带直方图的散点图#

在图的侧边显示散点图的边缘分布直方图。

为了很好地对齐主轴与边缘轴，下面显示了两种选项

虽然 Axes.inset_axes 可能有点复杂，但它允许正确处理具有固定纵横比的主轴。

使用 axes_grid1 工具箱生成类似图形的另一种方法在散点直方图（可定位轴）示例中显示。最后，也可以使用 Figure.add_axes（此处未显示）以绝对坐标定位所有轴。

首先，让我们定义一个函数，该函数以 x 和 y 数据作为输入，以及三个轴：散点图的主轴和两个边缘轴。然后，它将在提供的轴内创建散点图和直方图。

import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)

# some random data
x = np.random.randn(1000)
y = np.random.randn(1000)


def scatter_hist(x, y, ax, ax_histx, ax_histy):
    # no labels
    ax_histx.tick_params(axis="x", labelbottom=False)
    ax_histy.tick_params(axis="y", labelleft=False)

    # the scatter plot:
    ax.scatter(x, y)

    # now determine nice limits by hand:
    binwidth = 0.25
    xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))
    lim = (int(xymax/binwidth) + 1) * binwidth

    bins = np.arange(-lim, lim + binwidth, binwidth)
    ax_histx.hist(x, bins=bins)
    ax_histy.hist(y, bins=bins, orientation='horizontal')

使用 gridspec 定义轴位置 #

我们定义了一个具有不等宽高比的 gridspec，以实现所需布局。另请参阅在图形中排列多个轴教程。

# Start with a square Figure.
fig = plt.figure(figsize=(6, 6))
# Add a gridspec with two rows and two columns and a ratio of 1 to 4 between
# the size of the marginal Axes and the main Axes in both directions.
# Also adjust the subplot parameters for a square plot.
gs = fig.add_gridspec(2, 2,  width_ratios=(4, 1), height_ratios=(1, 4),
                      left=0.1, right=0.9, bottom=0.1, top=0.9,
                      wspace=0.05, hspace=0.05)
# Create the Axes.
ax = fig.add_subplot(gs[1, 0])
ax_histx = fig.add_subplot(gs[0, 0], sharex=ax)
ax_histy = fig.add_subplot(gs[1, 1], sharey=ax)
# Draw the scatter plot and marginals.
scatter_hist(x, y, ax, ax_histx, ax_histy)

使用 inset_axes 定义轴位置 #

inset_axes 可用于在主轴外部定位边缘轴。这样做的优点是可以固定主轴的纵横比，并且边缘轴将始终相对于轴的位置绘制。

# Create a Figure, which doesn't have to be square.
fig = plt.figure(layout='constrained')
# Create the main Axes, leaving 25% of the figure space at the top and on the
# right to position marginals.
ax = fig.add_gridspec(top=0.75, right=0.75).subplots()
# The main Axes' aspect can be fixed.
ax.set(aspect=1)
# Create marginal Axes, which have 25% of the size of the main Axes.  Note that
# the inset Axes are positioned *outside* (on the right and the top) of the
# main Axes, by specifying axes coordinates greater than 1.  Axes coordinates
# less than 0 would likewise specify positions on the left and the bottom of
# the main Axes.
ax_histx = ax.inset_axes([0, 1.05, 1, 0.25], sharex=ax)
ax_histy = ax.inset_axes([1.05, 0, 0.25, 1], sharey=ax)
# Draw the scatter plot and marginals.
scatter_hist(x, y, ax, ax_histx, ax_histy)

plt.show()

参考文献

本示例展示了以下函数、方法、类和模块的使用情况

脚本的总运行时间：（0 分钟 1.370 秒）

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带直方图的散点图#

使用 gridspec 定义轴位置#

使用 inset_axes 定义轴位置#

使用 gridspec 定义轴位置 #

使用 inset_axes 定义轴位置 #