# -*- coding: utf-8 -*-


import cv2
import numpy as np
from PIL import Image
#

import raven_utils.decode
from raven_utils.render.const import CENTER, DEFAULT_WIDTH, IMAGE_SIZE

from raven_utils.render_ import COLOR_VALUES, SIZE_VALUES, TYPE_VALUES, ANGLE_VALUES, RENDER_POSITIONS


def imshow(array):
    image = Image.fromarray(array)
    image.show()


def imsave(array, filepath):
    image = Image.fromarray(array)
    image.save(filepath)


def generate_matrix(array_list):
    # row-major array_list
    assert len(array_list) <= 9
    img_grid = np.zeros((IMAGE_SIZE * 3, IMAGE_SIZE * 3), np.uint8)
    for idx in range(len(array_list)):
        i, j = divmod(idx, 3)
        img_grid[i * IMAGE_SIZE:(i + 1) * IMAGE_SIZE, j * IMAGE_SIZE:(j + 1) * IMAGE_SIZE] = array_list[idx]
    # draw grid
    for x in [0.33, 0.67]:
        img_grid[int(x * IMAGE_SIZE * 3) - 1:int(x * IMAGE_SIZE * 3) + 1, :] = 0
    for y in [0.33, 0.67]:
        img_grid[:, int(y * IMAGE_SIZE * 3) - 1:int(y * IMAGE_SIZE * 3) + 1] = 0
    return img_grid


def generate_answers(array_list):
    assert len(array_list) <= 8
    img_grid = np.zeros((IMAGE_SIZE * 2, IMAGE_SIZE * 4), np.uint8)
    for idx in range(len(array_list)):
        i, j = divmod(idx, 4)
        img_grid[i * IMAGE_SIZE:(i + 1) * IMAGE_SIZE, j * IMAGE_SIZE:(j + 1) * IMAGE_SIZE] = array_list[idx]
    # draw grid
    for x in [0.5]:
        img_grid[int(x * IMAGE_SIZE * 2) - 1:int(x * IMAGE_SIZE * 2) + 1, :] = 0
    for y in [0.25, 0.5, 0.75]:
        img_grid[:, int(y * IMAGE_SIZE * 4) - 1:int(y * IMAGE_SIZE * 4) + 1] = 0
    return img_grid


def generate_matrix_answer(array_list):
    # row-major array_list
    assert len(array_list) <= 18
    img_grid = np.zeros((IMAGE_SIZE * 6, IMAGE_SIZE * 3), np.uint8)
    for idx in range(len(array_list)):
        i, j = divmod(idx, 3)
        img_grid[i * IMAGE_SIZE:(i + 1) * IMAGE_SIZE, j * IMAGE_SIZE:(j + 1) * IMAGE_SIZE] = array_list[idx]
    # draw grid
    for x in [0.33, 0.67, 1.00, 1.33, 1.67]:
        img_grid[int(x * IMAGE_SIZE * 3), :] = 0
    for y in [0.33, 0.67]:
        img_grid[:, int(y * IMAGE_SIZE * 3)] = 0
    return img_grid


def merge_matrix_answer(matrix, answer):
    matrix_image = generate_matrix(matrix)
    answer_image = generate_answers(answer)
    img_grid = np.ones((IMAGE_SIZE * 5 + 20, IMAGE_SIZE * 4), np.uint8) * 255
    img_grid[:IMAGE_SIZE * 3, int(0.5 * IMAGE_SIZE):int(3.5 * IMAGE_SIZE)] = matrix_image
    img_grid[-(IMAGE_SIZE * 2):, :] = answer_image
    return img_grid


def render_panels(feature, target=True, angle=None):
    # Decompose the panel into a structure and its entities
    # root
    # rv.decode_output(root)
    # rv.decode_output_reshape(root)
    # decoded =
    # panel = decoded[0]

    # hack due to different order for in_4_out_1
    feature = np.concatenate(
        [
            feature[:, :74],
            feature[:, 86:89],
            feature[:, 77:86],
            feature[:, 74:77],
            feature[:, 89:]
        ],
        axis=-1
    )

    panels = []
    for group, exist, color, size, type_ in zip(*raven_utils.decode.decode_target_flat(feature)):
        canvas = np.ones((IMAGE_SIZE, IMAGE_SIZE), np.uint8) * 255
        structure_img = render_structure(group)
        background = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.uint8)
        # note left components entities are in the lower layer
        for i, entity in enumerate(exist):
            if entity:
                entity_img = render_entity(RENDER_POSITIONS[i], color[i], size[i], type_[i] + 1, angle=angle)
                background = layer_add(background, entity_img)
        background = layer_add(background, structure_img)
        panels.append(canvas - background)
    return np.stack(panels)


def render_structure(structure):
    if structure == 5:
        ret = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.uint8)
        ret[:, int(0.5 * IMAGE_SIZE)] = 255.0
    elif structure == 6:
        ret = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.uint8)
        ret[int(0.5 * IMAGE_SIZE), :] = 255.0
    else:
        ret = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.uint8)
    return ret


def render_entity(bbox, color, size, type_, angle=None):
    color = COLOR_VALUES[color]
    size = SIZE_VALUES[size]
    type_ = TYPE_VALUES[type_]
    if angle is None:
        angle = np.random.randint(0, 7, 1)[0]
    angle = ANGLE_VALUES[angle]
    img = np.zeros((IMAGE_SIZE, IMAGE_SIZE), np.uint8)

    # planar position: [x, y, w, h]
    # angular position: [x, y, w, h, x_c, y_c, omega]
    # center: (columns, rows)
    center = (int(bbox[1] * IMAGE_SIZE), int(bbox[0] * IMAGE_SIZE))
    if type_ == "triangle":
        unit = min(bbox[2], bbox[3]) * IMAGE_SIZE / 2
        dl = int(unit * size)
        pts = np.array([[center[0], center[1] - dl],
                        [center[0] + int(dl / 2.0 * np.sqrt(3)), center[1] + int(dl / 2.0)],
                        [center[0] - int(dl / 2.0 * np.sqrt(3)), center[1] + int(dl / 2.0)]],
                       np.int32)
        pts = pts.reshape((-1, 1, 2))
        color = 255 - color
        width = DEFAULT_WIDTH
        draw_triangle(img, pts, color, width)
    elif type_ == "square":
        unit = min(bbox[2], bbox[3]) * IMAGE_SIZE / 2
        dl = int(unit / 2 * np.sqrt(2) * size)
        pt1 = (center[0] - dl, center[1] - dl)
        pt2 = (center[0] + dl, center[1] + dl)
        color = 255 - color
        width = DEFAULT_WIDTH
        draw_square(img, pt1, pt2, color, width)
    elif type_ == "pentagon":
        unit = min(bbox[2], bbox[3]) * IMAGE_SIZE / 2
        dl = int(unit * size)
        pts = np.array([[center[0], center[1] - dl],
                        [center[0] - int(dl * np.cos(np.pi / 10)), center[1] - int(dl * np.sin(np.pi / 10))],
                        [center[0] - int(dl * np.sin(np.pi / 5)), center[1] + int(dl * np.cos(np.pi / 5))],
                        [center[0] + int(dl * np.sin(np.pi / 5)), center[1] + int(dl * np.cos(np.pi / 5))],
                        [center[0] + int(dl * np.cos(np.pi / 10)), center[1] - int(dl * np.sin(np.pi / 10))]],
                       np.int32)
        pts = pts.reshape((-1, 1, 2))
        color = 255 - color
        width = DEFAULT_WIDTH
        draw_pentagon(img, pts, color, width)
    elif type_ == "hexagon":
        unit = min(bbox[2], bbox[3]) * IMAGE_SIZE / 2
        dl = int(unit * size)
        pts = np.array([[center[0], center[1] - dl],
                        [center[0] - int(dl / 2.0 * np.sqrt(3)), center[1] - int(dl / 2.0)],
                        [center[0] - int(dl / 2.0 * np.sqrt(3)), center[1] + int(dl / 2.0)],
                        [center[0], center[1] + dl],
                        [center[0] + int(dl / 2.0 * np.sqrt(3)), center[1] + int(dl / 2.0)],
                        [center[0] + int(dl / 2.0 * np.sqrt(3)), center[1] - int(dl / 2.0)]],
                       np.int32)
        pts = pts.reshape((-1, 1, 2))
        color = 255 - color
        width = DEFAULT_WIDTH
        draw_hexagon(img, pts, color, width)
    elif type_ == "circle":
        # Minus because of the way we show the image. See: render_panel's return
        color = 255 - color
        unit = min(bbox[2], bbox[3]) * IMAGE_SIZE / 2
        radius = int(unit * size)
        width = DEFAULT_WIDTH
        draw_circle(img, center, radius, color, width)
    elif type_ == "none":
        pass
    # angular
    if len(bbox) > 4:
        # [x, y, w, h, x_c, y_c, omega]
        angle = bbox[6]
        center = (int(bbox[5] * IMAGE_SIZE), int(bbox[4] * IMAGE_SIZE))
        img = rotate(img, angle, center=center)
    # planar 
    else:
        img = rotate(img, angle, center=center)
    # img = shift(img, *entity_position)

