ocean-model-skill-assessor

A package to fully run the comparison between data and model to assess model skill.

Project based on the cookiecutter science project template.

Run Demo without Installation

Click the binder button to open up a demonstration notebook in your browser window

Installation

Set up fresh environment for this package

First, make sure you have Anaconda or Miniconda installed.

Then, clone this repository:

$ git clone https://github.com/axiom-data-science/ocean-model-skill-assessor.git

In the ocean_model_skill_assessor directory, install a conda environment with convenient packages for working with this package (beyond the requirements):

$ conda env create -f environment.yml

Note that installing the packages is faster if you first install mamba to your base Python and then use mamba in place of conda.

Activate your new Python environment to use it with

$ conda activate ocean-model-skill-assessor

Install into existing Python environment

Install the package plus its requirements from conda-forge with

$ conda install -c conda-forge ocean_model_skill_assessor

Or you can git clone the repository and then pip install it locally into your existing Python environment: For local package install, in the ocean_model_skill_assessor directory:

$ pip install -e .

Extra packages for development

To also develop this package, install additional packages with:

$ conda install --file requirements-dev.txt

To then check code before committing and pushing it to github, locally run

$ pre-commit run --all-files

Run Demo

In your terminal window, activate your Python environment if you are using one, then type jupyter lab in the ocean_model_skill_assessor directory. This will open into your browser window. Navigate to docs/Demo-AK.ipynb or any of the other notebooks and double-click to open. Inside a notebook, push shift-enter to run individual cells, or the play button at the top to run all cells, or select commands under the Run menu.