有没有办法在numpy.hist回到同一长度的数组？ [英] Is there a way to return same length arrays in numpy.hist?

问题描述

我想在Python中创建直方图，一些自定义的值正常化y轴上的值。对于这一点，我想这样做是这样的：

I'm trying to create a histogram plot in python, normalizing with some custom values the y-axis values. For this, I was thinking to do it like this:

import numpy as np
import matplotlib.pyplot as plt

data = np.loadtxt('foo.bar')
fig = plt.figure()
ax = fig.add_subplot(111)

hist=np.histogram(data, bins=(1.0, 1.5 ,2.0,2.5,3.0))
x=[hist[0]*5,hist[1]]
ax.plot(x[0], x[1], 'o')

，但当然，最后一行给出：

but of course, the last line gives:

ValueError: x and y must have same first dimension

有没有办法强制np.hist给了X [0]和X相同数量的元素[1]的阵列，例如通过删除了其中一人的第一个或最后一个元素？

Is there a way to force np.hist to give the same number of elements for the x[0] and x[1] arrays, for example by deleting the first or last element for one of them?

推荐答案

HIST [1]包含在其中所做的直方图的限制。我猜你可能想获得这些区间的中心，是这样的：

hist[1] contains the limits in which you have made the histogram. I guess you probably want to get the centers of those intervals, something like:

x = [hist[0], 0.5*(hist[1][1:]+hist[1][:-1])]

然后剧情应该没问题吧？

and then the plot should be ok, right?

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