input : array-like
input array to filter
sigma : scalar
standard deviation for Gaussian kernel
axis : integer, optional
axis of input along which to calculate. Default is -1
order : {0, 1, 2, 3}, optional
An order of 0 corresponds to convolution with a Gaussian
kernel. An order of 1, 2, or 3 corresponds to convolution with
the first, second or third derivatives of a Gaussian. Higher
order derivatives are not implemented
output : array, optional
The output parameter passes an array in which to store the
filter output.
mode : {‘reflect’,’constant’,’nearest’,’mirror’, ‘wrap’}, optional
The mode parameter determines how the array borders are
handled, where cval is the value when mode is equal to
‘constant’. Default is ‘reflect’
cval : scalar, optional
Value to fill past edges of input if mode is ‘constant’. Default
is 0.0
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