Python中的 Matplotlib.axes.Axes.autoscale_view()

Matplotlib是Python中的一个库，它是 NumPy 库的数值数学扩展。 Axes 类包含大部分图形元素：Axis、Tick、Line2D、Text、Polygon 等，并设置坐标系。 Axes 的实例通过回调属性支持回调。

matplotlib.axes.Axes.autoscale_view()函数

matplotlib 库的 axes 模块中的Axes.autoscale_view()函数用于使用数据限制自动缩放视图限制。

Syntax: Axes.autoscale_view(self, tight=None, scalex=True, scaley=True)

Parameters: This method accepts the following parameters.

scalex: This parameter is used to whether to autoscale the x axis.
scaley: This parameter is used to whether to autoscale the y axis.
tight: This parameter is used to expand the axis limits using the margins.

Return value: This method does not return any value.

编程需要懂一点英语

下面的示例说明了 matplotlib.axes 中的 matplotlib.axes.Axes.autoscale()函数：

示例 1：

# ImpleIn Reviewtation of matplotlib function  
import numpy as np
from basic_units import cm, inch
import matplotlib.pyplot as plt
  
  
N = 5
val1 = [150 * cm, 160 * cm, 146 * cm, 
        172 * cm, 155 * cm]
  
val2 = [20 * cm, 30 * cm, 32 * cm, 
        10 * cm, 20 * cm]
  
fig, ax = plt.subplots()
  
ind = np.arange(N)
width = 0.35      
ax.bar(ind, val1, width, bottom = 0 * cm,
       yerr = val2, label ='In Review')
  
woval1 = (145 * cm, 149 * cm, 172 * cm,
          165 * cm, 200 * cm)
woval2 = (30 * cm, 25 * cm, 20 * cm, 
          31 * cm, 22 * cm)
ax.bar(ind + width, woval1, width,
       bottom = 0 * cm, yerr = woval2,
       label ='Published')
  
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(('Geek1', 'Geek2', 
                    'Geek3', 'Geek4',
                    'Geek5'))
  
ax.legend()
ax.set_ylabel("Articles")
ax.autoscale_view()
  
fig.suptitle('matplotlib.axes.Axes.autoscale_view()\
function Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()

输出：

示例 2：

# Implementation of matplotlib function  
import matplotlib.pyplot as plt
from matplotlib import collections, colors, transforms
import numpy as np
  
nverts = 50
npts = 100
  
r = np.arange(nverts)
theta = np.linspace(0, 2 * np.pi, nverts)
xx = r * np.sin(theta)
yy = r * np.cos(theta)
spiral = np.column_stack([xx, yy])
  
rs = np.random.RandomState(19680801)
  
xyo = rs.randn(npts, 2)
  
colors = [colors.to_rgba(c)
          for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]
  
fig, [ax1, ax2] = plt.subplots(1, 2)
  
col = collections.RegularPolyCollection(
    7, sizes = np.abs(xx) * 10.0, offsets = xyo,
    transOffset = ax1.transData)
trans = transforms.Affine2D().scale(fig.dpi / 72.0)
col.set_transform(trans) 
ax1.add_collection(col, autolim = True)
col.set_color(colors)
ax1.set_title("Without autoscale_view() function")
  
col = collections.RegularPolyCollection(
    7, sizes = np.abs(xx) * 10.0, offsets = xyo, 
    transOffset = ax2.transData)
  
trans = transforms.Affine2D().scale(fig.dpi / 72.0)
col.set_transform(trans) 
ax2.add_collection(col, autolim = True)
col.set_color(colors)
ax2.autoscale_view()
ax2.set_title("Using autoscale_view() function")
  
fig.suptitle('matplotlib.axes.Axes.autoscale_view()\
 function Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()

输出：