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Fonction correlate - module scipy.ndimage

Signature de la fonction correlate

def correlate(input, weights, output=None, mode='reflect', cval=0.0, origin=0) 

Description

correlate.__doc__

    Multidimensional correlation.

    The array is correlated with the given kernel.

    Parameters
    ----------
    input : array_like
        The input array.
    weights : ndarray
        array of weights, same number of dimensions as input
    output : array or dtype, optional
        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.
    mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
        The `mode` parameter determines how the input array is extended
        beyond its boundaries. Default is 'reflect'. Behavior for each valid
        value is as follows:
    
        '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.
    
        '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.
    
        '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.
    
        'wrap' (`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'.
    cval : scalar, optional
        Value to fill past edges of input if `mode` is 'constant'. Default
        is 0.0.
    origin : int or sequence, optional
        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. By passing a sequence of origins with length equal to
        the number of dimensions of the input array, different shifts can
        be specified along each axis.

    Returns
    -------
    result : ndarray
        The result of correlation of `input` with `weights`.

    See Also
    --------
    convolve : Convolve an image with a kernel.

    Examples
    --------
    Correlation is the process of moving a filter mask often referred to
    as kernel over the image and computing the sum of products at each location.

    >>> from scipy.ndimage import correlate
    >>> input_img = np.arange(25).reshape(5,5)
    >>> print(input_img)
    [[ 0  1  2  3  4]
    [ 5  6  7  8  9]
    [10 11 12 13 14]
    [15 16 17 18 19]
    [20 21 22 23 24]]

    Define a kernel (weights) for correlation. In this example, it is for sum of
    center and up, down, left and right next elements.

    >>> weights = [[0, 1, 0],
    ...            [1, 1, 1],
    ...            [0, 1, 0]]

    We can calculate a correlation result:
    For example, element ``[2,2]`` is ``7 + 11 + 12 + 13 + 17 = 60``.

    >>> correlate(input_img, weights)
    array([[  6,  10,  15,  20,  24],
        [ 26,  30,  35,  40,  44],
        [ 51,  55,  60,  65,  69],
        [ 76,  80,  85,  90,  94],
        [ 96, 100, 105, 110, 114]])