medpy.filter.image.average_filter#
- medpy.filter.image.average_filter(input, size=None, footprint=None, output=None, mode='reflect', cval=0.0, origin=0)[source]#
Calculates a multi-dimensional average filter.
- Parameters:
- inputarray-like
input array to filter
- sizescalar or tuple, optional
See footprint, below
- footprintarray, optional
Either size or footprint must be defined. size gives the shape that is taken from the input array, at every element position, to define the input to the filter function. footprint is a boolean array that specifies (implicitly) a shape, but also which of the elements within this shape will get passed to the filter function. Thus
size=(n,m)
is equivalent tofootprint=np.ones((n,m))
. We adjust size to the number of dimensions of the input array, so that, if the input array is shape (10,10,10), and size is 2, then the actual size used is (2,2,2).- outputarray, 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, wherecval
is the value when mode is equal to ‘constant’. Default is ‘reflect’- cvalscalar, optional
Value to fill past edges of input if
mode
is ‘constant’. Default is 0.0- originscalar, optional
The
origin
parameter controls the placement of the filter. Default 0
- Returns:
- average_filterndarray
Returned array of same shape as input.
See also
scipy.ndimage.convolve
Convolve an image with a kernel.
Notes
Convenience implementation employing convolve.