healpy.sphtfunc.map2alm(maps, lmax=None, mmax=None, iter=3, pol=True, use_weights=False, datapath=None, gal_cut=0, use_pixel_weights=False)

Computes the alm of a Healpix map. The input maps must all be in ring ordering.

mapsarray-like, shape (Npix,) or (n, Npix)

The input map or a list of n input maps. Must be in ring ordering.

lmaxint, scalar, optional

Maximum l of the power spectrum. Default: 3*nside-1

mmaxint, scalar, optional

Maximum m of the alm. Default: lmax

iterint, scalar, optional

Number of iteration (default: 3)

polbool, 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.

datapathNone or str, optional

If given, the directory where to find the weights data.

gal_cutfloat [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

almsarray or tuple of array

alm or a tuple of 3 alm (almT, almE, almB) if polarized input.


The pixels which have the special UNSEEN value are replaced by zeros before spherical harmonic transform. They are converted back to UNSEEN value, so that the input maps are not modified. Each map have its own, independent mask.