import cv2 as cv

def hue_constant_interpolation(_mosaic):
    _mosaic = cv.normalize(_mosaic.astype('double'), None, 0.0, 1.0, cv.NORM_MINMAX)
    # split the image into three channel
    b, g, r = cv.split(_mosaic)

    # set the value which is useless to 0
    b = fill_with_zero_b(b)
    g = fill_with_zero_g(g)
    r = fill_with_zero_r(r)

    # do the linear interpolation for green channel
    g = bilinear_interpolation_g(g)

    # using the estimated green channel to calculate
    # the red and blue channels, hue has been interpolated
    g = cv.copyMakeBorder(g, 1, 1, 1, 1, cv.BORDER_REFLECT)
    b = hue_constant_channel_b(b, g)
    r = hue_constant_channel_r(r, g)

    return cv.merge((b, g, r))


def hue_constant_channel_r(estimating, interpolated):
    estimating = cv.copyMakeBorder(estimating, 1, 1, 1, 1, cv.BORDER_REFLECT)
    e_row_num = len(estimating)
    for row in range(1, e_row_num - 1):
        e_col_num = len(estimating[row])
        interpolated_row_median = np.median(interpolated[row])
        for col in range(1, e_col_num - 1):
            if row % 2 != 0 and col % 2 == 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row][col - 1]
                    g2 = interpolated[row][col + 1]
                    estimating[row][col] = 0.5 * interpolated[row][col] * (
                        estimating[row][col - 1] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row][col + 1] / (g2 if g2 != 0 else interpolated_row_median)
                    )

            elif row % 2 == 0 and col % 2 != 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row - 1][col]
                    g2 = interpolated[row + 1][col]
                    estimating[row][col] = 0.5 * interpolated[row][col] * (
                        estimating[row - 1][col] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row + 1][col] / (g2 if g2 != 0 else interpolated_row_median)
                    )

            elif row % 2 == 0 and col % 2 == 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row - 1][col - 1]
                    g2 = interpolated[row - 1][col + 1]
                    g3 = interpolated[row + 1][col - 1]
                    g4 = interpolated[row + 1][col + 1]
                    estimating[row][col] = 0.25 * interpolated[row][col] * (
                        estimating[row - 1][col - 1] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row - 1][col + 1] / (g2 if g2 != 0 else interpolated_row_median)
                        + estimating[row + 1][col - 1] / (g3 if g3 != 0 else interpolated_row_median)
                        + estimating[row + 1][col + 1] / (g4 if g4 != 0 else interpolated_row_median)
                    )

    return estimating


def hue_constant_channel_b(estimating, interpolated):
    estimating = cv.copyMakeBorder(estimating, 1, 1, 1, 1, cv.BORDER_REFLECT)
    e_row_num = len(estimating)
    for row in range(1, e_row_num - 1):
        e_col_num = len(estimating[row])
        interpolated_row_median = np.median(interpolated[row])
        for col in range(1, e_col_num - 1):
            if row % 2 == 0 and col % 2 != 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row][col - 1]
                    g2 = interpolated[row][col + 1]
                    estimating[row][col] = 0.5 * interpolated[row][col] * (
                        estimating[row][col - 1] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row][col + 1] / (g2 if g2 != 0 else interpolated_row_median)
                    )

            elif row % 2 != 0 and col % 2 == 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row - 1][col]
                    g2 = interpolated[row + 1][col]
                    estimating[row][col] = 0.5 * interpolated[row][col] * (
                        estimating[row - 1][col] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row + 1][col] / (g2 if g2 != 0 else interpolated_row_median)
                    )

            elif row % 2 != 0 and col % 2 != 0:
                if estimating[row][col] == 0:
                    g1 = interpolated[row - 1][col - 1]
                    g2 = interpolated[row - 1][col + 1]
                    g3 = interpolated[row + 1][col - 1]
                    g4 = interpolated[row + 1][col + 1]
                    estimating[row][col] = 0.25 * interpolated[row][col] * (
                        estimating[row - 1][col - 1] / (g1 if g1 != 0 else interpolated_row_median)
                        + estimating[row - 1][col + 1] / (g2 if g2 != 0 else interpolated_row_median)
                        + estimating[row + 1][col - 1] / (g3 if g3 != 0 else interpolated_row_median)
                        + estimating[row + 1][col + 1] / (g4 if g4 != 0 else interpolated_row_median)
                    )

    return estimating