Matplotlib.axes.Axes.spy() in Python

matplotlib.axes.Axes.loglog() in Python

Last Updated : 13 Apr, 2020

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.loglog() Function

The Axes.errorbar() function in axes module of matplotlib library is used to make a plot with log scaling on both the x and y axis.

Syntax:
Axes.loglog(self, *args, **kwargs)
Parameters: This method accept the following parameters that are described below:

basex, basey: These parameter are Base of the x/y logarithm and are optional with default value 10.

subsx, subsy: These parameter are the sequence of location of the minor x/y ticks and are optional.

nonposx, nonposy: These parameter are non-positive values in x or y that can be masked as invalid, or clipped to a very small positive number.

Returns: This returns the following:

lines:This returns the list of Line2D objects representing the plotted data..

Below examples illustrate the matplotlib.axes.Axes.loglog() function in matplotlib.axes: Example-1:

Python3

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

t = np.arange(0.01, 20.0, 0.01)

# Create figure
fig, ax = plt.subplots()

# log x and y axis
ax.loglog(t, 20 * np.exp(-t / 10.0), basex = 2)

ax.set_title('matplotlib.axes.Axes.loglog Example2')
plt.show()

Output:

Example-2:

Python3

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

fig, ax = plt.subplots(constrained_layout = True)
x = np.arange(0.02, 1, 0.02)
np.random.seed(19680801)
y = np.random.randn(len(x)) ** 2
ax.loglog(x, y)
ax.set_xlabel('f [Hz]')
ax.set_ylabel('PSD')
ax.set_title('Random spectrum')


def forward(x):
    return 1 / x


def inverse(x):
    return 1 / x

ax.set_title('matplotlib.axes.Axes.loglog Example2')
plt.show()

Output:

Matplotlib.axes.Axes.spy() in Python

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