如何为直方图绘制两层x轴标签

Question

是否有一种方法可以对这两个x轴标签进行相同的操作，但用于直方图?如何在matplotlib的第一个底部添加第二个x轴。

我想用两个级别来显示这些值，一个是公制的，第二个是英制的。我试图将上面链接中的脚本改编为直方图脚本，但我不确定如何将直方图函数与ax1连接起来。处理。

"""
Demo of the histogram (hist) function with a few features.
In addition to the basic histogram, this demo shows a few optional features:
    * Setting the number of data bins
    * The ``normed`` flag, which normalizes bin heights so that the integral of
      the histogram is 1. The resulting histogram is a probability density.
    * Setting the face color of the bars
    * Setting the opacity (alpha value).
"""
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twiny()
# example data
mu = 100  # mean of distribution
sigma = 15  # standard deviation of distribution
x = mu + sigma * np.random.randn(10000)
num_bins = 50
# the histogram of the data
n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)
ax1.set_xlabel(r"Original x-axis: $X$")
new_tick_locations = np.array([.2, .5, .9])
def tick_function(X):
    V = 1/(1+X)
    return ["%.3f" % z for z in V]

# Move twinned axis ticks and label from top to bottom
ax2.xaxis.set_ticks_position("bottom")
ax2.xaxis.set_label_position("bottom")
# Offset the twin axis below the host
ax2.spines["bottom"].set_position(("axes", -0.15))
# Turn on the frame for the twin axis, but then hide all
# but the bottom spine
ax2.set_frame_on(True)
ax2.patch.set_visible(False)
for sp in ax2.spines.itervalues():
    sp.set_visible(False)
ax2.spines["bottom"].set_visible(True)
ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(tick_function(new_tick_locations))
ax2.set_xlabel(r"Modified x-axis: $1/(1+X)$")


y = mlab.normpdf(bins, mu, sigma)
plt.xlabel('Smarts')
plt.ylabel('Probability')
plt.title(r'Histogram of IQ: $mu=100$, $sigma=15$')
# Tweak spacing to prevent clipping of ylabel
plt.subplots_adjust(left=0.15)

plt.show()

Answer 1

将hist调用替换为:

n, bins, patches = ax1.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)

查看Axes的文档，查看可用的成员函数