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588 lines
20 KiB
Python
588 lines
20 KiB
Python
#+
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# VIDE -- Void IDentification and Examination -- ./python_tools/vide/voidUtil/catalogUtil.py
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# Copyright (C) 2010-2014 Guilhem Lavaux
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# Copyright (C) 2011-2014 P. M. Sutter
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; version 2 of the License.
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#
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
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#+
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# Various utilities for loading and modifying particle datasets
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import numpy as np
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from netCDF4 import Dataset
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import sys
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from backend import *
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import pickle
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from .periodic_kdtree import PeriodicCKDTree
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import os
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NetCDFFile = Dataset
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ncFloat = 'f8'
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# -----------------------------------------------------------------------------
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def loadPart(sampleDir):
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print(" Loading particle data...")
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sys.stdout.flush()
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with open(sampleDir+"/sample_info.dat", 'rb') as input:
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sample = pickle.load(input)
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infoFile = sampleDir+"/zobov_slice_"+sample.fullName+".par"
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File = NetCDFFile(infoFile, 'r')
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ranges = np.zeros((3,2))
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ranges[0][0] = getattr(File, 'range_x_min')
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ranges[0][1] = getattr(File, 'range_x_max')
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ranges[1][0] = getattr(File, 'range_y_min')
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ranges[1][1] = getattr(File, 'range_y_max')
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ranges[2][0] = getattr(File, 'range_z_min')
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ranges[2][1] = getattr(File, 'range_z_max')
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isObservation = getattr(File, 'is_observation')
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maskIndex = getattr(File, 'mask_index')
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File.close()
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mul = np.zeros((3))
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mul[:] = ranges[:,1] - ranges[:,0]
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partFile = sampleDir+"/zobov_slice_"+sample.fullName
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iLine = 0
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partData = []
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part = np.zeros((3))
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with open(partFile, mode="rb") as File:
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chk = np.fromfile(File, dtype=np.int32,count=1)
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Np = np.fromfile(File, dtype=np.int32,count=1)[0]
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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x = np.fromfile(File, dtype=np.float32,count=Np)
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x *= mul[0]
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if isObservation != 1:
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x += ranges[0][0]
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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y = np.fromfile(File, dtype=np.float32,count=Np)
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y *= mul[1]
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if isObservation != 1:
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y += ranges[1][0]
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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z = np.fromfile(File, dtype=np.float32,count=Np)
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z *= mul[2]
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if isObservation != 1:
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z += ranges[2][0]
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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RA = np.fromfile(File, dtype=np.float32,count=Np)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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Dec = np.fromfile(File, dtype=np.float32,count=Np)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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redshift = np.fromfile(File, dtype=np.float32,count=Np)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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uniqueID = np.fromfile(File, dtype=np.int64,count=Np)
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chk = np.fromfile(File, dtype=np.int32,count=1)
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if isObservation == 1:
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x = x[0:maskIndex]# * 100/300000
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y = y[0:maskIndex]# * 100/300000
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z = z[0:maskIndex]# * 100/300000
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RA = RA[0:maskIndex]
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Dec = Dec[0:maskIndex]
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redshift = redshift[0:maskIndex]
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uniqueID = uniqueID[0:maskIndex]
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partData = np.column_stack((x,y,z))
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extraData = np.column_stack((RA,Dec,redshift,uniqueID))
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boxLen = mul
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#if isObservation == 1:
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# # look for the mask file
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# if os.access(sample.maskFile, os.F_OK):
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# maskFile = sample.maskFile
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# else:
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# maskFile = sampleDir+"/"+os.path.basename(sample.maskFile)
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# print "Using maskfile found in:", maskFile
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# props = getSurveyProps(maskFile, sample.zBoundary[0],
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# sample.zBoundary[1],
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# sample.zBoundary[0],
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# sample.zBoundary[1], "all",
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# selectionFuncFile=sample.selFunFile,
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# useComoving=sample.useComoving)
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# boxVol = props[0]
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# volNorm = maskIndex/boxVol
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#else:
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boxVol = np.prod(boxLen)
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volNorm = len(x)/boxVol
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isObservationData = isObservation == 1
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return partData, boxLen, volNorm, isObservationData, ranges, extraData
