convolve1d(input, weights, axis=-1, output=None, mode='reflect', cval=0.0, origin=0)
The lines of the array along the given axis are convolved with the given weights.
The input array.
1-D sequence of numbers.
The axis of :None:None:`input` along which to calculate. Default is -1.
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.
The :None:None:`mode` parameter determines how the input array is extended beyond its boundaries. Default is 'reflect'. Behavior for each valid value is as follows:
'reflect' (:None:None:`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. This mode is also sometimes referred to as half-sample symmetric.
'constant' (:None:None:`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 :None:None:`cval` parameter.
'nearest' (:None:None:`a a a a | a b c d | d d d d`)
The input is extended by replicating the last pixel.
'mirror' (:None:None:`d c b | a b c d | c b a`)
The input is extended by reflecting about the center of the last pixel. This mode is also sometimes referred to as whole-sample symmetric.
'wrap' (:None:None:`a b c d | a b c d | a b c d`)
The input is extended by wrapping around to the opposite edge.
For consistency with the interpolation functions, the following mode names can also be used:
'grid-mirror'
This is a synonym for 'reflect'.
'grid-constant'
This is a synonym for 'constant'.
'grid-wrap'
This is a synonym for 'wrap'.
Value to fill past edges of input if :None:None:`mode` is 'constant'. Default is 0.0.
Controls the placement of the filter on the input array's pixels. A value of 0 (the default) centers the filter over the pixel, with positive values shifting the filter to the left, and negative ones to the right.
Convolved array with same shape as input
Calculate a 1-D convolution along the given axis.
>>> from scipy.ndimage import convolve1dSee :
... convolve1d([2, 8, 0, 4, 1, 9, 9, 0], weights=[1, 3]) array([14, 24, 4, 13, 12, 36, 27, 0])
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.ndimage._filters.convolve1d
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