计算Matlab中2D点列表的熵 [英] Calculate the entropy of a list of 2D points in Matlab

问题描述

我在这样的数组中有一个点列表

  points = [[1,2]; [2,5]; [7,1] ... [x，y]] 

x在0到1020之间，y在0到1920之间.

如何在Matlab中计算点数组的熵?

非常感谢！

我假设您想将每个 [x，y] 点视为一个数据点.让我们定义一些示例性数据:

  A = [[1,2]; [2,5]; [7,1]; [1,2]]; 

首先我们给相等的点相等的标识符，我们可以使用

  [〜，〜，ic] = unique(A，'rows'); 

然后我们计算频率以及每个标识符的概率:

  [frequency，〜] = histcounts(ic，max(ic));概率=频率/总和(频率); 

有了这个，我们可以立即计算熵:

 熵= -sum(概率.* log(概率)) 

(请确保使用正确的对数，传统上不同的字段使用不同的底数.)

I have a list of points in an array like this

points = [[1,2];[2,5];[7,1]...[x,y]]

The x is between 0 and 1020 and y is between 0 and 1920.

How can I calculate the entropy of the points array in Matlab?

Many thanks!

解决方案

I assume you want to consider each [x,y] point as one data point. Let us define some exemplary data:

A = [[1,2];[2,5];[7,1];[1,2]];

First we give equal points equal identifiers, we can do this using

[~,~,ic] = unique(A, 'rows');

Then we compute the frequency and with that the probability of each identifier:

[frequency, ~] = histcounts(ic,max(ic));
probability = frequency/sum(frequency);

With this we can immediately compute the entropy:

entropy = -sum(probability .* log(probability))

(Make sure you use the right logarithm, different fields conventionally use different bases.)

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