Generating DSWx Datasets

Instuctions TBD

Example image classification workflow

https://github.com/OPERA-Cal-Val/DSWx-SCP-validation-generation

Setup

A .env file should have the following information:

PLANET_API_KEY='<API_KEY>'
ES_USERNAME='<JPL USERNAME>'
ES_PASSWORD='<JPL PASSWORD>'

In your ~/.netrc, place earthdata login credentials:

machine urs.earthdata.nasa.gov
    login <username>
    password <password>

Install

It is recommended to install mamba in the user's base environment to speed up the installation process:

conda install -c conda-forge mamba

From this repo:

1. mamba env create -f environment.yml
2. conda activate dswx_val

To run notebook with kernel

After activatating

python -m ipykernel install --user --name dswx_val

Contributing

1. Create a branch from dev and create a pull request.

2. Do you development.

3. Make sure to run before you commit:

   jupyter nbconvert --ClearOutputPreprocessor.enabled=True --ClearMetadataPreprocessor.enabled=True --inplace *.ipynb

   This will clear ouput and metadata (including when you executed your notebook) for easier version control.

4. Have another member review.

5. Make sure to clear your outputs for better version control.