gdal/dem.py

import math
import os
import shutil
import tomli
import ezdxf
from osgeo import gdal
import numpy as np
import pandas as pd
from pw import DFile, ControlFile
import dem_utils
from nwed import Nwed
import cad


class Dem:
    def __init__(self, toml_path):
        with open(toml_path, "rb") as tf:
            toml_dict = tomli.load(tf)
        self._toml_dict = toml_dict
        dem_file_path = toml_dict["parameter"]["dem_file_path"]
        self._tree_height = toml_dict["parameter"]["tree_height"]
        self._dataset = gdal.Open(dem_file_path)
        self._dem_resolution = self._dataset.GetGeoTransform()[1]

    def get_dem_info(self, if_print=False):
        """Get the information of DEM data.
        Parameters:
            dem_data <osgeo.gdal.Dataset> -- The data of DEM.
            if_print <bool> -- If print the information of DEM. Default is False (not print).
        Return:
            ... <...> -- The information and parameters of DEM.
        """
        dem_data = self._dataset
        dem_row = dem_data.RasterYSize  # height
        dem_col = dem_data.RasterXSize  # width
        dem_band = dem_data.RasterCount
        dem_gt = dem_data.GetGeoTransform()
        dem_proj = dem_data.GetProjection()

        if if_print:
            print("\nThe information of DEM:")
            print("The number of row (height) is: %d" % dem_row)
            print("The number of column (width) is: %d" % dem_col)
            print("The number of band is: %d" % dem_band)
            print("The 6 GeoTransform parameters are:\n", dem_gt)
            print("The GCS/PCS information is:\n", dem_proj)

        return dem_row, dem_col, dem_band, dem_gt, dem_proj

    def write(self):
        # TODO:不应该设置缩放因数
        dxfs=[]
        zoom_factor = 1
        excel_pfs = self._read_path_file()
        segments = []
        plate_doc = ezdxf.new(dxfversion="R2010")
        plate_msp = plate_doc.modelspace()
        toml_dict = self._toml_dict
        out_dxf_file_dir = toml_dict["parameter"]["out_dxf_file_dir"]
        # 写整个断面
        dm_whole_doc = ezdxf.new(dxfversion="R2004")
        dm_whole_accumulative_distance = 0  # 累加里程
        dm_whole_msp = dm_whole_doc.modelspace()
        for foo in range(len(excel_pfs) - 1):
            start_point_name: str = excel_pfs.iloc[foo, 3]
            end_point_name: str = excel_pfs.iloc[foo + 1, 3]
            point_x_s = float(excel_pfs.iloc[foo, 1])
            point_y_s = float(excel_pfs.iloc[foo, 2])
            point_x_e = float(excel_pfs.iloc[foo + 1, 1])
            point_y_e = float(excel_pfs.iloc[foo + 1, 2])
            line_coordination = self.to_line_coordination(
                point_x_s, point_y_s, point_x_e, point_y_e
            )
            left_elevation = self.get_elevation(line_coordination[:, 0:2])
            center_elevation = self.get_elevation(line_coordination[:, 2:4])
            right_elevation = self.get_elevation(line_coordination[:, 4:6])
            dm_doc = ezdxf.new(dxfversion="R2004")
            # 设置线形
            # for name, desc, pattern in linetypes():
            #     if name not in dm_doc.linetypes:
            #         dm_doc.linetypes.add(
            #             name=name,
            #             pattern=pattern,
            #             description=desc,
            #         )
            dm_msp = dm_doc.modelspace()
            x_axis = [0]
            cord_0 = line_coordination[0, 2:4]  # 取中线的x轴作为横坐标
            for cord in line_coordination[1:, 2:4]:
