import itertools

import cupy as cp
import numpy as np
import pytest
from cupy.testing import assert_allclose
from cupyx.scipy.ndimage import fourier_shift
from skimage.data import camera, eagle

from cucim.skimage import img_as_float
from cucim.skimage._shared._warnings import expected_warnings
from cucim.skimage._shared.fft import fftmodule as fft
from cucim.skimage.data import binary_blobs
from cucim.skimage.registration._phase_cross_correlation import (
    _upsampled_dft, phase_cross_correlation)


@pytest.mark.parametrize('normalization', [None, 'phase'])
def test_correlation(normalization):
    reference_image = fft.fftn(cp.array(camera()))
    shift = (-7, 12)
    shifted_image = fourier_shift(reference_image, shift)

    # pixel precision
    result, _, _ = phase_cross_correlation(reference_image,
                                           shifted_image,
                                           space="fourier",
                                           normalization=normalization)
    assert_allclose(result[:2], -cp.array(shift))


@pytest.mark.parametrize('normalization', ['nonexisting'])
def test_correlation_invalid_normalization(normalization):
    reference_image = fft.fftn(cp.array(camera()))
    shift = (-7, 12)
    shifted_image = fourier_shift(reference_image, shift)

    # pixel precision
    with pytest.raises(ValueError):
        phase_cross_correlation(reference_image,
                                shifted_image,
                                space="fourier",
                                normalization=normalization)


@pytest.mark.parametrize('normalization', [None, 'phase'])
def test_subpixel_precision(normalization):
    reference_image = fft.fftn(cp.array(camera()))
    subpixel_shift = (-2.4, 1.32)
    shifted_image = fourier_shift(reference_image, subpixel_shift)

    # subpixel precision
    result, _, _ = phase_cross_correlation(reference_image,
                                           shifted_image,
                                           upsample_factor=100,
                                           space="fourier",
                                           normalization=normalization)
    assert_allclose(result[:2], -cp.array(subpixel_shift), atol=0.05)


@pytest.mark.parametrize('dtype', [cp.float16, cp.float32, cp.float64])
def test_real_input(dtype):
    reference_image = cp.array(camera()).astype(dtype, copy=False)
    subpixel_shift = (-2.4, 1.32)
    shifted_image = fourier_shift(fft.fftn(reference_image), subpixel_shift)
    shifted_image = fft.ifftn(shifted_image).real.astype(dtype, copy=False)

    # subpixel precision
    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       upsample_factor=100)
    assert isinstance(result, tuple)
    assert all(isinstance(s, float) for s in result)
    assert_allclose(result[:2], -cp.array(subpixel_shift), atol=0.05)


def test_size_one_dimension_input():
    # take a strip of the input image
    reference_image = fft.fftn(cp.array(camera())[:, 15]).reshape((-1, 1))
    subpixel_shift = (-2.4, 4)
    shifted_image = fourier_shift(reference_image, subpixel_shift)

    # subpixel precision
    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       upsample_factor=20,
                                                       space="fourier")
    assert_allclose(result[:2], -cp.array((-2.4, 0)), atol=0.05)


def test_3d_input():
    phantom = img_as_float(binary_blobs(length=32, n_dim=3))
    reference_image = fft.fftn(phantom)
    shift = (-2.0, 1.0, 5.0)
    shifted_image = fourier_shift(reference_image, shift)

    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       space="fourier")
    assert_allclose(result, -cp.array(shift), atol=0.05)

    # subpixel precision now available for 3-D data

    subpixel_shift = (-2.3, 1.7, 5.4)
    shifted_image = fourier_shift(reference_image, subpixel_shift)
    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       upsample_factor=100,
                                                       space="fourier")
    assert_allclose(result, -cp.array(subpixel_shift), atol=0.05)


def test_unknown_space_input():
    image = cp.ones((5, 5))
    with pytest.raises(ValueError):
        phase_cross_correlation(image, image, space="frank")


def test_wrong_input():
    # Dimensionality mismatch
    image = cp.ones((5, 5, 1))
    template = cp.ones((5, 5))
    with pytest.raises(ValueError):
        phase_cross_correlation(template, image)

    # Size mismatch
    image = cp.ones((5, 5))
    template = cp.ones((4, 4))
    with pytest.raises(ValueError):
        phase_cross_correlation(template, image)

    # NaN values in data
    image = cp.ones((5, 5))
    image[0][0] = cp.nan
    template = cp.ones((5, 5))
    with expected_warnings([r'invalid value encountered in true_divide|\A\Z']):
        with pytest.raises(ValueError):
            phase_cross_correlation(template, image, return_error=True)


def test_4d_input_pixel():
    phantom = img_as_float(binary_blobs(length=32, n_dim=4))
    reference_image = fft.fftn(phantom)
    shift = (-2.0, 1.0, 5.0, -3)
    shifted_image = fourier_shift(reference_image, shift)
    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       space="fourier")
    assert_allclose(result, -cp.array(shift), atol=0.05)


def test_4d_input_subpixel():
    phantom = img_as_float(binary_blobs(length=32, n_dim=4))
    reference_image = fft.fftn(phantom)
    subpixel_shift = (-2.3, 1.7, 5.4, -3.2)
    shifted_image = fourier_shift(reference_image, subpixel_shift)
    result, error, diffphase = phase_cross_correlation(reference_image,
                                                       shifted_image,
                                                       upsample_factor=10,
                                                       space="fourier")
    assert_allclose(result, -cp.array(subpixel_shift), atol=0.05)


def test_mismatch_upsampled_region_size():
    with pytest.raises(ValueError):
        _upsampled_dft(
            cp.ones((4, 4)),
            upsampled_region_size=[3, 2, 1, 4])


def test_mismatch_offsets_size():
    with pytest.raises(ValueError):
        _upsampled_dft(cp.ones((4, 4)), 3,
                       axis_offsets=[3, 2, 1, 4])


@pytest.mark.parametrize(
    ('shift0', 'shift1'),
    itertools.product((100, -100, 350, -350), (100, -100, 350, -350)),
)
def test_disambiguate_2d(shift0, shift1):
    image = cp.array(eagle()[500:, 900:])  # use a highly textured image region
    shift = (shift0, shift1)
    origin0 = []
    for s in shift:
        if s > 0:
            origin0.append(0)
        else:
            origin0.append(-s)
    origin1 = np.array(origin0) + shift
    slice0 = tuple(slice(o, o + 450) for o in origin0)
    slice1 = tuple(slice(o, o + 450) for o in origin1)
    reference = image[slice0]
    moving = image[slice1]
    computed_shift, _, _ = phase_cross_correlation(
        reference, moving, disambiguate=True, return_error='always'
    )
    np.testing.assert_equal(shift, computed_shift)


def test_disambiguate_zero_shift():
    """When the shift is 0, disambiguation becomes degenerate.
    Some quadrants become size 0, which prevents computation of
    cross-correlation. This test ensures that nothing bad happens in that
    scenario.
    """
    image = cp.array(camera())
    computed_shift, _, _ = phase_cross_correlation(
        image, image, disambiguate=True, return_error='always'
    )
    assert computed_shift == (0, 0)
