Changes from version 5.0 to 5.1

A complete list of all new features and changes is given below. Relevant PRs and Issues, whose issue numbers are listed below for the relevant items.

API Changes

This isn’t quite an API change, but it’s worth highlighting. We left the default behavior of the cross_patch_weight to match the behavior of previous versions of TreeCorr. However, it now emits a warning that you should probably switch to using cross_patch_weight='match' for jackknife covariances or cross_patch_weight='geom' for bootstrap covariances. We may in the future switch these to be the default values, so if you want any existing scripts you have to keep the current behavior, you should explicitly set cross_patch_weight='simple' to avoid the warning. And if you want the improved weighting, you should update your script to the appropriate value. (#180)

Added an option to the process commands, corr_only=True, which will skip the computations of ancillary quantities like meanlogr, meanphi, and npairs, which are not necessary for the calculation of the correlation function. This doesn’t make much difference for most classes, but for NNCorrelation, it can be a significant speedup. (#182)

Added many new classes for three-point functions with mixed field types in the different vertices, such as NNG, NKK, KGK, etc. See Three-point Correlation Functions for details about all the new classes. (#32, #178, #179, #181)
Added the ability to use the metrics Rlens and Rperp with three-point correlations. (#177, #184)
Added the ability to use min_rpar and max_rpar with three-point correlations. (#177, #184)
Added a new option for how to handle pairs that cross between two patches when doing patch-based covariance estimates. This work is based on the paper by Mohammad and Percival (2022), who recommend using “match” for jackknife covariances and “geom” for bootstrap= covariances. The default is called “simple” and is the same behavior as what TreeCorr has been doing in previous versions, but we recommend users explicitly set cross_patch_weight to the appropriate value to take advantage of the more optimal weighting. (#180, #183)

Fixed an error in the manifest, which omitted a file from the source distribution on pypi.