                x_axis.append(dem_utils.distance(cord, cord_0))
            # 左边线
            left_line = [
                (x_axis[i] / 5 / zoom_factor, left_elevation[i] * 2 / zoom_factor)
                for i in range(len(left_elevation))
            ]
            dm_whole_msp.add_polyline2d(
                np.array(left_line)
                + np.hstack(
                    (
                        dm_whole_accumulative_distance * np.ones((len(x_axis), 1)) / 5,
                        np.zeros((len(x_axis), 1)),
                    )
                ),
                dxfattribs={"color": 1},
            )  # 红色
            dm_msp.add_polyline2d(left_line, dxfattribs={"color": 1})  # 红色
            mid_line = [
                (x_axis[i] / 5 / zoom_factor, center_elevation[i] * 2 / zoom_factor)
                for i in range(len(center_elevation))
            ]  # 中线
            dm_whole_msp.add_polyline2d(
                np.array(mid_line)
                + np.hstack(
                    (
                        dm_whole_accumulative_distance * np.ones((len(x_axis), 1)) / 5,
                        np.zeros((len(x_axis), 1)),
                    )
                )
            )
            dm_msp.add_polyline2d(mid_line)
            # 右边线
            right_line = [
                (x_axis[i] / 5 / zoom_factor, right_elevation[i] * 2 / zoom_factor)
                for i in range(len(right_elevation))
            ]
            dm_whole_msp.add_polyline2d(
                np.array(right_line)
                + np.hstack(
                    (
                        dm_whole_accumulative_distance * np.ones((len(x_axis), 1)) / 5,
                        np.zeros((len(x_axis), 1)),
                    )
                ),
                dxfattribs={"color": 5},  # 蓝色
            )
            dm_msp.add_polyline2d(
                right_line,
                dxfattribs={"color": 5},
            )  # 蓝色
            # 树的线
            # 考虑用最高边线的情况
            tree_line = [
                (
                    x_axis[i] / 5 / zoom_factor,
                    (
                        np.max(
                            (
                                center_elevation[i],
                                left_elevation[i],
                                right_elevation[i],
                            )
                        )
                        + self._tree_height
                    )
                    * 2
                    / zoom_factor,
                )
                for i in range(len(center_elevation))
            ]
            if self._tree_height > 0:
                dm_whole_msp.add_polyline2d(
                    np.array(tree_line)
                    + np.hstack(
                        (
                            dm_whole_accumulative_distance
                            * np.ones((len(x_axis), 1))
                            / 5,
                            np.zeros((len(x_axis), 1)),
                        )
                    ),
                    dxfattribs={"color": 5},
                )
                dm_msp.add_polyline2d(tree_line, dxfattribs={"color": 5})
            dm_whole_accumulative_distance += x_axis[-1]
            os.makedirs(out_dxf_file_dir, exist_ok=True)
            ezdxf.options.set(
                "odafc-addon",
                "win_exec_path",
                "d:/ProgramFiles/ODAFileConverter/ODAFileConverter.exe",
            )
            from ezdxf.addons.odafc import export_dwg

