mirror of
https://bitbucket.org/cosmicvoids/vide_public.git
synced 2025-07-04 15:21:11 +00:00
removed extra cross-comparison files
This commit is contained in:
P.M. Sutter
parent
b441758a64
commit
1218ba3bdd
9 changed files with 0 additions and 1586 deletions
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@ -1,176 +0,0 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/analysis/makeCocenterProfiles.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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#!/usr/bin/env python
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#+
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# VIDE -- Void IDentification and Examination -- ./pipeline/apAnalysis.py
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# Copyright (C) 2010-2013 Guilhem Lavaux
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# Copyright (C) 2011-2013 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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# takes voids of given radii, computes 1 profiles,
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# then computes 1d profiles for higher-resolution catalogs using
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# same positions
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# computes radial density profiles centered on baseSample
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import imp
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import pickle
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import os
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import numpy as np
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import argparse
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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from void_python_tools.backend import *
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from util import *
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# ------------------------------------------------------------------------------
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parser = argparse.ArgumentParser(description='Analyze.')
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parser.add_argument('--parm', dest='parm', default='datasetsToAnalyze.py', help='path to parameter file')
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parser.add_argument('--show', dest='showPlot', action='store_const',
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const=True, default=False,
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help='display the plot (default: just write eps)')
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args = parser.parse_args()
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# -----------------------------------------------------------------------------
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# plot a slice of the density around the void in baseIDList,
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# with any voids in the slice shown and any voids in baseIDList flagged
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def saveProfiles(baseSample, stack, sampleList, profileList, radii,
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figDir, showPlot, outputDir):
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thisRadius = str(stack.rMin) + "-" + str(stack.rMax)
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plotName = "1dprofile_cocenter_" + baseSample.fullName+"_"+thisRadius
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np.savez(outputDir+"/1dprofile_cocentered_"+plotName+".dat",
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profileList, radii)
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return
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# -----------------------------------------------------------------------------
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filename = args.parm
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print " Loading parameters from", filename
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if not os.access(filename, os.F_OK):
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print " Cannot find parameter file %s!" % filename
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exit(-1)
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parms = imp.load_source("name", filename)
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globals().update(vars(parms))
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if not os.access(outputDir, os.F_OK):
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os.makedirs(outputDir)
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if not os.access(logDir, os.F_OK):
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os.makedirs(logDir)
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if not os.access(figDir, os.F_OK):
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os.makedirs(figDir)
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# get list of base voids
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with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
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baseSample = pickle.load(input)
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baseSampleName = baseSample.fullName
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baseVoidList = np.loadtxt(workDir+baseSampleDir+"/centers_central_"+\
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baseSampleName+".out")
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sampleList = []
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for sampleDir in sampleDirList:
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if compareSampleTag in sampleDir: continue
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with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
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sampleList.append(pickle.load(input))
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sampleDirList.insert(0,baseSampleDir)
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sampleList.insert(0,baseSample)
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# pick our void sample
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for stack in baseSample.stacks:
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print " Stack:", stack.rMin, "-", stack.rMax
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accepted = (baseVoidList[:,4] > stack.rMin) & (baseVoidList[:,4] < stack.rMax)
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stackVoidList = baseVoidList[accepted]
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print " We have", len(stackVoidList), "voids here"
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profileList = []
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radii = []
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rMaxProfile = stack.rMin*3 + 2
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if baseSample.profileBinSize == "auto":
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density = 0.5 * 50 / rMaxProfile / 2
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else:
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density = baseSample.profileBinSize
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nBins = rMaxProfile*density
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for (iSample, sampleDir) in enumerate(sampleDirList):
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if compareSampleTag in sampleDir: continue
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sample = sampleList[iSample]
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print " Working with", sample.fullName, "..."
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sys.stdout.flush()
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sampleName = sample.fullName
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print " Loading particle data..."
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partData, boxLen, volNorm = loadPart(workDir, sampleDir, sample)
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stackedProfile = np.zeros((nBins))
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print " Stacking voids..."
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binCenters = []
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for void in stackVoidList:
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periodicLine = getPeriodic(sample)
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center = void[0:3]
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shiftedPart = shiftPart(partData, center, periodicLine, boxLen)
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dist = np.sqrt(shiftedPart[:,0]**2 + shiftedPart[:,1]**2 + \
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shiftedPart[:,2]**2)
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thisProfile, radii = np.histogram(dist, bins=nBins, range=(0,rMaxProfile))
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deltaV = 4*np.pi/3*(radii[1:]**3-radii[0:(radii.size-1)]**3)
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thisProfile = np.float32(thisProfile)
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thisProfile /= deltaV
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stackedProfile += thisProfile
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binCenters = 0.5*(radii[1:]+radii[:-1])
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stackedProfile /= volNorm
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stackedProfile /= len(stackVoidList)
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profileList.append(stackedProfile)
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# plot these profiles
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print " Plotting..."
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sys.stdout.flush()
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#binCenters = 0.5*(radii[1:] + radii[:-1])
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saveProfiles(baseSample, stack, sampleList, profileList, binCenters,
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figDir, args.showPlot, outputDir)
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print " Done!"
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@ -1,103 +0,0 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/analysis/overlapVoids.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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#!/usr/bin/env python
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/analysis/mergerTree.py
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# Copyright (C) 2010-2013 Guilhem Lavaux
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# Copyright (C) 2011-2013 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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# computes the overlap between two void catalogs
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from void_python_tools.backend import *
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from void_python_tools.plotting import *
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import imp
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import pickle
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import os
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import matplotlib.pyplot as plt
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import numpy as np
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import argparse
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# ------------------------------------------------------------------------------
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parser = argparse.ArgumentParser(description='Analyze.')
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parser.add_argument('--parm', dest='parm', default='datasetsToAnalyze.py',
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help='path to parameter file')
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args = parser.parse_args()
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# ------------------------------------------------------------------------------
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filename = args.parm
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print " Loading parameters from", filename
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if not os.access(filename, os.F_OK):
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print " Cannot find parameter file %s!" % filename
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exit(-1)
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parms = imp.load_source("name", filename)
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globals().update(vars(parms))
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if not os.access(outputDir, os.F_OK):
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os.makedirs(outputDir)
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if not os.access(logDir, os.F_OK):
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os.makedirs(logDir)
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outFileName = outputDir + "/" + "voidOverlap" #+ ".dat"
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with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
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baseSample = pickle.load(input)
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for (iSample, sampleDir) in enumerate(sampleDirList):
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with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
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sample = pickle.load(input)
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print " Working with", sample.fullName, "...",
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sys.stdout.flush()
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sampleName = sample.fullName
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binPath = CTOOLS_PATH+"/analysis/voidOverlap"
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logFile = logDir+"/mergertree_"+baseSample.fullName+"_"+sampleName+".out"
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stepOutputFileName = outFileName + "_" + baseSample.fullName + "_" + \
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sampleName + "_"
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launchVoidOverlap(baseSample, sample, workDir+baseSampleDir,
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workDir+sampleDir, binPath,
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thisDataPortion="central", logFile=logFile,
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continueRun=False, workDir=workDir,
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outputFile=stepOutputFileName,
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#matchMethod="useID")
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matchMethod="prox")
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print " Done!"
