Subplots, axes and figures

1. Axes Props

你可以控制坐标轴刻度和网格属性

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.0, 2.0, 0.01)
s = np.sin(2 * np.pi * t)

fig, ax = plt.subplots()
ax.plot(t, s)

ax.grid(True, linestyle='-.')
ax.tick_params(labelcolor='r', labelsize='medium', width=3)

plt.show()

2. Invert Axes

通过翻转坐标轴限制的正常顺序，可以使用递减轴

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.01, 5.0, 0.01)
s = np.exp(-t)
plt.plot(t, s)

plt.xlim(5, 0)  # decreasing time

plt.xlabel('decreasing time (s)')
plt.ylabel('voltage (mV)')
plt.title('Should be growing...')
plt.grid(True)

plt.show()

3. Subplot Toolbar

Matplotlib 有一个工具栏可用于调整 suplot 间距。

import matplotlib.pyplot as plt
import numpy as np

fig, axs = plt.subplots(2, 2)

axs[0, 0].imshow(np.random.random((100, 100)))

axs[0, 1].imshow(np.random.random((100, 100)))

axs[1, 0].imshow(np.random.random((100, 100)))

axs[1, 1].imshow(np.random.random((100, 100)))

plt.subplot_tool()
plt.show()

4. Multiple Figs Demo

使用多个图形窗口和 subplots

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.0, 2.0, 0.01)
s1 = np.sin(2*np.pi*t)
s2 = np.sin(4*np.pi*t)

创建图1

plt.figure(1)
plt.subplot(211)
plt.plot(t, s1)
plt.subplot(212)
plt.plot(t, 2*s1)

创建图2

plt.figure(2)
plt.plot(t, s2)

现在切换回图1并进行一些更改

plt.figure(1)
plt.subplot(211)
plt.plot(t, s2, 's')
ax = plt.gca()
ax.set_xticklabels([])

plt.show()

5. Multiple subplots

具有多个 subplots 的简单演示

import numpy as np
import matplotlib.pyplot as plt


x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.subplot(2, 1, 1)
plt.plot(x1, y1, 'o-')
plt.title('A tale of 2 subplots')
plt.ylabel('Damped oscillation')

plt.subplot(2, 1, 2)
plt.plot(x2, y2, '.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')

plt.show()

6. Subplots Adjust

使用 subplots_adjust() 调整边距和 subplots 的间距。

import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)


plt.subplot(211)
plt.imshow(np.random.random((100, 100)), cmap=plt.cm.BuPu_r)
plt.subplot(212)
plt.imshow(np.random.random((100, 100)), cmap=plt.cm.BuPu_r)

plt.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
cax = plt.axes([0.85, 0.1, 0.075, 0.8])
plt.colorbar(cax=cax)
plt.show()

7. Geographic Projections

这显示了使用了 subplot 的4种可能的预测。Matplotlib 还支持Basemaps Toolkit 和 Cartopy 地理预测。

import matplotlib.pyplot as plt

plt.figure()
plt.subplot(111, projection="aitoff")
plt.title("Aitoff")
plt.grid(True)

plt.figure()
plt.subplot(111, projection="hammer")
plt.title("Hammer")
plt.grid(True)

plt.figure()
plt.subplot(111, projection="lambert")
plt.title("Lambert")
plt.grid(True)

plt.figure()
plt.subplot(111, projection="mollweide")
plt.title("Mollweide")
plt.grid(True)

plt.show()

8. Basic Subplot Demo

两个 subplots 演示。有关更多选项，请参阅 Subplots Demo

import numpy as np
import matplotlib.pyplot as plt

# Data for plotting
x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

# Create two subplots sharing y axis
fig, (ax1, ax2) = plt.subplots(2, sharey=True)

ax1.plot(x1, y1, 'ko-')
ax1.set(title='A tale of 2 subplots', ylabel='Damped oscillation')

ax2.plot(x2, y2, 'r.-')
ax2.set(xlabel='time (s)', ylabel='Undamped')

plt.show()

