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# ppe_tools | ||
tools for creating and analyzing parameter perturbation experiments | ||
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### To use our python environment: | ||
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conda env create -f environment.yml | ||
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Then you should hopefully have ppe-py available as an environment in JupyterHub |
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name: ppe-py | ||
channels: | ||
- conda-forge | ||
- defaults | ||
dependencies: | ||
- python=3.7 # Python version 3.7 | ||
- bottleneck # C-optimized array functions for NumPy | ||
- cartopy # Geographic plotting toolkit | ||
- cftime | ||
- dask # Parallel processing library | ||
- geopandas | ||
- future # Python 2/3 compatibility | ||
- h5py # Wrapper for HDF5 | ||
- ipython # IPython interpreter and tools | ||
- jupyter # Jupyter federation architecture | ||
- jupyterlab | ||
- matplotlib # 2D plotting library | ||
- ncar-jobqueue | ||
- nc-time-axis | ||
- netcdf4 # Wrapper for netcdf4 | ||
- notebook # Notebook interface | ||
- numpy # N-d array and numerics | ||
- pandas # Labeled array library | ||
- scipy # Common math/stats/science functions | ||
- scikit-learn # Macine learning library | ||
- seaborn # Statistical visualizations | ||
- shapely | ||
- six # Python 2/3 compatibility | ||
- sparse | ||
- tqdm # Nice progressbar for longer computations | ||
- xarray # N-d labeled array library | ||
- xesmf |