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# coding = utf-8 import numpy as np from IPython import embed # xy 输入,可支持浮点数操作 速度很快哦 # return xy 去重后结果 def duplicate_removal(xy): if xy.shape[0] < 2: return xy _tmp = (xy*4000).astype('i4') # 转换成 i4 处理 _tmp = _tmp[:,0] + _tmp[:,1]*1j # 转换成复数处理 keep = np.unique(_tmp, return_index=True)[1] # 去重 得到索引 return xy[keep] # 得到数据并返回 # _tmp[:,0] 切片操作,因为时二维数组,_tmp[a:b, c:d]为通用表达式, # 表示取第一维的索引 a 到索引 b,和第二维的索引 c 到索引 d # 当取所有时可以直接省略,但要加':'冒号 、当 a == b 时可只写 a ,同时不用':'冒号 if __name__ == '__main__': if 1: # test xy = np.array([[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 0.0, 0.0], [1.0, 1.0, 1.00]]) print(xy) new_xy = duplicate_removal(xy) print(new_xy) embed()
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