9. Custom Figure Class

如果要从默认图形派生，可以将自定义图形构造函数传递给图。这个简单的示例创建一个具有图形标题的图形。

import matplotlib.pyplot as plt
from matplotlib.figure import Figure


class MyFigure(Figure):
    def __init__(self, *args, **kwargs):
        """
        custom kwarg figtitle is a figure title
        """
        figtitle = kwargs.pop('figtitle', 'hi mom')
        Figure.__init__(self, *args, **kwargs)
        self.text(0.5, 0.95, figtitle, ha='center')


fig = plt.figure(FigureClass=MyFigure, figtitle='my title')
ax = fig.subplots()
ax.plot([1, 2, 3])

plt.show()

10. Shared Axis Demo

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.01, 5.0, 0.01)
s1 = np.sin(2 * np.pi * t)
s2 = np.exp(-t)
s3 = np.sin(4 * np.pi * t)

ax1 = plt.subplot(311)
plt.plot(t, s1)
plt.setp(ax1.get_xticklabels(), fontsize=6)

# share x only
ax2 = plt.subplot(312, sharex=ax1)
plt.plot(t, s2)
# make these tick labels invisible
plt.setp(ax2.get_xticklabels(), visible=False)

# share x and y
ax3 = plt.subplot(313, sharex=ax1, sharey=ax1)
plt.plot(t, s3)
plt.xlim(0.01, 5.0)
plt.show()

11. Zooming in and out using Axes.margins

此示例演示如何使用 margins 而不是 set_xlim 和 set_ylim 。

import numpy as np
import matplotlib.pyplot as plt


def f(t):
    return np.exp(-t) * np.cos(2*np.pi*t)


t1 = np.arange(0.0, 3.0, 0.01)

ax1 = plt.subplot(212)
ax1.margins(0.05)           # Default margin is 0.05, value 0 means fit
ax1.plot(t1, f(t1), 'k')

ax2 = plt.subplot(221)
ax2.margins(2, 2)           # Values >0.0 zoom out
ax2.plot(t1, f(t1), 'r')
ax2.set_title('Zoomed out')

ax3 = plt.subplot(222)
ax3.margins(x=0, y=-0.25)   # Values in (-0.5, 0.0) zooms in to center
ax3.plot(t1, f(t1), 'g')
ax3.set_title('Zoomed in')

plt.show()

12. Creating adjacent subplots

import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.0, 2.0, 0.01)

s1 = np.sin(2 * np.pi * t)
s2 = np.exp(-t)
s3 = s1 * s2

fig, axs = plt.subplots(3, 1, sharex=True)
# Remove horizontal space between axes
fig.subplots_adjust(hspace=0)

# Plot each graph, and manually set the y tick values
axs[0].plot(t, s1)
axs[0].set_yticks(np.arange(-0.9, 1.0, 0.4))
axs[0].set_ylim(-1, 1)

axs[1].plot(t, s2)
axs[1].set_yticks(np.arange(0.1, 1.0, 0.2))
axs[1].set_ylim(0, 1)

axs[2].plot(t, s3)
axs[2].set_yticks(np.arange(-0.9, 1.0, 0.4))
axs[2].set_ylim(-1, 1)

plt.show()

13. Aligning Labels

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

fig = plt.figure(tight_layout=True)
gs = gridspec.GridSpec(2, 2)

ax = fig.add_subplot(gs[0, :])
ax.plot(np.arange(0, 1e6, 1000))
ax.set_ylabel('YLabel0')
ax.set_xlabel('XLabel0')

for i in range(2):
    ax = fig.add_subplot(gs[1, i])
    ax.plot(np.arange(1., 0., -0.1) * 2000., np.arange(1., 0., -0.1))
    ax.set_ylabel('YLabel1 %d' % i)
    ax.set_xlabel('XLabel1 %d' % i)
    if i == 0:
        for tick in ax.get_xticklabels():
            tick.set_rotation(55)
fig.align_labels()  # same as fig.align_xlabels(); fig.align_ylabels()

plt.show()