Python 中的 matplotlib . axis . tick . set _ transform()函数
原文:https://www . geesforgeks . org/matplotlib-axis-tick-set _ 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 . tick . set _ transform()函数
matplotlib 库的轴模块中的 Tick.set_transform()函数用于设置艺术家变换。
语法: Tick.set_transform(self，t)
参数:该方法接受以下参数。
- t: 此参数为变换。
返回值:此方法不返回值。
以下示例说明 matplotlib . axis . tick . set _ transform()函数在 matplotlib.axis: 示例 1:
Python 3
# Implementation of matplotlib function
from matplotlib.axis import Tick
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
delta = 0.5
x = y = np.arange(-2.0, 4.0, delta)
X, Y = np.meshgrid(x**2, y)
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2)
transform = mtransforms.Affine2D().rotate_deg(30)
fig, ax = plt.subplots()
im = ax.imshow(Z, interpolation ='none',
origin ='lower',
extent =[-2, 4, -3, 2],
clip_on = True)
trans_data = transform + ax.transData
Tick.set_transform(im, trans_data)
x1, x2, y1, y2 = im.get_extent()
ax.plot([x1, x2, x2, x1, x1],
[y1, y1, y2, y2, y1],
"ro-",
transform = trans_data)
ax.set_xlim(-3, 6)
ax.set_ylim(-5, 5)
fig.suptitle('matplotlib.axis.Tick.set_transform() \
function Example', fontweight ="bold")
plt.show()
输出:
例 2:
Python 3
# Implementation of matplotlib function
from matplotlib.axis import Tick
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)
Tick.set_transform(col, trans)
ax1.add_collection(col, autolim = True)
col.set_color(colors)
fig.suptitle('matplotlib.axis.Tick.set_transform() \
function Example', fontweight ="bold")
plt.show()
输出:
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