This repository stores all of the python examples (.py), data (.csv,.nc), and jupyter notebooks (.ipynb) used in the course. The python examples and their data can just be downloaded or run on Google's Colaboratory.
Code was written on an Apple M1 Max using Python 3.9.
- conda create --name env-ats655 python=3.9
- conda activate env-ats655
- conda install -c apple tensorflow-deps
- python -m pip install tensorflow-macos
- pip install tensorflow-probability==0.15
- pip install --upgrade numpy scipy pandas statsmodels matplotlib seaborn palettable progressbar2 tabulate icecream flake8 keras-tuner jupyterlab black isort jupyterlab_code_formatter
- pip install -U scikit-learn
- pip install silence-tensorflow tqdm
- conda install -c conda-forge cmocean cartopy xarray dask netCDF4 bottleneck nc-time-axis
- pip install pydot graphviz
- pip install MiniSom
- conda install scikit-image
- pip install --upgrade seaborn
- pip install curve_fit
- brew install pandoc
- brew install graphviz
The majority of the materials were created by Dr. Elizabeth A. Barnes, while additional collaborators are specified in the code when relevant.
This project is licensed under an MIT license.
MIT © Elizabeth A. Barnes