Instructions :: CA Astro - Data Science and Machine Learning Workshop

Instructions

This set of tutorials are written in Python and they act as stand-alone notebooks. There are 2 ways of accessing them.

Using Google’s Colab

The ideal method of accessing these notebooks and resources is through My Binder or Google Colab.

You can simply click on the badge for opening it on MyBinder or Google Colab:

Just press on it and it will redirect you to the website dedicated to hosting these notebooks.

Getting the repository onto your computer

The first method of accessing the set of notebooks and resources is by cloning the whole repository into your computer. In that way, you will be able to :

Install the necessary Python packages
Run each notebook on its own and check the results yourself.

For this to work, you will first need to:

Clone your repository to specified directory
- Go to your Documents directory (or any other directory)
```
# Let's go to your Documents folder
cd $HOME/Documents
```
- Clone the directory : Keep in mind that you don’t have to clone it into Documents, but you can choose any other directory.
```
git clone https://github.com/vcalderon2009/2020_06_CA_Astro_Data_Science_Workshop.git
```
- Go into the directory
```
cd ./2020_06_CA_Astro_Data_Science_Workshop
```
- Checkout the master branch
```
git checkout master
```
Create a new Python environment
- The next step is to create a new Python environment for the project
```
make create_environment
```
  This will create the necessary Python environment for the project. If you have Anaconda installed on your computer, this command will create a new Python environment with the name 2020_06_CA_Astro_Data_Science_Workshop.
- If using Anaconda, you will have to activate the environment:
```
conda activate 2020_06_CA_Astro_Data_Science_Workshop
```
  or if you’re using venv, you can activate it as:
```
workon 2020_06_CA_Astro_Data_Science_Workshop
```
  assuming you have it properly installed.
- Install the necessary packages
  
  Now that the Python environment exists, you will need to install the packages into the environment:
```
make requirements
```

Accessing the notebooks

You can finally access the notebooks of the project by:

# Going into the `notebooks` directory
cd notebooks

# Start jupyter lab
jupyter lab

You can now look through the different notebooks and play around with them!