Question

有人可以分享一个示例来创建4个散点图作为子图吗？澄清。我打算创建一个pdf绘图。每页将有4个子图。每个子图都是散布直方图。

创建散布直方图的示例似乎是this

与使用此散点图示例并对每个子图进行子图绘制相比，是否还有其他替代函数可以用更少的行来完成此操作？

Answer 1

使用链接的示例，您要做的就是增加subplots的数量。

然后为每个子图浏览示例代码，以使每个子图成为散布直方图。

我在下面粘贴了一个玩具示例：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig, axes = plt.subplots(figsize=(10,10),nrows=2, ncols=2)
print(axes)
colors = ['r','b','g','m']

for row in axes:
    for axScatter in row:
        print()
        x = np.random.randn(1000)
        y = np.random.randn(1000)
        # the scatter plot:
        # gets color from the end ('m' will be first)
        color = colors.pop()
        axScatter.scatter(x, y,color = color)
        axScatter.set_aspect(1.)

        # create new axes on the right and on the top of the current axes
        # The first argument of the new_vertical(new_horizontal) method is
        # the height (width) of the axes to be created in inches.
        divider = make_axes_locatable(axScatter)
        axHistx = divider.append_axes("top", 1.2, pad=0.1, sharex=axScatter)
        axHisty = divider.append_axes("right", 1.2, pad=0.1, sharey=axScatter)

        # make some labels invisible
        axHistx.xaxis.set_tick_params(labelbottom=False)
        axHisty.yaxis.set_tick_params(labelleft=False)

        # 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)
        axHistx.hist(x, bins=bins,color=color)
        axHisty.hist(y, bins=bins, orientation='horizontal',color=color)

        # the xaxis of axHistx and yaxis of axHisty are shared with axScatter,
        # thus there is no need to manually adjust the xlim and ylim of these
        # axis.

        axHistx.set_yticks([0, 50, 100])

        axHisty.set_xticks([0, 50, 100])

plt.show()

子图几个散点直方图

1 个答案: