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, nest=False)

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 pixel weights data. See the docstring of map2alm for details on how to set it up

verbosebool, optional

Deprecated, has not effect.

nestbool, optional

If True, the input map ordering is assumed to be NESTED. Default: False (RING) This function will temporary reorder the NESTED map into RING to perform the smoothing and order the output back to NESTED. If the map is in RING ordering no internal reordering will be performed.

mapsarray or list of 3 arrays

The smoothed map(s)