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 to- footprint=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 - outputparameter passes an array in which to store the filter output.
- mode{‘reflect’,’constant’,’nearest’,’mirror’, ‘wrap’}, optional
- The - modeparameter determines how the array borders are handled, where- cvalis the value when mode is equal to ‘constant’. Default is ‘reflect’
- cvalscalar, optional
- Value to fill past edges of input if - modeis ‘constant’. Default is 0.0
- originscalar, optional
- The - originparameter 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.