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@ -1,51 +0,0 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/parm/sampleParm.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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#!/usr/bin/env python
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workDir = "" # base directory for all samples
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outputDir = ""
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logDir = "./logs/"
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figDir = "./figs/"
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# path to c_tools directory in VIDE
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CTOOLS_PATH = "/home/psutter2/projects/Voids/vide/c_tools/"
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# the path under workDir/ which which holds the sample you want to compare againt (e.g., the fiducial case)
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baseSampleDir = "sample_/"
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# comma-separated list of samples to compare against baseSampleDir
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sampleDirList = [
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"sample1_/",
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"sample2_/",
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"sample3_/",
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]
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dataPortions = [ "all" ]
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# this name gets appended to all output filenames and plots
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plotLabel = "test"
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# title to place on plots
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plotTitle = "Test"
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# don't touch this for now; it will be fully implemented and explained later
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compareSampleTag = ""
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doTheory = False
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@ -1,37 +0,0 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/datasetsToPlot.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
|
||||
# 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
|
||||
# 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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#!/usr/bin/env python
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workDir = "/home/psutter2/workspace/Voids/"
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figDir = "./figs"
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sampleDirList = [
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# "multidark/md_ss0.1_pv/sample_md_ss0.1_pv_z0.56_d00/",
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# "multidark/md_halos_min1.393e12_pv/sample_md_halos_min1.393e12_pv_z0.56_d00/",
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# "random/ran_ss0.000175/sample_ran_ss0.000175_z0.56_d00/",
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# "random/ran_ss0.1/sample_ran_ss0.1_z0.56_d00/",
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# "multidark/md_hod_dr9mid_pv/sample_md_hod_dr9mid_pv_z0.56_d00/",
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# "multidark/md_ss0.000175_pv/sample_md_ss0.000175_pv_z0.56_d00/",
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"sdss_dr9/sample_lss.dr9cmassmid.dat/",
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"lanl/masked/masked_lanl_hod_dr9mid_pv/sample_masked_lanl_hod_dr9mid_pv_z0.5/" ]
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dataPortion = "central"
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|
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@ -1,193 +0,0 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotCocenterProfiles.py
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# Copyright (C) 2010-2014 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2014 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
#!/usr/bin/env python
|
||||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./pipeline/apAnalysis.py
|
||||
# Copyright (C) 2010-2013 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2013 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
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# plots radial density profiles centered on baseVoid.
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# requires makeCocenteredProfiles to be run first!
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import imp
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import pickle
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import os
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import numpy as np
|
||||
import argparse
|
||||
import matplotlib
|
||||
matplotlib.use('Agg')
|
||||
import matplotlib.pyplot as plt
|
||||
from void_python_tools.backend import *
|
||||
from util import *
|
||||
from globalOptions import *
|
||||
from scipy.optimize import curve_fit
|
||||
|
||||
matplotlib.rcParams.update({'font.size': 20})
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|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
parser = argparse.ArgumentParser(description='Analyze.')
|
||||
parser.add_argument('--parm', dest='parm', default='datasetsToAnalyze.py', help='path to parameter file')
|
||||
parser.add_argument('--show', dest='showPlot', action='store_const',
|
||||
const=True, default=False,
|
||||
help='display the plot (default: just write eps)')
|
||||
args = parser.parse_args()
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||||
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# -----------------------------------------------------------------------------
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# Lavaux & Wandelt (2012) profile
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||||
def LWProfile(r, A0, A3, alpha):
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return A0 + A3*r**3.
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||||
#return A0 + A3*r**alpha
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||||
|
||||
# -----------------------------------------------------------------------------
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||||
# http://arxiv.org/pdf/astro-ph/0508297v1.pdf eq. 5
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||||
def PadillaProfile(r, A1, A2, alpha):
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||||
return 1.5-A1*np.exp(-(A2*r)**alpha)
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||||
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||||
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||||
# -----------------------------------------------------------------------------
|
||||
# plot a slice of the density around the void in baseIDList,
|
||||
# with any voids in the slice shown and any voids in baseIDList flagged
|
||||
def plotProfiles(baseSample, stack, sampleList,
|
||||
figDir, showPlot, outputDir, doTheory):
|
||||
|
||||
thisRadius = str(stack.rMin) + "-" + str(stack.rMax)
|
||||
plotName = "1dprofile_cocenter_" + baseSample.fullName+"_"+thisRadius
|
||||
|
||||
filename = "1dprofile_cocenter_" + baseSample.fullName+"_"+thisRadius
|
||||
npzfile = np.load(outputDir+"/1dprofile_cocentered_"+plotName+".dat.npz")
|
||||
profileList = npzfile['arr_0']
|
||||
radii = npzfile['arr_1']
|
||||
|
||||
plt.clf()
|
||||
|
||||
plt.xlabel(r"$R/R_{eff}$")
|
||||
#plt.xlabel(r"$R/R_{v,\mathrm{max}}$")
|
||||
plt.ylabel(r"$n / \bar n$")
|
||||
plt.xlim(xmin=0.0, xmax=2.5)
|
||||
plt.ylim(ymin=0.0, ymax=1.7)
|
||||
#plt.xscale('log')
|
||||
|
||||
for (iSample, sample) in enumerate(sampleList):
|
||||
lineTitle = sample.nickName[:-10]
|
||||
if "DM LowDen" in lineTitle or "DM HighDen" in lineTitle: continue
|
||||
|
||||
thisPlotTitle = r"$R_{eff}$ = "+thisRadius+ r" $h^{-1}$Mpc"
|
||||
legendTitle = "Fixed Center Samples"
|
||||
|
||||
thisProfile = profileList[iSample]
|
||||
if np.all(thisProfile == 0.): continue
|
||||
|
||||
rV = (stack.rMin + stack.rMax)/2.
|
||||
|
||||
if len(radii) > 0:
|
||||
scaledRadii = radii/rV
|
||||
plt.plot(scaledRadii, thisProfile, label=lineTitle,
|
||||
color=colorList[iSample],
|
||||
linewidth=linewidth)
|
||||
|
||||
if doTheory:
|
||||
nBins = len(scaledRadii)/2
|
||||
try:
|
||||
popt, pcov = curve_fit(PadillaProfile, scaledRadii[0:nBins],
|
||||
thisProfile[0:nBins], maxfev=10000, xtol=5.e-3)
|
||||
except RuntimeError:
|
||||
print "Warning: no convergence reached"
|
||||
|
||||
label = r"A1=%.2f, A2=%.2f, $\alpha$=%.2f" % (popt[0], popt[1], popt[2])
|
||||
rho = PadillaProfile(scaledRadii, popt[0], popt[1], popt[2])
|
||||
plt.plot(scaledRadii, rho, '--', label=label,
|
||||
color=colorList[iSample], linewidth=2)
|
||||
|
||||
|
||||
plt.title(thisPlotTitle + " (center from " + plotTitle + ")", fontsize=18)
|
||||
plt.legend(title = legendTitle, loc = "lower right", prop={'size':16})
|
||||
|
||||
plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
|
||||
|
||||
if (showPlot):
|
||||
os.system("display %s" % figDir+"/fig_"+plotName+".png")
|
||||
|
||||
return
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
|
||||
filename = args.parm
|
||||
print " Loading parameters from", filename
|
||||
if not os.access(filename, os.F_OK):
|
||||
print " Cannot find parameter file %s!" % filename
|
||||
exit(-1)
|
||||
parms = imp.load_source("name", filename)
|
||||
globals().update(vars(parms))
|
||||
|
||||
if not os.access(outputDir, os.F_OK):
|
||||
os.makedirs(outputDir)
|
||||
|
||||
if not os.access(logDir, os.F_OK):
|
||||
os.makedirs(logDir)
|
||||
|
||||
if not os.access(figDir, os.F_OK):
|
||||
os.makedirs(figDir)
|
||||
|
||||
# get list of base voids
|
||||
with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
|
||||
baseSample = pickle.load(input)
|
||||
baseSampleName = baseSample.fullName
|
||||
baseVoidList = np.loadtxt(workDir+baseSampleDir+"/centers_central_"+\
|
||||
baseSampleName+".out")
|
||||
|
||||
sampleList = []
|
||||
for sampleDir in sampleDirList:
|
||||
if compareSampleTag in sampleDir: continue
|
||||
with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
|
||||
sampleList.append(pickle.load(input))
|
||||
|
||||
sampleDirList.insert(0,baseSampleDir)
|
||||
sampleList.insert(0,baseSample)
|
||||
|
||||
# pick our void sample
|
||||
for stack in baseSample.stacks:
|
||||
print " Stack:", stack.rMin, "-", stack.rMax
|
||||
|
||||
# plot these profiles
|
||||
print " Plotting..."
