笔记
单击此处 下载完整的示例代码
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)
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()
参考
此示例中显示了以下函数、方法、类和模块的使用:
脚本总运行时间:(0分1.217秒)