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.Axis.reset_ticks() Function
The Axis.reset_ticks() function in axis module of matplotlib library is used to re-initialize the major and minor Tick lists.
Syntax: Axis.reset_ticks(self)
Parameters: This method does not accepts any parameter.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Axis.reset_ticks() function in matplotlib.axis:
Example 1:
# Implementation of matplotlib function from matplotlib.axis import Axis
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.gridspec as gridspec
import numpy as np
plt.rcParams[ 'savefig.facecolor' ] = "0.8"
plt.rcParams[ 'figure.figsize' ] = 6 , 5
fig, ax = plt.subplots()
ax.plot([ 1 , 2 ])
ax.locator_params( "x" ,nbins = 3 )
ax.locator_params( "y" ,nbins = 5 )
ax.set_xlabel( 'x-label' )
ax.set_ylabel( 'y-label' )
ax.yaxis.reset_ticks() ax.grid() fig.suptitle( """matplotlib.axis.Axis.reset_ticks()
function Example\n""" , fontweight = "bold")
plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.axis import Axis
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
Axis.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( - 5 , 5 )
ax.set_ylim( - 4 , 4 )
ax.yaxis.reset_ticks() ax.grid() fig.suptitle( """matplotlib.axis.Axis.reset_ticks()
function Example\n""" , fontweight = "bold")
plt.show() |
Output: