ModelSkill wishes to be your modelling assistant. It should be useful enough for you to use every time you do a MIKE 21/3 simulation.
We want ModelSkill to make it easy to
- assess the skill of a model by comparing with measurements
- assess model skill also when result is split on several files (2d, 3d, yearly, ...)
- compare the skill of different calibration runs
- compare your model with other models
- use a wide range of common evaluation metrics
- create common plots such as time series, scatter and taylor diagrams
- do aggregations - assess for all observations, geographic areas, monthly, ...
- make fast comparisons (optimized code)
And it should be
- Difficult to make mistakes by verifying input
- Trustworthy by having >95% test coverage
- Easy to install (
pip install modelskill) - Easy to get started by providing many notebook examples and documentation
ModelSkill wants to balance general and specific needs:
- It should be general enough to cover >90% of MIKE FM simulations
- But specific enough to be useful
- Primarily support dfs files (using mikeio)
- Handle circular variables such as wave direction
- Handle vector variables such as u- and v-components of current
- Tidal analysis
ModelSkill does not wish to cover
- Extreme value analysis
- Deterministic wave analysis such as crossing analysis
- Rare alternative file formats
- Rarely used model result types
- Rare observation types
- Anything project specific
Create a web app that wraps this library