""" @Project ：microproduct @File ：AtmosphericDelayDT.py @Function ：主函数 @Author ：LMM @Date ：2021/10/19 14:39 @Version ：1.0.0 """ from osgeo import gdal, gdalconst, osr from tool.algorithm.image.ImageHandle import ImageHandler class DataTransform: """数据转换""" def __int__(self): pass def Cover(self, filepath): """读取数据""" array = ImageHandler().get_data(filepath) return array def get_arr(self, filepath): """读取数据""" testDst = gdal.Open(filepath, gdalconst.GA_Update) width = testDst.RasterXSize height = testDst.RasterYSize band_count = testDst.RasterCount band1 = testDst.GetRasterBand(1) img_arr = band1.ReadAsArray(0, 0, width, height) return img_arr def write_tif(self, out_path, lat_path, lon_path, in_path): lat_arr = self.Cover(lat_path) # 读取lat_rdr lon_arr = self.Cover(lon_path) # 读取lon_rdr in_arr = self.Cover(in_path) # 读取hgt_rdr band = ImageHandler().get_bands(in_path) if band == 2: save_array = in_arr[1, :, :] else: save_array = in_arr """读取数据""" # 转换参数 # lat_res = abs(lat_arr[1, 0]-lat_arr[0, 0]) # lon_res = abs(lon_arr[0, 1] - lon_arr[0, 0]) import numpy as np lon_leftup = np.min(lon_arr[np.nonzero(lon_arr)]) lon_rightup = np.max(lon_arr[np.nonzero(lon_arr)]) lat_leftup = np.max(lat_arr[np.nonzero(lat_arr)]) lat_leftdown = np.min(lat_arr[np.nonzero(lat_arr)]) lon_res1 = (lon_rightup - lon_leftup) / lon_arr.shape[1] lat_res1 = (lat_leftup - lat_leftdown) / lat_arr.shape[0] # 定义投影系 dst_srs = osr.SpatialReference() dst_srs.ImportFromEPSG(4326) # 定义一个WGS84坐标系 im_proj = dst_srs.ExportToWkt() im_geo = [lon_leftup, lon_res1, 0, lat_leftup, 0, -lat_res1] # [(左上角像元的位置), (像元的宽度), (如果影像是指北的，0),(左上角像元的位置),（如果影像是指北的，0）, （像元的高度）] ImageHandler().write_img(out_path, im_proj, im_geo, save_array, no_data='null') def unw_write_tif(self, out_path, lat_path, lon_path, in_path): lat_arr = self.Cover(lat_path) # 读取lat_rdr lon_arr = self.Cover(lon_path) # 读取lon_rdr in_arr = self.Cover(in_path) # 读取hgt_rdr band = ImageHandler().get_bands(in_path) save_array = in_arr """读取数据""" # 转换参数 lat_res = abs(lat_arr[1, 0]-lat_arr[0, 0]) lon_res = abs(lon_arr[0, 1] - lon_arr[0, 0]) # 定义投影系 dst_srs = osr.SpatialReference() dst_srs.ImportFromEPSG(4326) # 定义一个WGS84坐标系 im_proj = dst_srs.ExportToWkt() im_geo = [lon_arr[0][0], lon_res, 0, lat_arr[0][0], 0, -lat_res] # [(左上角像元的位置), (像元的宽度), (如果影像是指北的，0),(左上角像元的位置),（如果影像是指北的，0）, （像元的高度）] ImageHandler().write_img(out_path, im_proj, im_geo, save_array, no_data='null') def write_tif1(self, out_path, lat_path, lon_path, in_path): """输入的in_path数据翻转，输入的lat_path数据翻转""" lat_arr_src = self.Cover(lat_path) # 读取lat_rdr lon_arr_src = self.Cover(lon_path) # 读取lon_rdr in_arr_src = self.Cover(in_path) # 读取hgt_rdr lat_arr2 = lat_arr_src[::-1] lon_arr2 = lon_arr_src band = ImageHandler().get_bands(in_path) if band == 2: save_array = in_arr_src[1, :, :] else: save_array = in_arr_src """读取数据""" # geo = [0, 0, 0, 0, 0, 0] lon_width = ImageHandler().get_img_width(lon_path) # 栅格矩阵的行数 lat_width = ImageHandler().get_img_height(lat_path) # 栅格矩阵的行数 # 转换参数 lat_res = abs(lat_arr2[-1, 0] - lat_arr2[0, 0])/lat_width lon_res = abs(lon_arr2[0, -1] - lon_arr2[0, 0])/lon_width # 定义投影系 dst_srs = osr.SpatialReference() dst_srs.ImportFromEPSG(4326) # 定义一个WGS84坐标系 im_proj = dst_srs.ExportToWkt() im_geo = [lon_arr2[0][0], lon_res, 0, lat_arr2[0][0], 0, -lat_res] # [(左上角像元的位置), (像元的宽度), (如果影像是指北的，0),(左上角像元的位置),（如果影像是指北的，0）, （像元的高度）] ImageHandler().write_img(out_path, im_proj, im_geo, save_array, no_data='null') def tif_vrt(self, tif_path, vrt_path): """ 干涉图.tif重采样为.int的大小 """ delayDst = gdal.Open(tif_path) if delayDst is None: return False delayWidth = delayDst.RasterXSize delayHeight = delayDst.RasterYSize delayBands = delayDst.RasterCount delayArray = delayDst.ReadAsArray(0, 0, delayWidth, delayHeight) testDst = gdal.Open(vrt_path, gdalconst.GA_Update) if testDst is None: return False width = testDst.RasterXSize height = testDst.RasterYSize Bands = testDst.RasterCount band1 = testDst.GetRasterBand(1) # img_arr = band1.ReadAsArray(0, 0, width, height) # 1 if delayWidth!=width or delayHeight!=height or delayBands!=Bands: return False # print("修改前：\t", img_arr[0, 0]) # 1 # print("修改后：\t", delayArray[0, 0]) # 1 band1.WriteArray(delayArray) band1 = None testDst = None img_arr = None # testDst2 = gdal.Open(vrt_path, gdalconst.GA_Update) # 1 # width2 = testDst2.RasterXSize # 1 # height2 = testDst2.RasterYSize # 1 # band12 = testDst2.GetRasterBand(1) # 1 # img_arr2 = band12.ReadAsArray(0, 0, width2, height2) # 1 # print("重新读取后：\t", img_arr2[0, 0]) # 1 # print("over") # 1 return True def read_tif(self, Atmosp_path): testDst=gdal.Open(Atmosp_path,gdalconst.GA_Update) width=testDst.RasterXSize height=testDst.RasterYSize band_count=testDst.RasterCount band1=testDst.GetRasterBand(1) img_arr=band1.ReadAsArray(0,0,width,height) return img_arr def tran(self, vrt_path,Atmo_arr1): testDst=gdal.Open(vrt_path,gdalconst.GA_Update) width=testDst.RasterXSize height=testDst.RasterYSize band_count=testDst.RasterCount band1=testDst.GetRasterBand(1) img_arr=band1.ReadAsArray(0,0,width,height) # print("修改前：\t",img_arr.dtype) # print("修改前：\t",img_arr[500,500]) # print("修改后：\t",Atmo_arr1[500,500]) # print("修改后：\t",Atmo_arr1.dtype) band1.WriteArray(Atmo_arr1) # band1.WriteArray(img_arr) band1.FlushCache() del testDst band1=None testDst=None img_arr=None def tran_af(self, vrt_path): testDst2=gdal.Open(vrt_path, gdalconst.GA_Update) width2=testDst2.RasterXSize height2=testDst2.RasterYSize band_count2=testDst2.RasterCount band12=testDst2.GetRasterBand(1) img_arr2=band12.ReadAsArray(0,0,width2,height2) # print("重新读取后：\t",img_arr2[500,500]) # print("重新读取后：\t", img_arr2.dtype) # print("over")