Metadata-Version: 2.1
Name: mlstream
Version: 0.1.1
Summary: Machine learning for streamflow prediction
Home-page: http://github.com/gauchm/mlstream
Author: Martin Gauch
Author-email: martin.gauch@uwaterloo.ca
License: Apache-2.0
Description: # mlstream
        [![Documentation Status](https://readthedocs.org/projects/mlstream/badge/?version=latest)](https://mlstream.readthedocs.io/en/latest/?badge=latest)
        
        Machine learning for streamflow prediction.
        
        **PyPI:** https://pypi.org/project/mlstream/
        
        **Documentation:** https://mlstream.readthedocs.io/
        
        ## Usage
        
        This project is work in progress.
        The idea is to create an easy way of training machine learning streamflow models:
        Just provide your data, select a model (or provide your own), and get the predictions.
        
        ### Training
        ```python
        exp = Experiment(data_path, is_train=True, run_dir=run_dir,
                         start_date='01012000', end_date='31122015',
                         basins=train_basin_ids, 
                         forcing_attributes=['precip', 'tmax', 'tmin'],
                         static_attributes=['area', 'regulation'])
        
        exp.set_model(model)
        exp.train()
        ```
        
        ### Inference
        ```python
        run_dir = Path('./experiments')
        exp = Experiment(data_path, is_train=False, 
                         run_dir=run_dir, 
                         basins=test_basin_ids,
                         start_date='01012016', end_date='31122018')
        model.load(run_dir / 'model.pkl')
        exp.set_model(model)  
        results = exp.predict()
        ```
        
        
Keywords: ml hydrology streamflow machine learning
Platform: UNKNOWN
Description-Content-Type: text/markdown
