scipy.ndimage.minimum_filter1d

scipy.ndimage.minimum_filter1d(input, size, axis=-1, output=None, mode='reflect', cval=0.0, origin=0)

Calculate a one-dimensional minimum filter along the given axis.

The lines of the array along the given axis are filtered with a minimum filter of given size.

Parameters:

input : array_like

Input array to filter.

size : int

length along which to calculate 1D minimum

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.

Notes

This function implements the MINLIST algorithm [R183], as described by Richard Harter [R184], and has a guaranteed O(n) performance, n being the input length, regardless of filter size.

References

[R183]

(1, 2) http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.2777

[R184]

(1, 2) http://www.richardhartersworld.com/cri/2001/slidingmin.html

Examples

>>> from scipy.ndimage import minimum_filter1d
>>> minimum_filter1d([2, 8, 0, 4, 1, 9, 9, 0], size=3)
array([2, 0, 0, 0, 1, 1, 0, 0])