spatial_smooth_cube

FITS_tools.cube_regrid.spatial_smooth_cube(cube, kernelwidth, kernel=<class 'astropy.convolution.kernels.Gaussian2DKernel'>, cubedim=0, numcores=None, use_fft=True, **kwargs)

Parallelized spatial smoothing

Parameters:

cube : ndarray

A data cube, with ndim=3

kernelwidth : float

Width of the kernel. Defaults to Gaussian.

kernel : Kernel2D

A 2D kernel from astropy

cubedim : int

The axis to map across. If you have a normal FITS data cube with AXIS1=RA, AXIS2=Dec, and AXIS3=wavelength, for example, cubedim is 0 (because axis3 -> 0, axis2 -> 1, axis1 -> 2)

numcores : int

Number of cores to use in parallel-processing.

use_fft : bool

Use astropy.convolution.convolve_fft or astropy.convolution.convolve?

kwargs : dict

Passed to convolve