            # export_dwg(
            #     dm_doc,
            #     f"{out_dxf_file_dir}/D{100+int(start_point_name[1:])}.dwg",
            #     replace=True,
            # )  # 写断面文件
            dm_doc.saveas(f"{out_dxf_file_dir}/D{100+int(start_point_name[1:])}.dxf",)
            dxfs.append(f"{out_dxf_file_dir}/D{100+int(start_point_name[1:])}.dxf")
            # 写Z文件
            z_file_path = f"{out_dxf_file_dir}/ZD{100+int(start_point_name[1:])}"
            with open(z_file_path, "w") as z_file:
                z_file.write("0     ")
                z_file.write(f"{center_elevation[0]*2}     ")
                z_file.write("0     ")
                z_file.write("0     ")
                z_file.write(f"{center_elevation[0]*2-50}")
            if foo == 0:
                # copy file a to dist b
                shutil.copy(z_file_path, f"{out_dxf_file_dir}/ZDA")
            # 写平面文件
            plate_msp.add_polyline2d(
                line_coordination[:, 0:2],
                dxfattribs={"color": 1},
            )  # 红色
            plate_msp.add_polyline2d(
                line_coordination[:, 2:4],
            )
            plate_msp.add_polyline2d(
                line_coordination[:, 4:6],
                dxfattribs={"color": 5},
            )  # 蓝色
            mileage = [0]
            start_point = line_coordination[0, 2:4]
            for bar in line_coordination[1:, 2:4]:
                mileage.append(round(dem_utils.distance(start_point, bar)))
            mileage = np.array(mileage)
            start_num = 4000 + int(start_point_name[1:])
            segments.append(start_num)
            end_num = 4000 + int(end_point_name[1:])
            if foo == len(excel_pfs) - 2:
                segments.append(end_num)
            d_file = DFile(
                start_num,
                end_num,
                mileage,
                center_elevation,
                left_elevation,
                right_elevation,
                self._tree_height,
            )
            d_file.save(out_dxf_file_dir)
            self._copy_db_file()
            tower_start_num = toml_dict["parameter"]["tower_number_start"]
            control_file_template_path = toml_dict["parameter"][
                "control_file_template_path"
            ]
            c_file = ControlFile(
                segments, tower_start_num, control_file_template_path, out_dxf_file_dir
            )
            c_file.save()
            ##################
            ##################
            # 写nwed
            section_name = f"{100+int(start_point_name[1:])}"
            licheng = f"{mileage[-1]}"
            remarks_start = f"{int(start_point_name[1:])}"
            pole_name_start = f"{start_num}"
            remarks_end = f"{int(end_point_name[1:])}"
            pole_name_end = f"{end_num}"
            toml_dict = self._toml_dict
            side_width = toml_dict["parameter"]["side_width"]  # 边线宽度
            verticalExtent2 = f"{side_width}"
            mid_vec_list = list(map(lambda x: [f"{x[0]*5}", f"{x[1]/2}"], mid_line))
            right_vec_list = list(map(lambda x: [f"{x[0]*5}", f"{x[1]/2}"], right_line))
            left_vec_list = list(map(lambda x: [f"{x[0]*5}", f"{x[1]/2}"], left_line))
            nwed = Nwed(
                section_name,
                licheng,
                remarks_start,
                pole_name_start,
                remarks_end,
                pole_name_end,
                verticalExtent2,
                mid_vec_list,
                right_vec_list,
                left_vec_list,
            )
            nwed.write(
                f"{out_dxf_file_dir}/{100+int(start_point_name[1:])}.nwed",
            )
        # 写整个断面文件
        # export_dwg(
        #     dm_whole_doc,
        #     f"{out_dxf_file_dir}/DA.dwg",
        #     replace=True,
        # )
        dm_whole_doc.saveas(f"{out_dxf_file_dir}/DA.dxf")
        # cad.convert_dxf_to_dwg([f"{out_dxf_file_dir}/DA.dxf"])
        dxfs.append(f"{out_dxf_file_dir}/DA.dxf")
        # 写平面文件
        plate_doc.saveas(f"{out_dxf_file_dir}/plate.dxf")
        dxfs.append(f"{out_dxf_file_dir}/plate.dxf")
        cad.convert_dxf_to_dwg(dxf_files=dxfs)

