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193 lines
6.7 KiB
Python
193 lines
6.7 KiB
Python
#+
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# VIDE -- Void IDentification and Examination -- ./crossCompare/plotting/plotCocenterProfiles.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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# 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
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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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from globalOptions import *
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from scipy.optimize import curve_fit
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matplotlib.rcParams.update({'font.size': 20})
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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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# 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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# 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 plotProfiles(baseSample, stack, sampleList,
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figDir, showPlot, outputDir, doTheory):
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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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filename = "1dprofile_cocenter_" + baseSample.fullName+"_"+thisRadius
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npzfile = np.load(outputDir+"/1dprofile_cocentered_"+plotName+".dat.npz")
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profileList = npzfile['arr_0']
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radii = npzfile['arr_1']
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plt.clf()
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plt.xlabel(r"$R/R_{eff}$")
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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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plt.xlim(xmin=0.0, xmax=2.5)
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plt.ylim(ymin=0.0, ymax=1.7)
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#plt.xscale('log')
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for (iSample, sample) in enumerate(sampleList):
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lineTitle = sample.nickName[:-10]
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if "DM LowDen" in lineTitle or "DM HighDen" in lineTitle: continue
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thisPlotTitle = r"$R_{eff}$ = "+thisRadius+ r" $h^{-1}$Mpc"
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legendTitle = "Fixed Center Samples"
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thisProfile = profileList[iSample]
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if np.all(thisProfile == 0.): continue
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rV = (stack.rMin + stack.rMax)/2.
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if len(radii) > 0:
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scaledRadii = radii/rV
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plt.plot(scaledRadii, thisProfile, label=lineTitle,
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color=colorList[iSample],
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linewidth=linewidth)
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if doTheory:
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nBins = len(scaledRadii)/2
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try:
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popt, pcov = curve_fit(PadillaProfile, scaledRadii[0:nBins],
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thisProfile[0:nBins], maxfev=10000, xtol=5.e-3)
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except RuntimeError:
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print "Warning: no convergence reached"
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label = r"A1=%.2f, A2=%.2f, $\alpha$=%.2f" % (popt[0], popt[1], popt[2])
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rho = PadillaProfile(scaledRadii, popt[0], popt[1], popt[2])
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plt.plot(scaledRadii, rho, '--', label=label,
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color=colorList[iSample], linewidth=2)
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plt.title(thisPlotTitle + " (center from " + plotTitle + ")", fontsize=18)
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plt.legend(title = legendTitle, loc = "lower right", prop={'size':16})
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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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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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# plot these profiles
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print " Plotting..."
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sys.stdout.flush()
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plotProfiles(baseSample, stack, sampleList,
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figDir, args.showPlot, outputDir, doTheory)
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print " Done!"
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