more work on merger tree analysis code

crossCompare/plotting/plotCompareDist.py

@@ -1,121 +0,0 @@
-#!/usr/bin/env python
-
-# plots cumulative distributions of number counts
-
-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
-
-# ------------------------------------------------------------------------------
-
-plotNameBase = "compdist"
-
-obsFudgeFactor = 1.0 # what fraction of the volume are we *reall* capturing?
-#obsFudgeFactor = .66 # what fraction of the volume are we *reall* capturing?
-
-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('--parmFile', dest='parmFile', default='datasetsToPlot.py',
-                    help='path to parameter file')
-args = parser.parse_args()
-
-# ------------------------------------------------------------------------------
-
-filename = args.parmFile
-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 = []
-
-for sampleDir in sampleDirList:
-  with open(workDir+sampleDir+"/sample_info.dat", 'rb') as input:
-    dataSampleList.append(pickle.load(input))
-
-plt.clf()
-plt.xlabel("Void Radius [Mpc/h]")
-plt.ylabel(r"N > R [$h^3$ Gpc$^{-3}$]")
-plt.yscale('log')
-plt.xlim(xmax=120.)
-
-plotName = plotNameBase
-allData = []
-
-for (iSample,sample) in enumerate(dataSampleList):
-
-  sampleName = sample.fullName
-  lineTitle = sampleName
-
-  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
-
-  filename = workDir+"/"+sampleDirList[iSample]+"/centers_"+dataPortion+"_"+\
-             sampleName+".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
-  data = data[:,4]
-  indices = np.arange(0, len(data), 1)
-  sorted = np.sort(data)
-
-  plt.plot(sorted, indices[::-1]/boxVol, '-',
-           label=lineTitle, color=colorList[iSample],
-           linewidth=linewidth)
-
-  hist, bin_edges = np.histogram(data, bins=100, range=(0,100)) 
-  allData.append(hist)
-
-plt.legend(title = "Samples", loc = "upper right", prop={'size':8})
-#plt.title(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")
-
-dataFile = figDir+"/data_"+plotName+".dat"
-fp = open(dataFile, 'w')
-fp.write("# R [Mpc/h], N [h^3 Gpc^-3]\n")
-fp.write("# ")
-for sample in dataSampleList:
-  fp.write(sample.fullName+" ")
-fp.write("\n")
-for i in xrange(100):
-  fp.write(str(bin_edges[i]) + " ")
-  for iSample in xrange(len(dataSampleList)):
-    fp.write(str(allData[iSample][i])+" ")
-  fp.write("\n")
-fp.close()
-
-if args.showPlot:
-  os.system("display %s" % figDir+"/fig_"+plotName+".png")
-
-