spline_filter1d(input, order=3, axis=-1, output=<class 'numpy.float64'>, mode='mirror')
The lines of the array along the given axis are filtered by a spline filter. The order of the spline must be >= 2 and <= 5.
All of the interpolation functions in ndimage do spline interpolation of the input image. If using B-splines of order > 1, the input image values have to be converted to B-spline coefficients first, which is done by applying this 1-D filter sequentially along all axes of the input. All functions that require B-spline coefficients will automatically filter their inputs, a behavior controllable with the prefilter keyword argument. For functions that accept a mode parameter, the result will only be correct if it matches the mode used when filtering.
For complex-valued input, this function processes the real and imaginary components independently.
The input array.
The order of the spline, default is 3.
The axis along which the spline filter is applied. Default is the last axis.
The array in which to place the output, or the dtype of the returned array. Default is numpy.float64
.
The mode parameter determines how the input array is extended beyond its boundaries. Default is 'mirror'. Behavior for each valid value is as follows (see additional plots and details on boundary modes <ndimage-interpolation-modes>
):
'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. This mode is also sometimes referred to as half-sample symmetric.
'grid-mirror'
This is a synonym for 'reflect'.
'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. No interpolation is performed beyond the edges of the input.
'grid-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. Interpolation occurs for samples outside the input's extent as well.
'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. This mode is also sometimes referred to as whole-sample symmetric.
'grid-wrap' (a b c d | a b c d | a b c d)
The input is extended by wrapping around to the opposite edge.
'wrap' (d b c d | a b c d | b c a b)
The input is extended by wrapping around to the opposite edge, but in a way such that the last point and initial point exactly overlap. In this case it is not well defined which sample will be chosen at the point of overlap.
The filtered input.
Calculate a 1-D spline filter along the given axis.
spline_filter
from scipy.ndimage import spline_filter1d
import numpy as np
import matplotlib.pyplot as plt
orig_img = np.eye(20) # create an image
orig_img[10, :] = 1.0
sp_filter_axis_0 = spline_filter1d(orig_img, axis=0)
sp_filter_axis_1 = spline_filter1d(orig_img, axis=1)
f, ax = plt.subplots(1, 3, sharex=True)
for ind, data in enumerate([[orig_img, "original image"],
[sp_filter_axis_0, "spline filter (axis=0)"],
[sp_filter_axis_1, "spline filter (axis=1)"]]):
ax[ind].imshow(data[0], cmap='gray_r')
ax[ind].set_title(data[1])
plt.tight_layout()
plt.show()
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