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363 lines
11 KiB
Python
363 lines
11 KiB
Python
#+
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# VIDE -- Void IDentification and Examination -- ./python_tools/void_python_tools/plotting/plotTools.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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__all__=['plotRedshiftDistribution', 'plotSizeDistribution', 'plot1dProfiles',
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'plotMarg1d', 'plotNumberDistribution', 'plotVoidDistribution']
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from void_python_tools.backend.classes import *
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from plotDefs import *
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import numpy as np
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import os
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import pylab as plt
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import void_python_tools.apTools as vp
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import void_python_tools.xcor as xcor
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# -----------------------------------------------------------------------------
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def plotRedshiftDistribution(workDir=None, sampleList=None, figDir=None,
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plotNameBase="zdist",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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plt.clf()
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plt.xlabel("Redshift")
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plt.ylabel("Number of Voids")
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plotTitle = setName
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plotName = plotNameBase
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xMin = 1.e00
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xMax = 0
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for (iSample,sample) in enumerate(sampleList):
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sampleName = sample.fullName
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lineTitle = sampleName
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filename = workDir+"/sample_"+sampleName+"/centers_"+dataPortion+"_"+\
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sampleName+".out"
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if not os.access(filename, os.F_OK):
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print "File not found: ", filename
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continue
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data = np.loadtxt(filename, comments="#")
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if data.ndim == 1:
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print " Too few!"
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continue
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zMin = sample.zRange[0]
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zMax = sample.zRange[1]
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range = (zMin, zMax)
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nbins = np.ceil((zMax-zMin)/0.02)
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thisMax = np.max(data[:,5])
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thisMin = np.min(data[:,5])
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if thisMax > xMax: xMax = thisMax
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if thisMin < xMin: xMin = thisMin
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plt.hist(data[:,5], bins=nbins,
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label=lineTitle, color=colorList[iSample],
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histtype = "step", range=range,
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linewidth=linewidth)
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#plt.legend(title = "Samples", loc = "upper right")
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plt.title(plotTitle)
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plt.xlim(xMin, xMax)
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#plt.xlim(xMin, xMax*1.4) # make room for legend
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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# -----------------------------------------------------------------------------
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def plotSizeDistribution(workDir=None, sampleList=None, figDir=None,
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plotNameBase="sizedist",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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plt.clf()
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plt.xlabel("Void Radius (Mpc/h)")
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plt.ylabel("Number of Voids")
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plotTitle = setName
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plotName = plotNameBase
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xMin = 1.e00
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xMax = 0
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for (iSample,sample) in enumerate(sampleList):
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sampleName = sample.fullName
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lineTitle = sampleName
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filename = workDir+"/sample_"+sampleName+"/centers_"+dataPortion+"_"+\
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sampleName+".out"
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if not os.access(filename, os.F_OK):
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print "File not found: ", filename
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continue
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data = np.loadtxt(filename, comments="#")
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if data.ndim == 1:
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print " Too few!"
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continue
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xMin = 5
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xMax = 140
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range = (xMin, xMax)
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nbins = np.ceil((xMax-xMin)/5)
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#thisMax = np.max(data[:,5])
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#thisMin = np.min(data[:,5])
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#if thisMax > xMax: xMax = thisMax
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#if thisMin < xMin: xMin = thisMin
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plt.hist(data[:,4], bins=nbins,
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label=lineTitle, color=colorList[iSample],
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histtype = "step", range=range,
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linewidth=linewidth)
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plt.legend(title = "Samples", loc = "upper right")
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plt.title(plotTitle)
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plt.xlim(xMin, xMax)
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#plt.xlim(xMin, xMax*1.4) # make room for legend
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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# -----------------------------------------------------------------------------
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def plot1dProfiles(workDir=None, sampleList=None, figDir=None,
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plotNameBase="1dprofile",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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plt.clf()
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plt.xlabel(r"$R/R_{v,\mathrm{max}}$")
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plt.ylabel(r"$n / \bar n$")
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for (iSample,sample) in enumerate(sampleList):
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sampleName = sample.fullName
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for (iStack,stack) in enumerate(sample.stacks):
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plotTitle = setName
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plotName = plotNameBase
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runSuffix = getStackSuffix(stack.zMin, stack.zMax, stack.rMin,
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stack.rMax, dataPortion)
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plotTitle = sampleName + ", z = "+str(stack.zMin)+"-"+str(stack.zMax)+", R = "+str(stack.rMin)+"-"+str(stack.rMax)+ r" $h^{-1}$ Mpc"
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filename = workDir+"/sample_"+sampleName+"/stacks_"+runSuffix+\
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"profile_1d.txt"
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if not os.access(filename, os.F_OK):
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print "File not found: ", filename
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continue
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data = np.loadtxt(filename, comments="#")
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if data.ndim == 1:
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print " Too few!"
