如何在python中标准化直方图? [英] How to normalize a histogram in python?

问题描述

我正在尝试绘制归一直方图，但不是在 y 轴上获得 1 作为最大值，而是获得了不同的数字.

I'm trying to plot normed histogram, but instead of getting 1 as maximum value on y axis, I'm getting different numbers.

对于数组 k=(1,4,3,1)

For array k=(1,4,3,1)

 import numpy as np

 def plotGraph():

    import matplotlib.pyplot as plt

    k=(1,4,3,1)

    plt.hist(k, normed=1)

    from numpy import *
    plt.xticks( arange(10) ) # 10 ticks on x axis

    plt.show()  

plotGraph()

我得到了这个直方图，看起来好像不是正常的.

I get this histogram, that doesn't look like normed.

对于另一个数组k =(3,3,3,3)

For a different array k=(3,3,3,3)

 import numpy as np

 def plotGraph():

    import matplotlib.pyplot as plt

    k=(3,3,3,3)

    plt.hist(k, normed=1)

    from numpy import *
    plt.xticks( arange(10) ) # 10 ticks on x axis

    plt.show()  

plotGraph()

我得到最大y值为10的直方图.

I get this histogram with max y-value is 10.

对于不同的 k，即使 normed=1 或 normed=True，我也会得到不同的 y 最大值.

For different k I get different max value of y even though normed=1 or normed=True.

为什么归一化(如果有效)会根据数据发生变化，如何使 y 的最大值等于 1?

Why the normalization (if it works) changes based on the data and how can I make maximum value of y equals to 1?

更新:

我正在尝试实施 CarstenKönig答案/questions/3866520/plotting-histograms-whose-bar-heights-sum-to-1-in-matplotlib">在 matplotlib 中绘制条形高度总和为 1 的直方图 并得到非常奇怪的结果:

I am trying to implement Carsten König answer from plotting histograms whose bar heights sum to 1 in matplotlib and getting very weird result:

import numpy as np

def plotGraph():

    import matplotlib.pyplot as plt

    k=(1,4,3,1)

    weights = np.ones_like(k)/len(k)
    plt.hist(k, weights=weights)

    from numpy import *
    plt.xticks( arange(10) ) # 10 ticks on x axis

    plt.show()  

plotGraph()

结果:

我做错了什么?

谢谢

推荐答案

绘制归一化直方图时，高度不应该合计为1，而曲线下方的面积应合计为1:>

When you plot a normalized histogram, it is not the height that should sum up to one, but the area underneath the curve should sum up to one:

In [44]:

import matplotlib.pyplot as plt
k=(3,3,3,3)
x, bins, p=plt.hist(k, density=True)  # used to be normed=True in older versions
from numpy import *
plt.xticks( arange(10) ) # 10 ticks on x axis
plt.show()  
In [45]:

print bins
[ 2.5  2.6  2.7  2.8  2.9  3.   3.1  3.2  3.3  3.4  3.5]

在此示例中，箱宽为0.1，曲线下方的面积总计为一(0.1 * 10).

Here, this example, the bin width is 0.1, the area underneath the curve sums up to one (0.1*10).

要使高度总和为 1，请在 plt.show() 前添加以下内容:

To have the sum of height to be 1, add the following before plt.show():

for item in p:
    item.set_height(item.get_height()/sum(x))

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