# Calculating the angular correlation function, $$\omega(\theta)$$¶

Angular pair counts can be converted into a $$\omega(\theta)$$ by using the helper function Corrfunc.utils.convert_3d_counts_to_cf. First, we have to compute the relevant pair counts using the python wrapper Corrfunc.mocks.DDtheta_mocks

>>> from os.path import dirname, abspath, join as pjoin
>>> import numpy as np
>>> import Corrfunc
>>> from Corrfunc.mocks.DDtheta_mocks import DDtheta_mocks
>>> from Corrfunc.utils import convert_3d_counts_to_cf

>>> 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, _ = read_catalog(galaxy_catalog)

# Read the supplied randoms catalog
>>> random_catalog=pjoin(dirname(abspath(Corrfunc.__file__)),
...                     "../mocks/tests/data", "Mr19_randoms_northonly.rdcz.ff")
>>> rand_RA, rand_DEC, _ = read_catalog(random_catalog)
>>> rand_N = len(rand_RA)

# Setup the bins
>>> nbins = 10
>>> bins = np.linspace(0.1, 10.0, nbins + 1) # note the +1 to nbins

# Number of threads to use

# Auto pair counts in DD
>>> autocorr=1
>>> DD_counts = DDtheta_mocks(autocorr, nthreads, bins,
...                          RA, DEC)

# Cross pair counts in DR
>>> autocorr=0
>>> DR_counts = DDtheta_mocks(autocorr, nthreads, bins,
...                           RA, DEC,
...                           RA2=rand_RA, DEC2=rand_DEC)

# Auto pairs counts in RR
>>> autocorr=1
>>> RR_counts = DDtheta_mocks(autocorr, nthreads, bins,
...                           rand_RA, rand_DEC)

# All the pair counts are done, get the angular correlation function
>>> wtheta = convert_3d_counts_to_cf(N, N, rand_N, rand_N,
...                                 DD_counts, DR_counts,
...                                 DR_counts, RR_counts)


See the complete reference here Corrfunc.