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continue
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data[:,1] /= stack.rMax
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plt.ylim(ymin=0.0, ymax=np.amax(data[:,2])+0.1)
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plt.xlim(xmin=0.0, xmax=2.1)
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plt.plot(data[:,1], data[:,2], label=lineTitle, color=colorList[0],
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linewidth=linewidth)
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plt.title(plotTitle)
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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# -----------------------------------------------------------------------------
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def plotMarg1d(workDir=None, sampleList=None, figDir=None,
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plotNameBase="marg1d",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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plotNames = ("Om", "w0", "wa")
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plotTitles = ("$\Omega_M$", "$w_0$", "$w_a$")
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files = ("Om", "w0", "wa")
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for iPlot in range(len(plotNames)):
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plt.clf()
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plotName = plotNameBase+"_"+plotNames[iPlot]+"_"+dataPortion
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plotTitle = plotTitles[iPlot]
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dataFile = workDir + "/likelihoods_"+dataPortion+"_"+files[iPlot]+".dat"
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plt.xlabel(plotTitle, fontsize="20")
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plt.ylabel("Likelihood", fontsize="20")
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plt.ylim(0.0, 1.0)
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data = np.loadtxt(dataFile, comments="#")
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plt.plot(data[:,0], data[:,1], color='k', linewidth=linewidth)
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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# -----------------------------------------------------------------------------
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def plotNumberDistribution(workDir=None, sampleList=None, figDir=None,
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plotNameBase="numberdist",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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plt.clf()
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plt.xlabel("Void Radius (Mpc/h)")
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plt.ylabel(r"N > R [$h^3$ Mpc$^{-3}$]")
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plotTitle = setName
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plotName = plotNameBase
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plt.yscale('log')
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for (iSample,sample) in enumerate(sampleList):
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sampleName = sample.fullName
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lineTitle = sampleName
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if sample.dataType == "observation":
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boxVol = vp.getSurveyProps(sample.maskFile,
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sample.zBoundary[0], sample.zBoundary[1],
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sample.zRange[0], sample.zRange[1], "all",
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selectionFuncFile=None)[0]
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else:
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boxVol = sample.boxLen*sample.boxLen*(sample.zBoundaryMpc[1] -
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sample.zBoundaryMpc[0])
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boxVol *= 1.e-9
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filename = workDir+"/sample_"+sampleName+"/untrimmed_centers_"+dataPortion+"_"+\
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sampleName+".out"
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if not os.access(filename, os.F_OK):
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print "File not found: ", filename
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continue
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data = np.loadtxt(filename, comments="#")
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if data.ndim == 1:
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print " Too few!"
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continue
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data = data[:,4]
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indices = np.arange(0, len(data), 1)
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sorted = np.sort(data)
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plt.plot(sorted, indices[::-1]/boxVol, '-',
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label=lineTitle, color=colorList[iSample],
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linewidth=linewidth)
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plt.legend(title = "Samples", loc = "upper right")
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plt.title(plotTitle)
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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# -----------------------------------------------------------------------------
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def plotVoidDistribution(workDir=None, sampleList=None, figDir=None,
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plotNameBase="dv",
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showPlot=False, dataPortion=None, setName=None):
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plt.ioff()
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maptplotlib.pyplot.switch_backed('Agg')
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Nmesh = 256
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for (iSample,sample) in enumerate(sampleList):
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plt.clf()
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plt.xlabel("x (Mpc/h)")
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plt.ylabel("y (Mpc/h)")
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sampleName = sample.fullName
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plotName = plotNameBase+"_"+sampleName
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filename = workDir+"/sample_"+sampleName+"/untrimmed_centers_"+dataPortion+"_"+\
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sampleName+".out"
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if not os.access(filename, os.F_OK):
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print "File not found: ", filename
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continue
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void_file = open(filename,'r')
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void_header1 = void_file.readline().split(",")
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void_data1 = np.reshape(void_file.read().split(),
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(-1,len(void_header1))).astype(np.float32)
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void_file.close()
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xv = void_data1[:,0:3]
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rv = void_data1[:,4]
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vv = void_data1[:,6]
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dv, wm, ws = xcor.cic(xv, sample.boxLen, Lboxcut = 0., Nmesh = Nmesh)
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plt.imshow(np.sum(dv+1,2)/Nmesh,extent=[0,sample.boxLen,0,sample.boxLen],
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aspect='equal',
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cmap='YlGnBu_r',interpolation='gaussian')
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plt.colorbar()
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plt.title("Voids: "+sampleName)
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plt.savefig(figDir+"/fig_"+plotName+".pdf", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".eps", bbox_inches="tight")
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plt.savefig(figDir+"/fig_"+plotName+".png", bbox_inches="tight")
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if showPlot:
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os.system("display %s" % figDir+"/fig_"+plotName+".png")
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