Python 缩小Matplotlib Gridspec中具有紧密_布局（）的单个子地块之间的空间

我正在使用

matplotlib.gridspec

和

tight_layout（）

创建复杂的绘图布局。我当前的代码看起来像

import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib
from matplotlib.ticker import MaxNLocator

fig = plt.figure(figsize=(15,15))
gs1 = gridspec.GridSpec(8, 2)

gs1.update(left=0.05, right=0.95, wspace=0.05, hspace=0.05)

ax1 = plt.subplot(gs1[0:4, 0]) # Original
ax2 = plt.subplot(gs1[0:4, 1]) # Model
ax3 = plt.subplot(gs1[4:8, 0]) # Residual+Sky
ax4 = plt.subplot(gs1[4:7, 1]) # SB profile
ax5 = plt.subplot(gs1[7:8, 1])# SB residuals

# Hide tick labels
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_yticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_yticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plt.setp(ax4.get_xticklabels(), visible=False)

ax4.invert_yaxis()
ax4.set_ylabel(r'Surface Brightness, $\mu$ [mag arcsec$^{-2}$]')
ax5.set_ylabel(r'$\Delta\mu$')
ax5.set_xlabel('Semi-major Axis [arcsec]')
ax5.grid(b=True)
ax4.set_xscale('log')
ax5.set_xscale('log')

gs1.tight_layout(fig)

nbins = len(ax5.get_xticklabels())
ax5.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))
ax4.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))

# Show the plot
plt.show()

这将生成一个类似于

import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib
from matplotlib.ticker import MaxNLocator

fig = plt.figure(figsize=(15,15))
gs1 = gridspec.GridSpec(8, 2)

gs1.update(left=0.05, right=0.95, wspace=0.05, hspace=0.05)

ax1 = plt.subplot(gs1[0:4, 0]) # Original
ax2 = plt.subplot(gs1[0:4, 1]) # Model
ax3 = plt.subplot(gs1[4:8, 0]) # Residual+Sky
ax4 = plt.subplot(gs1[4:7, 1]) # SB profile
ax5 = plt.subplot(gs1[7:8, 1])# SB residuals

# Hide tick labels
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_yticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_yticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plt.setp(ax4.get_xticklabels(), visible=False)

ax4.invert_yaxis()
ax4.set_ylabel(r'Surface Brightness, $\mu$ [mag arcsec$^{-2}$]')
ax5.set_ylabel(r'$\Delta\mu$')
ax5.set_xlabel('Semi-major Axis [arcsec]')
ax5.grid(b=True)
ax4.set_xscale('log')
ax5.set_xscale('log')

gs1.tight_layout(fig)

nbins = len(ax5.get_xticklabels())
ax5.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))
ax4.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))

# Show the plot
plt.show()

我需要做的是

缩小ax4和ax5之间的垂直空间（两个右下角子批次），或

使ax4和ax5共享相同的x轴，以便子批次之间的空间为零

---

我非常喜欢

gridspec

和

tight_layout（）

格式化绘图的方式，但是我不知道如何“强制”各个子绘图之间的间距。使用

matplotlib.gridspec

和

tight_layout（）

是否有一种简单的方法来实现这一点

可以使用axes实例的get_position和set_position方法来更改轴在图中的位置（）

get_position返回一个Bbox实例，您可以使用get_points获得一个2x2 numpy数组，其形式为[[x0，y0]，[x1，y1]]，其中x0，y0，x1，y1是轴的图形坐标

import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib
from matplotlib.ticker import MaxNLocator

fig = plt.figure(figsize=(15,15))
gs1 = gridspec.GridSpec(8, 2)

gs1.update(left=0.05, right=0.95, wspace=0.05, hspace=0.05)

ax1 = plt.subplot(gs1[0:4, 0]) # Original
ax2 = plt.subplot(gs1[0:4, 1]) # Model
ax3 = plt.subplot(gs1[4:8, 0]) # Residual+Sky
ax4 = plt.subplot(gs1[4:7, 1]) # SB profile
ax5 = plt.subplot(gs1[7:8, 1])# SB residuals

# Hide tick labels
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
plt.setp(ax2.get_yticklabels(), visible=False)
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_yticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plt.setp(ax4.get_xticklabels(), visible=False)

ax4.invert_yaxis()
ax4.set_ylabel(r'Surface Brightness, $\mu$ [mag arcsec$^{-2}$]')
ax5.set_ylabel(r'$\Delta\mu$')
ax5.set_xlabel('Semi-major Axis [arcsec]')
ax5.grid(b=True)
ax4.set_xscale('log')
ax5.set_xscale('log')

gs1.tight_layout(fig)

nbins = len(ax5.get_xticklabels())
ax5.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))
ax4.yaxis.set_major_locator(MaxNLocator(nbins=nbins, prune='upper'))

# change axis location of ax5
pos4 = ax4.get_position()
pos5 = ax5.get_position()

points4 = pos4.get_points()
points5 = pos5.get_points()

points5[1][1]=points4[0][1]

pos5.set_points(points5)

ax5.set_position(pos5)
# Show the plot
plt.show()

此代码应生成以下内容：

---

好极了。工作完美。谢谢