Easy model to fit logistic curve to COVID19 data from Italy.
Data is taken from this official repo
Live demo: https://fit-covid19.herokuapp.com (It could be slow because it is a free heroku app)
For single regions: https://fit-covid19.herokuapp.com/regione/nome
(Ex. Toscana: https://fit-covid19.herokuapp.com/regione/Toscana)
usage: fit.py [-h] [--img IMG] [--avg AVG] [--style STYLE]
Modello COVID-19 in Italia.
optional arguments:
-h, --help show this help message and exit
--img IMG y, save imgs - n do not save imgs
--avg AVG if > 1 draw plot of avg last --avg days.
--style STYLE [normal, cyberpunk] : normal, standard mpl - cyberpunk,
cyberpunk style
--old_pred OLD_PRED if True plot also the prediction curve from a week ago.usage: regione_fit.py [-h] --regione REGIONE [--img IMG] [--avg AVG] [--style STYLE]
Modello COVID-19 per regione.
optional arguments:
-h, --help show this help message and exit
--regione REGIONE Nome regione su cui effettuare le predizioni.
--img IMG y, save imgs - n do not save imgs
--avg AVG if > 1 draw plot of avg last --avg days.
--style STYLE [normal, cyberpunk] : normal, standard mpl - cyberpunk,
cyberpunk style
--old_pred OLD_PRED if True plot also the prediction curve from a week ago.
If you know this stuff and you think you can contribute please just let me know: fork this repo, pull request, star this repo, send me an email.
- Python >=3
- Pandas
- Numpy
- ScyPy