https://github.com/enthought/numpy-tutorial-scipyconf-2022
Public GitHub repo for SciPy 2022 tutorial (Introduction to Numerical Computing With NumPy)
https://github.com/enthought/numpy-tutorial-scipyconf-2022
Last synced: about 1 year ago
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Public GitHub repo for SciPy 2022 tutorial (Introduction to Numerical Computing With NumPy)
- Host: GitHub
- URL: https://github.com/enthought/numpy-tutorial-scipyconf-2022
- Owner: enthought
- License: other
- Created: 2022-04-05T10:03:05.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-08-24T23:55:17.000Z (almost 4 years ago)
- Last Synced: 2025-03-25T06:51:10.745Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 5.48 MB
- Stars: 14
- Watchers: 3
- Forks: 11
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: history/placeholder.txt
- License: LICENSE
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README
# SciPy 2022 Tutorial: Introduction to Numerical Computing With NumPy
#### Presented by: Logan Thomas, [Enthought, Inc.](https://www.enthought.com)
#### YouTube recording of live tutorial [here](https://youtu.be/bveHFn0G4Zg)
This repository contains all the material needed by students registered for the Numpy tutorial of [SciPy 2022](https://www.scipy2022.scipy.org/) on Monday, July 11th 2022.
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: [](https://mybinder.org/v2/gh/enthought/Numpy-Tutorial-SciPyConf-2022/main)
## 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](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.
1. 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
```
1. 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-2022/` with all the content you will need.
```
$ git clone git@github.com:enthought/Numpy-Tutorial-SciPyConf-2022.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-2022/archive/main.zip. Then, unpack the zipped archive into a directoy named `Numpy-Tutorial-SciPyConf-2022`. You may have to rename the unpacked directory to explicitly be `Numpy-Tutorial-SciPyConf-2022`.
1. 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-2022/
$ 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-2022/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-2022.git
```
The above command will create a new folder named `Numpy-Tutorial-SciPyConf-2022/` 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.
## 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://scipy2022.slack.com](https://scipy2022.slack.com) .
## Additional Anaconda Resources
- [Managing environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)
- 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](https://docs.anaconda.com/anaconda/install/uninstall/).
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All Rights Reserved. Use only permitted under license. Copying, sharing, redistributing or other unauthorized use strictly prohibited.
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