Tutorial 4 -- Graphical Outputs in Python

In this tutorial, we learn how to produce graphical outputs in python with the easy-to-use, yet sophisticated Matplotlib module. This review is limited to the pyplot submodule which can be imported with the following statement

import matplotlib.pyplot as plt

matplotlib.pyplot is a collection of plotting functions that make matplotlib work like MATLAB.

The documentation can be found here: Matplotlib User Guide. You will find many simple and complex illustrations of what this module can produce.

Simple Plots from Arrays of Points

In this example, the pyplot submodule is used to produce a simple y vs x plot from data written in the form of two (1D) numpy arrays. We can easily add labels and a title, along with a grid. The default format string is ‘b-', which is a solid blue line. Three different plotting options are shown. There are many other available options.

import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0.0, 4.0*np.pi, 0.1) # array of x values from 0 to 4*pi with increment of 0.1
y = 1 + np.sin(x)  # array of y values
plt.plot(x, y) # plot y vs x with continuous line (default)
plt.plot(x+np.pi/4, y, 'r.') # red (r) isolated points (.): the previous plot is shifted along x-axis by pi/4
plt.plot(x+np.pi/2, y, 'gx') # green (g) et cross (x)
plt.xlabel('x(m): distance traveled')
plt.ylabel('y(m): height')
plt.title('Oscillatory Motion of P')
plt.savefig('x-y.png') # save graph in png file

The result is shown below (the default did not produce a solid blue line):

You could also replace the 3 plot commands by a single one:

plt.plot(x, y, 'r--', x+np.pi/4, y, 'bs', x+np.pi/2, y, 'g^')

Multiple Plots

You can plot multiple graphs with matplotlib. Here is a simple script where two graphs are plotted side by side.

import matplotlib.pyplot as plt
import numpy as np

#-- figure setup

fig = plt.figure(1, figsize=(10, 5)) # size in inches
plt.subplots_adjust(left=0.1, wspace=0.4, top= 0.8)
plt.suptitle('Multiple Plots', fontsize=16)
# plot figure 1
x = np.linspace(0, 2*np.pi, 400)
y1 = np.sin(x**2) + np.cos(x)
fig1 = plt.subplot(121) # nbr of rows =1, nbr of columns =2, plot_number =1
plt.title('Title 1')
fig1.plot(x, y1)
# plot figure 2
y2 = 2 * x * np.cos(x**2) - np.sin(x)
fig2 = plt.subplot(122) # nbr of rows =1, nbr columns =2, plot_number =2
plt.title('Title 2')
plt.tight_layout() # this makes sure that the figures are not overlaid
plt.savefig('x-y2.png') # save graph in png file

Plot Simple Geometric Objects

Matplotlib allows you to create simple geometric objects (which could later be animated!). Here is a simple script with text, circle, ellipse and rectangle objects.

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

fig, ax = plt.subplots()
# plot some text
x,y = 0.1, 0.4
plt.text(x, y, 'Simple Shapes', ha="center", family='sans-serif', size=14)
# plot a circle
x,y = 0.5,0.6
r = 0.15
circ = plt.Circle((x,y), r, facecolor= 'blue', edgecolor= 'black')
# plot an ellipse
x,y = 0.2,0.3
rx,ry = 0.2, 0.05
angle = 30 # (degrees)
elli = mpatches.Ellipse((x,y), rx, ry, angle, facecolor= 'yellow', edgecolor= 'red')
# plot a rectangle
x,y = 0.,0. # lower left corner
dx,dy= 0.3, 0.1 # dimensions
rect = plt.Rectangle((x,y), dx,dy, facecolor= 'red', edgecolor= 'black')
plt.axis('off') # no frame/axes

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