Calculating the projected correlation function, \(wp(rp)\)ΒΆ
2-D Pair counts can be converted into a \(wp(rp)\)
by using the helper function Corrfunc.utils.convert_rp_pi_counts_to_wp
.
First, we have to compute the relevant pair counts using the python
wrapper Corrfunc.mocks.DDrppi_mocks
>>> import numpy as np
>>> from os.path import dirname, abspath, join as pjoin
>>> import Corrfunc
>>> from Corrfunc.mocks.DDrppi_mocks import DDrppi_mocks
>>> from Corrfunc.io import read_catalog
>>> from Corrfunc.utils import convert_rp_pi_counts_to_wp
>>> galaxy_catalog=pjoin(dirname(abspath(Corrfunc.__file__)),
... "../mocks/tests/data", "Mr19_mock_northonly.rdcz.ff")
# Read the supplied galaxies on a periodic box
>>> RA, DEC, CZ = read_catalog(galaxy_catalog)
>>> N = len(RA)
# Read the supplied randoms catalog
>>> random_catalog=pjoin(dirname(abspath(Corrfunc.__file__)),
... "../mocks/tests/data", "Mr19_randoms_northonly.rdcz.ff")
>>> rand_RA, rand_DEC, rand_CZ = read_catalog(random_catalog)
>>> rand_N = len(rand_RA)
# Setup the bins
>>> nbins = 10
>>> bins = np.linspace(0.1, 20.0, nbins + 1)
>>> pimax = 40.0
>>> cosmology = 1
>>> nthreads = 2
# Auto pair counts in DD
>>> autocorr=1
>>> DD_counts = DDrppi_mocks(autocorr, cosmology, nthreads, pimax, bins,
... RA, DEC, CZ)
# Cross pair counts in DR
>>> autocorr=0
>>> DR_counts = DDrppi_mocks(autocorr, cosmology, nthreads, pimax, bins,
... RA, DEC, CZ,
... RA2=rand_RA, DEC2=rand_DEC, CZ2=rand_CZ)
# Auto pairs counts in RR
>>> autocorr=1
>>> RR_counts = DDrppi_mocks(autocorr, cosmology, nthreads, pimax, bins,
... rand_RA, rand_DEC, rand_CZ)
# All the pair counts are done, get the angular correlation function
>>> wp = convert_rp_pi_counts_to_wp(N, N, rand_N, rand_N,
... DD_counts, DR_counts,
... DR_counts, RR_counts, nbins, pimax)
See the complete reference here Corrfunc
.