View Discussion
Improve Article
Save Article
View Discussion
Improve Article
Save Article
Prerequisites: Matplotlib
Matplotlib is a comprehensive library for creating interactive, static and animated visualizations in python. Using general-purpose GUI toolkits like wxPython, SciPy, Tkinter or SciPy, it provides an object-oriented API for embedding plots into applications. Matplotlib.pyplot is a collection of functions that makes Matplotlib work like MATLAB.
Here, we will be exploring loglog[] function of Matplotlib.pyplot. It is used to plot a log scale over both x and y-axis.
Syntax:
loglog[X,Y]
Where,
X and Y refer to x and y coordinates respectively.
Other function used is linespace[]. It returns evenly spaced numbers over a specified interval.
Syntax:
np.linspace[start, stop, num, endpoint, retstep, dtype, axis]
Where,
- Start : The starting value of sequence from where you want to show the line, or we can say starting point of line
- Stop : It is the end value of the sequence at where the line stops, unless ‘endpoint’ is set to False.
- Num : Number of samples to generate. Must be non-negative. By default, it is 50.
- Endpoint : It works same as stop. If it is True then stop is the last sample else stop is excluded from the sequence.
- Retstep : If True, return [‘samples’, ‘step’], where `step` is the spacing between samples.
- Dtype : The type of the output array.
- Axis : The axis in the result to store the samples and it is relevant only if start or stop are array-like
Example : Without loglog[]
Python
import
matplotlib.pyplot as plt
import
numpy as np
x_input
=
np.linspace[
0
,
10
,
50000
]
y_input
=
x_input
*
*
8
plt.plot[x_input, y_input]
Output:
Example : With loglog[]
Python3
import
matplotlib.pyplot as plt
import
numpy as np
x_input
=
np.linspace[
0
,
10
,
50000
]
y_input
=
x_input
*
*
8
plt.loglog[x_input, y_input]
Output:
View Discussion
Improve Article
Save Article
View Discussion
Improve Article
Save Article
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:
import
numpy as np
import
matplotlib.pyplot as plt
t
=
np.arange[
0.01
,
20.0
,
0.01
]
fig, ax
=
plt.subplots[]
ax.loglog[t,
20
*
np.exp[
-
t
/
10.0
], basex
=
2
]
ax.set_title[
'matplotlib.axes.Axes.loglog Example2'
]
plt.show[]
Output:
Example-2:
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: