SciPy 2020 Tutorial: Introduction to Numerical Computing With NumPy
This repository contains all the material needed by students registered for the Numpy tutorial of SciPy 2020 on Tuesday, 7 July 2020.
For a smooth experience, you will need to make sure that you install or update your Python distribution and download the tutorial material before the day of the tutorial.
Running the Exercises the (recommended) Easy Way
Running the Exercise Locally
If you don't already have a working python distribution, you may download Enthought EDM (https://www.enthought.com/enthought-deployment-manager/), Anaconda Python (https://www.anaconda.com/products/individual) or Python.org (https://www.python.org/downloads/).
To be able to run the examples, demos and exercises, you must have the following packages installed:
- numpy 1.15+
- matplotlib 2.2+
- ipython (for running, experimenting and doing exercises)
- pyqt 5.7+
With Enthought EDM, install EDM, then follow the
Getting Started instructions on the download page. Make sure you install the required packages in your default environment:
$ edm install numpy matplotlib ipython pyqt5 jupyter pillow
If you are using Python from python.org or your system, you can install the necessary packages with:
$ pip install -U numpy matplotlib ipython PyQt5 jupyter pillow
If you are using Anaconda, you can create an environment with the necessary packages with:
$ conda create -n numpy-tutorial numpy matplotlib ipython pyqt
To test your installation, please execute the
check_env.py script in the environment where you have installed the requirements. For example, if you installed using Enthought EDM and are using the default environment, open up a terminal (or command prompt), navigate to where you have this GitHub repository, and type:
$ edm shell $ python check_env.py
You should see a window pop up with a plot that looks vaguely like a smiley face.
Download Tutorial Materials
This GitHub repository is all that is needed in terms of tutorial content. The simplest solution is to download the material using this link:
If you are familiar with Git, you can also clone this repository with:
$ git clone https://github.com/enthought/Numpy-Tutorial-SciPyConf-2020.git
It will create a new folder named
Numpy-Tutorial-SciPyConf-2020/ with all the content you will need: the slides I will go through (
slides.pdf), and a folder of exercises.
You may post messages to the
#tutorial_numpy Slack channel for this tutorial at in the official Slack team: https://scipy2020.slack.com .