healpy.sphtfunc.smoothing

healpy.sphtfunc.smoothing(maps, fwhm=0.0, sigma=None, invert=False, pol=True, iter=3, lmax=None, mmax=None, use_weights=False, regression=True, datapath=None)

Smooth a map with a Gaussian symmetric beam.

Parameters :

maps : array or sequence of 3 arrays

Either an array representing one map, or a sequence of 3 arrays representing 3 maps

fwhm : float, optional

The full width half max parameter of the Gaussian. Default:0.0

sigma : float, optional

The sigma of the Gaussian. Override fwhm.

invert : bool, optional

If True, alms are divided by Gaussian beam function (un-smooth). Otherwise, alms are multiplied by Gaussian beam function (smooth). Default: False.

pol : bool, optional

If True, assumes input maps are TQU. Output will be TQU maps. (input must be 1 or 3 alms) If False, each map is assumed to be a spin 0 map and is treated independently (input can be any number of alms). If there is only one input map, it has no effect. Default: True.

iter : int, scalar, optional

Number of iteration (default: 3)

lmax : int, scalar, optional

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

mmax : int, scalar, optional

Maximum m of the alm. Default: lmax

use_weights: bool, scalar, optional :

If True, use the ring weighting. Default: False.

regression: bool, scalar, optional :

If True, subtract map average before computing alm. Default: True.

datapath : None or str, optional

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

Returns :

maps : array or list of 3 arrays

The smoothed map(s)

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