# scipy.ndimage.spline_filter

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

  Multidimensional spline filter.

  For more details, see `spline_filter1d`.

  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.

  New in version 1.6.0: Complex-valued support added.

  Examples

  We can filter an image using multidimentional splines:

      >>> from scipy.ndimage import spline_filter
      >>> 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()

scipy.ndimage.shift scipy.ndimage.spline_filter1d