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https://bitbucket.org/cosmicvoids/vide_public.git
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setting the stage for on-the-fly mask and edge calculation
This commit is contained in:
Paul M. Sutter
parent
99a441013d
commit
aded7a7c2c
6 changed files with 143 additions and 67 deletions
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@ -20,3 +20,4 @@
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from .classes import *
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from .launchers import *
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from .cosmologyTools import *
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from .surveyTools import *
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@ -22,11 +22,10 @@
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import numpy as np
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import scipy.integrate as integrate
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import healpy as healpy
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import os
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from backend import *
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__all__=['expansion', 'angularDiameter', 'aveExpansion', 'getSurveyProps']
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__all__=['expansion', 'angularDiameter', 'aveExpansion']
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# returns 1/E(z) for the given cosmology
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def expansion(z, Om = 0.27, Ot = 1.0, w0 = -1.0, wa = 0.0):
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@ -51,62 +50,3 @@ def aveExpansion(zStart, zEnd, Om = 0.27, Ot = 1.0, w0 = -1.0, wa = 0.0):
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ave = integrate.quad(expansion, zStart, zEnd, args=(Om, Ot, w0, wa))[0]
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ave = (zEnd-zStart)/ave
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return ave
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# -----------------------------------------------------------------------------
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# returns the volume and galaxy density for a given redshit slice
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def getSurveyProps(maskFile, zmin, zmax, selFunMin, selFunMax, portion, selectionFuncFile=None, useComoving=False):
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LIGHT_SPEED = 299792.458
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mask = healpy.read_map(maskFile)
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area = (1.*np.size(np.where(mask > 0)) / np.size(mask)) * 4.*np.pi
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if useComoving:
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zmin = LIGHT_SPEED/100.*angularDiameter(zmin, Om=0.27)
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zmax = LIGHT_SPEED/100.*angularDiameter(zmax, Om=0.27)
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selFunMin = LIGHT_SPEED/100.*angularDiameter(selFunMin, Om=0.27)
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selFunMax = LIGHT_SPEED/100.*angularDiameter(selFunMax, Om=0.27)
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else:
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zmin = zmin * 3000
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zmax = zmax * 3000
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selFunMin *= 3000
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selFunMax *= 3000
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volume = area * (zmax**3 - zmin**3) / 3
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if selectionFuncFile == None:
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nbar = 1.0
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elif not os.access(selectionFuncFile, os.F_OK):
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print(" Warning, selection function file %s not found, using default of uniform selection." % selectionFuncFile)
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nbar = 1.0
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else:
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selfunc = np.genfromtxt(selectionFuncFile)
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selfunc = np.array(selfunc)
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selfunc[:,0] = selfunc[:,0]/100.
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selfuncUnity = selfunc
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selfuncUnity[:,1] = 1.0
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selfuncMin = selfunc[0,0]
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selfuncMax = selfunc[-1,0]
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selfuncDx = selfunc[1,0] - selfunc[0,0]
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selfuncN = np.size(selfunc[:,0])
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selFunMin = max(selFunMin, selfuncMin)
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selFunMax = min(selFunMax, selfuncMax)
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def f(z): return selfunc[np.ceil((z-selfuncMin)/selfuncDx), 1]*z**2
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def fTotal(z): return selfuncUnity[np.ceil((z-selfuncMin)/selfuncDx), 1]*z**2
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zrange = np.linspace(selFunMin, selFunMax)
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nbar = scipy.integrate.quad(f, selFunMin, selFunMax)
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nbar = nbar[0]
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ntotal = scipy.integrate.quad(fTotal, 0.0, max(selfuncUnity[:,0]))
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ntotal = ntotal[0]
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nbar = ntotal / area / nbar
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return (volume, nbar)
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@ -36,6 +36,7 @@ from pylab import figure
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from netCDF4 import Dataset
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from backend.classes import *
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from backend.cosmologyTools import *
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from backend.surveyTools import *
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import pickle
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import scipy.interpolate as interpolate
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@ -531,7 +532,7 @@ def launchPrune(sample, binPath,
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cmd += " --outputDir=" + zobovDir
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cmd += " --sampleName=" + str(sampleName)
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log = open(logFile, 'w')
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log.write(f"Command is {cmd}\n")
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#log.write(f"Command is {cmd}\n")
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subprocess.call(cmd, stdout=log, stderr=log, shell=True)
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log.close()
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129
python_source/backend/surveyTools.py
Normal file
129
python_source/backend/surveyTools.py
Normal file
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@ -0,0 +1,129 @@
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#+
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# VIDE -- Void IDentification and Examination -- ./python_tools/vide/apTools/chi2/cosmologyTools.py
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# Copyright (C) 2010-2014 Guilhem Lavaux
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# Copyright (C) 2011-2014 P. M. Sutter
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; version 2 of the License.