    def get_elevation(self, site_x_y):
        """Get the elevation of given locations from DEM in GCS.
        Parameters:
            dem_gcs <osgeo.gdal.Dataset> -- The input DEM (in GCS).
            site_latlng <numpy.ndarray> -- The latitude and longitude of given locations.
        Return:
            site_ele <numpy.ndarray> -- The elevation and other information of given locations.
        """
        gdal_data = self._dataset

        # gdal_band = gdal_data.GetRasterBand(1)
        # nodataval = gdal_band.GetNoDataValue()
        # if np.any(gdal_array == nodataval):
        #     gdal_array[gdal_array == nodataval] = np.nan

        gt = gdal_data.GetGeoTransform()
        # print("\nThe 6 GeoTransform parameters of DEM are:\n", gt)

        N_site = site_x_y.shape[0]
        Xgeo = site_x_y[:, 0]
        Ygeo = site_x_y[:, 1]
        site_ele = np.zeros(N_site)
        for i in range(N_site):
            # Note:
            #     Xgeo = gt[0] + Xpixel * gt[1] + Yline * gt[2]
            #     Ygeo = gt[3] + Xpixel * gt[4] + Yline * gt[5]
            #
            #     Xpixel - Pixel/column of DEM
            #     Yline - Line/row of DEM
            #
            #     Xgeo - Longitude
            #     Ygeo - Latitude
            #
            #     [0] = Longitude of left-top pixel
            #     [3] = Latitude of left-top pixel
            #
            #     [1] = + Pixel width
            #     [5] = - Pixel height
            #
            #     [2] = 0 for north up DEM
            #     [4] = 0 for north up DEM
            Xpixel = (Xgeo[i] - gt[0]) / gt[1]
            Yline = (Ygeo[i] - gt[3]) / gt[5]
            # 寻找左上，左下，右上，右下4个点
            lu_xy = np.array([math.floor(Xpixel), math.ceil(Yline)])  # 左上
            ld_xy = np.array([math.floor(Xpixel), math.floor(Yline)])  # 左下
            ru_xy = np.array([math.ceil(Xpixel), math.ceil(Yline)])  # 右上
            rd_xy = np.array([math.ceil(Xpixel), math.floor(Yline)])  # 右下
            lu_elevation = gdal_data.ReadAsArray(
                int(lu_xy[0]), int(lu_xy[1]), 1, 1
            ).astype(float)
            ld_elevation = gdal_data.ReadAsArray(
                int(ld_xy[0]), int(ld_xy[1]), 1, 1
            ).astype(float)
            ru_elevation = gdal_data.ReadAsArray(
                int(ru_xy[0]), int(ru_xy[1]), 1, 1
            ).astype(float)
            rd_elevation = gdal_data.ReadAsArray(
                int(rd_xy[0]), int(rd_xy[1]), 1, 1
            ).astype(float)
            # 依据https://blog.csdn.net/jameschen9051/article/details/109469228中的公司
            point_z = (
                lu_elevation[0]
                * (
                    (1 - math.fabs(Xpixel - lu_xy[0]))
                    * (1 - math.fabs(Yline - lu_xy[1]))
                )
                + ld_elevation[0]
                * (
                    (1 - math.fabs(Xpixel - ld_xy[0]))
                    * (1 - math.fabs(Yline - ld_xy[1]))
                )
                + ru_elevation[0]
                * (
                    (1 - math.fabs(Xpixel - ru_xy[0]))
                    * (1 - math.fabs(Yline - ru_xy[1]))
                )
                + rd_elevation[0]
                * (
                    (1 - math.fabs(Xpixel - rd_xy[0]))
                    * (1 - math.fabs(Yline - rd_xy[1]))
                )
            )
            site_ele[i] = point_z
            pass
        return site_ele

    def to_line_coordination(self, point_x_s, point_y_s, point_x_e, point_y_e):
        path_length = (
            (point_x_s - point_x_e) ** 2 + (point_y_s - point_y_e) ** 2
        ) ** 0.5
        dem_resolution = self._dem_resolution  # dem的精度
        # TODO:设定为5m 1个点。
        # n = round(path_length / dem_resolution)
        n = round(path_length / 5)
        center_point_x = np.linspace(point_x_s, point_x_e, n, endpoint=True)
        center_point_y = np.linspace(point_y_s, point_y_e, n, endpoint=True)
        # 计算左右边线
        # 计算角度
        toml_dict = self._toml_dict
        side_width = toml_dict["parameter"]["side_width"]  # 边线宽度
        _line_angel = math.atan((point_y_e - point_y_s) / (point_x_e - point_x_s))
        if point_x_e < point_x_s:
            line_angel = _line_angel + math.pi
        else:
            line_angel = _line_angel
        left_offset_x = side_width * math.cos(line_angel + math.pi / 2)
        left_offset_y = side_width * math.sin(line_angel + math.pi / 2)
        left_offset_point_x = center_point_x + left_offset_x
        left_offset_point_y = center_point_y + left_offset_y
        right_offset_point_x = center_point_x - left_offset_x  # 向左偏移和向右偏移正好是相反的
        right_offset_point_y = center_point_y - left_offset_y
        r = np.array(
            [
                np.array(left_offset_point_x),
                np.array(left_offset_point_y),
                center_point_x,
                center_point_y,
                np.array(right_offset_point_x),
                np.array(right_offset_point_y),
            ]
        ).T
        return r

    def _read_path_file(self):
        toml_dict = self._toml_dict
        path_file = toml_dict["parameter"]["path_file"]
        excel_pds = pd.read_excel(path_file, header=None)
        return excel_pds

    def _copy_db_file(self):
        toml_dict = self._toml_dict
        db_file_dir = toml_dict["parameter"]["db_file_dir"]
        out_dxf_file_dir = toml_dict["parameter"]["out_dxf_file_dir"]
        shutil.copy(f"{db_file_dir}/Tower.db", f"{out_dxf_file_dir}/Tower.db")
        shutil.copy(f"{db_file_dir}/ATMOS.db", f"{out_dxf_file_dir}/ATMOS.db")
        shutil.copy(f"{db_file_dir}/Fit.db", f"{out_dxf_file_dir}/Fit.db")
        shutil.copy(f"{db_file_dir}/RULE.db", f"{out_dxf_file_dir}/RULE.db")
        shutil.copy(f"{db_file_dir}/WIRE.db", f"{out_dxf_file_dir}/WIRE.db")