Matplotlib是Python中的一個庫，它是數字的-NumPy庫的數學擴展。 Figure模塊提供了頂層Artist，即Figure，其中包含所有繪圖元素。此模塊用於控製所有圖元的子圖和頂層容器的默認間距。
matplotlib.figure.Figure.get_tight_layout()方法
matplotlib庫的get_tight_layout()方法圖形模塊用於檢查繪圖時是否調用了tight_layout。
用法： get_size_inches(self)
參數：此方法不接受任何參數。
返回：此方法返回是否調用tight_layout。
以下示例說明了matplotlib.figure中的matplotlib.figure.Figure.get_tight_layout()函數：
範例1：
# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(-5, 5, 0.01)
y1 = -3 * x*x + 10 * x + 10
y2 = 3 * x*x + x
fig, ax = plt.subplots()
fig.tight_layout()
ax.plot(x, y1, x, y2, color ='black')
ax.fill_between(x, y1, y2, where = y2 >y1,
facecolor ='green',
alpha = 0.8)
ax.fill_between(x, y1, y2, where = y2 <= y1,
facecolor ='black',
alpha = 0.8)
w = fig.get_tight_layout()
ax.text(-3, -80,
"Value Return by get_tight_layout():"
+ str(w),
fontweight ="bold")
fig.canvas.draw()
fig.suptitle('matplotlib.figure.Figure.get_tight_layout()\
function Example', fontweight ="bold")
plt.show()輸出：
範例2：
# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
import numpy as np
# Create triangulation.
x = np.asarray([0, 1, 2, 3, 0.5,
1.5, 2.5, 1, 2,
1.5])
y = np.asarray([0, 0, 0, 0, 1.0,
1.0, 1.0, 2, 2,
3.0])
triangles = [[0, 1, 4], [1, 5, 4],
[2, 6, 5], [4, 5, 7],
[5, 6, 8], [5, 8, 7],
[7, 8, 9], [1, 2, 5],
[2, 3, 6]]
triang = mtri.Triangulation(x, y, triangles)
z = np.cos(1.5 * x) * np.cos(1.5 * y)
fig, axs = plt.subplots()
axs.tricontourf(triang, z)
axs.triplot(triang, 'go-', color ='white')
fig.tight_layout(rect =(0.1, 0.1, 0.95, 0.95))
w = fig.get_tight_layout()
axs.text(.7, 2.8,
"Value Return by get_tight_layout():"
+ str(w),
fontweight ="bold")
fig.canvas.draw()
fig.suptitle('matplotlib.figure.Figure.get_tight_layout() \
function Example', fontweight ="bold")
plt.show()輸出：
相關用法
注：本文由純淨天空篩選整理自SHUBHAMSINGH10大神的英文原創作品 Matplotlib.figure.Figure.get_tight_layout() in Python。非經特殊聲明，原始代碼版權歸原作者所有，本譯文未經允許或授權，請勿轉載或複製。