This repository investigates whether the storm impacts (i.e. Sallenger, 2000) f the June 2016 Narrabeen Storm could have been forecasted in advance.
This repository investigates whether the storm impacts (i.e. Sallenger, 2000) of the June 2016 Narrabeen Storm could have been forecasted in advance.
## Repository and analysis format
This repository follows the [Cookiecutter Data Science](https://drivendata.github.io/cookiecutter-data-science/)
@ -69,9 +69,9 @@ been corrected for systematic errors, so actual elevations should be taken from
- [ ] Setup precomit hook for automatic code formatting using [black](https://ljvmiranda921.github.io/notebook/2018/06/21/precommits-using-black-and-flake8/). Low priority as can run black using the command `make format`.
- [ ] Raw tide WL's are interpolated based on location from tide gauges. This probably isn't the most accurate method, but should have a small effect since surge elevation was low during this event. Need to assess the effect of this method.
- [ ] Estimate max TWL from elevation where pre storm and post storm profiles are the same. Need to think more about this as runup impacting dune toe will move the dune face back, incorrectly raising the observed twl. Perhaps this estimation of max TWL is only useful for the swash regime.
- [ ] Implement (bayesian change detection algorithm)[https://github.com/hildensia/bayesian_changepoint_detection] to help detect dune crests and toes from profiles. Probably low priority at the moment since we are doing manual detection.
- [ ] Implement [bayesian change detection algorithm](https://github.com/hildensia/bayesian_changepoint_detection) to help detect dune crests and toes from profiles. Probably low priority at the moment since we are doing manual detection.
- [ ] Implement dune impact calculations as per Palmsten & Holman. Calculation should be done in a new dataframe.
- [ ] Implement data/interim/*.csv file checking using py.test. Check for correct columns, number of nans etc. Testing of code is probably a lower priority than just checking the interim data files at the moment.
- [ ] Investigate using [modin](https://github.com/modin-project/modin) to help speed up analysis.
- [ ] Need to think about how relative imports are handled, see [here](https://chrisyeh96.github.io/2017/08/08/definitive-guide-python-imports.html). Maybe the click CLI interface should be moved to the `./src/` folder and it can import all the other packages?
- [ ] Simplify runup_models in Stockdon06 - we should really only have one function for each runup model. Need to make it work with individual values or entire dataframe. Use (np.maskedarray)[https://docs.scipy.org/doc/numpy-1.15.0/reference/maskedarray.generic.html]
- [ ] Simplify runup_models in Stockdon06 - we should really only have one function for each runup model. Need to make it work with individual values or entire dataframe. Use [np.maskedarray](https://docs.scipy.org/doc/numpy-1.15.0/reference/maskedarray.generic.html)