Matplotlib - start

https://matplotlib.org/
Matplotlib: Visualization with Python

https://matplotlib.org/tutorials/index.html

INSTALLING MATPLOTLIB

If you already have Python, you can install Matplotlib with:

ANACONDA
conda install matplotlib

PIP (in a virtual environment)
pip install matplotlib

APT (for the entire computer)
Debian packages: python-matplotlib, python3-matplotlib, and dependencies.

INTRODUCTION

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

Matplotlib 3 (3.0.3 in Debian 10) is Python 3 only, Matplotlib 2 (2.2.3 in Debian 10) supports Python 2.

matplotlib.pyplot is a state-based interface to matplotlib. It provides a MATLAB-like way of plotting. pyplot is mainly intended for interactive plots and simple cases of programmatic plot generation. The object-oriented API is recommended for more complex plots.

There are two big components that you need to take into account:

• The Figure is the overall window or page that everything is drawn on. You can create multiple independent Figures.
• To the figure you add Axes. The Axes is the area on which the data is plotted with functions such as plot() and scatter() and that can have ticks, labels, etc. associated with it. This explains why Figures can contain multiple Axes.

# (0,1)                  (1,1)
# +----------------------+
# | Figure               |  Figure provides the working area (canvas).
# | +------------------+ |  Axes provides coordinates.
# | | Axes             | |
# | |                  | |
# | |                  | |
# | |                  | |
# | +------------------+ |
# |                      |
# +----------------------+
# (0,0)                   (1,0)

# (0,1)               (1,1)
# +-------------------+
# | Figure            |
# | +------+ +------+ |  Multiple axes.
# | | Axes | | Axes | |
# | |  1   | |  2   | |
# | +------+ +------+ |
# |                   |
# +-------------------+
# (0,0)               (1,0)

import matplotlib.pyplot as plt

plt.plot([1, 2, 3, 4], [10, 20, 25, 30])   # line segments
plt.scatter([0.3, 3.8, 1.2, 2.5], [11, 25, 9, 26])   # points
plt.show()   # display a figure
plt.savefig("plot1.png")   # saving a figure to a file

DATA FOR MATPLOTLIB PLOTS

Matplotlib is often used to visualize analyses or calcuations. Data can be stored in Python lists, NumPy arrays, PIL images. All sequences are converted to numpy arrays internally.

# The vectorization technique. Plotting a function
# f(x) = x^2 exp(-a*x) sin(pi*x)
import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0,10,1000)
a = 1.0
y = x**2 * np.exp(-a*x) * np.sin(np.pi*x)   # numpy functions!

plt.plot(x, y)
plt.title("f(x)")
plt.xlabel("x")
plt.ylabel("y")
plt.show()