[yt-svn] commit/yt: 8 new changesets
Bitbucket
commits-noreply at bitbucket.org
Sat Sep 8 10:19:41 PDT 2012
8 new commits in yt:
https://bitbucket.org/yt_analysis/yt/changeset/45f9ac33caf2/
changeset: 45f9ac33caf2
branch: yt
user: bcrosby
date: 2012-09-05 22:44:10
summary: Changes to the sorting of halos in mergertree.py to improve performance.
affected #: 1 file
diff -r 2825fd89deeba490c2d5dfc1c0200ed5493f0a1f -r 45f9ac33caf22fe5caca8cd255fdeaa7a67469b9 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -450,9 +450,9 @@
# the parent dataset.
parent_names = list(self.names[parent_currt])
parent_names.sort()
- parent_IDs = na.array([], dtype='int64')
- parent_masses = na.array([], dtype='float64')
- parent_halos = na.array([], dtype='int32')
+ parent_IDs = []
+ parent_masses = []
+ parent_halos = []
for i,pname in enumerate(parent_names):
if i>=self.comm.rank and i%self.comm.size==self.comm.rank:
h5fp = h5py.File(pname)
@@ -460,19 +460,22 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- parent_IDs = na.concatenate((parent_IDs, thisIDs))
- parent_masses = na.concatenate((parent_masses, thisMasses))
- parent_halos = na.concatenate((parent_halos,
- na.ones(thisIDs.size, dtype='int32') * gID))
+ parent_IDs.append(thisIDs)
+ parent_masses.append(thisMasses)
+ parent_halos.append(na.ones(thisIDs.size,
+ dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
-
+
# Sort the arrays by particle index in ascending order.
- sort = parent_IDs.argsort()
- parent_IDs = parent_IDs[sort]
- parent_masses = parent_masses[sort]
- parent_halos = parent_halos[sort]
- del sort
+ if len(parent_IDs)==0:
+ parent_IDs = na.array([], dtype='int32')
+ parent_masses = na.array([], dtype='int32')
+ parent_halos = na.array([], dtype='int32')
+ else:
+ parent_IDs = na.concatenate(parent_IDs)
+ parent_masses = na.concatenate(parent_masses)
+ parent_halos = na.concatenate(parent_halos)
else:
# We can use old data and save disk reading.
(parent_IDs, parent_masses, parent_halos) = last
@@ -482,30 +485,33 @@
# Now get the child halo data.
child_names = list(self.names[child_currt])
child_names.sort()
- child_IDs = na.array([], dtype='int64')
- child_masses = na.array([], dtype='float64')
- child_halos = na.array([], dtype='int32')
- for i,cname in enumerate(child_names):
+ child_IDs = []
+ child_masses = []
+ child_halos = []
+ for i,pname in enumerate(child_names):
if i>=self.comm.rank and i%self.comm.size==self.comm.rank:
- h5fp = h5py.File(cname)
+ h5fp = h5py.File(pname)
for group in h5fp:
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- child_IDs = na.concatenate((child_IDs, thisIDs))
- child_masses = na.concatenate((child_masses, thisMasses))
- child_halos = na.concatenate((child_halos,
- na.ones(thisIDs.size, dtype='int32') * gID))
+ child_IDs.append(thisIDs)
+ child_masses.append(thisMasses)
+ child_halos.append(na.ones(thisIDs.size,
+ dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
-
- # Sort the arrays by particle index.
- sort = child_IDs.argsort()
- child_IDs = child_IDs[sort]
- child_masses = child_masses[sort]
- child_halos = child_halos[sort]
+
+ # Sort the arrays by particle index in ascending order.
+ if len(child_IDs)==0:
+ child_IDs = na.array([], dtype='int32')
+ child_masses = na.array([], dtype='int32')
+ child_halos = na.array([], dtype='int32')
+ else:
+ child_IDs = na.concatenate(child_IDs)
+ child_masses = na.concatenate(child_masses)
+ child_halos = na.concatenate(child_halos)
child_send = na.ones(child_IDs.size, dtype='bool')
- del sort
# Match particles in halos.
self._match(parent_IDs, child_IDs, parent_halos, child_halos,
https://bitbucket.org/yt_analysis/yt/changeset/16388c698349/
changeset: 16388c698349
branch: yt
user: bcrosby
date: 2012-09-05 23:06:50
summary: Fixing pname and cname typo. Only for consistency, code function isn't affected.
