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.md gives 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.py and run_hourly.py) with some resolution specific settings
    • data store got method get_default() that behaves similar to the standard dict.get()