redshift boundary tolerance is now user-selectable

c_source/pruning/pruneVoids.cpp

@@ -851,8 +851,8 @@ int main(int argc, char **argv) {
   // toss out voids near non-periodic box edges
   iGood = 0;
   for (iVoid = 0; iVoid < voids.size(); iVoid++) {
-    if (tolerance*voids[iVoid].maxRadius > voids[iVoid].nearestEdge || 
+    if (voids[iVoid].maxRadius > voids[iVoid].nearestEdge || 
-        tolerance*voids[iVoid].radius > voids[iVoid].nearestEdge) {
+        voids[iVoid].radius > voids[iVoid].nearestEdge) {
       numNearZ++;
     } else {
       voids[iGood++] = voids[iVoid];

examples/example_observation/example_observation.py

@@ -99,6 +99,10 @@ newSample = Sample(
                    # max and min redshifts where you want to find voids
                    zRange = (0.1, 0.15),
 
+                   # width of redshift boundaries to flag edge galaxies
+                   # (interpreted as boundaryWidth*(zMax-zMin))
+                   boundaryWidth = 0.1,
+
                    # leave this at -1 for mean particle separation,
                    # or specify your own in Mpc/h
                    minVoidRadius = -1,

python_source/backend/classes.py

@@ -73,6 +73,7 @@ class Sample:
   selFunFile = "czselfunc.all.dr72dim.dat"
   zBoundary = (0.0, 0.1)
   zBoundaryMpc = (0., 300)
+  boundaryWidth = 0.02
   shiftSimZ = False
   zRange    = (0.0, 0.1)
   omegaM    = 0.27
@@ -100,7 +101,8 @@ class Sample:
 
   def __init__(self, dataFile="", fullName="", dataUnit=1,
                nickName="", maskFile="", nsideForMask=128, selFunFile="",
-               zBoundary=(), zRange=(), zBoundaryMpc=(), shiftSimZ=False,
+               zBoundary=(), zRange=(), zBoundaryMpc=(), boundaryWidth=0.1,
+               shiftSimZ=False,
                minVoidRadius=-1, fakeDensity=0.01, volumeLimited=True,
                numAPSlices=1,
                includeInHubble=True, partOfCombo=False, isCombo=False, 
@@ -119,6 +121,7 @@ class Sample:
     self.selFunFile = selFunFile
     self.zBoundary = zBoundary 
     self.zBoundaryMpc = zBoundaryMpc
+    self.boundaryWidth = boundaryWidth
     self.shiftSimZ = shiftSimZ
     self.zRange = zRange
     self.minVoidRadius = minVoidRadius

python_source/backend/launchers.py

@@ -74,7 +74,7 @@ def launchPrep(sample, binPath, workDir=None, inputDataDir=None,
     edgeMaskFile = outputDir + "/mask_edge_map.fits"
     findEdgeGalaxies(datafile, sample.maskFile, edgeGalFile, edgeMaskFile,
                      sample.zBoundary[0], sample.zBoundary[1], sample.omegaM,
-                     useComoving)
+                     useComoving, sample.boundaryWidth)
 
     if useComoving:
       useComovingFlag = "useComoving"

python_source/backend/surveyTools.py

@@ -130,11 +130,13 @@ def figureOutMask(galFile, nside, outMaskFile):
 # figures out which galaxies live on a mask edge, and also writes the edge
 #   map to an auxillary file
 def findEdgeGalaxies(galFile, maskFile, edgeGalFile, edgeMaskFile,
-                     zmin, zmax, omegaM, useComoving=False):
+                     zmin, zmax, omegaM, useComoving, boundaryWidth):
 
-  #if useComoving:
+  if useComoving:
-  #  zmin = LIGHT_SPEED/100.*comovingDistance(zmin, Om=omegaM)
+    zmin = comovingDistance(zmin, Om=omegaM)
-  #  zmax = LIGHT_SPEED/100.*comovingDistance(zmax, Om=omegaM)
+    zmax = comovingDistance(zmax, Om=omegaM)
+    #zmin = LIGHT_SPEED/100.*comovingDistance(zmin, Om=omegaM)
+    #zmax = LIGHT_SPEED/100.*comovingDistance(zmax, Om=omegaM)
   #else:
   #  zmin *= LIGHT_SPEED/100.
   #  zmax *= LIGHT_SPEED/100.
@@ -166,8 +168,7 @@ def findEdgeGalaxies(galFile, maskFile, edgeGalFile, edgeMaskFile,
     isOnMaskEdge = any(mask[p] == 0 for p in neighbors)
   
     # check the redshift boundaries
-    tol = 0.05 # TODO: made this user-adjustable
+    zbuffer = (zmax-zmin)*boundaryWidth
-    zbuffer = (zmax-zmin)*tol
     isOnHighZEdge = (z >= zmax-zbuffer)
     isOnLowZEdge  = (z <= zmin+zbuffer)
 
@@ -182,6 +183,7 @@ def findEdgeGalaxies(galFile, maskFile, edgeGalFile, edgeMaskFile,
       edgeFile.write("0\n")
 
   edgeFile.close()
-  healpy.write_map(edgeMaskFile, edgeMask, overwrite=True, dtype=np.dtype('float64'))
+  healpy.write_map(edgeMaskFile, edgeMask, overwrite=True,
+                   dtype=np.dtype('float64'))
 
   return

python_source/vide_pipeline/__main__.py

@@ -121,8 +121,7 @@ for sample in dataSampleList:
     launchPrune(sample, PRUNE_PATH, 
                 logFile=logFile, outputDir=outputDir, 
                 useComoving=sample.useComoving, continueRun=continueRun,
-                mergingThreshold=mergingThreshold,
+                mergingThreshold=mergingThreshold)
-                boundaryTolerance=boundaryTolerance)
 
 # -------------------------------------------------------------------------
 if (startCatalogStage <= 4) and (endCatalogStage >= 4):

python_source/vide_pipeline/defaults.py

@@ -143,10 +143,6 @@ numZobovThreads = 2
 #   1e-9 (or smaller != 0) -> Do not merge anything
 mergingThreshold = 1.e-9
 
-# when trimming away voids near the bounaries, what multiple of the radius to
-#   use for safety
-boundaryTolerance = 1.0
-
 # simulation information
 numPart = 512*512*512
 lbox = 999.983 # Mpc/h

python_source/voidUtil/plotUtil.py

@@ -25,6 +25,7 @@ import numpy as np
 import os
 import pylab as plt
 import backend.cosmologyTools as vp
+import backend.surveyTools as sp
 from voidUtil import getArray, shiftPart, getVoidPart
 
 def fill_between(x, y1, y2=0, ax=None, **kwargs):
@@ -77,17 +78,18 @@ def plotNumberFunction(catalogList,
     if sample.dataType == "observation":
       maskFile = sample.maskFile
   
-      boxVol = vp.getSurveyProps(maskFile,
+      boxVol = sp.getSurveyProps(maskFile,
                                  sample.zBoundary[0], sample.zBoundary[1],
                                  sample.zRange[0], sample.zRange[1], "all",
-                                 selectionFuncFile=sample.selFunFile)[0]
+                                 selectionFuncFile=sample.selFunFile,
+                                 omegaM=sample.omegaM)[0]
     else:
       boxVol = sample.boxLen*sample.boxLen*(sample.zBoundaryMpc[1] -
                                             sample.zBoundaryMpc[0])
   
     boxVol *= 1.e-9 # Mpc->Gpc
   
-    bins = 100./binWidth
+    bins = int(100./binWidth)
     hist, binEdges = np.histogram(data, bins=bins, range=(0., 100.))
     binCenters = 0.5*(binEdges[1:] + binEdges[:-1])