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Fonction map_coordinates - module scipy.ndimage

Signature de la fonction map_coordinates

def map_coordinates(input, coordinates, output=None, order=3, mode='constant', cval=0.0, prefilter=True) 

Description

map_coordinates.__doc__

    Map the input array to new coordinates by interpolation.

    The array of coordinates is used to find, for each point in the output,
    the corresponding coordinates in the input. The value of the input at
    those coordinates is determined by spline interpolation of the
    requested order.

    The shape of the output is derived from that of the coordinate
    array by dropping the first axis. The values of the array along
    the first axis are the coordinates in the input array at which the
    output value is found.

    Parameters
    ----------
    input : array_like
        The input array.
    coordinates : array_like
        The coordinates at which `input` is evaluated.
    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.
    order : int, optional
        The order of the spline interpolation, default is 3.
        The order has to be in the range 0-5.
    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 'constant'. 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.
    cval : scalar, optional
        Value to fill past edges of input if `mode` is 'constant'. Default
        is 0.0.
    prefilter : bool, optional
        Determines if the input array is prefiltered with `spline_filter`
        before interpolation. The default is True, which will create a
        temporary `float64` array of filtered values if `order > 1`. If
        setting this to False, the output will be slightly blurred if
        `order > 1`, unless the input is prefiltered, i.e. it is the result
        of calling `spline_filter` on the original input.

    Returns
    -------
    map_coordinates : ndarray
        The result of transforming the input. The shape of the output is
        derived from that of `coordinates` by dropping the first axis.

    See Also
    --------
    spline_filter, geometric_transform, scipy.interpolate

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

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

    Examples
    --------
    >>> from scipy import ndimage
    >>> a = np.arange(12.).reshape((4, 3))
    >>> a
    array([[  0.,   1.,   2.],
           [  3.,   4.,   5.],
           [  6.,   7.,   8.],
           [  9.,  10.,  11.]])
    >>> ndimage.map_coordinates(a, [[0.5, 2], [0.5, 1]], order=1)
    array([ 2.,  7.])

    Above, the interpolated value of a[0.5, 0.5] gives output[0], while
    a[2, 1] is output[1].

    >>> inds = np.array([[0.5, 2], [0.5, 4]])
    >>> ndimage.map_coordinates(a, inds, order=1, cval=-33.3)
    array([  2. , -33.3])
    >>> ndimage.map_coordinates(a, inds, order=1, mode='nearest')
    array([ 2.,  8.])
    >>> ndimage.map_coordinates(a, inds, order=1, cval=0, output=bool)
    array([ True, False], dtype=bool)