healpy.sphtfunc.smoothing(map_in, fwhm=0.0, sigma=None, beam_window=None, pol=True, iter=3, lmax=None, mmax=None, use_weights=False, use_pixel_weights=False, datapath=None, verbose=True)

Smooth a map with a Gaussian symmetric beam.

No removal of monopole or dipole is performed.

map_inarray or sequence of 3 arrays

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

fwhmfloat, optional

The full width half max parameter of the Gaussian [in radians]. Default:0.0

sigmafloat, optional

The sigma of the Gaussian [in radians]. Override fwhm.

beam_window: array, optional

Custom beam window function. Override fwhm and sigma.

polbool, 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.

iterint, scalar, optional

Number of iteration (default: 3)

lmaxint, scalar, optional

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

mmaxint, scalar, optional

Maximum m of the alm. Default: lmax

use_weights: bool, scalar, optional

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

use_pixel_weights: bool, optional

If True, use pixel by pixel weighting, healpy will automatically download the weights, if needed See the map2alm docs for details about weighting

datapathNone or str, optional

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

verbosebool, optional

If True prints diagnostic information. Default: True

mapsarray or list of 3 arrays

The smoothed map(s)