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