grasp2alm.BeamMap.to_alm

BeamMap.to_alm(lmax=None, mmax=None, iter=3, pol=True, use_weights=False, datapath=None, gal_cut=0, use_pixel_weights=False)[source]

Converts the beam map to spherical harmonic coefficients.

Parameters:

  • lmax (int) – Maximum l value for the spherical harmonic expansion.

  • mmax (int) – Maximum m value for the spherical harmonic expansion.

  • iter – int, scalar, optional Number of iteration (default: 3)

  • pol – bool, optional If True, assumes input maps are TQU. Output will be TEB alm’s. (input must be 1 or 3 maps) If False, apply spin 0 harmonic transform to each map. (input can be any number of maps) If there is only one input map, it has no effect. Default: True.

  • use_weights – bool, scalar, optional If True, use the ring weighting. Default: False.

  • datapath – None or str, optional If given, the directory where to find the pixel weights. See in the docstring above details on how to set it up.

  • gal_cut – float [degrees] pixels at latitude in [-gal_cut;+gal_cut] are not taken into account

  • use_pixel_weights – bool, optional If True, use pixel by pixel weighting, healpy will automatically download the weights, if needed

Returns:

The spherical harmonic coefficients.

Return type:

numpy.ndarray

Raises:

AssertionError – If lmax is greater than 3*nside-1 or if mmax is greater than lmax.