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# -----------------------------------------------------------------------------
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def getVolNorm(sampleDir):
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with open(sampleDir+"/sample_info.dat", 'rb') as input:
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sample = pickle.load(input)
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infoFile = sampleDir+"/zobov_slice_"+sample.fullName+".par"
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File = NetCDFFile(infoFile, 'r')
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ranges = np.zeros((3,2))
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ranges[0][0] = getattr(File, 'range_x_min')
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ranges[0][1] = getattr(File, 'range_x_max')
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ranges[1][0] = getattr(File, 'range_y_min')
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ranges[1][1] = getattr(File, 'range_y_max')
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ranges[2][0] = getattr(File, 'range_z_min')
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ranges[2][1] = getattr(File, 'range_z_max')
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isObservation = getattr(File, 'is_observation')
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maskIndex = getattr(File, 'mask_index')
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File.close()
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mul = np.zeros((3))
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mul[:] = ranges[:,1] - ranges[:,0]
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partFile = sampleDir+"/zobov_slice_"+sample.fullName
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with open(partFile, mode="rb") as File:
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chk = np.fromfile(File, dtype=np.int32,count=1)
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Np = np.fromfile(File, dtype=np.int32,count=1)[0]
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boxLen = mul
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#if isObservation == 1:
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# # look for the mask file
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# if os.access(sample.maskFile, os.F_OK):
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# maskFile = sample.maskFile
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# else:
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# maskFile = sampleDir+"/"+os.path.basename(sample.maskFile)
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# print "Using maskfile found in:", maskFile
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# props = getSurveyProps(maskFile, sample.zBoundary[0],
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# sample.zBoundary[1],
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# sample.zBoundary[0],
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# sample.zBoundary[1], "all",
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# selectionFuncFile=sample.selFunFile,
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# useComoving=sample.useComoving)
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# boxVol = props[0]
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# volNorm = maskIndex/boxVol
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#else:
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boxVol = np.prod(boxLen)
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volNorm = Np/boxVol
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return volNorm
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# -----------------------------------------------------------------------------
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def loadPartVel(sampleDir):
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#print " Loading particle velocities..."
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sys.stdout.flush()
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with open(sampleDir+"/sample_info.dat", 'rb') as input:
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sample = pickle.load(input)
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infoFile = sampleDir+"/zobov_slice_"+sample.fullName+".par"
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File = NetCDFFile(infoFile, 'r')
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isObservation = getattr(File, 'is_observation')
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if isObservation:
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print("No velocities for observations!")
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return -1
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vx = File.variables['vel_x'][0:]
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vy = File.variables['vel_y'][0:]
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vz = File.variables['vel_z'][0:]
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File.close()
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partVel = np.column_stack((vx,vy,vz))
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return partVel
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# -----------------------------------------------------------------------------
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def getPartTree(catalog):
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sample = catalog.sampleInfo
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partData = catalog.partPos
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boxLen = catalog.boxLen
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periodicLine = getPeriodic(sample)
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periodic = 1.*boxLen
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if not "x" in periodicLine: periodic[0] = -1
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if not "y" in periodicLine: periodic[1] = -1
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if not "z" in periodicLine: periodic[2] = -1
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return PeriodicCKDTree(periodic, partData)
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# -----------------------------------------------------------------------------
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def getBall(partTree, center, radius):
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return partTree.query_ball_point(center, r=radius)
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# -----------------------------------------------------------------------------
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def shiftPart(inPart, center, periodicLine, ranges):
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part = inPart.copy()
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newCenter = 1.*center;
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boxLen = np.zeros((3))
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boxLen[0] = ranges[0][1] - ranges[0][0]
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boxLen[1] = ranges[1][1] - ranges[1][0]
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boxLen[2] = ranges[2][1] - ranges[2][0]
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# shift to box coordinates
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part[:,0] -= ranges[0][0]
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part[:,1] -= ranges[1][0]
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part[:,2] -= ranges[2][0]
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newCenter[:] -= ranges[:,0]
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part[:,0] -= newCenter[0]
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part[:,1] -= newCenter[1]
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part[:,2] -= newCenter[2]
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shiftUs = np.abs(part[:,0]) > boxLen[0]/2.
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if ("x" in periodicLine): part[shiftUs,0] -= \
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np.copysign(boxLen[0], part[shiftUs,0])
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shiftUs = np.abs(part[:,1]) > boxLen[1]/2.
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if ("y" in periodicLine): part[shiftUs,1] -= \
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np.copysign(boxLen[1], part[shiftUs,1])
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shiftUs = np.abs(part[:,2]) > boxLen[2]/2.
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if ("z" in periodicLine): part[shiftUs,2] -= \
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np.copysign(boxLen[2], part[shiftUs,2])
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#part[:,0] += ranges[0][0]
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#part[:,1] += ranges[1][0]
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#part[:,2] += ranges[2][0]
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return part
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# -----------------------------------------------------------------------------
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class Bunch:
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def __init__(self, **kwds):
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self.__dict__.update(kwds)
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class Catalog:
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numVoids = 0
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numPartTot = 0
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numZonesTot = 0
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volNorm = 0
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boxLen = np.zeros((3))
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ranges = np.zeros((3,2))
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part = None
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zones2Parts = None
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void2Zones = None
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voids = None
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sampleInfo = None
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# -----------------------------------------------------------------------------
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def loadVoidCatalog(sampleDir, dataPortion="central", loadParticles=True,
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untrimmed=False):
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# loads a void catalog
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# by default, loads parent-level voids with central densities greater than 0.2*mean
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# sampleDir: path to VIDE output directory
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# dataPortion: "central" or "all"
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# loadParticles: if True, also load particle information
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# untrimmed: if True, catalog contains all voids, regardless of density or hierarchy level
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sys.stdout.flush()
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catalog = Catalog()
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with open(sampleDir+"/sample_info.dat", 'rb') as input:
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sample = pickle.load(input)
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catalog.sampleInfo = sample
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print("Loading info...")
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infoFile = sampleDir+"/zobov_slice_"+sample.fullName+".par"
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File = NetCDFFile(infoFile, 'r')
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ranges = np.zeros((3,2))
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ranges[0][0] = getattr(File, 'range_x_min')
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ranges[0][1] = getattr(File, 'range_x_max')
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ranges[1][0] = getattr(File, 'range_y_min')
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ranges[1][1] = getattr(File, 'range_y_max')
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ranges[2][0] = getattr(File, 'range_z_min')
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ranges[2][1] = getattr(File, 'range_z_max')
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catalog.boxLen[0] = ranges[0][1] - ranges[0][0]
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catalog.boxLen[1] = ranges[1][1] - ranges[1][0]
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catalog.boxLen[2] = ranges[2][1] - ranges[2][0]
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catalog.ranges = ranges
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File.close()
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volNorm = getVolNorm(sampleDir)
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catalog.volNorm = volNorm
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if untrimmed:
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prefix = "untrimmed_"
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else:
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prefix = ""
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print("Loading voids...")
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fileName = sampleDir+"/"+prefix+"voidDesc_"+dataPortion+"_"+sample.fullName+".out"
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catData = np.loadtxt(fileName, comments="#", skiprows=2)
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catalog.voids = []
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for line in catData:
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catalog.voids.append(Bunch(iVoid = int(line[0]),
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voidID = int(line[1]),
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coreParticle = line[2],
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coreDens = line[3],
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zoneVol = line[4],
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zoneNumPart = line[5],
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numZones = int(line[6]),
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voidVol = line[7],
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numPart = int(line[8]),
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densCon = line[9],
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voidProb = line[10],
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radius = 0., # this is read in later
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macrocenter = np.zeros((3)),
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redshift = 0,
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RA = 0,
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Dec = 0,
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parentID = 0,
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treeLevel = 0,
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numChildren = 0,
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centralDen = 0.,
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ellipticity = 0.,
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eigenVals = np.zeros((3)),
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eigenVecs = np.zeros((3,3)),
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))
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catalog.numVoids = len(catalog.voids)
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print("Read %d voids" % catalog.numVoids)
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print("Loading macrocenters...")
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iLine = 0
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for line in open(sampleDir+"/"+prefix+"macrocenters_"+dataPortion+"_"+sample.fullName+".out"):
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line = line.split()
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catalog.voids[iLine].macrocenter[0] = float(line[1])
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catalog.voids[iLine].macrocenter[1] = float(line[2])
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catalog.voids[iLine].macrocenter[2] = float(line[3])
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iLine += 1
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iLine = 0
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fileName = sampleDir+"/"+prefix+"sky_positions_"+dataPortion+"_"+sample.fullName+".out"
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catData = np.loadtxt(fileName, comments="#")
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for line in catData:
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catalog.voids[iLine].RA = float(line[0])
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catalog.voids[iLine].Dec = float(line[1])
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iLine += 1
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print("Loading derived void information...")
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fileName = sampleDir+"/"+prefix+"centers_"+dataPortion+"_"+sample.fullName+".out"
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catData = np.loadtxt(fileName, comments="#")
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for (iLine,line) in enumerate(catData):
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catalog.voids[iLine].volume = float(line[6])
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catalog.voids[iLine].radius = float(line[4])
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catalog.voids[iLine].redshift = float(line[5])
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catalog.voids[iLine].parentID = float(line[10])
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catalog.voids[iLine].treeLevel = float(line[11])
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catalog.voids[iLine].numChildren = float(line[12])
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catalog.voids[iLine].centralDen = float(line[13])
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iLine += 1
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fileName = sampleDir+"/"+prefix+"shapes_"+dataPortion+"_"+sample.fullName+".out"
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catData = np.loadtxt(fileName, comments="#")
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for (iLine,line) in enumerate(catData):
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catalog.voids[iLine].ellipticity = float(line[1])
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catalog.voids[iLine].eigenVals[0] = float(line[2])
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catalog.voids[iLine].eigenVals[1] = float(line[3])
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catalog.voids[iLine].eigenVals[2] = float(line[4])
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catalog.voids[iLine].eigenVecs[0][0] = float(line[5])
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catalog.voids[iLine].eigenVecs[0][1] = float(line[6])
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catalog.voids[iLine].eigenVecs[0][2] = float(line[7])
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catalog.voids[iLine].eigenVecs[1][0] = float(line[8])
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catalog.voids[iLine].eigenVecs[1][1] = float(line[9])
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catalog.voids[iLine].eigenVecs[1][2] = float(line[10])
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catalog.voids[iLine].eigenVecs[2][0] = float(line[11])
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catalog.voids[iLine].eigenVecs[2][1] = float(line[12])
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catalog.voids[iLine].eigenVecs[2][2] = float(line[13])
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iLine += 1
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if loadParticles:
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print("Loading all particles...")
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partData, boxLen, volNorm, isObservationData, ranges, extraData = loadPart(sampleDir)
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numPartTot = len(partData)
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catalog.numPartTot = numPartTot
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catalog.partPos = partData
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catalog.part = []
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for i in range(len(partData)):
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catalog.part.append(Bunch(x = partData[i][0],
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y = partData[i][1],
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z = partData[i][2],
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volume = 0,
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ra = extraData[i][0],
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dec = extraData[i][1],
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redshift = extraData[i][2],
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uniqueID = extraData[i][3]))
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print("Loading volumes...")
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if sample.hasWeightedVolumes:
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volFile = sampleDir+"/vol_weighted_"+sample.fullName+".dat"
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else:
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volFile = sampleDir+"/vol_"+sample.fullName+".dat"
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with open(volFile, mode="rb") as File:
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chk = np.fromfile(File, dtype=np.int32,count=1)
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vols = np.fromfile(File, dtype=np.float32,count=numPartTot)
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for ivol in range(len(vols)):
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catalog.part[ivol].volume = vols[ivol] / volNorm
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print("Loading zone-void membership info...")
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zoneFile = sampleDir+"/voidZone_"+sample.fullName+".dat"
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catalog.void2Zones = []
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with open(zoneFile, mode="rb") as File:
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|
numZonesTot = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
catalog.numZonesTot = numZonesTot
|
|
for iZ in range(numZonesTot):
|
|
numZones = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
catalog.void2Zones.append(Bunch(numZones = numZones,
|
|
zoneIDs = []))
|
|
|
|
for p in range(numZones):
|
|
zoneID = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
catalog.void2Zones[iZ].zoneIDs.append(zoneID)
|
|
|
|
print("Loading particle-zone membership info...")