    return img


def shift(img, dx, dy):
    M = np.array([[1, 0, dx], [0, 1, dy]], np.float32)
    img = cv2.warpAffine(img, M, (IMAGE_SIZE, IMAGE_SIZE), flags=cv2.INTER_LINEAR)
    return img


def rotate(img, angle, center=CENTER):
    M = cv2.getRotationMatrix2D(center, angle, 1)
    img = cv2.warpAffine(img, M, (IMAGE_SIZE, IMAGE_SIZE), flags=cv2.INTER_LINEAR)
    return img


def scale(img, tx, ty, center=CENTER):
    M = np.array([[tx, 0, center[0] * (1 - tx)], [0, ty, center[1] * (1 - ty)]], np.float32)
    img = cv2.warpAffine(img, M, (IMAGE_SIZE, IMAGE_SIZE), flags=cv2.INTER_LINEAR)
    return img


def layer_add(lower_layer_np, higher_layer_np):
    # higher_layer_np is superimposed on lower_layer_np
    # new_np = lower_layer_np.copy()
    # lower_layer_np is modified
    lower_layer_np[higher_layer_np > 0] = 0
    return lower_layer_np + higher_layer_np


# Draw primitives
def draw_triangle(img, pts, color, width):
    # if filled
    if color != 0:
        # fill the interior
        cv2.fillConvexPoly(img, pts, color)
        # draw the edge
        cv2.polylines(img, [pts], True, 255, width)
    # if not filled
    else:
        cv2.polylines(img, [pts], True, 255, width)


def draw_square(img, pt1, pt2, color, width):
    # if filled
    if color != 0:
        # fill the interior
        cv2.rectangle(img,
                      pt1,
                      pt2,
                      color,
                      -1)
        # draw the edge
        cv2.rectangle(img,
                      pt1,
                      pt2,
                      255,
                      width)
    # if not filled
    else:
        cv2.rectangle(img,
                      pt1,
                      pt2,
                      255,
                      width)


def draw_pentagon(img, pts, color, width):
    # if filled
    if color != 0:
        # fill the interior
        cv2.fillConvexPoly(img, pts, color)
        # draw the edge
        cv2.polylines(img, [pts], True, 255, width)
    # if not filled
    else:
        cv2.polylines(img, [pts], True, 255, width)


def draw_hexagon(img, pts, color, width):
    # if filled
    if color != 0:
        # fill the interior
        cv2.fillConvexPoly(img, pts, color)
        # draw the edge
        cv2.polylines(img, [pts], True, 255, width)
    # if not filled
    else:
        cv2.polylines(img, [pts], True, 255, width)


def draw_circle(img, center, radius, color, width):
    # if filled
    if color != 0:
        # fill the interior
        cv2.circle(img,
                   center,
                   radius,
                   color,
                   -1)
        # draw the edge
        cv2.circle(img,
                   center,
                   radius,
                   255,
                   width)
    # if not filled
    else:
        cv2.circle(img,
                   center,
                   radius,
                   255,
                   width)