# coding=utf-8
#author:        4N
#createtime:    2021/3/24
#email:         nheweijun@sina.com

from app.util import *
import traceback
from osgeo import gdal
from osgeo.gdal import *
from numpy import ndarray
import numpy
from flask import Response
import io
import os
from PIL import Image

import time
import cv2
from app.modules.service.image.models import ImageService,Image
from app.models import db
from app.util.component.ApiTemplate import ApiTemplate
import uuid
from app.util.component.SliceScheme import SliceScheme
from app.util.component.FileProcess import FileProcess
from app.util.component.ParameterUtil import ParameterUtil
from app.util.component.GeometryAdapter import GeometryAdapter
import os
import json
from kazoo.client import KazooClient
from app import GLOBAL_DIC
from threading import Thread

from app.modules.service.image.util.ThriftConnect import ThriftConnect
from flask import current_app
import gzip
import random
class Api(ApiTemplate):

    api_name = "切片"

    def __init__(self,guid,level, row, col):
        super().__init__()
        self.guid = guid
        self.level = level
        self.row = row
        self.col = col

    def process(self):

        result = {}
        parameter: dict = self.para

        try:
            if parameter.get("guid"):
                self.guid = parameter.get("guid")

            image_service = ImageService.query.filter_by(guid = self.guid).one_or_none()
            images = image_service.images.all()

            zoo = GLOBAL_DIC.get("zookeeper")
            if zoo is None:
                zoo :KazooClient = KazooClient(hosts=configure.zookeeper, timeout=100)
                zoo.start()
                GLOBAL_DIC["zookeeper"] = zoo
            else :
                if not zoo.connected:
                    zoo.start()

            bands = [1, 2, 3]


            # 转换参数
            parameter = ParameterUtil.to_lower(parameter)


            if parameter.get("tilematrix"):
                if parameter.get("tilematrix").__contains__(":"):
                    self.level = int(parameter.get("tilematrix").split(":")[-1])
                else:
                    self.level = int(parameter.get("tilematrix"))
            if parameter.get("tilerow"):
                self.row = int(parameter.get("tilerow"))
            if parameter.get("tilecol"):
                self.col = int(parameter.get("tilecol"))

            image_type = parameter.get("format") if parameter.get("format") else "image/png"
            quality = int(parameter.get("quality")) if parameter.get("quality") else 30
            slice_para = json.loads(image_service.slice_scheme)
            extent = SliceScheme.get_polygon(slice_para, self.level, self.row, self.col)

            height, width = 256,256

            # 多线程获取分布式数据
            if abs(extent[0])>180:
                intersect_image = [im for im in images if self.determin_intersect(json.loads(im.origin_extent),extent)]
            else:
                intersect_image = [im for im in images if self.determin_intersect(json.loads(im.geo_origin_extent), extent)]


            if len(intersect_image) > 1:

                # 结果矩阵
                empty_list = [numpy.zeros((height, width), dtype=int) + 65536,
                              numpy.zeros((height, width), dtype=int) + 65536,
                              numpy.zeros((height, width), dtype=int) + 65536]

                pixel_array = numpy.zeros((height, width, 3), dtype=int)
                thread_list = []

                for image in intersect_image:
                    # 该影像的服务器，随机选取一个
                    image_servers = image.server.split(",")
                    indx = int(random.random() * len(image_servers))
                    image_server = image_servers[indx]

                    thread: MyThread = MyThread(self.get_data,
                                                args=(zoo, image_server, image, extent, bands, height, width))
                    thread.start()
                    thread_list.append(thread)

                for thread in thread_list:
                    thread.join()
                    data = thread.get_result()

                    # 掩膜在中央接口生成,合图
                    mask = numpy.zeros((height, width), dtype=int)
                    mask2 = numpy.zeros((height, width), dtype=int)
                    jizhun = data[:, :, 0]
                    mask[jizhun == 65536] = 1
                    mask[jizhun != 65536] = 0
                    mask2[jizhun == 65536] = 0
                    mask2[jizhun != 65536] = 1
                    # 掩膜计算
                    for i, d in enumerate(empty_list):
                        empty_list[i] = empty_list[i] * mask + data[:, :, i] * mask2

                for ii in [0, 1, 2]:
                    # opencv 颜色排序为GBR
                    pixel_array[:, :, 2 - ii] = empty_list[ii]


            elif len(intersect_image) == 1:
                # 该影像的服务器，随机选取一个
                image = intersect_image[0]
                image_servers = image.server.split(",")
                indx = int(random.random() * len(image_servers))
                image_server = image_servers[indx]
                pixel_array_t = self.get_data(zoo, image_server, image, extent, bands, height, width)
                pixel_array = numpy.zeros((height, width, 3), dtype=int)
                for ii in [0, 1, 2]:
                    # opencv 颜色排序为GBR
                    pixel_array[:, :, 2 - ii] = pixel_array_t[:, :, ii]


            else:
                # 结果矩阵
                pixel_array = numpy.zeros((height, width, 3), dtype=int) + 65536

