552 lines
21 KiB
Python
552 lines
21 KiB
Python
from osgeo import gdal
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import math,os
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import time
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from sklearn.cluster import k_means
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from rscder.utils.geomath import geo2imageRC, imageRC2geo
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from rscder.utils.project import Project, PairLayer
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import numpy as np
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from .ACD import ACD
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from .AHT import AHT
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from .OCD import OCD
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from .LHBA import LHBA
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from .SH import SH
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def warp(file,ds:gdal.Dataset,srcWin=[0,0,0,0]):
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driver = gdal.GetDriverByName('GTiff')
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xsize=ds.RasterXSize
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ysize=ds.RasterYSize
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geo=ds.GetGeoTransform()
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orj=ds.GetProjection()
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band=ds.RasterCount
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out_ds:gdal.Dataset=driver.Create(file, xsize, ysize, band, gdal.GDT_Byte)
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out_ds.SetGeoTransform(geo)
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out_ds.SetProjection(orj)
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for b in range(1,band+1):
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out_ds.GetRasterBand(b).WriteArray(ds.ReadAsArray(*srcWin,band_list=[b]),*(0,0))
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del out_ds
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def basic_cd(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
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ds1:gdal.Dataset=gdal.Open(pth1)
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ds2:gdal.Dataset=gdal.Open(pth2)
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cell_size = layer_parent.cell_size
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xsize = layer_parent.size[0]
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ysize = layer_parent.size[1]
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band = ds1.RasterCount
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yblocks = ysize // cell_size[1]
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driver = gdal.GetDriverByName('GTiff')
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out_tif = os.path.join(Project().other_path, 'temp.tif')
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out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
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geo=layer_parent.grid.geo
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proj=layer_parent.grid.proj
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out_ds.SetGeoTransform(geo)
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out_ds.SetProjection(proj)
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max_diff = 0
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min_diff = math.inf
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start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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for j in range(yblocks + 1):#该改这里了
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send_message.emit(f'计算{j}/{yblocks}')
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block_xy1 = (start1x, start1y+j * cell_size[1])
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block_xy2 = (start2x,start2y+j*cell_size[1])
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block_xy=(0,j * cell_size[1])
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if block_xy1[1] > end1y or block_xy2[1] > end2y:
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break
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block_size=(xsize, cell_size[1])
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block_size1 = (xsize, cell_size[1])
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block_size2 = (xsize,cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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if block_xy1[1] + block_size1[1] > end1y:
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block_size1 = (xsize,end1y - block_xy1[1])
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if block_xy2[1] + block_size2[1] > end2y:
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block_size2 = (xsize, end2y - block_xy2[1])
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block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
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block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
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if band == 1:
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block_data1 = block_data1[None, ...]
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block_data2 = block_data2[None, ...]
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# pdb.set_trace()
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block_diff = block_data1.sum(0) - block_data2.sum(0)
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block_diff = block_diff.astype(np.float32)
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block_diff = np.abs(block_diff)
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min_diff = min(min_diff, block_diff[block_diff > 0].min())
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max_diff = max(max_diff, block_diff.max())
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out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
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send_message.emit(f'完成{j}/{yblocks}')
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del ds2
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del ds1
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out_ds.FlushCache()
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del out_ds
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send_message.emit('归一化概率中...')
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temp_in_ds = gdal.Open(out_tif)
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out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
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out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
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out_normal_ds.SetGeoTransform(geo)
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out_normal_ds.SetProjection(proj)
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# hist = np.zeros(256, dtype=np.int32)
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for j in range(yblocks+1):
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block_xy = (0, j * cell_size[1])
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if block_xy[1] > ysize:
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break
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block_size = (xsize, cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
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block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
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block_data = block_data.astype(np.uint8)
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out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
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# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
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# hist += hist_t
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# print(hist)
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del temp_in_ds
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del out_normal_ds
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try:
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os.remove(out_tif)
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except:
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pass
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send_message.emit('差分法计算完成')
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return out_normal_tif
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def LSTS(pth1:str,pth2:str,layer_parent:PairLayer,send_message,n=5,w_size=(3,3)):
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ds1:gdal.Dataset=gdal.Open(pth1)
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ds2:gdal.Dataset=gdal.Open(pth2)
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cell_size = layer_parent.cell_size
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xsize = layer_parent.size[0]
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ysize = layer_parent.size[1]
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band = ds1.RasterCount
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yblocks = ysize // cell_size[1]
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driver = gdal.GetDriverByName('GTiff')
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out_tif = os.path.join(Project().other_path, 'temp.tif')
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out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
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geo=layer_parent.grid.geo
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proj=layer_parent.grid.proj
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out_ds.SetGeoTransform(geo)
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out_ds.SetProjection(proj)
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pixnum=w_size[0]*w_size[1]
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print('pixnum',pixnum)
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max_diff = 0
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min_diff = math.inf
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win_h=w_size[0]//2 #half hight of window
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win_w=w_size[1]//2 #half width of window
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a=[[(i+1)**j for j in range(n+1)] for i in range(pixnum)]
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A=np.array(a).astype(np.float64)#
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k_=np.array(range(1,n+1))
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df1=np.zeros(pixnum).astype(np.float64)
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df2=np.zeros(pixnum).astype(np.float64)
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start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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for j in range(yblocks + 1):
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send_message.emit(f'计算{j}/{yblocks}')
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block_xy1 = (start1x, start1y+j * cell_size[1])
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block_xy2 = (start2x,start2y+j*cell_size[1])
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block_xy=(0,j * cell_size[1])
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if block_xy1[1] > end1y or block_xy2[1] > end2y:
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break
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block_size=(xsize, cell_size[1])
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block_size1 = (xsize, cell_size[1])
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block_size2 = (xsize,cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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if block_xy1[1] + block_size1[1] > end1y:
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block_size1 = (xsize,end1y - block_xy1[1])
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if block_xy2[1] + block_size2[1] > end2y:
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block_size2 = (xsize, end2y - block_xy2[1])
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block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
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block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
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if band == 1:
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block_data1 = block_data1[None, ...]
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block_data2 = block_data2[None, ...]
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# pdb.set_trace()
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else:
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block_data1=np.mean(block_data1,0)
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block_data2=np.mean(block_data2,0)
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block_diff=np.zeros(block_data1.shape).astype(np.float64)
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for i in range(win_h,block_size1[1]-win_h):
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for j_ in range(win_w,block_size1[0]-win_w):
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pix=0
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#get b
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# b1=block_data[i+win_h:i+win_h] c in range(j_-win_w,j_+win_w+1)
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b1=block_data1[i-win_h:i+win_h+1,j_-win_w:j_+win_w+1]
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b2=block_data2[i-win_h:i+win_h+1,j_-win_w:j_+win_w+1]
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b1=[b if (r+1)//2 else b[::-1] for r,b in enumerate(b1)]
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b2=[b if (r+1)//2 else b[::-1] for r,b in enumerate(b2)]
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b1=np.expand_dims(np.concatenate(b1,0),1)
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b2=np.expand_dims(np.concatenate(b2,0),1)
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#end get b
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x1=np.squeeze(np.linalg.pinv(A).dot(b1))
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x2=np.squeeze(np.linalg.pinv(A).dot(b2))
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#df
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k_=range(1,n+1)
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for pix in range(1,pixnum+1):
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df1[pix-1]=x1[1:n+1].dot(np.array([k*(pix**(k-1)) for k in k_]))
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df2[pix-1]=x2[1:n+1].dot(np.array([k*(pix**(k-1)) for k in k_]))
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#distance 欧式距离
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block_diff[i][j_]=np.dot(df1-df2,df1-df2)**0.5
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min_diff = min(min_diff, block_diff[block_diff > 0].min())
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max_diff = max(max_diff, block_diff.max())
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out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
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send_message.emit(f'完成{j}/{yblocks}')
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del ds2
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del ds1
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out_ds.FlushCache()
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del out_ds
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send_message.emit('归一化概率中...')
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temp_in_ds = gdal.Open(out_tif)
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out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
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out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
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out_normal_ds.SetGeoTransform(geo)
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out_normal_ds.SetProjection(proj)
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# hist = np.zeros(256, dtype=np.int32)
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for j in range(yblocks+1):
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block_xy = (0, j * cell_size[1])
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if block_xy[1] > ysize:
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break
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block_size = (xsize, cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
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block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
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block_data = block_data.astype(np.uint8)
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out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
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# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
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# hist += hist_t
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# print(hist)
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del temp_in_ds
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del out_normal_ds
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try:
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os.remove(out_tif)
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except:
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pass
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send_message.emit('LSTS法计算完成')
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return out_normal_tif
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def CVA(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
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ds1:gdal.Dataset=gdal.Open(pth1)
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ds2:gdal.Dataset=gdal.Open(pth2)
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cell_size = layer_parent.cell_size
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xsize = layer_parent.size[0]
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ysize = layer_parent.size[1]
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band = ds1.RasterCount
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yblocks = ysize // cell_size[1]
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driver = gdal.GetDriverByName('GTiff')
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out_tif = os.path.join(Project().other_path, 'temp.tif')
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out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
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geo=layer_parent.grid.geo
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proj=layer_parent.grid.proj
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out_ds.SetGeoTransform(geo)
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out_ds.SetProjection(proj)
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max_diff = 0
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min_diff = math.inf
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start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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for j in range(yblocks + 1):
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send_message.emit(f'计算{j}/{yblocks}')
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block_xy1 = (start1x, start1y+j * cell_size[1])
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block_xy2 = (start2x,start2y+j*cell_size[1])
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block_xy=(0,j * cell_size[1])
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if block_xy1[1] > end1y or block_xy2[1] > end2y:
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break
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block_size=(xsize, cell_size[1])
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block_size1 = (xsize, cell_size[1])
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block_size2 = (xsize,cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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if block_xy1[1] + block_size1[1] > end1y:
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block_size1 = (xsize,end1y - block_xy1[1])
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if block_xy2[1] + block_size2[1] > end2y:
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block_size2 = (xsize, end2y - block_xy2[1])
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block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
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block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
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if band == 1:
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block_data1 = block_data1[None, ...]
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block_data2 = block_data2[None, ...]
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# pdb.set_trace()
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block_diff=np.sum((block_data1-block_data2)**2,0)**0.5
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min_diff = min(min_diff, block_diff[block_diff > 0].min())
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max_diff = max(max_diff, block_diff.max())
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out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
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send_message.emit(f'完成{j}/{yblocks}')
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del ds2
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del ds1
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out_ds.FlushCache()
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del out_ds
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send_message.emit('归一化概率中...')
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temp_in_ds = gdal.Open(out_tif)
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out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
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out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
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out_normal_ds.SetGeoTransform(geo)
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out_normal_ds.SetProjection(proj)
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# hist = np.zeros(256, dtype=np.int32)
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for j in range(yblocks+1):
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block_xy = (0, j * cell_size[1])
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if block_xy[1] > ysize:
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break
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block_size = (xsize, cell_size[1])
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if block_xy[1] + block_size[1] > ysize:
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block_size = (xsize, ysize - block_xy[1])
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block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
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block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
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block_data = block_data.astype(np.uint8)
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out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
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# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
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# hist += hist_t
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# print(hist)
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del temp_in_ds
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del out_normal_ds
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try:
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os.remove(out_tif)
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except:
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pass
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send_message.emit('欧式距离计算完成')
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return out_normal_tif
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def acd(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
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xsize = layer_parent.size[0]
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ysize = layer_parent.size[1]
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geo=layer_parent.grid.geo
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proj=layer_parent.grid.proj
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#提取公共部分
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send_message.emit('提取重叠区域数据.....')
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ds2:gdal.Dataset=gdal.Open(pth2)
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temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
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start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
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del ds2
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send_message.emit('图像二提取完成')
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ds1:gdal.Dataset=gdal.Open(pth1)
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temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
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start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
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end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
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warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
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del ds1
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send_message.emit('图像一提取完成')
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#运算
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send_message.emit('开始ACD计算.....')
|
|
time.sleep(0.1)
|
|
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
|
|
ACD(temp_tif1,temp_tif2,out_normal_tif)
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|
#添加投影
|
|
send_message.emit('录入投影信息.....')
|
|
time.sleep(0.1)
|
|
ds=gdal.Open(out_normal_tif,1)
|
|
ds.SetGeoTransform(geo)
|
|
ds.SetProjection(proj)
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|
del ds
|
|
|
|
return out_normal_tif
|
|
|
|
def aht(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
|
|
xsize = layer_parent.size[0]
|
|
ysize = layer_parent.size[1]
|
|
geo=layer_parent.grid.geo
|
|
proj=layer_parent.grid.proj
|
|
#提取公共部分
|
|
send_message.emit('提取重叠区域数据.....')
|
|
|
|
ds2:gdal.Dataset=gdal.Open(pth2)
|
|
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
|
|
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
|
|
del ds2
|
|
send_message.emit('图像二提取完成')
|
|
|
|
|
|
ds1:gdal.Dataset=gdal.Open(pth1)
|
|
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
|
|
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
|
|
del ds1
|
|
send_message.emit('图像一提取完成')
|
|
|
|
|
|
|
|
#运算
|
|
send_message.emit('开始AHT计算.....')
