Is there a way to return same length arrays in numpy.hist?

问题

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')

but of course, the last line gives:

ValueError: x and y must have same first dimension

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?

回答1:

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])]

and then the plot should be ok, right?

回答2:

I would imagine it depends on your data source.

Try loading the data as a numpy array, and selecting the range of elements yourself before passing to the histogram function.

e.g.

dataForHistogram = data[0:100][0:100]   # Assuming your data is in this kind of structure.

来源：https://stackoverflow.com/questions/17966093/is-there-a-way-to-return-same-length-arrays-in-numpy-hist