|
||||
sys.stdout.flush()
|
||||
plotProfiles(baseSample, stack, sampleList,
|
||||
figDir, args.showPlot, outputDir, doTheory)
|
||||
|
||||
print " Done!"
|
||||
|
||||
|
|
@ -1,404 +0,0 @@
|
|||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotDenMaps.py
|
||||
# Copyright (C) 2010-2014 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2014 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
#!/usr/bin/env python
|
||||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./pipeline/apAnalysis.py
|
||||
# Copyright (C) 2010-2013 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2013 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
|
||||
# takes nVoids evenly distributed, plots a slice of the local density and
|
||||
# overlays the voids
|
||||
|
||||
import imp
|
||||
import pickle
|
||||
import os
|
||||
import numpy as np
|
||||
import argparse
|
||||
import matplotlib
|
||||
matplotlib.use('Agg')
|
||||
import matplotlib.pyplot as plt
|
||||
from void_python_tools.backend import *
|
||||
import void_python_tools.xcor as xcor
|
||||
from netCDF4 import Dataset
|
||||
#import pylab as plt
|
||||
|
||||
NetCDFFile = Dataset
|
||||
ncFloat = 'f8'
|
||||
|
||||
matplotlib.rcParams.update({'font.size': 16})
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
mergerNameBase = "voidOverlap"
|
||||
|
||||
parser = argparse.ArgumentParser(description='Analyze.')
|
||||
parser.add_argument('--parm', dest='parm', default='datasetsToAnalyze.py', help='path to parameter file')
|
||||
parser.add_argument('--show', dest='showPlot', action='store_const',
|
||||
const=True, default=False,
|
||||
help='display the plot (default: just write eps)')
|
||||
args = parser.parse_args()
|
||||
|
||||
nVoids = 10
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
# plot a slice of the density around the void in baseIDList,
|
||||
# with any voids in the slice shown and any voids in baseIDList flagged
|
||||
def plotVoidAndDen(idList, voidList, partData, boxLen, figDir,
|
||||
sliceCenter=None, sliceWidth=200,
|
||||
baseIDList=None, baseRadius=0, nickName=None,
|
||||
baseNickName=None,
|
||||
baseIndex=0,
|
||||
periodic=None, showPlot=False, plotName=None):
|
||||
|
||||
if len(voidList) <= 1: return
|
||||
plt.clf()
|
||||
|
||||
#sliceWidth = 220
|
||||
sliceWidth = max(220, sliceWidth)
|
||||
|
||||
# make an appropriate box
|
||||
xwidth = sliceWidth
|
||||
ywidth = sliceWidth
|
||||
zwidth = sliceWidth/4.
|
||||
#zwidth = max(sliceWidth/4., 50)
|
||||
|
||||
# get mean density
|
||||
part = 1.*partData
|
||||
totalNumPart = len(part)
|
||||
totalVol = (part[:,0].max() - part[:,0].min()) * \
|
||||
(part[:,1].max() - part[:,1].min()) * \
|
||||
(part[:,2].max() - part[:,2].min())
|
||||
|
||||
meanDen = totalNumPart/totalVol
|
||||
|
||||
# single out the matched void
|
||||
keepVoid = []
|
||||
if len(np.atleast_1d(idList)) > 0:
|
||||
keepVoid = voidList[voidList[:,7] == idList]
|
||||
if len(np.shape(keepVoid)) > 1: keepVoid = keepVoid[0,:]
|
||||
filter = voidList[:,7] != idList
|
||||
voidList = voidList[filter,:]
|
||||
|
||||
# convert everything to relative coordinates
|
||||
part[:,0] -= sliceCenter[0]
|
||||
part[:,1] -= sliceCenter[1]
|
||||
part[:,2] -= sliceCenter[2]
|
||||
|
||||
shiftUs = np.abs(part[:,0]) > boxLen[0]/2.
|
||||
if ("x" in periodicLine): part[shiftUs,0] -= \
|
||||
np.copysign(boxLen[0],part[shiftUs,0])
|
||||
shiftUs = np.abs(part[:,1]) > boxLen[1]/2.
|
||||
if ("y" in periodicLine): part[shiftUs,1] -= \
|
||||
np.copysign(boxLen[1],part[shiftUs,1])
|
||||
shiftUs = np.abs(part[:,2]) > boxLen[2]/2.
|
||||
if ("z" in periodicLine): part[shiftUs,2] -= \
|
||||
np.copysign(boxLen[2],part[shiftUs,2])
|
||||
|
||||
voidList = np.atleast_2d(voidList)
|
||||
np.atleast_2d(voidList)[:,0] -= sliceCenter[0]
|
||||
np.atleast_2d(voidList)[:,1] -= sliceCenter[1]
|
||||
np.atleast_2d(voidList)[:,2] -= sliceCenter[2]
|
||||
|
||||
shiftUs = np.abs(voidList[:,0]) > boxLen[0]/2.
|
||||
if ("x" in periodicLine):
|
||||
voidList[shiftUs,0] -= \
|
||||
np.copysign(boxLen[0],voidList[shiftUs,0])
|
||||
shiftUs = np.abs(voidList[:,1]) > boxLen[1]/2.
|
||||
if ("y" in periodicLine): voidList[shiftUs,1] -= \
|
||||
np.copysign(boxLen[1],voidList[shiftUs,1])
|
||||
shiftUs = np.abs(voidList[:,2]) > boxLen[2]/2.
|
||||
if ("z" in periodicLine): voidList[shiftUs,2] -= \
|
||||
np.copysign(boxLen[2],voidList[shiftUs,2])
|
||||
|
||||
if len(np.atleast_1d(keepVoid)) >= 1:
|
||||
keepVoid[0] -= sliceCenter[0]
|
||||
keepVoid[1] -= sliceCenter[1]
|
||||
keepVoid[2] -= sliceCenter[2]
|
||||
shiftUs = np.abs(keepVoid[0]) > boxLen[0]/2.
|
||||
if ("x" in periodicLine) and shiftUs: keepVoid[0] -= \
|
||||
np.copysign(boxLen[0],keepVoid[0])
|
||||
shiftUs = np.abs(keepVoid[1]) > boxLen[1]/2.
