Smooth a numeric array with a Gaussian kernel
Description
This function smoothes an array using a Gaussian kernel with a specified standard deviation.
Usage
1  gaussianSmooth(x, sigma)

Arguments
x 
An object that can be coerced to an array, or for which a

sigma 
A numeric vector giving the standard deviation of the kernel in each dimension. Can have lower dimensionality than the target array. 
Details
This implementation takes advantage of the separability of the Gaussian kernel for speed when working in multiple dimensions. It is therefore equivalent to, but much faster than, directly applying a multidimensional kernel.
Value
A morphed array with the same dimensions as the original array.
Author(s)
Jon Clayden <code@clayden.org>
See Also
morph
for the function underlying this operation,
gaussianKernel
for generating Gaussian kernels (which is
also used by this function), and erode
for mathematical
morphology functions.
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