46 lines
1.9 KiB
Python
46 lines
1.9 KiB
Python
from datetime import datetime
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import math
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from random import random
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from osgeo import gdal
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from rscder.utils.project import Project
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import os
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from rscder.utils.project import BasicLayer, ResultPointLayer
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def table_layer(pth:str,layer:BasicLayer, name, send_message = None):
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if send_message is not None:
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send_message.emit('正在计算表格结果...')
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cell_size = layer.layer_parent.cell_size
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ds = gdal.Open(pth)
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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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out_csv = os.path.join(Project().other_path, f'{name}_table_result_{ int(datetime.now().timestamp() * 1000) }.csv')
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yblocks = ysize // cell_size[1] + 1
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xblocks = xsize // cell_size[0] + 1
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with open(out_csv, 'w') as f:
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f.write('x,y,diff,status\n')
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for j in range(yblocks):
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block_xy = (0, j * cell_size[1])
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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 = ds.ReadAsArray(*block_xy, *block_size)
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for i in range(xblocks):
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start_x = i * cell_size[0]
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end_x = start_x + cell_size[0]
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if end_x > xsize:
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end_x = xsize
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block_data_xy = block_data[:, start_x:end_x]
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center_x = start_x + cell_size[0] // 2
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center_y = j * cell_size[1] + cell_size[1] // 2
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center_x = center_x * geo[1] + geo [0]
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center_y = center_y * geo[5] + geo [3]
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f.write(f'{center_x},{center_y},{block_data_xy.mean() * 100},{int(block_data_xy.mean() > 0.5)}\n')
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result_layer = ResultPointLayer(out_csv, enable=True, proj=layer.proj, geo=layer.geo,result_path={})
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# print(result_layer.result_path)
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layer.layer_parent.add_result_layer(result_layer)
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if send_message is not None:
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send_message.emit('计算完成') |