|
||||
if ("y" in periodicLine) and shiftUs: keepVoid[1] -= \
|
||||
np.copysign(boxLen[1],keepVoid[1])
|
||||
shiftUs = np.abs(keepVoid[2]) > boxLen[2]/2.
|
||||
if ("z" in periodicLine) and shiftUs: keepVoid[2] -= \
|
||||
np.copysign(boxLen[2],keepVoid[2])
|
||||
|
||||
xmin = -xwidth/2.
|
||||
xmax = xwidth/2.
|
||||
ymin = -ywidth/2.
|
||||
ymax = ywidth/2.
|
||||
zmin = -zwidth/2.
|
||||
zmax = zwidth/2.
|
||||
|
||||
# pull out voids that were potential matches
|
||||
filter = np.sqrt(voidList[:,0]**2 + voidList[:,1]**2 + voidList[:,2]**2) <=\
|
||||
baseRadius*1.5
|
||||
potentialMatches = voidList[filter]
|
||||
|
||||
# get centers and radii of any other voids in slice
|
||||
zminVoid = -zwidth/16.
|
||||
zmaxVoid = zwidth/16.
|
||||
|
||||
filter = (voidList[:,0] > xmin) & (voidList[:,0] < xmax) & \
|
||||
(voidList[:,1] > ymin) & (voidList[:,1] < ymax) & \
|
||||
(voidList[:,2] > zminVoid) & (voidList[:,2] < zmaxVoid)
|
||||
voidList = voidList[filter,:]
|
||||
|
||||
# slice particles
|
||||
filter = (part[:,0] > xmin) & (part[:,0] < xmax) & \
|
||||
(part[:,1] > ymin) & (part[:,1] < ymax) & \
|
||||
(part[:,2] > zmin) & (part[:,2] < zmax)
|
||||
part = part[filter]
|
||||
|
||||
# plot density
|
||||
extent = [xmin, xmax, ymin, ymax]
|
||||
hist, xedges, yedges = np.histogram2d(part[:,0], part[:,1], normed=False,
|
||||
bins=64)
|
||||
|
||||
#hist /= meanDen
|
||||
hist = np.log10(hist+1)
|
||||
plt.imshow(hist,
|
||||
aspect='equal',
|
||||
extent=extent,
|
||||
interpolation='gaussian',
|
||||
cmap='YlGnBu_r')
|
||||
#plt.colorbar()
|
||||
|
||||
# overlay voids as circles
|
||||
fig = plt.gcf()
|
||||
ax = fig.add_subplot(1,1,1)
|
||||
|
||||
# the original void
|
||||
circle = plt.Circle((0,0), baseRadius,
|
||||
edgecolor='orange', facecolor=None, fill=False,
|
||||
linewidth=5)
|
||||
fig.gca().add_artist(circle)
|
||||
|
||||
# our matched void
|
||||
if len(np.atleast_1d(keepVoid)) > 0:
|
||||
if idList == baseIDList:
|
||||
edgecolor = 'orange'
|
||||
else:
|
||||
edgecolor = 'red'
|
||||
|
||||
circle = plt.Circle((keepVoid[0], keepVoid[1]), keepVoid[4],
|
||||
edgecolor=edgecolor, facecolor=None, fill=False,
|
||||
linewidth=5)
|
||||
fig.gca().add_artist(circle)
|
||||
|
||||
# other voids in the slice
|
||||
for void in voidList:
|
||||
if np.any(void[7] == idList):
|
||||
continue
|
||||
else:
|
||||
color = 'white'
|
||||
circle = plt.Circle((void[0], void[1]), void[4],
|
||||
edgecolor=color, facecolor=None, fill=False,
|
||||
linewidth=5)
|
||||
fig.gca().add_artist(circle)
|
||||
|
||||
# potential match voids
|
||||
#for void in potentialMatches:
|
||||
# if np.any(void[7] == idList):
|
||||
# continue
|
||||
# else:
|
||||
# color = 'green'
|
||||
# circle = plt.Circle((void[0], void[1]), void[4],
|
||||
# edgecolor=color, facecolor=None, fill=False,
|
||||
# linewidth=5)
|
||||
# fig.gca().add_artist(circle)
|
||||
|
||||
baseNickName = baseNickName[:-10].lstrip()
|
||||
nickName = nickName[:-10].lstrip()
|
||||
if idList == baseIDList:
|
||||
title = "%d $h^{-1}$Mpc" % int(baseRadius)
|
||||
title += " (" + baseNickName + ")"
|
||||
else:
|
||||
title = r"$\rightarrow$ "
|
||||
if len(np.atleast_1d(keepVoid)) > 0:
|
||||
title += "%d $h^{-1}$Mpc" % int(keepVoid[4]) + " (" + nickName + ")"
|
||||
else:
|
||||
title += "No match"
|
||||
|
||||
#title += "(" + str(int(baseIDList)) + ")"
|
||||
|
||||
plt.title(title, fontsize=20)
|
||||
#plt.xlabel("x [$h^{-1}$Mpc]", fontsize=14)
|
||||
#plt.ylabel("y [$h^{-1}$Mpc]", fontsize=14)
|
||||
|
||||
plotName += "_" + str(int(baseIndex))
|
||||
#plotName += "_" + str(int(baseRadius))
|
||||
plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
|
||||
|
||||
if showPlot: os.system("display %s" % figDir+"/fig_"+plotName+".png")
|
||||
|
||||
return
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
|
||||
filename = args.parm
|
||||
print " Loading parameters from", filename
|
||||
if not os.access(filename, os.F_OK):
|
||||
print " Cannot find parameter file %s!" % filename
|
||||
exit(-1)
|
||||
parms = imp.load_source("name", filename)
|
||||
globals().update(vars(parms))
|
||||
|
||||
if not os.access(outputDir, os.F_OK):
|
||||
os.makedirs(outputDir)
|
||||
|
||||
if not os.access(logDir, os.F_OK):
|
||||
os.makedirs(logDir)
|
||||
|
||||
if not os.access(figDir, os.F_OK):
|
||||
os.makedirs(figDir)
|
||||
|
||||
mergerFileBase = outputDir + "/" + mergerNameBase
|
||||
|
||||
# get list of base voids
|
||||
with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
|
||||
baseSample = pickle.load(input)
|
||||
baseSampleName = baseSample.fullName
|
||||
baseVoidList = np.loadtxt(workDir+baseSampleDir+"/centers_central_"+\
|
||||
baseSampleName+".out")
|
||||
|
||||
# sort by size
|
||||
radii = baseVoidList[:,4]
|
||||
indices = np.argsort(radii)[::-1]
|
||||
baseVoidList = baseVoidList[indices,:]
|
||||
setName = baseSampleDir.split('/')[0]
|
||||
|
||||
# pick our void sample
|
||||
bigVoidList = baseVoidList[0:10,:]
|
||||
stride = len(baseVoidList)/nVoids
|
||||
baseVoidList = baseVoidList[::stride]
|
||||
baseVoidList = np.vstack((bigVoidList,baseVoidList))
|
||||
|
||||
sampleDirList.insert(0,baseSampleDir)
|
||||
|
||||
for (iSample, sampleDir) in enumerate(sampleDirList):
|
||||
if compareSampleTag in sampleDir: continue
|
||||
with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
|
||||
sample = pickle.load(input)
|
||||
print " Working with", sample.fullName, "..."
