Python的多边形散射图
我有一个n观察值的矩阵和f功能。在n观察值中，5表示我希望与他人（具有距离或相似性度量）进行比较的参考样本。取决于n功能与5个参考的距离，我想在多边形图上绘制它们，以更好地感知它们在5个情况之间的分布方式（即它们之间的距离有多遥远）。 这是我想获得的结果的一个示例：
如何在Python中制作此类型的图表？
另外，是否可以通过调节角数（低或高于5）来产生此类图？
I have a matrix of N observations and F features. Among the N observations, 5 represent reference samples that I wish to compare with others (with distance or similarity measures). Depending on how close the N features are from the 5 references, I would like to plot them on a polygonal diagram to have a better perception of how they are distributed between the 5 cases (i.e. how distant they are).
This is an example of result I would like to get:
Each corner represent a reference while black dots are the samples to locate between such references. How can I produce this type of diagram in python?
Also, would it be possible to produce such diagram by modulating the number of corners (lower or higher than 5)?
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