如何使用NumPy获得累积分布函数?

本文介绍了如何使用NumPy获得累积分布函数?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我想用NumPy创建CDF，下一个是我的代码:

I want to create a CDF with NumPy, my code is the next:

histo = np.zeros(4096, dtype = np.int32) for x in range(0, width): for y in range(0, height): histo[data[x][y]] += 1 q = 0 cdf = list() for i in histo: q = q + i cdf.append(q)

我正在数组旁边走，但是要花很长时间执行程序.具有此功能的内置功能，不是吗?

I am walking by the array but take a long time the program execution. There is a built function with this feature, isn't?

推荐答案

我不太确定您的代码在做什么，但是如果您有numpy.histogram返回的hist和bin_edges数组，则可以使用numpy.cumsum生成直方图内容的累积和.

I'm not really sure what your code is doing, but if you have hist and bin_edges arrays returned by numpy.histogram you can use numpy.cumsum to generate a cumulative sum of the histogram contents.

>>> import numpy as np >>> hist, bin_edges = np.histogram(np.random.randint(0,10,100), normed=True) >>> bin_edges array([ 0. , 0.9, 1.8, 2.7, 3.6, 4.5, 5.4, 6.3, 7.2, 8.1, 9. ]) >>> hist array([ 0.14444444, 0.11111111, 0.11111111, 0.1 , 0.1 , 0.14444444, 0.14444444, 0.08888889, 0.03333333, 0.13333333]) >>> np.cumsum(hist) array([ 0.14444444, 0.25555556, 0.36666667, 0.46666667, 0.56666667, 0.71111111, 0.85555556, 0.94444444, 0.97777778, 1.11111111])