|
|
time.sleep(0.1)
|
|
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
|
|
AHT(temp_tif1,temp_tif2,out_normal_tif)
|
|
#添加投影
|
|
send_message.emit('录入投影信息.....')
|
|
time.sleep(0.1)
|
|
ds=gdal.Open(out_normal_tif,1)
|
|
ds.SetGeoTransform(geo)
|
|
ds.SetProjection(proj)
|
|
del ds
|
|
|
|
return out_normal_tif
|
|
|
|
def ocd(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
|
|
xsize = layer_parent.size[0]
|
|
ysize = layer_parent.size[1]
|
|
geo=layer_parent.grid.geo
|
|
proj=layer_parent.grid.proj
|
|
#提取公共部分
|
|
send_message.emit('提取重叠区域数据.....')
|
|
|
|
ds2:gdal.Dataset=gdal.Open(pth2)
|
|
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
|
|
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
|
|
del ds2
|
|
send_message.emit('图像二提取完成')
|
|
|
|
|
|
ds1:gdal.Dataset=gdal.Open(pth1)
|
|
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
|
|
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
|
|
del ds1
|
|
send_message.emit('图像一提取完成')
|
|
|
|
|
|
|
|
#运算
|
|
send_message.emit('开始OCD计算.....')
|
|
time.sleep(0.1)
|
|
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
|
|
OCD(temp_tif1,temp_tif2,out_normal_tif,Project().other_path)
|
|
#添加投影
|
|
send_message.emit('录入投影信息.....')
|
|
time.sleep(0.1)
|
|
ds=gdal.Open(out_normal_tif,1)
|
|
ds.SetGeoTransform(geo)
|
|
ds.SetProjection(proj)
|
|
del ds
|
|
|
|
return out_normal_tif
|
|
|
|
def lhba(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
|
|
xsize = layer_parent.size[0]
|
|
ysize = layer_parent.size[1]
|
|
geo=layer_parent.grid.geo
|
|
proj=layer_parent.grid.proj
|
|
#提取公共部分
|
|
send_message.emit('提取重叠区域数据.....')
|
|
|
|
ds2:gdal.Dataset=gdal.Open(pth2)
|
|
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
|
|
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
|
|
del ds2
|
|
send_message.emit('图像二提取完成')
|
|
|
|
|
|
ds1:gdal.Dataset=gdal.Open(pth1)
|
|
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
|
|
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
|
|
del ds1
|
|
send_message.emit('图像一提取完成')
|
|
|
|
#运算
|
|
send_message.emit('开始LHBA计算.....')
|
|
time.sleep(0.1)
|
|
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
|
|
LHBA(temp_tif1,temp_tif2,out_normal_tif)
|
|
#添加投影
|
|
send_message.emit('录入投影信息.....')
|
|
time.sleep(0.1)
|
|
ds=gdal.Open(out_normal_tif,1)
|
|
ds.SetGeoTransform(geo)
|
|
ds.SetProjection(proj)
|
|
del ds
|
|
return out_normal_tif
|
|
|
|
def sh(pth1:str,pth2:str,layer_parent:PairLayer,send_message):
|
|
xsize = layer_parent.size[0]
|
|
ysize = layer_parent.size[1]
|
|
geo=layer_parent.grid.geo
|
|
proj=layer_parent.grid.proj
|
|
#提取公共部分
|
|
send_message.emit('提取重叠区域数据.....')
|
|
|
|
ds2:gdal.Dataset=gdal.Open(pth2)
|
|
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
|
|
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
|
|
del ds2
|
|
send_message.emit('图像二提取完成')
|
|
|
|
|
|
ds1:gdal.Dataset=gdal.Open(pth1)
|
|
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
|
|
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
|
|
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
|
|
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
|
|
del ds1
|
|
send_message.emit('图像一提取完成')
|
|
|
|
#运算
|
|
send_message.emit('开始SH计算.....')
|
|
time.sleep(0.1)
|
|
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
|
|
SH(temp_tif1,temp_tif2,out_normal_tif)
|
|
#添加投影
|
|
send_message.emit('录入投影信息.....')
|
|
time.sleep(0.1)
|
|
ds=gdal.Open(out_normal_tif,1)
|
|
ds.SetGeoTransform(geo)
|
|
ds.SetProjection(proj)
|
|
del ds
|
|
return out_normal_tif
|