affected #: 1 file
diff -r 45f9ac33caf22fe5caca8cd255fdeaa7a67469b9 -r 16388c69834985b99e28f1b68cac859e7ad7f31c yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -488,9 +488,9 @@
child_IDs = []
child_masses = []
child_halos = []
- for i,pname in enumerate(child_names):
+ for i,cname in enumerate(child_names):
if i>=self.comm.rank and i%self.comm.size==self.comm.rank:
- h5fp = h5py.File(pname)
+ h5fp = h5py.File(cname)
for group in h5fp:
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
https://bitbucket.org/yt_analysis/yt/changeset/0e857c676504/
changeset: 0e857c676504
branch: yt
user: bcrosby
date: 2012-09-07 00:25:40
summary: datatypes are now consistent and mass use float rather than int
affected #: 1 file
diff -r 16388c69834985b99e28f1b68cac859e7ad7f31c -r 0e857c676504a42d04893c0812d0ffc86d1cd3c2 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -470,12 +470,12 @@
# Sort the arrays by particle index in ascending order.
if len(parent_IDs)==0:
parent_IDs = na.array([], dtype='int32')
- parent_masses = na.array([], dtype='int32')
+ parent_masses = na.array([], dtype='float64')
parent_halos = na.array([], dtype='int32')
else:
- parent_IDs = na.concatenate(parent_IDs)
- parent_masses = na.concatenate(parent_masses)
- parent_halos = na.concatenate(parent_halos)
+ parent_IDs = na.concatenate(parent_IDs).astype('int32')
+ parent_masses = na.concatenate(parent_masses).astype('float64')
+ parent_halos = na.concatenate(parent_halos).astype('int32')
else:
# We can use old data and save disk reading.
(parent_IDs, parent_masses, parent_halos) = last
@@ -505,12 +505,12 @@
# Sort the arrays by particle index in ascending order.
if len(child_IDs)==0:
child_IDs = na.array([], dtype='int32')
- child_masses = na.array([], dtype='int32')
+ child_masses = na.array([], dtype='float64')
child_halos = na.array([], dtype='int32')
else:
- child_IDs = na.concatenate(child_IDs)
- child_masses = na.concatenate(child_masses)
- child_halos = na.concatenate(child_halos)
+ child_IDs = na.concatenate(child_IDs).astype('int32')
+ child_masses = na.concatenate(child_masses).astype('float64')
+ child_halos = na.concatenate(child_halos).astype('int32')
child_send = na.ones(child_IDs.size, dtype='bool')
# Match particles in halos.
https://bitbucket.org/yt_analysis/yt/changeset/1a87d0db31fc/
changeset: 1a87d0db31fc
branch: yt
user: bcrosby
date: 2012-09-07 20:10:12
summary: Switched to using extend() rather than append() to add halos and characteristics to an existing list as individual values rather than as a list
affected #: 1 file
diff -r 0e857c676504a42d04893c0812d0ffc86d1cd3c2 -r 1a87d0db31fc5d9d974d14b9f5d20e388959c5be yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -460,28 +460,32 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- parent_IDs.append(thisIDs)
- parent_masses.append(thisMasses)
- parent_halos.append(na.ones(thisIDs.size,
+ parent_IDs.extend(thisIDs)
+ parent_masses.extend(thisMasses)
+ parent_halos.extend(na.ones(len(thisIDs),
dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
-
# Sort the arrays by particle index in ascending order.
if len(parent_IDs)==0:
- parent_IDs = na.array([], dtype='int32')
+ parent_IDs = na.array([], dtype='int64')
parent_masses = na.array([], dtype='float64')
parent_halos = na.array([], dtype='int32')
else:
- parent_IDs = na.concatenate(parent_IDs).astype('int32')
- parent_masses = na.concatenate(parent_masses).astype('float64')
- parent_halos = na.concatenate(parent_halos).astype('int32')
+ parent_IDs = na.asarray(parent_IDs).astype('int64')
+ parent_masses = na.asarray(parent_masses).astype('float64')
+ parent_halos = na.asarray(parent_halos).astype('int32')
+ sort = parent_IDs.argsort()
+ parent_IDs = parent_IDs[sort]
+ parent_masses = parent_masses[sort]
+ parent_halos = parent_halos[sort]
+ del sort
else:
# We can use old data and save disk reading.
(parent_IDs, parent_masses, parent_halos) = last
# Used to communicate un-matched particles.
parent_send = na.ones(parent_IDs.size, dtype='bool')
-
+
# Now get the child halo data.
child_names = list(self.names[child_currt])
child_names.sort()
@@ -495,22 +499,27 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- child_IDs.append(thisIDs)
- child_masses.append(thisMasses)
- child_halos.append(na.ones(thisIDs.size,
+ child_IDs.extend(thisIDs)
+ child_masses.extend(thisMasses)
+ child_halos.extend(na.ones(len(thisIDs),
dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
-
# Sort the arrays by particle index in ascending order.
if len(child_IDs)==0:
- child_IDs = na.array([], dtype='int32')
+ child_IDs = na.array([], dtype='int64')
child_masses = na.array([], dtype='float64')
child_halos = na.array([], dtype='int32')
else:
- child_IDs = na.concatenate(child_IDs).astype('int32')
- child_masses = na.concatenate(child_masses).astype('float64')
- child_halos = na.concatenate(child_halos).astype('int32')
+ child_IDs = na.asarray(child_IDs).astype('int64')
+ child_masses = na.asarray(child_masses)
+ child_halos = na.asarray(child_halos)
+ sort = child_IDs.argsort()
+ child_IDs = child_IDs[sort]
+ child_masses = child_masses[sort]
+ child_halos = child_halos[sort]
+ del sort
+
child_send = na.ones(child_IDs.size, dtype='bool')
# Match particles in halos.
https://bitbucket.org/yt_analysis/yt/changeset/211e42b5af28/
changeset: 211e42b5af28
branch: yt
user: sskory
date: 2012-09-07 21:23:36
summary: This combination of append/concatenate works for me for the merger tree.
affected #: 1 file
diff -r 1a87d0db31fc5d9d974d14b9f5d20e388959c5be -r 211e42b5af287d7e811e8b8cc08f5f5a341a7b41 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -460,9 +460,9 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- parent_IDs.extend(thisIDs)
- parent_masses.extend(thisMasses)
- parent_halos.extend(na.ones(len(thisIDs),
+ parent_IDs.append(thisIDs)
+ parent_masses.append(thisMasses)
+ parent_halos.append(na.ones(len(thisIDs),
dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
@@ -472,9 +472,9 @@
parent_masses = na.array([], dtype='float64')
parent_halos = na.array([], dtype='int32')
else:
- parent_IDs = na.asarray(parent_IDs).astype('int64')
- parent_masses = na.asarray(parent_masses).astype('float64')
- parent_halos = na.asarray(parent_halos).astype('int32')
+ parent_IDs = na.concatenate(parent_IDs).astype('int64')
+ parent_masses = na.concatenate(parent_masses).astype('float64')
+ parent_halos = na.concatenate(parent_halos).astype('int32')
sort = parent_IDs.argsort()
parent_IDs = parent_IDs[sort]
parent_masses = parent_masses[sort]
@@ -499,9 +499,9 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- child_IDs.extend(thisIDs)
- child_masses.extend(thisMasses)
- child_halos.extend(na.ones(len(thisIDs),
+ child_IDs.append(thisIDs)
+ child_masses.append(thisMasses)
+ child_halos.append(na.ones(len(thisIDs),
dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
@@ -511,9 +511,9 @@
child_masses = na.array([], dtype='float64')
child_halos = na.array([], dtype='int32')
else:
- child_IDs = na.asarray(child_IDs).astype('int64')
- child_masses = na.asarray(child_masses)
- child_halos = na.asarray(child_halos)
+ child_IDs = na.concatenate(child_IDs).astype('int64')
+ child_masses = na.concatenate(child_masses)
+ child_halos = na.concatenate(child_halos)
sort = child_IDs.argsort()
child_IDs = child_IDs[sort]
child_masses = child_masses[sort]
https://bitbucket.org/yt_analysis/yt/changeset/62a260cea40d/
changeset: 62a260cea40d
branch: yt
user: sskory
date: 2012-09-07 22:29:10
summary: Swapping out fortran kdtree for the cython one.
affected #: 1 file
diff -r 211e42b5af287d7e811e8b8cc08f5f5a341a7b41 -r 62a260cea40df2a9c2b9784f471852bcab2ee4f7 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -37,10 +37,7 @@
from yt.convenience import load
from yt.utilities.logger import ytLogger as mylog
import yt.utilities.pydot as pydot
-try:
- from yt.utilities.kdtree import *
-except ImportError:
- mylog.debug("The Fortran kD-Tree did not import correctly.")
+from yt.utilities.spatial import cKDTree
from yt.utilities.parallel_tools.parallel_analysis_interface import \
ParallelDummy, \
ParallelAnalysisInterface, \
@@ -349,16 +346,8 @@
child_points.append([row[1] / self.period[0],
row[2] / self.period[1],
row[3] / self.period[2]])
- # Turn it into fortran.
child_points = na.array(child_points)
- fKD.pos = na.asfortranarray(child_points.T)
- fKD.qv = na.empty(3, dtype='float64')
- fKD.dist = na.empty(NumNeighbors, dtype='float64')
- fKD.tags = na.empty(NumNeighbors, dtype='int64')
- fKD.nn = NumNeighbors
- fKD.sort = True
- fKD.rearrange = True
- create_tree(0)
+ kdtree = cKDTree(child_points, leafsize = 10)
# Find the parent points from the database.
parent_pf = load(parentfile)
@@ -373,22 +362,20 @@
candidates = {}
for row in self.cursor:
# Normalize positions for use within the kdtree.
- fKD.qv = na.array([row[1] / self.period[0],
+ query = na.array([row[1] / self.period[0],
row[2] / self.period[1],
row[3] / self.period[2]])
- find_nn_nearest_neighbors()
- NNtags = fKD.tags[:] - 1
+ NNtags = kdtree.query(query, NumNeighbors, period=self.period)[1]
nIDs = []
for n in NNtags:
- nIDs.append(n)
+ if n not in nIDs:
+ nIDs.append(n)
# We need to fill in fake halos if there aren't enough halos,
# which can happen at high redshifts.
while len(nIDs) < NumNeighbors:
nIDs.append(-1)
candidates[row[0]] = nIDs
-
- del fKD.pos, fKD.tags, fKD.dist
- free_tree(0) # Frees the kdtree object.
+ del kdtree
else:
candidates = None
https://bitbucket.org/yt_analysis/yt/changeset/80c20f67f390/
changeset: 80c20f67f390
branch: yt
user: bcrosby
date: 2012-09-08 18:37:48
summary: Pulled in Stephen's modification. Tested against the standard halo merger tree database created for the Enzo_64 dataset and found identical results.
affected #: 1 file
diff -r 62a260cea40df2a9c2b9784f471852bcab2ee4f7 -r 80c20f67f390ea2eadf9358d7ccba79f2fabb2a6 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -506,7 +506,7 @@
child_masses = child_masses[sort]
child_halos = child_halos[sort]
del sort
-
+
child_send = na.ones(child_IDs.size, dtype='bool')
# Match particles in halos.
https://bitbucket.org/yt_analysis/yt/changeset/5e78fb4e3812/
changeset: 5e78fb4e3812
branch: yt
user: sskory
date: 2012-09-08 19:19:38
summary: Merged in bcrosby/crosby (pull request #266)
affected #: 1 file
diff -r 551e1238ab38bfd9f1951e6a3fe692cc995e5768 -r 5e78fb4e3812e186e208866d9b7300a244eb6ee5 yt/analysis_modules/halo_merger_tree/merger_tree.py
--- a/yt/analysis_modules/halo_merger_tree/merger_tree.py
+++ b/yt/analysis_modules/halo_merger_tree/merger_tree.py
@@ -37,10 +37,7 @@
from yt.convenience import load
from yt.utilities.logger import ytLogger as mylog
import yt.utilities.pydot as pydot
-try:
- from yt.utilities.kdtree import *
-except ImportError:
- mylog.debug("The Fortran kD-Tree did not import correctly.")
+from yt.utilities.spatial import cKDTree
from yt.utilities.parallel_tools.parallel_analysis_interface import \
ParallelDummy, \
ParallelAnalysisInterface, \
@@ -349,16 +346,8 @@
child_points.append([row[1] / self.period[0],
row[2] / self.period[1],
row[3] / self.period[2]])
- # Turn it into fortran.
child_points = na.array(child_points)
- fKD.pos = na.asfortranarray(child_points.T)
- fKD.qv = na.empty(3, dtype='float64')
- fKD.dist = na.empty(NumNeighbors, dtype='float64')
- fKD.tags = na.empty(NumNeighbors, dtype='int64')
- fKD.nn = NumNeighbors
- fKD.sort = True
- fKD.rearrange = True
- create_tree(0)
+ kdtree = cKDTree(child_points, leafsize = 10)
# Find the parent points from the database.
parent_pf = load(parentfile)
@@ -373,22 +362,20 @@
candidates = {}
for row in self.cursor:
# Normalize positions for use within the kdtree.
- fKD.qv = na.array([row[1] / self.period[0],
+ query = na.array([row[1] / self.period[0],
row[2] / self.period[1],
row[3] / self.period[2]])
- find_nn_nearest_neighbors()
- NNtags = fKD.tags[:] - 1
+ NNtags = kdtree.query(query, NumNeighbors, period=self.period)[1]
nIDs = []
for n in NNtags:
- nIDs.append(n)
+ if n not in nIDs:
+ nIDs.append(n)
# We need to fill in fake halos if there aren't enough halos,
# which can happen at high redshifts.
while len(nIDs) < NumNeighbors:
nIDs.append(-1)
candidates[row[0]] = nIDs
-
- del fKD.pos, fKD.tags, fKD.dist
- free_tree(0) # Frees the kdtree object.
+ del kdtree
else:
candidates = None
@@ -450,9 +437,9 @@
# the parent dataset.
parent_names = list(self.names[parent_currt])
parent_names.sort()
- parent_IDs = na.array([], dtype='int64')
- parent_masses = na.array([], dtype='float64')
- parent_halos = na.array([], dtype='int32')
+ parent_IDs = []
+ parent_masses = []
+ parent_halos = []
for i,pname in enumerate(parent_names):
if i>=self.comm.rank and i%self.comm.size==self.comm.rank:
h5fp = h5py.File(pname)
@@ -460,31 +447,38 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- parent_IDs = na.concatenate((parent_IDs, thisIDs))
- parent_masses = na.concatenate((parent_masses, thisMasses))
- parent_halos = na.concatenate((parent_halos,
- na.ones(thisIDs.size, dtype='int32') * gID))
+ parent_IDs.append(thisIDs)
+ parent_masses.append(thisMasses)
+ parent_halos.append(na.ones(len(thisIDs),
+ dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
-
# Sort the arrays by particle index in ascending order.
- sort = parent_IDs.argsort()
- parent_IDs = parent_IDs[sort]
- parent_masses = parent_masses[sort]
- parent_halos = parent_halos[sort]
- del sort
+ if len(parent_IDs)==0:
+ parent_IDs = na.array([], dtype='int64')
+ parent_masses = na.array([], dtype='float64')
+ parent_halos = na.array([], dtype='int32')
+ else:
+ parent_IDs = na.concatenate(parent_IDs).astype('int64')
+ parent_masses = na.concatenate(parent_masses).astype('float64')
+ parent_halos = na.concatenate(parent_halos).astype('int32')
+ sort = parent_IDs.argsort()
+ parent_IDs = parent_IDs[sort]
+ parent_masses = parent_masses[sort]
+ parent_halos = parent_halos[sort]
+ del sort
else:
# We can use old data and save disk reading.
(parent_IDs, parent_masses, parent_halos) = last
# Used to communicate un-matched particles.
parent_send = na.ones(parent_IDs.size, dtype='bool')
-
+
# Now get the child halo data.
child_names = list(self.names[child_currt])
child_names.sort()
- child_IDs = na.array([], dtype='int64')
- child_masses = na.array([], dtype='float64')
- child_halos = na.array([], dtype='int32')
+ child_IDs = []
+ child_masses = []
+ child_halos = []
for i,cname in enumerate(child_names):
if i>=self.comm.rank and i%self.comm.size==self.comm.rank:
h5fp = h5py.File(cname)
@@ -492,20 +486,28 @@
gID = int(group[4:])
thisIDs = h5fp[group]['particle_index'][:]
thisMasses = h5fp[group]['ParticleMassMsun'][:]
- child_IDs = na.concatenate((child_IDs, thisIDs))
- child_masses = na.concatenate((child_masses, thisMasses))
- child_halos = na.concatenate((child_halos,
- na.ones(thisIDs.size, dtype='int32') * gID))
+ child_IDs.append(thisIDs)
+ child_masses.append(thisMasses)
+ child_halos.append(na.ones(len(thisIDs),
+ dtype='int32') * gID)
del thisIDs, thisMasses
h5fp.close()
+ # Sort the arrays by particle index in ascending order.
+ if len(child_IDs)==0:
+ child_IDs = na.array([], dtype='int64')
+ child_masses = na.array([], dtype='float64')
+ child_halos = na.array([], dtype='int32')
+ else:
+ child_IDs = na.concatenate(child_IDs).astype('int64')
+ child_masses = na.concatenate(child_masses)
+ child_halos = na.concatenate(child_halos)
+ sort = child_IDs.argsort()
+ child_IDs = child_IDs[sort]
+ child_masses = child_masses[sort]
+ child_halos = child_halos[sort]
+ del sort
- # Sort the arrays by particle index.
- sort = child_IDs.argsort()
- child_IDs = child_IDs[sort]
- child_masses = child_masses[sort]
- child_halos = child_halos[sort]
child_send = na.ones(child_IDs.size, dtype='bool')
- del sort
# Match particles in halos.
self._match(parent_IDs, child_IDs, parent_halos, child_halos,
Repository URL: https://bitbucket.org/yt_analysis/yt/
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