Continuing development. Boundary handling seems to be stable and working. Now testing void finding.

python_source/backend/surveyTools.py

@@ -131,7 +131,7 @@ def figureOutMask(galFile, nside, outMaskFile):
 # figures out which galaxies live on a mask or redshift edge
 def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile,
                      zmin, zmax, omegaM, useComoving, boundaryWidth,
-                     meanPartSep):
+                     meanPartSep, outputDir):
 
   if useComoving:
     zmin = comovingDistance(zmin, Om=omegaM)*LIGHT_SPEED
@@ -145,15 +145,50 @@ def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile,
   npix = healpy.nside2npix(nside)
 
   # load in galaxies
-  galPos = np.genfromtxt(galFile)
+  #galPos = np.genfromtxt(galFile)
+  galPos = np.genfromtxt(outputDir+"/galaxies.txt")
+  with open(galFile, 'rb') as File:
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   Np = np.fromfile(File, dtype=np.int32,count=1)[0]
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   x = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   y = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   z = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   RA = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   Dec = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+   redshift = np.fromfile(File, dtype=np.float32,count=Np)
+   chk = np.fromfile(File, dtype=np.int32,count=1)
+
+  #print(galPos.shape)
+  #galPos = np.column_stack((x,y,z))
+  #print(galPos.shape)
+
   flagList = np.zeros(len(galPos[:,0]))
   galTree = scipy.spatial.cKDTree(galPos)
 
   # flag galaxies near mask edges
   # using the "ray marching" algorithm: follow rays along lines of sight
   #   of all mask edges, flagging nearest neighbor galaxies as we go
-  
+ 
   raySteps = np.arange(zmin, zmax, meanPartSep)
+  #print(meanPartSep, len(raySteps))
  
   contourPixels = np.nonzero(contourMap)[0]
   #print(contourPixels)
@@ -164,34 +199,42 @@ def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile,
     y = raySteps * vec[1]
     z = raySteps * vec[2]
     ray = np.array((x,y,z)).T
-    #print(ray)
     
     dist, nearest = galTree.query(ray)
     flagList[nearest] = 1
-    #print(nearest)
 
   # flag galaxies near redsfhit boundaries
-  # TODO - save time by only covering portion of sphere with data
-  ds = np.sqrt(healpy.nside2pixarea(nside)) / 1000.
-  phi = np.arange(0, 2*np.pi, ds*2)
-  theta = np.arange(0, np.pi, ds)
-  vec = healpy.ang2vec(theta, phi)
+  # TODO - save time by only covering portion of sphere that has data
 
+  sphereIndices = np.arange(len(contourMap))
+  vec = healpy.pix2vec(nside, sphereIndices)
+  vec = np.asarray(vec)
   maxEdge = zmax * vec
+  maxEdge = maxEdge.T
   dist, nearest = galTree.query(maxEdge)
-  #print(nearest)
-  #print(galPos[nearest])
   flagList[nearest] = 2
 
   minEdge = zmin * vec
+  minEdge = minEdge.T
   dist, nearest = galTree.query(minEdge)
-  #print(nearest)
-  #print(galPos[nearest])
   flagList[nearest] = 3
 
   # output flag information
   np.savetxt(edgeGalFile, flagList, fmt="%d")
 
+  # paint galaxy flags onto healpix map for diagnostics
+  # TODO - drop this when done testing
+  flagMap = np.zeros(len(contourMap))
+  justEdgeRA = RA[flagList == 1]
+  justEdgeDec = Dec[flagList == 1]
+
+  phi, theta = convertAngle(justEdgeRA, justEdgeDec)
+
+  ipix = healpy.ang2pix(nside, theta, phi)
+  np.put(flagMap, ipix, 1)
+
+  healpy.write_map("./flagged_galaxies.fits", flagMap, overwrite=True,
+                   dtype=np.dtype('float64'))
 
 
 #  # output galaxy edge flags