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more options for number function

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This commit is contained in:
P.M. Sutter 2014-05-26 08:09:52 -04:00
parent 792190ccc5
commit e177bddea2
1 changed files with 19 additions and 12 deletions
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31
python_tools/void_python_tools/voidUtil/plotUtil.py
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@ -42,12 +42,16 @@ def fill_between(x, y1, y2=0, ax=None, **kwargs):
# -----------------------------------------------------------------------------
def plotNumberFunction(catalogList,
figDir="./",
plotName="numberfunc"):
plotName="numberfunc",
cumulative=True,
binWidth=1):
# plots a cumulative number function
# catalogList: list of void catalogs to plot
# figDir: output directory for figures
# plotName: name to prefix to all outputs
# cumulative: if True, plots cumulative number function
# binWidth: width of histogram bins in Mpc/h
# returns:
# numberFuncList: array of len(catalogList),
# each element has array of size bins, number, +/- 1 sigma
@ -56,7 +60,11 @@ def plotNumberFunction(catalogList,
plt.clf()
plt.xlabel("$R_{eff}$ [$h^{-1}Mpc$]", fontsize=14)
plt.ylabel(r"log ($n$ (> R) [$h^3$ Gpc$^{-3}$])", fontsize=14)
if cumulative:
plt.ylabel(r"log ($n$ (> R) [$h^3$ Gpc$^{-3}$])", fontsize=14)
else:
plt.ylabel(r"log ($dn/dR$ [$h^3$ Gpc$^{-3}$])", fontsize=14)
numberFuncList = []
@ -70,25 +78,24 @@ def plotNumberFunction(catalogList,
boxVol = vp.getSurveyProps(maskFile,
sample.zBoundary[0], sample.zBoundary[1],
sample.zRange[0], sample.zRange[1], "all",
selectionFuncFile=None)[0]
#selectionFuncFile=sample.selFunFile)[0]
boxVol *= obsFudgeFactor
selectionFuncFile=sample.selFunFile)[0]
else:
boxVol = sample.boxLen*sample.boxLen*(sample.zBoundaryMpc[1] -
sample.zBoundaryMpc[0])
boxVol *= 1.e-9 # Mpc->Gpc
bins = 100.
bins = 100./binWidth
hist, binEdges = np.histogram(data, bins=bins, range=(0., 100.))
binCenters = 0.5*(binEdges[1:] + binEdges[:-1])
foundStart = False
for iBin in xrange(len(hist)):
if not foundStart and hist[iBin] == 0:
continue
foundStart = True
hist[iBin] = np.sum(hist[iBin:])
if cumulative:
foundStart = False
for iBin in xrange(len(hist)):
if not foundStart and hist[iBin] == 0:
continue
foundStart = True
hist[iBin] = np.sum(hist[iBin:])
nvoids = len(data)
var = hist * (1. - hist/nvoids)