scipy.ndimage.generic_gradient_magnitude(input, derivative, output=None, mode='reflect', cval=0.0, extra_arguments=(), extra_keywords=None)[source]

Gradient magnitude using a provided gradient function.


The input array.


Callable with the following signature:

derivative(input, axis, output, mode, cval,
           *extra_arguments, **extra_keywords)

See extra_arguments, extra_keywords below. derivative can assume that input and output are ndarrays. Note that the output from derivative is modified inplace; be careful to copy important inputs before returning them.

outputarray or dtype, optional

The array in which to place the output, or the dtype of the returned array. By default an array of the same dtype as input will be created.

modestr or sequence, optional

The mode parameter determines how the input array is extended when the filter overlaps a border. By passing a sequence of modes with length equal to the number of dimensions of the input array, different modes can be specified along each axis. Default value is ‘reflect’. The valid values and their behavior is as follows:

‘reflect’ (d c b a | a b c d | d c b a)

The input is extended by reflecting about the edge of the last pixel.

‘constant’ (k k k k | a b c d | k k k k)

The input is extended by filling all values beyond the edge with the same constant value, defined by the cval parameter.

‘nearest’ (a a a a | a b c d | d d d d)

The input is extended by replicating the last pixel.

‘mirror’ (d c b | a b c d | c b a)

The input is extended by reflecting about the center of the last pixel.

‘wrap’ (a b c d | a b c d | a b c d)

The input is extended by wrapping around to the opposite edge.

cvalscalar, optional

Value to fill past edges of input if mode is ‘constant’. Default is 0.0.

extra_keywordsdict, optional

dict of extra keyword arguments to pass to passed function.

extra_argumentssequence, optional

Sequence of extra positional arguments to pass to passed function.

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