Matplotlib is a library in Python and it is numerical — mathematical extension for NumPy library. Pyplot is a state-based interface to a matplotlib module which provides a MATLAB-like interface. There are various plots that can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.
In order to change the transparency of a graph plot in matplotlib we will use the matplotlib.pyplot.plot() function. The plot() function in pyplot module of matplotlib library is used to make 2D illustrations.
Syntax: matplotlib.pyplot.plot(\*args, scalex=True, scaley=True, data=None, \*\*kwargs)
Parameters: This method accept the following parameters that are described below:
- x, y: These parameter are the horizontal and vertical coordinates of the data points. x values are optional.
- fmt: This parameter is an optional parameter and it contains the string value.
- data: This parameter is an optional parameter and it is an object with labelled data.
Returns: This returns the following:
- lines : This returns the list of Line2D objects representing the plotted data.
Another argument that we are going to use is alpha argument, this argument is responsible for the transparency of any illustration depicted using matplotlib library. Its value ranges from 0 to 1, by default its value is 1 representing the opaqueness of the illustration.
Below are some examples which depict how to change the transparency of a Graph Plot using matplotlib library
Example 1:
Python3
# importing module import matplotlib.pyplot as plt # assigning x and y coordinates y = [0, 1, 2, 3, 4, 5] x = [0, 5, 10, 15, 20, 25] # depicting the visualization plt.plot(x, y, color='green', alpha=0.25) plt.xlabel('x') plt.ylabel('y') # displaying the title plt.title("Linear graph") plt.show() |
Output:
In the above program, the linear graph is depicted with transparency i.e alpha=0.25.
Example 2:
Python3
# importing module import matplotlib.pyplot as plt # assigning x and y coordinates x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5] y = [] for i in range(len(x)): y.append(max(0, x[i])) # depicting the visualization plt.plot(x, y, color='green', alpha=0.75) plt.xlabel('x') plt.ylabel('y') # displaying the title plt.title(label="ReLU function graph", fontsize=40, color="green") |
Output:
Here, the plot is quite opaque as the alphavalue is close to 1(opaque).
Example 3:
Python3
# importing modules from matplotlib import pyplot import numpy # assigning time values of the signal # initial time period, final time period # and phase angle signalTime = numpy.arange(0, 100, 0.5) # getting the amplitude of the signal signalAmplitude = numpy.sin(signalTime) # depicting the visualization pyplot.plot(signalTime, signalAmplitude, color='green', alpha=0.1) pyplot.xlabel('Time') pyplot.ylabel('Amplitude') # displaying the title pyplot.title("Signal", loc='right', rotation=45) |
Output:
The above example depicts a signal with an alpha value 0.1.
Example 4:
Python3
# importing module import matplotlib.pyplot as plt # assigning x and y coordinates z = [i for i in range(0, 6)] for i in range(0, 11, 2): # depicting the visualization plt.plot(z, z, color='green', alpha=i/10) plt.xlabel('x') plt.ylabel('y') # displaying the title print('\nIllustration with alpha =', i/10) plt.show() |
Output:
The above program depicts the same illustration with variable alpha values.
