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continued removal of extranneous parameters

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This commit is contained in:
Paul M. Sutter 2025-04-22 21:38:13 -04:00
parent 4e87854490
commit 4c48221699
3 changed files with 2 additions and 50 deletions
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6
examples/example_observation/example_observation.py
View file

@ -85,13 +85,11 @@ newSample = Sample(
# HEALpix mask file - set to None to auto-compute # HEALpix mask file - set to None to auto-compute
# NOTE: auto-computed masks are pretty terrible, so # NOTE: auto-computed masks are pretty terrible, so
# only do that if you have no other options # only do that if you have no other options
#maskFile = "",
maskFile = inputDataDir+"/example_observation_mask.fits", maskFile = inputDataDir+"/example_observation_mask.fits",
# resolution for HEALpix mapping of survey edge contours # resolution for HEALpix mapping of survey edge contours
# Set to -1 to use nside from given fits file # Set to -1 to use nside from given fits file
# MUST be set if auto-computing mask # MUST be set if auto-computing mask
#nsideForContour = -1,
nsideForContour = 128, nsideForContour = 128,
# radial selection function (if not volume limited) # radial selection function (if not volume limited)
@ -100,10 +98,6 @@ newSample = Sample(
# max and min redshifts of galaxies in your sample # max and min redshifts of galaxies in your sample
zBoundary = (0.0, 0.15), zBoundary = (0.0, 0.15),
# width of redshift boundaries to flag edge galaxies
# (interpreted as boundaryWidth*(zMax-zMin))
boundaryWidth = 0.01,
# leave this at -1 for mean particle separation, # leave this at -1 for mean particle separation,
# or specify your own in Mpc/h # or specify your own in Mpc/h
minVoidRadius = -1, minVoidRadius = -1,

2
python_source/backend/launchers.py
View file

@ -129,7 +129,7 @@ def launchPrep(sample, binPath, workDir=None, inputDataDir=None,
contourFile = outputDir + "/contour_map.fits" contourFile = outputDir + "/contour_map.fits"
findEdgeGalaxies(galFile, sample.maskFile, edgeGalFile, contourFile, findEdgeGalaxies(galFile, sample.maskFile, edgeGalFile, contourFile,
sample.zBoundary[0], sample.zBoundary[1], sample.omegaM, sample.zBoundary[0], sample.zBoundary[1], sample.omegaM,
useComoving, sample.boundaryWidth, sample.meanPartSep, useComoving, sample.meanPartSep,
outputDir, log) outputDir, log)
log.write("Done!\n") log.write("Done!\n")

44
python_source/backend/surveyTools.py
View file

@ -136,7 +136,7 @@ def figureOutMask(galFile, nside, outMaskFile):
# ----------------------------------------------------------------------------- # -----------------------------------------------------------------------------
# figures out which galaxies live on a mask or redshift edge # figures out which galaxies live on a mask or redshift edge
def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile, def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile,
zmin, zmax, omegaM, useComoving, boundaryWidth, zmin, zmax, omegaM, useComoving,
meanPartSep, outputDir, log): meanPartSep, outputDir, log):
if useComoving: if useComoving:
@ -271,46 +271,4 @@ def findEdgeGalaxies(galFile, maskFile, edgeGalFile, contourFile,
overwrite=True, overwrite=True,
dtype=np.dtype('float64')) dtype=np.dtype('float64'))
# # output galaxy edge flags
# edgeFile = open(edgeGalFile, "w")
#
# for line in open(galFile):
# line = line.split()
# RA = float(line[3])
# Dec = float(line[4])
# z = float(line[5])
#
# if useComoving:
# z = comovingDistance(z/LIGHT_SPEED, Om=omegaM)
# else:
# z *= LIGHT_SPEED/100.
#
# phi, theta = convertAngle(RA, Dec)
#
# # check the mask edges
# ipix = healpy.ang2pix(nside, theta, phi)
# neighbors = healpy.get_all_neighbours(nside, ipix)
# isOnMaskEdge = any(mask[p] == 0 for p in neighbors)
#
# # check the redshift boundaries
# zbuffer = (zmax-zmin)*boundaryWidth
# isOnHighZEdge = (z >= zmax-zbuffer)
# isOnLowZEdge = (z <= zmin+zbuffer)
#
# if isOnMaskEdge:
# edgeFile.write("1\n")
# edgeMask[ipix] = 1
# elif isOnHighZEdge:
# edgeFile.write("2\n")
# elif isOnLowZEdge:
#
#edgeFile.write("3\n")
# else:
# edgeFile.write("0\n")
#
# edgeFile.close()
# healpy.write_map(edgeMaskFile, edgeMask, overwrite=True,
# dtype=np.dtype('float64'))
return return