直方图#

如何使用 Matplotlib 绘制直方图。

import matplotlib.pyplot as plt
import numpy as np

from matplotlib import colors
from matplotlib.ticker import PercentFormatter

# Create a random number generator with a fixed seed for reproducibility
rng = np.random.default_rng(19680801)

生成数据并绘制简单直方图#

要生成一个一维直方图，我们只需要一个数字向量。对于二维直方图，我们需要第二个向量。我们将在下面生成这两个向量，并显示每个向量的直方图。

N_points = 100000
n_bins = 20

# Generate two normal distributions
dist1 = rng.standard_normal(N_points)
dist2 = 0.4 * rng.standard_normal(N_points) + 5

fig, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)

# We can set the number of bins with the *bins* keyword argument.
axs[0].hist(dist1, bins=n_bins)
axs[1].hist(dist2, bins=n_bins)

plt.show()

更新直方图颜色#

直方图方法返回（除其他外）一个 patches 对象。这使我们可以访问所绘制对象的属性。使用它，我们可以根据需要编辑直方图。让我们根据每个条形图的 y 值更改每个条形图的颜色。

fig, axs = plt.subplots(1, 2, tight_layout=True)

# N is the count in each bin, bins is the lower-limit of the bin
N, bins, patches = axs[0].hist(dist1, bins=n_bins)

# We'll color code by height, but you could use any scalar
fracs = N / N.max()

# we need to normalize the data to 0..1 for the full range of the colormap
norm = colors.Normalize(fracs.min(), fracs.max())

# Now, we'll loop through our objects and set the color of each accordingly
for thisfrac, thispatch in zip(fracs, patches):
    color = plt.cm.viridis(norm(thisfrac))
    thispatch.set_facecolor(color)

# We can also normalize our inputs by the total number of counts
axs[1].hist(dist1, bins=n_bins, density=True)

# Now we format the y-axis to display percentage
axs[1].yaxis.set_major_formatter(PercentFormatter(xmax=1))

绘制二维直方图#

要绘制二维直方图，只需要两个长度相同的向量，分别对应直方图的每个轴。

fig, ax = plt.subplots(tight_layout=True)
hist = ax.hist2d(dist1, dist2)

自定义直方图#

自定义二维直方图类似于一维情况，您可以控制视觉组件，例如 bin 大小或颜色归一化。

fig, axs = plt.subplots(3, 1, figsize=(5, 15), sharex=True, sharey=True,
                        tight_layout=True)

# We can increase the number of bins on each axis
axs[0].hist2d(dist1, dist2, bins=40)

# As well as define normalization of the colors
axs[1].hist2d(dist1, dist2, bins=40, norm=colors.LogNorm())

# We can also define custom numbers of bins for each axis
axs[2].hist2d(dist1, dist2, bins=(80, 10), norm=colors.LogNorm())

参考文献

本示例演示了以下函数、方法、类和模块的使用情况

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