scipy.ndimage.maximum_filter1d¶
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scipy.ndimage.
maximum_filter1d
(input, size, axis=-1, output=None, mode='reflect', cval=0.0, origin=0)[source]¶ Calculate a one-dimensional maximum filter along the given axis.
The lines of the array along the given axis are filtered with a maximum filter of given size.
Parameters: input : array_like
Input array to filter.
size : int
Length along which to calculate the 1-D maximum.
axis : int, optional
The axis of input along which to calculate. Default is -1.
output : array, optional
The output parameter passes an array in which to store the filter output. Output array should have different name as compared to input array to avoid aliasing errors.
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
origin : scalar, optional
The origin parameter controls the placement of the filter. Default 0.0.
Returns: maximum1d : ndarray, None
Maximum-filtered array with same shape as input. None if output is not None
Notes
This function implements the MAXLIST algorithm [R181], as described by Richard Harter [R182], and has a guaranteed O(n) performance, n being the input length, regardless of filter size.
References
[R181] (1, 2) http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.2777 [R182] (1, 2) http://www.richardhartersworld.com/cri/2001/slidingmin.html Examples
>>> from scipy.ndimage import maximum_filter1d >>> maximum_filter1d([2, 8, 0, 4, 1, 9, 9, 0], size=3) array([8, 8, 8, 4, 9, 9, 9, 9])