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Matplotlib.axes.Axes.get_xticklines() in Python

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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.get_xticklines() Function

The Axes.get_xticklines() function in axes module of matplotlib library is used to return the x tick lines as a list of Line2D instances.

Syntax: Axes.get_xticklines(self)

Parameters: This method does not accepts any parameters.

Return value: This method returns the x tick lines as a list of Line2D instances.

Below examples illustrate the matplotlib.axes.Axes.get_xticklines() function in matplotlib.axes:

Example 1:




# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
       
def func(x):
    return (x - 4) * (x - 6) * (x - 5) + 100
       
a, b = 2, 9  # integral limits
x = np.linspace(0, 10)
y = func(x)
       
fig, ax = plt.subplots()
ax.plot(x, y, "k", linewidth = 2)
ax.set_ylim(bottom = 0)
       
# Make the shaded region
ix = np.linspace(a, b)
iy = func(ix)
verts = [(a, 0), *zip(ix, iy), (b, 0)]
poly = Polygon(verts, facecolor ='green',
               edgecolor ='0.5', alpha = 0.4)
ax.add_patch(poly)
       
ax.text(0.5 * (a + b), 30,
        r"$\int_a ^ b f(x)\mathrm{d}x$",
        horizontalalignment ='center'
        fontsize = 20)
       
fig.text(0.9, 0.05, '$x$')
fig.text(0.1, 0.9, '$y$')
       
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
     
ax.set_xticks((a, b-a, b))
ax.set_xticklabels(('$a$', '$valx$', '$b$'))
  
w = ax.get_xticklines()
ax.text(3, 200, "xticklines values : "
       fontweight ="bold")
xx = 200
for i in w:
    ax.text(4, xx-15, str(i), fontweight ="bold")
    xx-= 15
    
fig.suptitle('matplotlib.axes.Axes.get_xticklines()\
 function Example\n\n', fontweight ="bold")
fig.canvas.draw()
plt.show()


Output:

Example 2:




# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
       
# Fixing random state for reproducibility
np.random.seed(19680801)
       
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)
y2 = y + 0.2 * np.random.normal(size = x.shape)
       
fig, ax = plt.subplots()
ax.plot(x, y)
ax.plot(x, y2)
      
ax.set_xticks([0, np.pi, 2 * np.pi])
ax.set_xticklabels(['0', r'$pi$', r'2$pi$'])
       
ax.spines['left'].set_bounds(-1, 1)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
  
w = ax.get_xticklines()
ax.text(2, 0.8, "xticklines values : "
        fontweight ="bold")
xx = 0.8
for i in w:
    ax.text(2.3, xx-0.2, str(i), fontweight ="bold")
    xx-= 0.2
    
fig.suptitle('matplotlib.axes.Axes.get_xticklines() \
function Example\n\n', fontweight ="bold")
fig.canvas.draw()
plt.show()


Output:



Last Updated : 19 Apr, 2020
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