|
||||
sys.stdout.flush()
|
||||
sampleName = sample.fullName
|
||||
|
||||
print " Loading particle data..."
|
||||
sys.stdout.flush()
|
||||
|
||||
|
||||
infoFile = workDir+"/"+sampleDir+"/zobov_slice_"+sample.fullName+".par"
|
||||
File = NetCDFFile(infoFile, 'r')
|
||||
ranges = np.zeros((3,2))
|
||||
ranges[0][0] = getattr(File, 'range_x_min')
|
||||
ranges[0][1] = getattr(File, 'range_x_max')
|
||||
ranges[1][0] = getattr(File, 'range_y_min')
|
||||
ranges[1][1] = getattr(File, 'range_y_max')
|
||||
ranges[2][0] = getattr(File, 'range_z_min')
|
||||
ranges[2][1] = getattr(File, 'range_z_max')
|
||||
File.close()
|
||||
mul = np.zeros((3))
|
||||
mul[:] = ranges[:,1] - ranges[:,0]
|
||||
boxLen = mul
|
||||
|
||||
partFile = workDir+"/"+sampleDir+"/zobov_slice_"+sample.fullName
|
||||
#partFile = catalogDir+"/"+sample.dataFile
|
||||
iLine = 0
|
||||
partData = []
|
||||
part = np.zeros((3))
|
||||
File = file(partFile)
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
Np = np.fromfile(File, dtype=np.int32,count=1)
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
x = np.fromfile(File, dtype=np.float32,count=Np)
|
||||
x *= mul[0]
|
||||
x += ranges[0][0]
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
y = np.fromfile(File, dtype=np.float32,count=Np)
|
||||
y *= mul[1]
|
||||
y += ranges[1][0]
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
z = np.fromfile(File, dtype=np.float32,count=Np)
|
||||
z *= mul[2]
|
||||
z += ranges[2][0]
|
||||
chk = np.fromfile(File, dtype=np.int32,count=1)
|
||||
File.close()
|
||||
partData = np.column_stack((x,y,z))#.transpose()
|
||||
|
||||
for (iBaseVoid,baseVoid) in enumerate(baseVoidList):
|
||||
print " Void:", int(baseVoid[7]), "(", int(baseVoid[4]), ")"
|
||||
baseIDList = baseVoid[7]
|
||||
sliceCenter = baseVoid[0:3]
|
||||
sliceWidth = baseVoid[4]*4
|
||||
|
||||
# get matched void
|
||||
idList = []
|
||||
if sample.fullName == baseSample.fullName:
|
||||
idList = baseIDList
|
||||
else:
|
||||
matchFile=mergerFileBase+"_"+baseSampleName+"_"+sampleName+"_summary.out"
|
||||
if os.access(matchFile, os.F_OK):
|
||||
matchList = np.loadtxt(matchFile)
|
||||
for i,testID in enumerate(matchList[:,0]):
|
||||
if testID == baseIDList:
|
||||
if (matchList[i,8] > 0): idList.append(matchList[i,8])
|
||||
idList = np.array(idList)
|
||||
idList = idList.astype(int)
|
||||
|
||||
voidList = np.loadtxt(workDir+sampleDir+"/trimmed_nodencut_centers_central_"+\
|
||||
sampleName+".out")
|
||||
|
||||
periodicLine = getPeriodic(sample)
|
||||
plotVoidAndDen(idList, voidList, partData, boxLen, figDir,
|
||||
sliceCenter=sliceCenter, sliceWidth=sliceWidth,
|
||||
baseIDList=baseIDList, baseRadius=baseVoid[4],
|
||||
baseIndex=iBaseVoid,
|
||||
nickName=sample.nickName, periodic=periodicLine,
|
||||
baseNickName=baseSample.nickName,
|
||||
showPlot=args.showPlot,
|
||||
plotName="denmap_"+setName+"_"+baseSampleName+"_"+sampleName)
|
||||
print " Done!"
|
||||
|
||||
|
|
@ -1,154 +0,0 @@
|
|||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotMatchEllipRatio.py
|
||||
# Copyright (C) 2010-2014 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2014 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
#!/usr/bin/env python
|
||||
|
||||
# plots cumulative distributions of number counts
|
||||
|
||||
import matplotlib
|
||||
matplotlib.use('Agg')
|
||||
from void_python_tools.backend import *
|
||||
from void_python_tools.plotting import *
|
||||
import void_python_tools.apTools as vp
|
||||
import imp
|
||||
import pickle
|
||||
import os
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import argparse
|
||||
from globalOptions import *
|
||||
|
||||
# plots the ratio of ellipticities for matched voids
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
parser = argparse.ArgumentParser(description='Plot.')
|
||||
parser.add_argument('--show', dest='showPlot', action='store_const',
|
||||
const=True, default=False,
|
||||
help='display the plot (default: just write eps)')
|
||||
parser.add_argument('--parm', dest='parm', default='datasetsToPlot.py',
|
||||
help='path to parameter file')
|
||||
args = parser.parse_args()
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
print "Plotting ellipticity ratio"
|
||||
|
||||
filename = args.parm
|
||||
print " Loading parameters from", filename
|
||||
if not os.access(filename, os.F_OK):
|
||||
print " Cannot find parameter file %s!" % filename
|
||||
exit(-1)
|
||||
parms = imp.load_source("name", filename)
|
||||
globals().update(vars(parms))
|
||||
|
||||
if not os.access(figDir, os.F_OK):
|
||||
os.makedirs(figDir)
|
||||
|
||||
dataSampleList = []
|
||||
compareSampleList = []
|
||||
|
||||
with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
|
||||
baseSample = pickle.load(input)
|
||||
|
||||
for sampleDir in sampleDirList:
|
||||
with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
|
||||
thisSample = pickle.load(input)
|
||||
if compareSampleTag in thisSample.fullName:
|
||||
compareSampleList.append(thisSample)
|
||||
else:
|
||||
dataSampleList.append(thisSample)
|
||||
|
||||
|
||||
plt.clf()
|
||||
|
||||
numSubPlots = len(dataSampleList)
|
||||
fig, axesList = plt.subplots(numSubPlots, sharex=True, sharey=True)
|
||||
axesList = np.atleast_1d(axesList)
|
||||
|
||||
for (iSample,sample) in enumerate(dataSampleList):
|
||||
|
||||
if sample.fullName == baseSample.fullName: continue
|
||||
|
||||
sampleName = sample.fullName
|
||||
lineTitle = sample.nickName[:-10]
|
||||
|
||||
# plt.xlabel("Void Radius [Mpc/h]")
|
||||
# plt.ylabel(r"1st Progenitor Relative Ellipticity")
|
||||
#plt.yscale('log')
|
||||
# plt.xlim(xmax=rMax)
|
||||
plt.xlim(rMin, rMax)
|
||||
|
||||
plotNameBase = "matchrelellip"
|
||||
plotName = plotNameBase + "_" + plotLabel# + "_" + sampleName
|
||||
|
||||
|
||||
filename = outputDir+"/voidOverlap_"+baseSample.fullName+"_"+sampleName+"_summary.out"
|
||||
if not os.access(filename, os.F_OK):
|
||||
print "File not found: ", filename
|
||||
continue
|
||||
|
||||
data = np.loadtxt(filename, comments="#")
|
||||
if data.ndim == 1:
|
||||
print " Too few!"
|
||||
continue
|
||||
|
||||
# find a sample to compare it to
|
||||
for compareSample in compareSampleList:
|
||||
if compareSample.nickName[:10] == sample.nickName[:10]:
|
||||
filename = outputDir+"/voidOverlap_"+baseSample.fullName+"_"+compareSample.fullName+"_summary.out"
|
||||
compareData = np.loadtxt(filename, comments="#")
|
||||
axesList[iSample].scatter(compareData[:,1], compareData[:,10],
|
||||
color='blue', alpha=alpha, s=pointsize)
|
||||
|
||||
#plt.scatter(data[:,1], data[:,10],
|
||||
# label=lineTitle, color=colorList[iSample])
|
||||
|
||||
axesList[iSample].scatter(data[:,1], data[:,10],
|
||||
label=lineTitle, color='red', alpha=alpha, s=pointsize)
|
||||
axesList[iSample].legend(loc = "upper left", prop={'size':10})
|
||||
|
||||
plt.ylim(0., 4.0)
|
||||
yticks = axesList[iSample].yaxis.get_major_ticks()
|
||||
yticks[-1].label1.set_visible(False)
|
||||
yticks[0].label1.set_visible(False)
|
||||
|
||||
#axesList[iSample].set_xlim([20,rMax])
|
||||
|
||||
fig.subplots_adjust(hspace=0)
|
||||
|
||||
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
|
||||
|
||||
axesList[0].set_title(plotTitle, fontsize=14)
|
||||
#axesList[0].set_title("Match ellipticity ratio - "+plotTitle)
|
||||
fig.text(0.5, 0.04, r'$R_{eff}$ [$h^{-1}$Mpc]', ha='center', va='center', fontsize=14)
|
||||
fig.text(0.06, 0.5, 'Match Ellipticity Ratio', ha='center', va='center', rotation='vertical', fontsize=14)
|
||||
|
||||
|
||||
#plt.legend(title = "Samples", loc = "upper left", prop={'size':8})
|
||||
#plt.title("Match ellipticity ratio - "+plotTitle+" - "+sample.nickName)
|
||||
|
||||
plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
|
||||
|
||||
if args.showPlot:
|
||||
os.system("display %s" % figDir+"/fig_"+plotName+".png")
|
||||
|
||||
|
||||
|
|
@ -1,163 +0,0 @@
|
|||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotMatchSizeRatio.py
|
||||
# Copyright (C) 2010-2014 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2014 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
#!/usr/bin/env python
|
||||
|
||||
# plots cumulative distributions of number counts
|
||||
|
||||
import matplotlib
|
||||
matplotlib.use('Agg')
|
||||
from void_python_tools.backend import *
|
||||
from void_python_tools.plotting import *
|
||||
import void_python_tools.apTools as vp
|
||||
import imp
|
||||
import pickle
|
||||
import os
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import argparse
|
||||
from globalOptions import *
|
||||
from scipy.optimize import curve_fit
|
||||
|
||||
# plots the ratio of sizes for matched voids
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
parser = argparse.ArgumentParser(description='Plot.')
|
||||
parser.add_argument('--show', dest='showPlot', action='store_const',
|
||||
const=True, default=False,
|
||||
help='display the plot (default: just write eps)')
|
||||
parser.add_argument('--parm', dest='parm', default='datasetsToPlot.py',
|
||||
help='path to parameter file')
|
||||
args = parser.parse_args()
|
||||
|
||||
# -----------------------------------------------------------------------------
|
||||
def Linear(x, a, b):
|
||||
return a*x+b
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
print "Plotting match size ratio"
|
||||
|
||||
filename = args.parm
|
||||
print " Loading parameters from", filename
|
||||
if not os.access(filename, os.F_OK):
|
||||
print " Cannot find parameter file %s!" % filename
|
||||
exit(-1)
|
||||
parms = imp.load_source("name", filename)
|
||||
globals().update(vars(parms))
|
||||
|
||||
if not os.access(figDir, os.F_OK):
|
||||
os.makedirs(figDir)
|
||||
|
||||
dataSampleList = []
|
||||
compareSampleList = []
|
||||
|
||||
with open(workDir+baseSampleDir+"/sample_info.dat", 'rb') as input:
|
||||
baseSample = pickle.load(input)
|
||||
|
||||
for sampleDir in sampleDirList:
|
||||
with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
|
||||
thisSample = pickle.load(input)
|
||||
if compareSampleTag in thisSample.fullName:
|
||||
compareSampleList.append(thisSample)
|
||||
else:
|
||||
dataSampleList.append(thisSample)
|
||||
|
||||
plt.clf()
|
||||
#plt.yscale('log')
|
||||
|
||||
numSubPlots = len(dataSampleList)
|
||||
fig, axesList = plt.subplots(numSubPlots, sharex=True, sharey=True)
|
||||
axesList = np.atleast_1d(axesList)
|
||||
|
||||
for (iSample,sample) in enumerate(dataSampleList):
|
||||
|
||||
if sample.fullName == baseSample.fullName: continue
|
||||
|
||||
sampleName = sample.fullName
|
||||
lineTitle = sample.nickName[:-10]
|
||||
|
||||
plotNameBase = "matchvolrelradius"
|
||||
plotName = plotNameBase + "_" + plotLabel# + "_" + sampleName
|
||||
|
||||
filename = outputDir+"/voidOverlap_"+baseSample.fullName+"_"+sampleName+"_summary.out"
|
||||
if not os.access(filename, os.F_OK):
|
||||
print "File not found: ", filename
|
||||
continue
|
||||
|
||||
data = np.loadtxt(filename, comments="#")
|
||||
if data.ndim == 1:
|
||||
print " Too few!"
|
||||
continue
|
||||
|
||||
# find a sample to compare it to
|
||||
for compareSample in compareSampleList:
|
||||
if compareSample.nickName[:10] == sample.nickName[:10]:
|
||||
filename = outputDir+"/voidOverlap_"+baseSample.fullName+"_"+compareSample.fullName+"_summary.out"
|
||||
compareData = np.loadtxt(filename, comments="#")
|
||||
axesList[iSample].scatter(compareData[:,1], compareData[:,2],
|
||||
color='blue', alpha=alpha, s=pointsize)
|
||||
|
||||
axesList[iSample].scatter(data[:,1], data[:,2],
|
||||
label=lineTitle, color='red', alpha=alpha, s=pointsize)
|
||||
|
||||
try:
|
||||
popt, pcov = curve_fit(Linear, data[:,1],
|
||||
data[:,2], maxfev=10000, xtol=5.e-3)
|
||||
except RuntimeError:
|
||||
print "Warning: no convergence reached"
|
||||
|
||||
label = r"$a$=%.2f, $b$=%.2f" % (popt[0], popt[1])
|
||||
radii = np.arange(rMin, rMax, 1)
|
||||
relRad = Linear(radii, popt[0], popt[1])
|
||||
#axesList[iSample].plot(radii, relRad, '-', label=label,
|
||||
# color='black', linewidth=2)
|
||||
|
||||
axesList[iSample].legend(loc = "best", fancybox=True,prop={'size':10})
|
||||
|
||||
plt.ylim(0., 2.5)
|
||||
|
||||
yticks = axesList[iSample].yaxis.get_major_ticks()
|
||||
yticks[-1].label1.set_visible(False)
|
||||
yticks[0].label1.set_visible(False)
|
||||
|
||||
axesList[iSample].set_xlim([rMin,rMax])
|
||||
|
||||
|
||||
fig.subplots_adjust(hspace=0)
|
||||
|
||||
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
|
||||
|
||||
axesList[0].set_title(plotTitle, fontsize=14)
|
||||
#axesList[0].set_title("Match size ratio - "+plotTitle)
|
||||
fig.text(0.5, 0.04, r'$R_{eff}$ [$h^{-1}$Mpc]', ha='center', va='center', fontsize=14)
|
||||
fig.text(0.06, 0.5, 'Match Relative Radius', ha='center', va='center', rotation='vertical', fontsize=14)
|
||||
|
||||
#plt.legend(title = "Samples", loc = "upper left", prop={'size':8})
|
||||
#plt.title("Match size ratio - "+plotTitle+" - "+sample.nickName)
|
||||
|
||||
plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
|
||||
|
||||
if args.showPlot:
|
||||
os.system("display %s" % figDir+"/fig_"+plotName+".png")
|
||||
|
||||
|
||||
|
|
@ -1,305 +0,0 @@
|
|||
#+
|
||||
# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotNumberFunc.py
|
||||
# Copyright (C) 2010-2014 Guilhem Lavaux
|
||||
# Copyright (C) 2011-2014 P. M. Sutter
|
||||
#
|
||||
# This program is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation; version 2 of the License.
|
||||
#
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License along
|
||||
# with this program; if not, write to the Free Software Foundation, Inc.,
|
||||
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
||||
#+
|
||||
#!/usr/bin/env python
|
||||
|
||||
# plots cumulative distributions of number counts
|
||||
|
||||
import matplotlib
|
||||
matplotlib.use('Agg')
|
||||
from void_python_tools.backend import *
|
||||
from void_python_tools.plotting import *
|
||||
import void_python_tools.apTools as vp
|
||||
import imp
|
||||
import pickle
|
||||
import os
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import argparse
|
||||
import svdw
|
||||
from scipy.optimize import curve_fit
|
||||
from scipy.interpolate import interp1d
|
||||
from globalOptions import *
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
histBinWidth = 1 # Mpc
|
||||
|
||||
parser = argparse.ArgumentParser(description='Plot.')
|
||||
parser.add_argument('--show', dest='showPlot', action='store_const',
|
||||
const=True, default=False,
|
||||
help='display the plot (default: just write eps)')
|
||||
parser.add_argument('--binned', dest='binned', action='store_const',
|
||||
const=True, default=False,
|
||||
help='plot binned function (default: cumulative)')
|
||||
parser.add_argument('--parm', dest='parm', default='datasetsToPlot.py',
|
||||
help='path to parameter file')
|
||||
parser.add_argument('--xmax', dest='xmax', default=120.,
|
||||
help='x limit of plot')
|
||||
parser.add_argument('--xmin', dest='xmin', default=20.,
|
||||
help='x limit of plot')
|
||||
args = parser.parse_args()
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
def svdwFunc(r, scaleFactor):
|
||||
radius, cumu_ps = svdw.getSvdW(.01, 100, 100, scaleFactor=scaleFactor)
|
||||
cumu_ps += 0.1
|
||||
cumu_ps = np.log10(cumu_ps)
|
||||
interped = interp1d(radius, cumu_ps)
|
||||
interpVal = interped(r)
|
||||
interpVal[interpVal<1.0] = 1.0
|
||||
#print "HELLO", r, interpVal
|
||||
return interpVal
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
|
||||
def loadData(sampleDir, dataPortion, treePortion='all'):
|
||||
with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
|
||||
sample = pickle.load(input)
|
||||
|
||||
filename = workDir+"/"+sampleDir+"/centers_"+dataPortion+"_"+sample.fullName+".out"
|
||||
if not os.access(filename, os.F_OK):
|
||||
print "File not found: ", filename
|
||||
return -1, -1, -1
|
||||
|
||||
data = np.loadtxt(filename, comments="#")
|
||||
if data.ndim == 1:
|
||||
print " Too few!"
|
||||
return -1, -1, -1
|
||||
|
||||
if treePortion == "parents":
|
||||
filter = data[:,10] == -1
|
||||
data = data[filter]
|
||||
elif treePortion == "children":
|
||||
filter = data[:,10] != -1
|
||||
data = data[filter]
|
||||
|
||||
data = data[:,4]
|
||||
indices = np.arange(0, len(data), 1)
|
||||
sorted = np.sort(data)
|
||||
|
||||
|
||||
if sample.dataType == "observation":
|
||||
boxVol = vp.getSurveyProps(sample.maskFile,
|
||||
sample.zBoundary[0], sample.zBoundary[1],
|
||||
sample.zRange[0], sample.zRange[1], "all",
|
||||
selectionFuncFile=None)[0]
|
||||
#selectionFuncFile=sample.selFunFile)[0]
|
||||
boxVol *= obsFudgeFactor
|
||||
else:
|
||||
boxVol = sample.boxLen*sample.boxLen*(sample.zBoundaryMpc[1] -
|
||||
sample.zBoundaryMpc[0])
|
||||
|
||||
boxVol *= 1.e-9 # Mpc->Gpc
|
||||
|
||||
indices /= boxVol
|
||||
|
||||
#xmin = sorted[0]
|
||||
#xmax = sorted[-1]
|
||||
#bins = int((xmax-xmin)/histBinWidth)
|
||||
bins = args.xmax/histBinWidth
|
||||
hist, binEdges = np.histogram(sorted, bins=bins, range=(0., args.xmax))
|
||||
#hist, binEdges = np.histogram(sorted, bins=bins, range=(xmin,xmax))
|
||||
binCenters = 0.5*(binEdges[1:] + binEdges[:-1])
|
||||
|
||||
if not args.binned:
|
||||
foundStart = False
|
||||
for iBin in xrange(len(hist)):
|
||||
if not foundStart and hist[iBin] == 0:
|
||||
continue
|
||||
foundStart = True
|
||||
hist[iBin] = np.sum(hist[iBin:])
|
||||
|
||||
hist /= boxVol
|
||||
|
||||
hist = np.log10(hist)
|
||||
|
||||
lineTitle = sample.nickName[:-10]
|
||||
|
||||
return hist, binCenters, lineTitle
|
||||
|
||||
def fill_between(x, y1, y2=0, ax=None, **kwargs):
|
||||
"""Plot filled region between `y1` and `y2`.
|
||||
|
||||
This function works exactly the same as matplotlib's fill_between, except
|
||||
that it also plots a proxy artist (specifically, a rectangle of 0 size)
|
||||
so that it can be added it appears on a legend.
|
||||
"""
|
||||
ax = ax if ax is not None else plt.gca()
|
||||
ax.fill_between(x, y1, y2, interpolate=True, **kwargs)
|
||||
p = plt.Rectangle((0, 0), 0, 0, **kwargs)
|
||||
ax.add_patch(p)
|
||||
|
||||
# ------------------------------------------------------------------------------
|
||||
|
||||
print "Plotting number function"
|
||||
|
||||
filename = args.parm
|
||||
print " Loading parameters from", filename
|
||||
if not os.access(filename, os.F_OK):
|
||||
print " Cannot find parameter file %s!" % filename
|
||||
exit(-1)
|
||||
parms = imp.load_source("name", filename)
|
||||
globals().update(vars(parms))
|
||||
|
||||
if not os.access(figDir, os.F_OK):
|
||||
os.makedirs(figDir)
|
||||
|
||||
plt.clf()
|
||||
plt.xlabel(r"$R_{eff}$ [$h^{-1}$Mpc]", fontsize=14)
|
||||
plt.ylabel(r"log ($n$ > $R_{eff}$ [$h^3$ Gpc$^{-3}$])", fontsize=14)
|
||||
#plt.yscale('log')
|
||||
plt.xlim(xmin=5.)
