Skip to content

Latest commit

 

History

History
69 lines (43 loc) · 2.13 KB

vision.md

File metadata and controls

69 lines (43 loc) · 2.13 KB

Vision

FMskill wishes to be your modelling assistant. It should be useful enough for you to use every time you do a MIKE 21/3 simulation.

Objective

We want FMskill 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 (from pypi and conda)
  • Easy to get started by providing many notebook examples and documentation

Scope

FMskill 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

Limitations

FMskill does not wish to cover

  • Extreme value analysis
  • Forecast skill assessments
  • Deterministic wave analysis such as crossing analysis
  • Alternative file types
  • Rarely used model result types
  • Rare observation types
  • Anything project specific

Future

Automatic reports

Both static as markdown, docx, pptx and interactive as html

Web app

Create a web app that wraps this library

Interface to observation APIs

Easy to get observation data from DHI's altimetry portal, CMEMS, etc.

Interface to alternative models

Should be easy to compare your model to publically available alternative e.g. from CMEMS or NOAA. Or from DHI's DataLink.