25 lines
748 B
Python
25 lines
748 B
Python
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import numpy as np
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def distance_to_origin(chromosome_results, data=None):
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# 如果data不为空，则堆叠数据
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if data is not None:
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chromosome_results = np.vstack((chromosome_results, data))
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# 获取每个特征的范数
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norms = np.linalg.norm(chromosome_results, axis=0)
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# 检查是否有零值并替换它们，以避免除以零
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norms[norms == 0] = 1.0 # 或使用一个非常小的数来替换零
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# 归一化处理
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normalized_data = chromosome_results / norms
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# 计算归一化数据到原点的距离
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distances = np.linalg.norm(normalized_data, axis=1)
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# 如果data不为空，则删除最后一行
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if data is not None:
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distances = distances[:-1]
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return distances
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