Matplotlib使用分层直方图

时间:2015-10-16 08:24:29

标签: python numpy matplotlib distribution

有没有办法在matplotlib / pyplot中制作分层直方图?

我已经了解了如何使用alpha标记的透明度,但我找不到分层方法,

例如。如果有两个具有共同y轴图的数据集,则应首先绘制最小频率,以便可以看到在较大频率之上分层。

透明度无法正常工作,因为它会改变颜色,然后使其与密钥不匹配。

1 个答案:

答案 0 :(得分:1)

我认为你可以通过根据高度设置各个条形的z顺序来获得你想要的效果:

import numpy as np
from matplotlib import pyplot as plt

# two overlapping distributions
x1 = np.random.beta(2, 5, 500)
x2 = np.random.beta(5, 2, 500)

fig, ax = plt.subplots(1, 1)
ax.hold(True)

# plot the histograms as usual
bins = np.linspace(0, 1, 20)
counts1, edges1, bars1 = ax.hist(x1, bins)
counts2, edges2, bars2 = ax.hist(x2, bins)

# plot the histograms as lines as well for clarity
ax.hist(x1, bins, histtype='step', ec='k', ls='solid', lw=3)
ax.hist(x2, bins, histtype='step', ec='k', ls='dashed', lw=3)

# set the z-order of each bar according to its relative height
x2_bigger = counts2 > counts1
for b1, b2, oo in zip(bars1, bars2, x2_bigger):
    if oo:
        # if bar 2 is taller than bar 1, place it behind bar 1
        b2.set_zorder(b1.get_zorder() - 1)
    else:
        # otherwise place it in front
        b2.set_zorder(b1.get_zorder() + 1)

plt.show()

enter image description here