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#
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License along
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# with this program; if not, write to the Free Software Foundation, Inc.,
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# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
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#+
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# a suite of functions to compute expansion rates, angular diameter
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# distances, and expected void stretching
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import numpy as np
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import healpy as healpy
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import os
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from backend import *
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__all__=['getSurveyProps', 'getNside', 'figureOutMask', 'findEdgeGalaxies']
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# -----------------------------------------------------------------------------
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# returns the volume and galaxy density for a given redshit slice
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def getSurveyProps(maskFile, zmin, zmax, selFunMin, selFunMax, portion, selectionFuncFile=None, useComoving=False):
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LIGHT_SPEED = 299792.458
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mask = healpy.read_map(maskFile)
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area = (1.*np.size(np.where(mask > 0)) / np.size(mask)) * 4.*np.pi
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if useComoving:
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zmin = LIGHT_SPEED/100.*angularDiameter(zmin, Om=0.27)
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zmax = LIGHT_SPEED/100.*angularDiameter(zmax, Om=0.27)
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selFunMin = LIGHT_SPEED/100.*angularDiameter(selFunMin, Om=0.27)
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selFunMax = LIGHT_SPEED/100.*angularDiameter(selFunMax, Om=0.27)
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else:
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zmin = zmin * 3000
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zmax = zmax * 3000
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selFunMin *= 3000
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selFunMax *= 3000
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volume = area * (zmax**3 - zmin**3) / 3
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if selectionFuncFile == None:
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nbar = 1.0
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elif not os.access(selectionFuncFile, os.F_OK):
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print(" Warning, selection function file %s not found, using default of uniform selection." % selectionFuncFile)
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nbar = 1.0
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else:
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selfunc = np.genfromtxt(selectionFuncFile)
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selfunc = np.array(selfunc)
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selfunc[:,0] = selfunc[:,0]/100.
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selfuncUnity = selfunc
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selfuncUnity[:,1] = 1.0
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selfuncMin = selfunc[0,0]
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selfuncMax = selfunc[-1,0]
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selfuncDx = selfunc[1,0] - selfunc[0,0]
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selfuncN = np.size(selfunc[:,0])
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selFunMin = max(selFunMin, selfuncMin)
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selFunMax = min(selFunMax, selfuncMax)
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def f(z): return selfunc[np.ceil((z-selfuncMin)/selfuncDx), 1]*z**2
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def fTotal(z): return selfuncUnity[np.ceil((z-selfuncMin)/selfuncDx), 1]*z**2
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zrange = np.linspace(selFunMin, selFunMax)
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nbar = scipy.integrate.quad(f, selFunMin, selFunMax)
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nbar = nbar[0]
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ntotal = scipy.integrate.quad(fTotal, 0.0, max(selfuncUnity[:,0]))
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ntotal = ntotal[0]
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nbar = ntotal / area / nbar
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return (volume, nbar)
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# -----------------------------------------------------------------------------
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# returns the nside resolution from the given maskfile
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def getNside(maskFile):
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nside = 1.0
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return nside
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# -----------------------------------------------------------------------------
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# computes the mask from a given datafile and writes it to a file
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def figureOutMask(galFile, nside, outMaskFile):
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npix = healpy.nside2npix(nside)
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mask = np.zeros((npix))
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for line in open(galFile):
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line = line.split()
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RA = np.float(line[3])
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Dec = np.float(line[4])
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z = np.float(line[5])
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phi = np.pi/180.*RA
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theta = Dec*np.pi/180.
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theta = np.pi/2. - Dec*np.pi/180.
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pos = np.zeros((3))
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pix = healpy.ang2pix(nside, theta, phi)
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mask[pix] = 1.
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healpy.write_map(outMaskFile, mask)
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return mask
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# -----------------------------------------------------------------------------
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# figures out which galaxies live on a mask edge, and also writes the edge
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# map to an auxillary file
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def findEdgeGalaxies(galFile, maskFile):
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return
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