            # 将图片生成在内存中,然后直接返回response
            im_data = self.create_by_opencv(image_type, pixel_array, quality)
            return Response(im_data, mimetype=image_type.lower())

        except Exception as e:
            print(traceback.format_exc())
            result["state"] = -1
            result["message"] = e.__str__()
            return result

    def determine_level(self, xysize, origin_extent, extent, max_level):
        '''
        根据范围判断调用金字塔的哪一层
        :param xysize:
        :param origin_extent:
        :param extent:
        :param max_level:
        :return:
        '''
        x = xysize[0]
        y = xysize[1]
        level = -1
        pixel = x * y * (((extent[2] - extent[0]) * (extent[3] - extent[1])) / (
                (origin_extent[2] - origin_extent[0]) * (origin_extent[3] - origin_extent[1])))
        while pixel > 100000 and level < max_level - 1:
            level += 1
            x = x / 2
            y = y / 2
            pixel = x * y * (((extent[2] - extent[0]) * (extent[3] - extent[1])) / (
                    (origin_extent[2] - origin_extent[0]) * (origin_extent[3] - origin_extent[1])))
        return level

    def create_by_opencv(self, image_type, pixel_array, quality):

        if image_type.__eq__("image/jpeg") or image_type.__eq__("image/jpg"):
            r, buf = cv2.imencode(".jpg", pixel_array, [cv2.IMWRITE_JPEG_QUALITY, quality])
            image_out = buf.tobytes()
        else:
            height, width = pixel_array[:, :, 0].shape
            four = numpy.zeros((height, width), dtype=int) + 255
            four[pixel_array[:, :, 0] == 65536] = 0
            r, buf = cv2.imencode(".png", numpy.dstack((pixel_array, four)))
            image_out = buf.tobytes()
        return image_out

    def get_data(self, zoo, image_server, image, extent, bands, height, width):

        if image_server.__eq__("本地服务器"):
            data = self.get_local_wms_data(image, extent, bands, height, width)
        else:
            ser = image_server
            if zoo.exists("/rpc/{}".format(ser)):
                data = self.get_remote_wms_data(image, extent, bands, height, width)
            else:
                data = numpy.zeros((height, width, 3), dtype=int) + 65536

        return data

    def get_remote_wms_data(self, image, extent, bands, height, width):
        '''
        通过RPC获取远程数据
        :param image:
        :param extent:
        :param bands:
        :return:
        '''
        thrift_connect = ThriftConnect(image.server)
        t1 = time.time()
        image_extent = image.origin_extent if abs(extent[0]) > 180 else image.geo_origin_extent

        data = thrift_connect.client.getData(image.path, extent, json.loads(image_extent), bands, width, height)

        thrift_connect.close()
        current_app.logger.info("time {}".format(time.time() - t1))
        data = gzip.decompress(data)
        data = numpy.frombuffer(data, dtype='int64')
        data = data.reshape((height, width, 3))

        return data

    def get_local_wms_data(self, image, extent, bands, height, width):
        '''
        获取本地数据
        :param image:
        :param extent:
        :param bands:
        :return:
        '''
        pixel_array = numpy.zeros((height, width, 3), dtype=int)
        ceng = 0
        img: Dataset = gdal.Open(image.path, 0)
        t1 = time.time()
        for band in bands:

            # 自决定金字塔等级
            xysize = [img.RasterXSize, img.RasterYSize]

            origin_extent = image.origin_extent if abs(extent[0]) > 180 else image.geo_origin_extent
            band_data: Band = img.GetRasterBand(band)

            max_level = band_data.GetOverviewCount()

