SciPy 2023 Tutorial: Introduction to Numerical Computing With NumPy

Presented by: Sandhya Govindaraju, Enthought, Inc.

This repository contains all the material needed by students registered for the Numpy tutorial of SciPy 2023 on Monday, July 10th 2023.

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

Run with Binder by clicking this icon:

Running the Exercise Locally

Install Python

If you don't already have a working python distribution, you may download Anaconda Python (https://www.anaconda.com/products/individual).

Install Packages

To be able to run the examples, demos and exercises, you must have the following packages installed:

• ipython (for running, experimenting, and doing exercises)
• jupyterlab (for access to the Jupyter Notebook web-based interactive computing platform)
• matplotlib
• numpy
• pillow
• pyqt

If you are using Anaconda, you can use the Anaconda Prompt (Windows) or Terminal.app (macOS) to create an environment with the necessary packages:

1. Open the Anaconda Prompt or Terminal.app using the below instructions:

   • Windows: Click Start and search for "Anaconda Prompt". Click on the application to launch a new Anaconda Prompt window.
   • macOS: Open Spotlight Search (using Cmd+Space) and type "Terminal.app". Click on the application to launch a new Terminal.app window.

2. Create a new Anaconda virtual environment by executing the below command in the application window you opened in step 1 above. You may be prompted to Proceed([y]/n)?. If so, type y and press Enter.

   conda create -n numpy-tutorial ipython jupyterlab matplotlib numpy pillow pyqt
   

3. Navigate to the directory where you'd like to store materials for this tutorial and download the materials from this GitHub repository by executing the below command. It will create a new folder named Numpy-Tutorial-SciPyConf-2023/ with all the content you will need.

   git clone [email protected]:enthought/Numpy-Tutorial-SciPyConf-2023.git
   

   NOTE: If you are not familiar with Git, you can download a zipped archive of the material by clicking on this link: https://github.com/enthought/Numpy-Tutorial-SciPyConf-2023/archive/main.zip. Then, unpack the zipped archive into a directoy named Numpy-Tutorial-SciPyConf-2023. You may have to rename the unpacked directory to explicitly be Numpy-Tutorial-SciPyConf-2023.

4. To test your installation, please execute the check_env.py script in the python virtual environment where you have installed the requirements (from step 2 above).

   If you created an Anaconda environment using the instructions above, you can use the same application window that you opened in step 1, or launch the platform specific application again -- Anaconda Prompt for Windows or Terminal.app for macOS. Be sure to navigate to where you downloaded this GitHub repository and activate your conda environment before executing python check_env.py:

   # Example path to course materials (yours may differ)
   $ cd ~/Desktop/Numpy-Tutorial-SciPyConf-2023/
   
   $ conda activate numpy-tutorial
   
   $ python check_env.py
   

   You should see a window pop up with a plot that looks vaguely like a smiley face (as shown below).

   

Tutorial Materials

This GitHub repository is all that is needed in terms of tutorial content. If you downloaded these materials in step 3 above, there is no need to do so again. If not, the simplest solution is to download the material using this link:

https://github.com/enthought/Numpy-Tutorial-SciPyConf-2023/archive/main.zip

If you are familiar with Git, you can also clone this repository with:

git clone https://github.com/enthought/Numpy-Tutorial-SciPyConf-2023.git

The above command will create a new folder named Numpy-Tutorial-SciPyConf-2023/ with all the content you will need: the slides I will go through (introduction_to_numerical_computing_with_numpy_manual.pdf), and a folder of exercises.

Updates

Please let me know how the tutorial went in survey.

All the code that was demoed in the class is saved to history/

Questions? Problems?

You may post messages to the #tutorial-intro-to-numerical-computing-with-numpy Slack channel for this tutorial at in the official Slack team: https://scipy2023.slack.com .

Additional Anaconda Resources

• Managing environments

  • To create an Anaconda environment from an existing environment.yml file:

    conda env create -f environment.yml -n numpy-tutorial
    

  • To remove an existing Anaconda environment:

    conda remove --name numpy-tutorial --all
    

• To completely uninstall Anaconda, see the "Uninstalling Anaconda" documentation here.

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