如何从子图中完全删除图并适当调整大小？

Question

我正在尝试为即将发表的论文创建角图，但运行遇到了困难。我正在创建一个 N x N 子图数组（目前，N = 6），然后删除其中一半以上的子图。问题是，在我删除无关的子图后，该图似乎没有自行调整大小，因此当我稍后使用虚拟子图添加图例时，它存在于一整行和一列已删除的子图所在的区域，从而扩大了图。我已经为此工作了几个小时，但还没有找到解决方案。这是 MWE：

import matplotlib.pyplot as plt
%matplotlib notebook

n_char = 8

# Set up the main figure.
fig, ax = plt.subplots(n_char, n_char, figsize=(n_char, n_char))

# Get rid of the axis labels unless it's on the left-most column or bottom-most row.
for i in range(0, n_char):

    # For each row, loop over each column.
    for j in range(0, n_char):

        # If the plot isn't in the bottom-most row, get rid of the x-axis tick labels.
        if i != n_char - 1:
            ax[i, j].set_xticklabels([])

        # If the plot isn't in the left-most column, get rid of the y-axis tick labels.
        if j != 0:
            ax[i, j].set_yticklabels([])

# Remove the plots that are repetitive or boring (plotting against the same characteristic).
for i in range(0, n_char):

    # For each row, loop over each column.
    for j in range(0, n_char):

        # Delete the offending axes.
        if j >= i:
            ax[i, j].remove()

# Set the spacing between the plots to a much smaller value.
fig.subplots_adjust(hspace=0.00, wspace=0.00)

# Create a big plot for the legend.  Have the frame hidden.
fig.add_subplot(111, frameon=False, xticks=[], yticks=[], xticklabels=[], yticklabels=[])

# Create some dummy data to serve as the source of the legend.
plt.scatter([10], [10], color="k", s=5, zorder=2, label="Targets")

# Set the x-axis limits such that the dummy data point is invisible.
fig.gca().set_xlim(-1, 1)

# Add the legend to the plot.  Have it located in the upper right.
plt.legend(scatterpoints=1, loc="upper right", fontsize=5)

# Save the final plot.
fig.savefig("./../Code Output/Other Plots/Corner_Plot_Test.png", bbox_inches="tight", dpi=500)

我在 Stack Overflow 上查看了许多不同的问题。两个最有希望的候选人 , but I found the solution wasn't quite workable due to the large number of plots (and, to be frank, I didn't fully understand the solution). I thought that the first answer in 也可能有效，因为我认为这是一个大小问题（即图形没有调整大小，所以创建一个新的子图就是创建一个与原始图形大小相同的子图），但所有它确实调整了 entire 图形的大小，所以这也不起作用。

为了提供帮助，我还会附上一张图片。我获取了上面代码的输出并对其进行了编辑以显示我想要的内容：

我应该补充一点，如果我不添加子图，输出是我预期的（即它是正确的大小），所以问题出现在添加子图，即行 fig.add_subplot(111, frameon=False, xticks=[], yticks=[], xticklabels=[], yticklabels=[]).

Answer 1

使用GridSpec可能会有帮助。 GridSpec 用于指定要绘制的轴数组。您可以在选项中将列宽和行高设置为比率。不需要的行应该有很小的高度比，而不需要的列应该有很小的宽度比。这是可运行的代码和输出图：-

import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
#import numpy as np

fig = plt.figure(figsize=(8, 8))
nn = 6

# will create gridspec of 6 rows, 6 columns
# 1st row will occupy v small heights
# last column will occupy v small widths

sm = 0.01            # the v small width/height
wh = (1.-sm)/(nn-1.) # useful width/height

gs = gridspec.GridSpec(nn, nn, width_ratios=[*[wh]*(nn-1), sm], \
                      height_ratios= [sm, *[wh]*(nn-1)])

cols, rows = nn, nn
ax = [[0 for i in range(cols)] for j in range(rows)] 

for ea in range(nn):
    for eb in range(nn):
        ax[ea][eb] = fig.add_subplot(gs[ea, eb])
        ax[ea][eb].set_xticklabels([])
        ax[ea][eb].set_yticklabels([])
        if eb>=ea:
            ax[ea][eb].remove()

# plot data on some axes
# note that axes on the first row (index=0) are gone
ax[2][0].plot([2,5,3,7])
ax[4][2].plot([2,3,7])

# make legend in upper-right axes (GridSpec's first row, last column)
# first index: 0
# second index: nn-1
rx, cx = 0, nn-1
ax[rx][cx] = fig.add_subplot(gs[rx,cx])
hdl = ax[rx][cx].scatter([10], [10], color="k", s=5, zorder=2, label="Targets")
ax[rx][cx].set_axis_off()
#ax[rx][cx].set_visible(True)  # already True
ax[rx][cx].set_xticklabels([])
ax[rx][cx].set_yticklabels([])

# plot legend
plt.legend(bbox_to_anchor=(1.0, 1.0), loc='upper right', borderaxespad=0.)

fig.subplots_adjust(hspace=0.00, wspace=0.00)

plt.show

如何从子图中完全删除图并适当调整大小？

How to fully delete plots from subplot and properly resize?

matplotlib

python-2.7

subplot

jupyter-notebook