Shyft is meant to provide facilities for conducting hydrologic simulations and accessing uncertainty resulting from the forcing data and decisions regarding model structure. It is a framework which provides an API. Shyft is written in Python and C++ using Boost Python to enable interoperability.
As much of the core functionality is written in C++, there may be some caveats and paradigms that will be unfamiliar to pure python users. As such, a few key pieces of information are provided below that you should be aware of before working through the tutorials.
Tutorials and notebooks are provided as the main tool for introducing the different elements of the Shyft framework. These are under continuous development, and we seek user input. If you are interested to contribute a notebook, please see the main shyft-doc repository for instructions.
IMPORTANT: read and understand the following guidelines before working with the tutorials.
The best way to get started with Shyft is to work on some of the notebooks that we have developed. To accomplish this it is recommended to checkout the shyft-doc repository and work using the Jupyter notebooks contained within the notebooks folder.
- An introduction to the api
- Getting started with configured simulations
- Some more advanced tools within Shyft