使用边距和sticky_edges 控制视图限制#

此示例中的第一个图显示了如何使用margins而不是set_xlim和来放大和缩小绘图set_ylim。第二个图展示了某些方法和艺术家引入的边缘“粘性”概念，以及如何有效地解决这个问题。

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon


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))

ax2 = plt.subplot(221)
ax2.margins(2, 2)           # Values >0.0 zoom out
ax2.plot(t1, f(t1))
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))
ax3.set_title('Zoomed in')

plt.show()

关于某些绘图方法的“粘性” #

一些绘图功能使轴限制“粘性”或不受方法意志的影响margins。例如，imshow并 pcolor期望用户希望限制在图中显示的像素附近。如果不需要此行为，则需要设置 use_sticky_edges为False. 考虑以下示例：

y, x = np.mgrid[:5, 1:6]
poly_coords = [
    (0.25, 2.75), (3.25, 2.75),
    (2.25, 0.75), (0.25, 0.75)
]
fig, (ax1, ax2) = plt.subplots(ncols=2)

# Here we set the stickiness of the axes object...
# ax1 we'll leave as the default, which uses sticky edges
# and we'll turn off stickiness for ax2
ax2.use_sticky_edges = False

for ax, status in zip((ax1, ax2), ('Is', 'Is Not')):
    cells = ax.pcolor(x, y, x+y, cmap='inferno', shading='auto')  # sticky
    ax.add_patch(
        Polygon(poly_coords, color='forestgreen', alpha=0.5)
    )  # not sticky
    ax.margins(x=0.1, y=0.05)
    ax.set_aspect('equal')
    ax.set_title('{} Sticky'.format(status))

plt.show()

参考

此示例中显示了以下函数、方法、类和模块的使用：

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