hourly data, result plots, advanced training setup
- general:
- implement plot routines
- advanced training setup (can be resumed and skipped)
- MLT supports now hourly data
-
src/run_modules/README.mdgives a short overview on the data workflow and the project structure
- new features:
- climatological and competitive skill scores
- many new plots: station map, monthly box plot, conditional quantiles plot, climatological skill score, competitive skill score, time series plot
- training is resumed, if last epoch of an existing model is smaller than the given epoch number
- if a model is available, training can be skipped
- advanced plot of model history including all model branches
- technical:
- improved speed of data generator by temporary storing processed data locally as pickle
- there are now two separate run scripts (
run.pyandrun_hourly.py) with some resolution specific settings - data store got method
get_default()that behaves similar to the standard dict.get()