Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
20
About Packt
22
References

11.2.2 Mouse events and textboxes

In the last example, we encountered mouse events in the context of a button widget. We can also catch a mouse event without using a button. To this end, we need to connect a general button click to a call-back function.

To demonstrate this, we consider again the previously generated plot of the sine wave and pick by mouse clicks points and display their coordinates in a textbox to the plot. If clicked with the right mouse button, we also display the point picked by means of a red circle in the plot.

First, we prepare a textbox widget. We already know that we first have to position the widget by defining an axes object and then providing the widget with the desired properties:

from matplotlib.widgets import TextBox
textbox_ax=axes([0.85,0.6,0.1,0.15])
txtbx=TextBox(textbox_ax, label='', initial='Clicked on:\nx=--\ny=--')

We provided the box with no label but some initial text. The textbox has the attribute...