Calculates contributions to pseudo-Cl for maps with correlated masks. In particular, it extends the Monte Carlo Apodised Spherical Transform EstimatoR (MASTER) approach (https://arxiv.org/abs/astro-ph/0105302) to situations where the map and mask exhibit correlations, as is the case for point source masks used in CMB analyses. If you use the code in a publication, please cite https://arxiv.org/abs/2302.05436.
For a user-inputted map and mask:
Modify or create yaml file similar to moto.yaml
Run: python main.py --config=moto.yaml
For the ensemble-averaged threshold mask operation:
Modify or create yaml file similar to threshold_moto.yaml
Run: python ensemble_threshold.py --config=threshold_moto.yaml
healpy
pywigxjpf
NaMaster
The main output is remastered_curves.p, computed in test_remastered.py. It is a list of seven 1D numpy arrays:
- aa_ww_term: 1D numpy array of length ellmax+1,
$\langle aa \rangle \langle ww \rangle$ term - aw_aw_term: 1D numpy array of length ellmax+1,
$\langle aw \rangle \langle aw \rangle$ term - w_aaw_term: 1D numpy array of length ellmax+1,
$\langle w \rangle \langle aaw \rangle$ term - a_waw_term: 1D numpy array of length ellmax+1,
$\langle a \rangle \langle waw \rangle$ term - aaww_term: 1D numpy array of length ellmax+1,
$\langle aaww \rangle$ term - directly_computed: 1D numpy array of length ellmax+1, directly computed power spectrum of masked map
- remastered: 1D numpy array of length ellmax+1, reMASTERed result for power spectrum of masked map
The bispectrum and trispectrum estimation code is adapted from https://github.com/oliverphilcox/PolyBin.