RascalC fixes and utility scripts for 2PCF covariance for s, µ bins and Legendre multipoles

This version is a large collection of bug fixes and utility scripts for v2.2, not introducing major new features like a new mode reserved for v2.3. Many corrections and improvements are in the documentation.

The extra convergence checks follow Rashkovetskyi et al 2023.

3PCF and power spectra functions remained largely unused and untested; most fixes concern the different 2PCF modes.

RascalC lesser expansion: covariance of 2PCF Legendre multipoles projected from µ bins (with jackknives)

This version features a new mode (LEGENDRE_MIX), corresponding to 2PCF Legendre multipoles not accumulated directly, but projected from many µ bins (as e.g. in pycorr). Usage of µ bins also allows to predict jackknife covariance more easily in the same run. (The disconnected term in the jackknife covariance is currently omitted in this mode, it has been very small in practice.) The corresponding documentation version is available on ReadTheDocs.

RascalC Expansion: Legendre Multipoles and the 3PCF

We introduce additional code allowing covariance matrices to be computed (in arbitrary survey geometries) for Legendre multipoles of the anisotropic 2-point correlation function and the isotropic 3-point correlation function. This accompanies the Philcox & Eisenstein (2019) paper and updated documentation is available at ReadTheDocs.

(Updated to fix bugs in the post-processing of multi-field covariance matrices)

RascalC Expansion: Legendre Multipoles and the 3PCF

We introduce additional code allowing covariance matrices to be computed (in arbitrary survey geometries) for Legendre multipoles of the anisotropic 2-point correlation function and the isotropic 3-point correlation function. This accompanies the Philcox & Eisenstein (2019) paper and updated documentation is available at ReadTheDocs.

Initial RascalC Release

Initial release of the RascalC code for galaxy correlation function covariance and cross-covariance estimation in arbitrary survey geometries. This is based on Philcox+ 2019. Full documentation is available at ReadTheDocs