带有直方图的散点图#

将散点图的边缘分布显示为图两侧的直方图。

为了使主轴与边缘很好地对齐,下面显示了两个选项:

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。

Scatter Histogram (Locatable Axes) 示例axes_grid1 中显示了使用该工具包生成类似图形的另一种方法。最后,还可以使用(此处未显示)将所有轴定位在绝对坐标中。Figure.add_axes

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

import numpy as np
import matplotlib.pyplot as plt

# 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 定义坐标轴位置

我们定义了一个不等宽高比的 gridspec 来实现所需的布局。另请参阅在图形教程中排列多个轴。

# 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)
分散历史

使用 inset_axes 定义坐标轴位置#

inset_axes可用于将边缘定位在主轴之外。这样做的好处是可以固定主轴的纵横比,并且总是会相对于轴的位置绘制边缘。

# Create a Figure, which doesn't have to be square.
fig = plt.figure(constrained_layout=True)
# 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()
分散历史

脚本总运行时间:(0分1.217秒)

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