Supports minimum halo mass cuts. Start of scripts to generate masked mock sets, some files added to later support more general preparation scripts

This commit is contained in:
Paul Matt Sutter 2012-11-17 13:00:54 -05:00
parent a53e3bf290
commit 10dfe29a26
9 changed files with 557 additions and 58 deletions

17
plotting/datasetsToPlot.py Executable file
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@ -0,0 +1,17 @@
#!/usr/bin/env python
workDir = "/home/psutter2/workspace/Voids/"
figDir = "./figs"
sampleDirList = [ "multidark/md_ss0.1_pv/sample_md_ss0.1_pv_z0.56_d00/",
"multidark/md_ss01.0_pv/sample_md_ss1.0_pv_z0.56_d00/",
"multidark/md_halos_min1.23e13_pv/sample_md_halos_min1.23e13_pv_z0.56_d00/",
"random/ran_ss0.0004/sample_ran_ss0.0004_z0.56_d00/",
"random/ran_ss0.1/sample_ran_ss0.1_z0.56_d00/",
"multidark/md_hod_dr9mid_pv/sample_md_hod_dr9mid_pv_z0.56_d00/",
"multidark/md_ss0.0004_pv/sample_md_ss0.0004_pv_z0.56_d00/",
"sdss_dr9/sample_lss.dr9cmassmid.dat/" ]
dataPortion = "central"

93
plotting/plotCompareDensCon.py Executable file
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#!/usr/bin/env python
# plots cumulative distributions of number counts versus density contrast
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 datasetsToPlot import *
plotNameBase = "compdenscon"
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)')
args = parser.parse_args()
# ------------------------------------------------------------------------------
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=80.)
plotName = plotNameBase
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=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[:,8]
indices = np.arange(0, len(data), 1)
sorted = np.sort(data)
plt.plot(sorted, indices[::-1]/boxVol, '-',
label=lineTitle, color=colorList[iSample],
linewidth=linewidth)
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")
if args.showPlot:
os.system("display %s" % figDir+"/fig_"+plotName+".png")

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@ -14,21 +14,10 @@ import argparse
# ------------------------------------------------------------------------------
workDir = "/home/psutter2/workspace/Voids/"
figDir = "./figs"
sampleDirList = [ "multidark/md_ss0.1_pv/sample_md_ss0.1_pv_z0.56_d00/",
"multidark/md_halos_pv/sample_md_halos_pv_z0.56_d00/",
"random/ran_ss0.0004/sample_ran_ss0.0004_z0.56_d00/",
"random/ran_ss0.1/sample_ran_ss0.1_z0.56_d00/",
"multidark/md_hod_dr9mid_pv/sample_md_hod_dr9mid_pv_z0.56_d00/",
"multidark/md_ss0.0004_pv/sample_md_ss0.0004_pv_z0.56_d00/",
"sdss_dr9/sample_lss.dr9cmassmid.dat/" ]
from datasetsToPlot import *
plotNameBase = "compdist"
dataPortion = "central"
obsFudgeFactor = .66 # what fraction of the volume are we *reall* capturing?
parser = argparse.ArgumentParser(description='Plot.')