Python中的MATLAB ksdensity等效项 [英] MATLAB ksdensity equivalent in Python

问题描述

我已经上网了，还没有找到答案或方法来说明以下内容

I've looked online and have yet to find an answer or way to figure the following

我正在将一些MATLAB代码转换为Python，在MATLAB中，我希望通过以下功能找到内核密度估算值:

I'm translating some MATLAB code to Python where in MATLAB im looking to find the kernel density estimation with the function:

[p,x] = ksdensity(data)

其中p是分布中x点的概率.

where p is the probability at point x in the distribution.

Scipy具有功能，但仅返回p.

Scipy has a function but only returns p.

有没有一种方法可以找到x值处的概率?

Is there a way to find the probability at values of x?

谢谢！

推荐答案

这种形式的ksdensity调用会自动生成任意的x. scipy.stats.gaussian_kde()返回一个可调用函数，可以使用您选择的任何x对其进行求值.等价的x将是np.linspace(data.min(), data.max(), 100).

That form of the ksdensity call automatically generates an arbitrary x. scipy.stats.gaussian_kde() returns a callable function that can be evaluated with any x of your choosing. The equivalent x would be np.linspace(data.min(), data.max(), 100).

import numpy as np
from scipy import stats

data = ...
kde = stats.gaussian_kde(data)
x = np.linspace(data.min(), data.max(), 100)
p = kde(x)

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