|
|
zonePartFile = sampleDir+"/voidPart_"+sample.fullName+".dat"
|
|
catalog.zones2Parts = []
|
|
with open(zonePartFile) as File:
|
|
chk = np.fromfile(File, dtype=np.int32,count=1)
|
|
numZonesTot = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
for iZ in range(numZonesTot):
|
|
numPart = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
catalog.zones2Parts.append(Bunch(numPart = numPart,
|
|
partIDs = []))
|
|
|
|
for p in range(numPart):
|
|
partID = np.fromfile(File, dtype=np.int32,count=1)[0]
|
|
catalog.zones2Parts[iZ].partIDs.append(partID)
|
|
|
|
return catalog
|
|
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def getArray(objectList, attr):
|
|
|
|
if hasattr(objectList[0], attr):
|
|
ndim = np.shape( np.atleast_1d( getattr(objectList[0], attr) ) )[0]
|
|
attrArr = np.zeros(( len(objectList), ndim ))
|
|
|
|
for idim in range(ndim):
|
|
attrArr[:,idim] = np.fromiter((np.atleast_1d(getattr(v, attr))[idim] \
|
|
for v in objectList), float )
|
|
|
|
if ndim == 1: attrArr = attrArr[:,0]
|
|
|
|
return attrArr
|
|
else:
|
|
print(" Attribute", attr, "not found!")
|
|
return -1
|
|
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def getVoidPart(catalog, voidID):
|
|
|
|
partOut = []
|
|
for iZ in range(catalog.void2Zones[voidID].numZones):
|
|
zoneID = catalog.void2Zones[voidID].zoneIDs[iZ]
|
|
for p in range(catalog.zones2Parts[zoneID].numPart):
|
|
partID = catalog.zones2Parts[zoneID].partIDs[p]
|
|
partOut.append(catalog.part[partID])
|
|
|
|
return partOut
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def filterVoidsOnSize(catalog, rMin):
|
|
catalog.voids = [v for v in catalog.voids if v.radius >= rMin]
|
|
catalog.numVoids = len(catalog.voids)
|
|
return catalog
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def filterVoidsOnTreeLevel(catalog, level):
|
|
catalog.voids = [v for v in catalog.voids if v.treeLevel == level]
|
|
if level == -1:
|
|
catalog.voids = [v for v in catalog.voids if v.numChildren == 0]
|
|
catalog.numVoids = len(catalog.voids)
|
|
return catalog
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def filterVoidsOnCentralDen(catalog, maxCentralDen):
|
|
catalog.voids = [v for v in catalog.voids if v.centralDen <= maxCentralDen]
|
|
catalog.numVoids = len(catalog.voids)
|
|
return catalog
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def filterVoidsOnCoreDen(catalog, maxCoreDen):
|
|
catalog.voids = [v for v in catalog.voids if v.coreDens <= maxCoreDen]
|
|
catalog.numVoids = len(catalog.voids)
|
|
return catalog
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def filterVoidsOnDenCon(catalog, minDenCon):
|
|
catalog.voids = [v for v in catalog.voids if v.densCon >= minDenCon]
|
|
catalog.numVoids = len(catalog.voids)
|
|
return catalog
|
|
|
|
|
|
|
|
# -----------------------------------------------------------------------------
|
|
def stackVoids(catalog, stackMode = "ball"):
|
|
|
|
# builds a stack of voids from the given catalog
|
|
# catalog: void catalog
|
|
# stackMode:
|
|
# "ball": spherical cut
|
|
# "voronoi": only void member particles
|
|
#
|
|
# returns:
|
|
# stackedPart: array of relative particle positions in the stack
|
|
|
|
rMax = 100.
|
|
periodicLine = getPeriodic(catalog.sampleInfo)
|
|
|
|
if stackMode == "ball":
|
|
partTree = getPartTree(catalog)
|
|
|
|
stackedPart = []
|
|
for void in catalog.voids:
|
|
center = void.macrocenter
|
|
|
|
if stackMode == "ball":
|
|
localPart = catalog.partPos[ getBall(partTree, center, rMax) ]
|
|
else:
|
|
voidPart = getVoidPart(catalog, void.voidID)
|
|
localPart = np.zeros((len(voidPart),3))
|
|
localPart[:,0] = getArray(voidPart, 'x')
|
|
localPart[:,1] = getArray(voidPart, 'y')
|
|
localPart[:,2] = getArray(voidPart, 'z')
|
|
|
|
shiftedPart = shiftPart(localPart, center, periodicLine, catalog.ranges)
|
|
|
|
stackedPart.extend(shiftedPart)
|
|
|
|
return stackedPart
|