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""" 

========================================================= 

Multi-dimensional image processing (:mod:`scipy.ndimage`) 

========================================================= 

 

.. currentmodule:: scipy.ndimage 

 

This package contains various functions for multi-dimensional image 

processing. 

 

 

Filters 

======= 

 

.. autosummary:: 

:toctree: generated/ 

 

convolve - Multi-dimensional convolution 

convolve1d - 1-D convolution along the given axis 

correlate - Multi-dimensional correlation 

correlate1d - 1-D correlation along the given axis 

gaussian_filter 

gaussian_filter1d 

gaussian_gradient_magnitude 

gaussian_laplace 

generic_filter - Multi-dimensional filter using a given function 

generic_filter1d - 1-D generic filter along the given axis 

generic_gradient_magnitude 

generic_laplace 

laplace - n-D Laplace filter based on approximate second derivatives 

maximum_filter 

maximum_filter1d 

median_filter - Calculates a multi-dimensional median filter 

minimum_filter 

minimum_filter1d 

percentile_filter - Calculates a multi-dimensional percentile filter 

prewitt 

rank_filter - Calculates a multi-dimensional rank filter 

sobel 

uniform_filter - Multi-dimensional uniform filter 

uniform_filter1d - 1-D uniform filter along the given axis 

 

Fourier filters 

=============== 

 

.. autosummary:: 

:toctree: generated/ 

 

fourier_ellipsoid 

fourier_gaussian 

fourier_shift 

fourier_uniform 

 

Interpolation 

============= 

 

.. autosummary:: 

:toctree: generated/ 

 

affine_transform - Apply an affine transformation 

geometric_transform - Apply an arbritrary geometric transform 

map_coordinates - Map input array to new coordinates by interpolation 

rotate - Rotate an array 

shift - Shift an array 

spline_filter 

spline_filter1d 

zoom - Zoom an array 

 

Measurements 

============ 

 

.. autosummary:: 

:toctree: generated/ 

 

center_of_mass - The center of mass of the values of an array at labels 

extrema - Min's and max's of an array at labels, with their positions 

find_objects - Find objects in a labeled array 

histogram - Histogram of the values of an array, optionally at labels 

label - Label features in an array 

labeled_comprehension 

maximum 

maximum_position 

mean - Mean of the values of an array at labels 

median 

minimum 

minimum_position 

standard_deviation - Standard deviation of an n-D image array 

sum - Sum of the values of the array 

variance - Variance of the values of an n-D image array 

watershed_ift 

 

Morphology 

========== 

 

.. autosummary:: 

:toctree: generated/ 

 

binary_closing 

binary_dilation 

binary_erosion 

binary_fill_holes 

binary_hit_or_miss 

binary_opening 

binary_propagation 

black_tophat 

distance_transform_bf 

distance_transform_cdt 

distance_transform_edt 

generate_binary_structure 

grey_closing 

grey_dilation 

grey_erosion 

grey_opening 

iterate_structure 

morphological_gradient 

morphological_laplace 

white_tophat 

 

Utility 

======= 

 

.. autosummary:: 

:toctree: generated/ 

 

imread - Load an image from a file 

 

""" 

 

# Copyright (C) 2003-2005 Peter J. Verveer 

# 

# Redistribution and use in source and binary forms, with or without 

# modification, are permitted provided that the following conditions 

# are met: 

# 

# 1. Redistributions of source code must retain the above copyright 

# notice, this list of conditions and the following disclaimer. 

# 

# 2. Redistributions in binary form must reproduce the above 

# copyright notice, this list of conditions and the following 

# disclaimer in the documentation and/or other materials provided 

# with the distribution. 

# 

# 3. The name of the author may not be used to endorse or promote 

# products derived from this software without specific prior 

# written permission. 

# 

# THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS 

# OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 

# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 

# ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY 

# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 

# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE 

# GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 

# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, 

# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 

# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 

# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 

 

from __future__ import division, print_function, absolute_import 

 

from .filters import * 

from .fourier import * 

from .interpolation import * 

from .measurements import * 

from .morphology import * 

from .io import * 

 

__version__ = '2.0' 

 

__all__ = [s for s in dir() if not s.startswith('_')] 

 

from scipy._lib._testutils import PytestTester 

test = PytestTester(__name__) 

del PytestTester