# Copyright (C) 2003-2005 Peter J. Verveer
#
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# modification, are permitted provided that the following conditions
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# 2. Redistributions in binary form must reproduce the above
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#    disclaimer in the documentation and/or other materials provided
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# 3. The name of the author may not be used to endorse or promote
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from __future__ import division, print_function, absolute_import

import math
import sys

import numpy
from numpy import fft
from numpy.testing import (assert_, assert_equal, assert_array_equal,
                           assert_array_almost_equal, assert_almost_equal)
import pytest
from pytest import raises as assert_raises
from scipy._lib._numpy_compat import suppress_warnings
import scipy.ndimage as ndimage


eps = 1e-12


def sumsq(a, b):
    return math.sqrt(((a - b)**2).sum())


class TestNdimage:
    def setup_method(self):
        # list of numarray data types
        self.integer_types = [
            numpy.int8, numpy.uint8, numpy.int16, numpy.uint16,
            numpy.int32, numpy.uint32, numpy.int64, numpy.uint64]

        self.float_types = [numpy.float32, numpy.float64]

        self.types = self.integer_types + self.float_types

        # list of boundary modes:
        self.modes = ['nearest', 'wrap', 'reflect', 'mirror', 'constant']

    def test_correlate01(self):
        array = numpy.array([1, 2])
        weights = numpy.array([2])
        expected = [2, 4]

        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, expected)

    def test_correlate02(self):
        array = numpy.array([1, 2, 3])
        kernel = numpy.array([1])

        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal(array, output)

        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal(array, output)

        output = ndimage.correlate1d(array, kernel)
        assert_array_almost_equal(array, output)

        output = ndimage.convolve1d(array, kernel)
        assert_array_almost_equal(array, output)

    def test_correlate03(self):
        array = numpy.array([1])
        weights = numpy.array([1, 1])
        expected = [2]

        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, expected)

        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, expected)

    def test_correlate04(self):
        array = numpy.array([1, 2])
        tcor = [2, 3]
        tcov = [3, 4]
        weights = numpy.array([1, 1])
        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, tcov)
        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, tcov)

    def test_correlate05(self):
        array = numpy.array([1, 2, 3])
        tcor = [2, 3, 5]
        tcov = [3, 5, 6]
        kernel = numpy.array([1, 1])
        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal(tcor, output)
        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal(tcov, output)
        output = ndimage.correlate1d(array, kernel)
        assert_array_almost_equal(tcor, output)
        output = ndimage.convolve1d(array, kernel)
        assert_array_almost_equal(tcov, output)

    def test_correlate06(self):
        array = numpy.array([1, 2, 3])
        tcor = [9, 14, 17]
        tcov = [7, 10, 15]
        weights = numpy.array([1, 2, 3])
        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, tcov)
        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, tcov)

    def test_correlate07(self):
        array = numpy.array([1, 2, 3])
        expected = [5, 8, 11]
        weights = numpy.array([1, 2, 1])
        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, expected)
        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, expected)
        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, expected)
        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, expected)

    def test_correlate08(self):
        array = numpy.array([1, 2, 3])
        tcor = [1, 2, 5]
        tcov = [3, 6, 7]
        weights = numpy.array([1, 2, -1])
        output = ndimage.correlate(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve(array, weights)
        assert_array_almost_equal(output, tcov)
        output = ndimage.correlate1d(array, weights)
        assert_array_almost_equal(output, tcor)
        output = ndimage.convolve1d(array, weights)
        assert_array_almost_equal(output, tcov)

    def test_correlate09(self):
        array = []
        kernel = numpy.array([1, 1])
        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal(array, output)
        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal(array, output)
        output = ndimage.correlate1d(array, kernel)
        assert_array_almost_equal(array, output)
        output = ndimage.convolve1d(array, kernel)
        assert_array_almost_equal(array, output)

    def test_correlate10(self):
        array = [[]]
        kernel = numpy.array([[1, 1]])
        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal(array, output)
        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal(array, output)

    def test_correlate11(self):
        array = numpy.array([[1, 2, 3],
                             [4, 5, 6]])
        kernel = numpy.array([[1, 1],
                              [1, 1]])
        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal([[4, 6, 10], [10, 12, 16]], output)
        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal([[12, 16, 18], [18, 22, 24]], output)

    def test_correlate12(self):
        array = numpy.array([[1, 2, 3],
                             [4, 5, 6]])
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        output = ndimage.correlate(array, kernel)
        assert_array_almost_equal([[2, 3, 5], [5, 6, 8]], output)
        output = ndimage.convolve(array, kernel)
        assert_array_almost_equal([[6, 8, 9], [9, 11, 12]], output)

