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Module « scipy.ndimage »

Fonction spline_filter - module scipy.ndimage

Signature de la fonction spline_filter

def spline_filter(input, order=3, output=<class 'numpy.float64'>, mode='mirror') 

Description

help(scipy.ndimage.spline_filter)

Multidimensional spline filter.

Parameters
----------
input : array_like
    The input array.
order : int, optional
    The order of the spline, default is 3.
output : ndarray or dtype, optional
    The array in which to place the output, or the dtype of the returned
    array. Default is ``numpy.float64``.
mode : {'reflect', 'grid-mirror', 'constant', 'grid-constant', 'nearest', 'mirror', 'grid-wrap', 'wrap'}, optional
    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
    :ref:`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.

Returns
-------
spline_filter : ndarray
    Filtered array. Has the same shape as `input`.

See Also
--------
spline_filter1d : Calculate a 1-D spline filter along the given axis.

Notes
-----
The multidimensional filter is implemented as a sequence of
1-D spline filters. The intermediate arrays are stored
in the same data type as the output. Therefore, for output types
with a limited precision, the results may be imprecise because
intermediate results may be stored with insufficient precision.

For complex-valued `input`, this function processes the real and imaginary
components independently.

.. versionadded:: 1.6.0
    Complex-valued support added.

Examples
--------
We can filter an image using multidimensional splines:

>>> from scipy.ndimage import spline_filter
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> orig_img = np.eye(20)  # create an image
>>> orig_img[10, :] = 1.0
>>> sp_filter = spline_filter(orig_img, order=3)
>>> f, ax = plt.subplots(1, 2, sharex=True)
>>> for ind, data in enumerate([[orig_img, "original image"],
...                             [sp_filter, "spline filter"]]):
...     ax[ind].imshow(data[0], cmap='gray_r')
...     ax[ind].set_title(data[1])
>>> plt.tight_layout()
>>> plt.show()

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