            # 超出空间范围
            if extent[2] < origin_extent[0] or extent[0] > origin_extent[2] or extent[1] > origin_extent[
                3] or extent[3] < origin_extent[1]:
                empty = numpy.zeros((height, width), dtype=int) + 65536
            # 空间范围相交
            else:
                image_level = self.determine_level(xysize, origin_extent, extent, max_level)

                if image_level == -1:
                    overview = band_data
                else:
                    try:
                        overview: Band = band_data.GetOverview(image_level)
                    except:
                        raise Exception("该影像不存在该级别的金字塔数据！")
                ox = overview.XSize
                oy = overview.YSize

                # 网格大小
                grid_x = (origin_extent[2] - origin_extent[0]) / (ox * 1.0)
                grid_y = (origin_extent[3] - origin_extent[1]) / (oy * 1.0)

                # 完全在影像范围内
                if extent[0] > origin_extent[0] and extent[1] > origin_extent[1] and extent[2] < \
                        origin_extent[2] and extent[3] < origin_extent[3]:

                    # 网格偏移量
                    off_x = math.floor((extent[0] - origin_extent[0]) / grid_x)
                    off_y = math.floor((origin_extent[3] - extent[3]) / grid_y)

                    # 截取后网格个数
                    x_g = math.ceil((extent[2] - extent[0]) / grid_x)

                    y_g = math.ceil((extent[3] - extent[1]) / grid_y)

                    empty = overview.ReadAsArray(off_x, off_y, x_g, y_g, width, height)


                # 部分相交
                else:

                    inter_extent = [0, 0, 0, 0]
                    inter_extent[0] = origin_extent[0] if origin_extent[0] > extent[0] else extent[0]
                    inter_extent[1] = origin_extent[1] if origin_extent[1] > extent[1] else extent[1]
                    inter_extent[2] = origin_extent[2] if origin_extent[2] < extent[2] else extent[2]
                    inter_extent[3] = origin_extent[3] if origin_extent[3] < extent[3] else extent[3]

                    # 网格偏移量
                    off_x = math.floor((inter_extent[0] - origin_extent[0]) / grid_x)
                    off_y = math.floor((origin_extent[3] - inter_extent[3]) / grid_y)

                    # 截取后网格个数
                    x_g = math.floor((inter_extent[2] - inter_extent[0]) / grid_x)
                    y_g = math.floor((inter_extent[3] - inter_extent[1]) / grid_y)

                    # 相对于出图的偏移量

                    # 出图的网格大小
                    out_grid_x = (extent[2] - extent[0]) / (width * 1.0)
                    out_grid_y = (extent[3] - extent[1]) / (height * 1.0)

                    out_off_x = int(math.ceil((inter_extent[0] - extent[0]) / out_grid_x))
                    out_off_y = int(math.ceil((extent[3] - inter_extent[3]) / out_grid_y))

                    out_x_g = int(math.floor((inter_extent[2] - inter_extent[0]) / out_grid_x))
                    out_y_g = int(math.floor((inter_extent[3] - inter_extent[1]) / out_grid_y))

                    # 相交部分在出图的哪个位置

                    overview_raster: ndarray = overview.ReadAsArray(off_x, off_y, x_g, y_g, out_x_g,
                                                                    out_y_g)

                    dat = numpy.zeros((height, width), dtype=int) + 65536
                    dat[out_off_y:out_off_y + out_y_g, out_off_x:out_off_x + out_x_g] = overview_raster

                    empty = dat

            pixel_array[:, :, ceng] = empty
            ceng += 1
        return pixel_array

    def determin_intersect(self, extent1, extent2):
        g1 = GeometryAdapter.envelop_2_polygon(extent1)
        g2 = GeometryAdapter.envelop_2_polygon(extent2)
        return g1.Intersect(g2)

    api_doc = {
        "tags": ["影像接口"],
        "parameters": [
            {"name": "guid",
             "in": "formData",
             "type": "string"},
            {"name": "tilematrix",
             "in": "formData",
             "type": "string"},
            {"name": "tilerow",
             "in": "formData",
             "type": "string"},
            {"name": "tilecol",
             "in": "formData",
             "type": "string"},
            {"name": "format",
             "in": "formData",
             "type": "string"},
            {"name": "quality",
             "in": "formData",
             "type": "string"}

        ],
        "responses": {
            200: {
                "schema": {
                    "properties": {
                    }
                }
            }
        }
    }

class MyThread(Thread):
    def __init__(self,func,args=()):
        super(MyThread,self).__init__()
        self.func = func
        self.args = args
    def run(self):
        self.result = self.func(*self.args)
    def get_result(self):
        try:
            return self.result
        except Exception:
            return None