    def test_correlate13(self):
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [4, 5, 6]], type1)
            for type2 in self.types:
                output = ndimage.correlate(array, kernel, output=type2)
                assert_array_almost_equal([[2, 3, 5], [5, 6, 8]], output)
                assert_equal(output.dtype.type, type2)

                output = ndimage.convolve(array, kernel,
                                          output=type2)
                assert_array_almost_equal([[6, 8, 9], [9, 11, 12]], output)
                assert_equal(output.dtype.type, type2)

    def test_correlate14(self):
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [4, 5, 6]], type1)
            for type2 in self.types:
                output = numpy.zeros(array.shape, type2)
                ndimage.correlate(array, kernel,
                                  output=output)
                assert_array_almost_equal([[2, 3, 5], [5, 6, 8]], output)
                assert_equal(output.dtype.type, type2)

                ndimage.convolve(array, kernel, output=output)
                assert_array_almost_equal([[6, 8, 9], [9, 11, 12]], output)
                assert_equal(output.dtype.type, type2)

    def test_correlate15(self):
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [4, 5, 6]], type1)
            output = ndimage.correlate(array, kernel,
                                       output=numpy.float32)
            assert_array_almost_equal([[2, 3, 5], [5, 6, 8]], output)
            assert_equal(output.dtype.type, numpy.float32)

            output = ndimage.convolve(array, kernel,
                                      output=numpy.float32)
            assert_array_almost_equal([[6, 8, 9], [9, 11, 12]], output)
            assert_equal(output.dtype.type, numpy.float32)

    def test_correlate16(self):
        kernel = numpy.array([[0.5, 0],
                              [0, 0.5]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3], [4, 5, 6]], type1)
            output = ndimage.correlate(array, kernel, output=numpy.float32)
            assert_array_almost_equal([[1, 1.5, 2.5], [2.5, 3, 4]], output)
            assert_equal(output.dtype.type, numpy.float32)

            output = ndimage.convolve(array, kernel, output=numpy.float32)
            assert_array_almost_equal([[3, 4, 4.5], [4.5, 5.5, 6]], output)
            assert_equal(output.dtype.type, numpy.float32)

    def test_correlate17(self):
        array = numpy.array([1, 2, 3])
        tcor = [3, 5, 6]
        tcov = [2, 3, 5]
        kernel = numpy.array([1, 1])
        output = ndimage.correlate(array, kernel, origin=-1)
        assert_array_almost_equal(tcor, output)
        output = ndimage.convolve(array, kernel, origin=-1)
        assert_array_almost_equal(tcov, output)
        output = ndimage.correlate1d(array, kernel, origin=-1)
        assert_array_almost_equal(tcor, output)
        output = ndimage.convolve1d(array, kernel, origin=-1)
        assert_array_almost_equal(tcov, output)

    def test_correlate18(self):
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [4, 5, 6]], type1)
            output = ndimage.correlate(array, kernel,
                                       output=numpy.float32,
                                       mode='nearest', origin=-1)
            assert_array_almost_equal([[6, 8, 9], [9, 11, 12]], output)
            assert_equal(output.dtype.type, numpy.float32)

            output = ndimage.convolve(array, kernel,
                                      output=numpy.float32,
                                      mode='nearest', origin=-1)
            assert_array_almost_equal([[2, 3, 5], [5, 6, 8]], output)
            assert_equal(output.dtype.type, numpy.float32)

    def test_correlate19(self):
        kernel = numpy.array([[1, 0],
                              [0, 1]])
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [4, 5, 6]], type1)
            output = ndimage.correlate(array, kernel,
                                       output=numpy.float32,
                                       mode='nearest', origin=[-1, 0])
            assert_array_almost_equal([[5, 6, 8], [8, 9, 11]], output)
            assert_equal(output.dtype.type, numpy.float32)

            output = ndimage.convolve(array, kernel,
                                      output=numpy.float32,
                                      mode='nearest', origin=[-1, 0])
            assert_array_almost_equal([[3, 5, 6], [6, 8, 9]], output)
            assert_equal(output.dtype.type, numpy.float32)

    def test_correlate20(self):
        weights = numpy.array([1, 2, 1])
        expected = [[5, 10, 15], [7, 14, 21]]
        for type1 in self.types:
            array = numpy.array([[1, 2, 3],
                                 [2, 4, 6]], type1)
            for type2 in self.types:
                output = numpy.zeros((2, 3), type2)