_function("Max_Temperature")
-def find_maximum_temperature(data):
- ma, maxi, mx, my, mz, mg = data.quantities['MaxLocation']('Temperature',
- preload=False)
- return (mx, my, mz)
-
diff -r 2e2d9a9bc75add24c98e8fc13217e3033985e1f3 -r 7e7ef2aaa7159717cda503f44cdcf379f8060aa2 yt/analysis_modules/halo_profiler/halo_filters.py
--- a/yt/analysis_modules/halo_profiler/halo_filters.py
+++ /dev/null
@@ -1,153 +0,0 @@
-"""
-Halo filters to be used with the HaloProfiler.
-
-
-
-"""
-
-#-----------------------------------------------------------------------------
-# Copyright (c) 2013, yt Development Team.
-#
-# Distributed under the terms of the Modified BSD License.
-#
-# The full license is in the file COPYING.txt, distributed with this software.
-#-----------------------------------------------------------------------------
-
-from copy import deepcopy
-import numpy as np
-
-from yt.funcs import *
-from yt.utilities.physical_constants import TINY
-
-def VirialFilter(profile, overdensity_field='ActualOverdensity',
- virial_overdensity=200., must_be_virialized=True,
- virial_filters=[['TotalMassMsun', '>=','1e14']],
- virial_quantities=['TotalMassMsun', 'RadiusMpc'],
- virial_index=None, use_log=False):
- r"""Filter halos by virial quantities.
-
- Return values are a True or False whether the halo passed the filter,
- along with a dictionary of virial quantities for the fields specified in
- the virial_quantities keyword. Thresholds for virial quantities are
- given with the virial_filters keyword in the following way:
- [field, condition, value].
-
- This is typically used as part of a call to `add_halo_filter`.
-
- Parameters
- ----------
- overdensity_field : string
- The field used for interpolation with the
- specified critical value given with 'virial_overdensity'.
- Default='ActualOverdensity'.
- virial_overdensity : float
- The value used to determine the outer radius of the virialized halo.
- Default: 200.
- must_be_virialized : bool
- If no values in the profile are above the
- value of virial_overdensity, the halo does not pass the filter.
- Default: True.
- virial_filters : array_like
- Conditional filters based on virial quantities
- given in the following way: [field, condition, value].
- Default: [['TotalMassMsun', '>=','1e14']].
- virial_quantities : array_like
- Fields for which interpolated values should
- be calculated and returned. Default: ['TotalMassMsun', 'RadiusMpc'].
- virial_index : array_like
- If given as a list, the index of the radial profile
- which is used for interpolation is placed here. Default: None.
- use_log : bool
- If True, interpolation is done in log space.
- Default: False.
-
- Examples
- --------
- >>> hp.add_halo_filter(HP.VirialFilter, must_be_virialized=True,
- overdensity_field='ActualOverdensity',
- virial_overdensity=200,
- virial_filters=[['TotalMassMsun','>=','1e14']],
- virial_quantities=['TotalMassMsun','RadiusMpc'])
-
- """
-
- fields = deepcopy(virial_quantities)
- if virial_filters is None: virial_filters = []
- for vfilter in virial_filters:
- if not vfilter[0] in fields:
- fields.append(vfilter[0])
-
- overDensity = []
- temp_profile = dict((field, []) for field in fields)
-
- for q in range(len(profile[overdensity_field])):
- good = True
- if (profile[overdensity_field][q] != profile[overdensity_field][q]):
- good = False
- continue
- for field in fields:
- if (profile[field][q] != profile[field][q]):
- good = False
- break
- if good:
- overDensity.append(profile[overdensity_field][q])
- for field in fields:
- temp_profile[field].append(profile[field][q])
-
- if use_log:
- for field in temp_profile.keys():
- temp_profile[field] = np.log10(np.clip(temp_profile[field], TINY,
- max(temp_profile[field])))
-
- virial = dict((field, 0.0) for field in fields)
-
- if (not (np.array(overDensity) >= virial_overdensity).any()) and \
- must_be_virialized:
- mylog.debug("This halo is not virialized!")
- return [False, {}]
-
- if (len(overDensity) < 2):
- mylog.debug("Skipping halo with no valid points in profile.")
- return [False, {}]
-
- if (overDensity[1] <= virial_overdensity):
- index = 0
- elif (overDensity[-1] >= virial_overdensity):
- index = -2
- else:
- for q in (np.arange(len(overDensity),0,-1)-1):
- if (overDensity[q] < virial_overdensity) and (overDensity[q-1] >= virial_overdensity):
- index = q - 1
- break
-
- if type(virial_index) is list:
- virial_index.append(index)
-
- for field in fields:
- if (overDensity[index+1] - overDensity[index]) == 0:
- mylog.debug("Overdensity profile has slope of zero.")
- return [False, {}]
- else:
- slope = (temp_profile[field][index+1] - temp_profile[field][index]) / \
- (overDensity[index+1] - overDensity[index])
- value = slope * (virial_overdensity - overDensity[index]) + \
- temp_profile[field][index]
- virial[field] = value
-
- if use_log:
- for field in virial.keys():
- virial[field] = np.power(10, virial[field])
-
- for vfilter in virial_filters:
- if eval("%s %s %s" % (virial[vfilter[0]],vfilter[1],vfilter[2])):
- mylog.debug("(%s %s %s) returned True for %s." % \
- (vfilter[0],vfilter[1],vfilter[2],virial[vfilter[0]]))
- continue
- else:
- mylog.debug("(%s %s %s) returned False for %s." % \
- (vfilter[0],vfilter[1],vfilter[2],virial[vfilter[0]]))
- return [False, {}]
-
- return [True, dict((("%s_%s" % (q, virial_overdensity)), virial[q])
- for q in virial_quantities)]
-
This diff is so big that we needed to truncate the remainder.
Repository URL: https://bitbucket.org/yt_analysis/yt/
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