So visualisations in prison, so in this course, and when we solve the optimization problem, I usually
prefer to show you how to visualize the decision variables and also the objective function for this
purpose.
There are some multiple packages in Python, like Seabourne, like GGGI Plot, like Beaucaire, like
Pygle and also plotly and your plot leap and gleam and missing no leather.
And also the main one that I'm going to use it throughout this course is matplotlib so we can use these
tools to visualize or decision variables or and also the objective function, how they are changing
with, uh, with the decision maker.
OK, and also so we don't have any insist of using any specific, um, package in Python, but for simplicity
I have chosen the Mathlouthi.
But you feel free to change that part of the code and do the visualization by your own creativity.
So in order to learn more about the matplotlib, you can Google it.
And there is a website called matplotlib dot org and it has a gallery.
It has multiples of.
Solved examples.
So you can easily use them and you don't need to memorize everything, of course.
But if you need anything, you can go to a gallery and find out which of these examples are much closer
to what you exactly need.
So this is an example, for example, and you need to import matplotlib.
That's Pyplot aspect and import numpy as NP.
And for example, in this plot you can see there are some random shapes are scattered in the plane.
OK, so this is the application of a scatter plot and you finally show that plot to your audience.
OK, so that's the way you visualize the things in Python.
This is very simple, but you need to practice as well.
Thank you very much.