guilhem_lavaux/vide_public
0
0
Fork 0
mirror of https://bitbucket.org/cosmicvoids/vide_public.git synced 2025-07-04 23:31:12 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge branch 'master' of https://bitbucket.org/cosmicvoids/vide_public

Browse source
This commit is contained in:
P.M. Sutter 2014-05-15 09:01:07 -04:00
commit 4ad245d62f
2 changed files with 3 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

2
python_tools/void_python_tools/voidUtil/catalogUtil.py
View file

@ -196,7 +196,7 @@ def loadPartVel(sampleDir):
def getPartTree(catalog): def getPartTree(catalog):
sample = catalog.sampleInfo sample = catalog.sampleInfo
partData = catalog.partData partData = catalog.partPos
boxLen = catalog.boxLen boxLen = catalog.boxLen
periodicLine = getPeriodic(sample) periodicLine = getPeriodic(sample)

3
python_tools/void_python_tools/voidUtil/profileUtil.py
View file

@ -67,7 +67,7 @@ def buildProfile(catalog, rMin, rMax):
shiftedPart = shiftPart(localPart, center, periodicLine, catalog.ranges) shiftedPart = shiftPart(localPart, center, periodicLine, catalog.ranges)
dist = np.sqrt(np.sum(shiftedPart[:,:]**2, axis=1)) dist = np.sqrt(np.sum(shiftedPart[:,:]**2, axis=1))
thisProfile, radii = np.histogram(dist, bins=nBins, range=(0,rMaxProfile)) thisProfile, radii = np.histogram(dist, bins=10, range=(0,rMaxProfile))
deltaV = 4*np.pi/3*(radii[1:]**3-radii[0:(radii.size-1)]**3) deltaV = 4*np.pi/3*(radii[1:]**3-radii[0:(radii.size-1)]**3)
thisProfile = np.float32(thisProfile) thisProfile = np.float32(thisProfile)
thisProfile /= deltaV thisProfile /= deltaV
@ -75,6 +75,7 @@ def buildProfile(catalog, rMin, rMax):
allProfiles.append(thisProfile) allProfiles.append(thisProfile)
binCenters = 0.5*(radii[1:] + radii[:-1]) binCenters = 0.5*(radii[1:] + radii[:-1])
nVoid = len(voidsToStack)
stackedProfile = np.std(allProfiles, axis=0) / np.sqrt(nVoids) stackedProfile = np.std(allProfiles, axis=0) / np.sqrt(nVoids)
sigmas = np.std(allProfiles, axis=0) / np.sqrt(nVoids) sigmas = np.std(allProfiles, axis=0) / np.sqrt(nVoids)