|
||||
plt.xlim(xmax=100.)
|
||||
plt.ylim(ymin=1)
|
||||
plt.ylim(ymax=5)
|
||||
|
||||
plotNameBase = "numberfunc"
|
||||
plotName = plotNameBase + "_" + plotLabel
|
||||
|
||||
sampleDirList.append(baseSampleDir)
|
||||
|
||||
for (iSample,sampleDir) in enumerate(sampleDirList):
|
||||
for dataPortion in dataPortions:
|
||||
# get all the data
|
||||
allHist = []
|
||||
if "ZZZZ" in sampleDir:
|
||||
for fileZ in fileList:
|
||||
thisSampleDir = sampleDir.replace("ZZZZ", fileZ)
|
||||
hist, binCenters, lineTitle = loadData(thisSampleDir, dataPortion)
|
||||
if lineTitle == -1: continue
|
||||
allHist.append(hist)
|
||||
|
||||
lineLabel = lineTitle.replace(fileZ, "all")
|
||||
if dataPortion != 'all': lineLabel += ", " + dataPortion
|
||||
|
||||
maxHist = 1.*allHist[-1]
|
||||
minHist = 1.*allHist[-1]
|
||||
for iHist in xrange(len(allHist)-1):
|
||||
maxHist = np.maximum(maxHist, allHist[iHist])
|
||||
minHist = np.minimum(minHist, allHist[iHist])
|
||||
|
||||
trim = (maxHist > 1)
|
||||
minHist = minHist[trim]
|
||||
maxHist = maxHist[trim]
|
||||
binCentersToUse = binCenters[trim]
|
||||
alpha = 0.75
|
||||
if dataPortion == "central":
|
||||
hatch = '//'
|
||||
else:
|
||||
hatch = None
|
||||
fill_between(binCentersToUse, minHist, maxHist,
|
||||
label=lineLabel, color=colorList[iSample],
|
||||
alpha=alpha,
|
||||
hatch=hatch
|
||||
)
|
||||
|
||||
else:
|
||||
|
||||
#treeList = ["children", "parents", "all"]
|
||||
treeList = ["all"]
|
||||
for (iTree,treeItem) in enumerate(treeList):
|
||||
hist, binCenters, lineLabel = loadData(sampleDir, dataPortion, treePortion=treeItem)
|
||||
trim = (hist > 1)
|
||||
hist = hist[trim]
|
||||
binCentersToUse = binCenters[trim]
|
||||
if lineLabel == -1: continue
|
||||
if dataPortion != 'all': lineLabel += ", " + dataPortion
|
||||
|
||||
if treeItem != "all": lineLabel += ", " + treeItem
|
||||
iColor = iSample + iTree
|
||||
|
||||
if dataPortion == "central":
|
||||
lineStyle = '--'
|
||||
else:
|
||||
lineStyle = '-'
|
||||
|
||||
if "DM" in lineLabel: lineColor = colorList[0]
|
||||
if "Halos" in lineLabel: lineColor = colorList[1]
|
||||
if "HOD" in lineLabel: lineColor = colorList[2]
|
||||
|
||||
if "FullDen" in lineLabel:
|
||||
lineColor = colorList[4]
|
||||
lineStyle = '-'
|
||||
linewidth = 5
|
||||
|
||||
if "HighDen" in lineLabel or "HighRes" in lineLabel or \
|
||||
"All" in lineLabel:
|
||||
lineStyle = "-"
|
||||
linewidth = 5
|
||||
if "LowDen" in lineLabel or "LowRes" in lineLabel or \
|
||||
"1.20" in lineLabel:
|
||||
lineStyle = "--"
|
||||
linewidth = 5
|
||||
|
||||
plt.plot(binCentersToUse, hist, lineStyle,
|
||||
label=lineLabel, color=lineColor,
|
||||
linewidth=linewidth)
|
||||
|
||||
#if doTheory and "LowRes" in sampleDir:
|
||||
# popt, pcov = curve_fit(svdwFunc, binCentersToUse, hist, p0=25.)
|
||||
# radius, cumu_ps = svdw.getSvdW(.01, 100, 100, scaleFactor=popt[0])
|
||||
# cumu_ps = np.log10(cumu_ps)
|
||||
# print "HELLO", binCentersToUse, hist, cumu_ps
|
||||
# plt.plot(radius, cumu_ps, color='black', label="SVdW/%g" % popt[0])
|
||||
|
||||
# and now the theoretical curve
|
||||
if doTheory:
|
||||
#radius, cumu_ps = svdw.getSvdW(.01, 100, 100)
|
||||
#cumu_ps = np.log10(cumu_ps)
|
||||
#plt.plot(radius, cumu_ps, color='black', label="SVdW" )
|
||||
|
||||
iLine = 0
|
||||
scaleFactorList = []
|
||||
#scaleFactorList = [10, 5]
|
||||
for scaleFactor in scaleFactorList:
|
||||
#radius, cumu_ps = svdw.getSvdW(.01, 100, 100, scaleFactor=scaleFactor)
|
||||
#cumu_ps = np.log10(cumu_ps)
|
||||
#plt.plot(radius, cumu_ps, lineList[iLine], color='black', label="SVdW/%g" % scaleFactor)
|
||||
iLine += 1
|
||||
|
||||
dvList = [-.07]
|
||||
iLine = 0
|
||||
for dv in dvList:
|
||||
radius, cumu_ps = svdw.getSvdW(.01, 100, 1000, d_v=dv)
|
||||
cumu_ps = np.log10(cumu_ps)
|
||||
plt.plot(radius, cumu_ps, lineList[iLine], color='black', label=r"SVdW $\delta_v$=%g" % dv, linewidth=3)
|
||||
iLine += 1
|
||||
|
||||
dvList = [-.015]
|
||||
for dv in dvList:
|
||||
radius, cumu_ps = svdw.getSvdW(.01, 100, 1000, d_v=dv)
|
||||
#radius, cumu_ps = svdw.getSvdW(.01, 100, 100, d_v=dv)
|
||||
cumu_ps = np.log10(cumu_ps)
|
||||
plt.plot(radius, cumu_ps, lineList[iLine], color='black', label="SVdW $\delta_v$=%g" % dv, linewidth=3)
|
||||
iLine += 1
|
||||
|
||||
plt.legend(loc = "best", fancybox=True, prop={'size':12})
|
||||
#plt.legend(title = "Samples", loc = "upper right", prop={'size':8})
|
||||
#plt.title("Number func - "+plotTitle)
|
||||
|
||||
plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
|
||||
plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
|
||||
|
||||
if args.showPlot:
|
||||
os.system("display %s" % figDir+"/fig_"+plotName+".png")
|
||||
|
||||
|
||||
Loading…
Add table
Add a link
Reference in a new issue