A Python-wrapped and modified version of the CUTE correlation function code

The original CUTE (Correlation Utilities and Two point Estimation) code was written by David Alonso and is available at https://github.com/damonge/CUTE. This version is derived from that original, but with added functionalities and with a Python wrapper.

The additional functionalities over the original CUTE are:

• option to compute cross-correlation function for two different point populations
• for periodic boxes, the option to compute xi(sigma, pi) and xi(r, mu) in addition to the monopole; these functionalities are also present for cross-correlations in both the box version and the sky survey version of the code

Note: The computation of cross-correlations requires the input of two different data catalogues, D1 and D2, and (in the sky survey case), two corresponding random catalogues R1 and R2.

You will need SWIG installed (which in turn requires GSL and PCRE), see PythonCUTE/PYTHON_README. You need to change the PYTHONINC and PYTHONLIB paths in the Makefile to match your system (for PythonCUTE, also change GSL_INC and GSL_LIB).

In addition to everyone who contributed to the original development of CUTE and is mentioned in that GitHub download, contributions to this version of pyCUTE were made by:

• Seshadri Nadathur
• Hans Winther