Python 中的 matplotlib . axis . axis . get _ transform()函数
原文:https://www . geeksforgeeks . org/matplotlib-axis-axis-get _ transform-python 中的函数/
Matplotlib 是 Python 中的一个库，是 NumPy 库的数值-数学扩展。这是一个神奇的 Python 可视化库，用于 2D 数组图，并用于处理更广泛的 SciPy 堆栈。
matplotlib . axis . axis . get _ transform()函数
matplotlib 库的 Axis 模块中的 Axis.get_transform()函数用来获取该艺术家使用的 transform 实例。
语法: Axis.get_transform(self)
参数:该方法不接受任何参数。
返回值:该方法返回该艺术家使用的 Transform 实例。
下面的例子说明了 matplotlib . axis . axis . get _ transform()函数在 matplotlib.axis:
例 1:
Python 3
# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
fig, ax = plt.subplots()
l1, = ax.plot([0.1, 0.5, 0.9],
[0.1, 0.9, 0.5],
"bo-")
l2, = ax.plot([0.1, 0.5, 0.9],
[0.5, 0.2, 0.7],
"ro-")
for l in [l1, l2]:
xx = l.get_xdata()
yy = l.get_ydata()
shadow, = ax.plot(xx, yy)
shadow.update_from(l)
ot = mtransforms.offset_copy(l.get_transform(),
ax.figure,
x = 4.0, y =-6.0,
units ='points')
shadow.set_transform(ot)
fig.suptitle("""matplotlib.axis.Axis.get_transform()
function Example\n""", fontweight ="bold")
plt.show()
输出:
例 2:
Python 3
# Implementation of matplotlib function
from matplotlib.axis import Axis
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 = plt.subplots()
col = collections.RegularPolyCollection(
7, sizes = np.abs(xx) * 10.0,
offsets = xyo,
transOffset = ax1.transData)
trans = transforms.Affine2D().scale(fig.dpi / 72.0)
Axis.set_transform(col, trans)
ax1.add_collection(col, autolim = True)
col.set_color(colors)
print("Value Return by get_transform() :\n",
col.get_transform())
fig.suptitle("""matplotlib.axis.Axis.get_transform()
function Example\n""", fontweight ="bold")
plt.show()
输出:
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