Matplotlib子图添加外部色条后如何保持相同帧宽度？

我需要生成包含大量曲线的两个子图，因此定义了一个生成色条（colorbar）的函数，以避免使用过长且难以阅读的图例。创建色条的函数如下：

import matplotlib as mpl, matplotlib.pyplot as plt

def colorbar(cmap, vmin, vmax, label, ax=None, **cbar_opts):
    norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax, clip=False)
    cbar = plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),
                        label=label, ax=ax, **cbar_opts)
    return cbar

由于两个子图的色条取值范围相同，我仅在第二个子图右侧添加一个色条，代码如下：

import pandas as pd, numpy as np

df1 = pd.DataFrame({i: np.linspace(i*i, 10, 10) for i in range(50)})
df2 = pd.DataFrame({i: np.linspace(2*i*i, 10, 10) for i in range(50)})

fig, axs = plt.subplots(1,2, figsize=(5,3))
df1.plot(ax=axs[0], legend=False, cmap='turbo')
df2.plot(ax=axs[1], legend=False, cmap='turbo')

colorbar(ax = axs[1], cmap='turbo', vmin=0, vmax=49, label='My title')

axs[1].set_title('I want this frame \n as large as \n the first one')

plt.tight_layout()

问题：现在两个子图的宽度不同，因为色条被计入第二个子图的宽度测量中，如何让两个子图的帧宽度保持一致？

解决方案1：使用make_axes_locatable分割轴区域 #

通过mpl_toolkits.axes_grid1.make_axes_locatable工具，为色条单独创建一个轴，避免占用原子图的空间，确保两个子图宽度一致。

修改后的完整代码：

import pandas as pd, numpy as np
import matplotlib as mpl, matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

def colorbar(cmap, vmin, vmax, label, ax=None, **cbar_opts):
    norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax, clip=False)
    cbar = plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),
                        label=label, ax=ax, **cbar_opts)
    return cbar

df1 = pd.DataFrame({i: np.linspace(i*i, 10, 10) for i in range(50)})
df2 = pd.DataFrame({i: np.linspace(2*i*i, 10, 10) for i in range(50)})

fig, axs = plt.subplots(1,2, figsize=(5,3))
df1.plot(ax=axs[0], legend=False, cmap='turbo')
df2.plot(ax=axs[1], legend=False, cmap='turbo')

# 分割第二个子图的轴，为色条创建独立空间
divider = make_axes_locatable(axs[1])
cax = divider.append_axes("right", size="5%", pad=0.1)
colorbar(cmap='turbo', vmin=0, vmax=49, label='My title', cax=cax)

axs[1].set_title('I want this frame \n as large as \n the first one')

plt.tight_layout()
plt.show()

解决方案2：使用GridSpec规划布局 #

通过GridSpec设置布局的列宽度比例，让两个子图占用相同宽度的列，色条单独占用一列窄空间，从根源上保证子图宽度一致。

修改后的完整代码：

import pandas as pd, numpy as np
import matplotlib as mpl, matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

def colorbar(cmap, vmin, vmax, label, ax=None, **cbar_opts):
    norm = mpl.colors.Normalize(vmin=vmin, vmax=vmax, clip=False)
    cbar = plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap),
                        label=label, ax=ax, **cbar_opts)
    return cbar

df1 = pd.DataFrame({i: np.linspace(i*i, 10, 10) for i in range(50)})
df2 = pd.DataFrame({i: np.linspace(2*i*i, 10, 10) for i in range(50)})

# 定义1行3列的布局，前两列宽度相同，第三列用于色条
fig = plt.figure(figsize=(5,3))
gs = GridSpec(1, 3, width_ratios=[1, 1, 0.05])

ax1 = fig.add_subplot(gs[0])
ax2 = fig.add_subplot(gs[1])
cax = fig.add_subplot(gs[2])

df1.plot(ax=ax1, legend=False, cmap='turbo')
df2.plot(ax=ax2, legend=False, cmap='turbo')

colorbar(cmap='turbo', vmin=0, vmax=49, label='My title', cax=cax)

ax2.set_title('I want this frame \n as large as \n the first one')

plt.tight_layout()
plt.show()

内容的提问来源于stack exchange，提问作者gioarma