Matplotlib.axes.Axes.get_yticks() in Python

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_yticks() Function

The Axes.get_yticks() function in axes module of matplotlib library is used to return the y ticks as a list of locations.

Syntax: Axes.get_yticks(self, minor=False)

Parameters: This method accepts the following parameters.

• minor : This parameter is used whether set major ticks or to set minor ticks

Return value: This method does not returns any value

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

Example 1:

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms


fig, ax = plt.subplots()
ax.plot(range(12, 24), range(12))
ax.set_yticks((2, 5, 7, 10))

w = ax.get_yticks()
ax.text(15, 9, "ytick values : "+str(w),
       fontweight ="bold")

fig.suptitle('matplotlib.axes.Axes.get_yticks() \
function Example\n\n', fontweight ="bold")
plt.show()

Output:

Example 2:

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.gridspec as gridspec


fs = 1000
t = np.linspace(0, 0.3, 301)
A = np.array([2, 8]).reshape(-1, 1)
f = np.array([150, 140]).reshape(-1, 1)
xn = (A * np.sin(2 * np.pi * f * t)).sum(axis = 0)
xn += 5 * np.random.randn(*t.shape)

fig, ax = plt.subplots()

yticks = np.arange(-50, 30, 10)

ax.psd(xn, NFFT = 301,
       Fs = fs,
       window = mlab.window_none,
       pad_to = 1024,
        scale_by_freq = True)

ax.set_yticks(yticks)
ax.grid(True)

w = ax.get_yticks()
ax.text(80, 12, "ytick values : "+str(w),
        fontweight ="bold")

fig.suptitle('matplotlib.axes.Axes.get_yticks() \
function Example\n\n', fontweight ="bold")
plt.show()

Output: