In [1]:

import matplotlib
import matplotlib.pyplot as plt
import matplotlib.pylab as pylab
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
%matplotlib inline

最普通的也是最丑的

In [2]:

fig, axes = plt.subplots(3, 3, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        col.imshow(np.arange(100).reshape((10,10)))
        col.set_xlabel('x')
        col.set_ylabel('y')
        
plt.tight_layout()

只在最外层坐标轴显示 Label

In [3]:

fig, axes = plt.subplots(3, 3, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        col.imshow(np.arange(100).reshape((10,10)))
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
plt.tight_layout()

如果 x label y label 都一样可以只显示一个

In [4]:

fig, axes = plt.subplots(3, 3, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        col.imshow(np.arange(100).reshape((10,10)))
        
fig.text(0.5, 0, 'x', ha='center')
fig.text(0, 0.5, 'y', va='center', rotation='vertical')
            
plt.tight_layout()

刻度也只在最外侧显示

In [5]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        col.imshow(np.arange(100).reshape((10,10)))
        
fig.text(0.5, 0, 'x', ha='center')
fig.text(0, 0.5, 'y', va='center', rotation='vertical')
            
plt.tight_layout()

或者Label仍然分开显示

In [6]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        col.imshow(np.arange(100).reshape((10,10)))
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
plt.tight_layout()

加入 colorbar

In [7]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,6))

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        im = col.imshow(np.arange(100).reshape((10,10)))
        ax_cb = fig.colorbar(im, ax=col)
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
plt.tight_layout()

整个 fig 共用一个 colorbar

In [8]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,6))
fig.subplots_adjust(wspace = .1,hspace = 0)

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        im = col.imshow(np.arange(100).reshape((10,10)))
#         ax_cb = fig.colorbar(im, ax=col)
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
cb = fig.colorbar(im, ax=axes.ravel().tolist())
cb.ax.tick_params()
cb.set_label("colorbar")

# plt.tight_layout() # 使用 tight layout 需要手动调整 colorbar 位置，否则会很难看
plt.show()

colorbar 横置

In [9]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,6))
fig.subplots_adjust(wspace = 0,hspace = 0.1)

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        im = col.imshow(np.arange(100).reshape((10,10)))
#         ax_cb = fig.colorbar(im, ax=col)
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
cb = fig.colorbar(im, ax=axes.ravel().tolist(),orientation='horizontal')
cb.ax.tick_params()
cb.set_label("colorbar")

# plt.tight_layout() # 使用 tight layout 需要手动调整 colorbar 位置，否则会很难看
plt.show()

调整 colorbar 位置和尺寸

In [10]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,5))
fig.subplots_adjust(wspace = .1,hspace = 0)

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        im = col.imshow(np.arange(100).reshape((10,10)))
#         ax_cb = fig.colorbar(im, ax=col)
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
            
fig.subplots_adjust(bottom=0, right=0.9, top=1)
cax = plt.axes([0.92, 0.03, 0.03, 0.95])
cb = fig.colorbar(im, cax=cax)
cb.ax.tick_params()
cb.set_label('colorbar')

# plt.tight_layout() # 使用 tight layout 需要手动调整 colorbar 位置，否则会很难看
plt.show()

调整 ticks 显示位置以及 label

最后一个 ax 有点问题

In [11]:

fig, axes = plt.subplots(3, 3, sharex=True, sharey=True, figsize=(6,5))
fig.subplots_adjust(wspace = .1,hspace = 0)

for i, row in enumerate(axes):
    for j, col in enumerate(row):
        im = col.imshow(np.arange(100).reshape((10,10)))
#         ax_cb = fig.colorbar(im, ax=col)
        if col.is_last_row():
            col.set_xlabel('x')
        if col.is_first_col():
            col.set_ylabel('y')
        col.set_xticks(np.arange(0, 11, 2))
        col.set_yticks(np.arange(0, 11, 2))
        col.set_xticklabels(np.arange(1, 11, 2))
        col.set_yticklabels(np.arange(1, 11, 2))
            
fig.subplots_adjust(bottom=0, right=0.9, top=1)
cax = plt.axes([0.92, 0.03, 0.03, 0.95])
cb = fig.colorbar(im, cax=cax)
cb.ax.tick_params()
cb.set_label('colorbar')

# plt.tight_layout() # 使用 tight layout 需要手动调整 colorbar 位置，否则会很难看
plt.show()

twin x¶

In [12]:

fig, ax = plt.subplots(figsize=(6,4))

t = np.linspace(0, 2*np.pi, 50, endpoint=False)
sins = np.sin(t)
coss = np.cos(t)

ax.plot(t, sins, 'r', alpha=0.5, lw=0.5, ls='-', marker='+', label='sin')

ax2 = ax.twinx()
ax2.plot(t, coss, 'g', alpha=0.5, lw=0.5, ls='-', marker='+', label='cos')
for tl in ax2.get_yticklabels():
    tl.set_color("r")

plt.tight_layout()

Matplotlib中多子图绘图时，坐标轴及其label的几种排布方式

twin x¶

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