Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.
Matplotlib.axis.Tick.set_transform() Function
The Tick.set_transform() function in axis module of matplotlib library is used to set the artist transform.
Syntax: Tick.set_transform(self, t)
Parameters: This method accepts the following parameters.
- t: This parameter is the Transform.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Tick.set_transform() function in matplotlib.axis:
Example 1:
# 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() |
Output:
Example 2:
# 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() |
Output: