official name released MLAir, new Workflows, easy Model plug-in possible
  • general:
    • Official project name is released: MLAir (Machine Learning on Air data)
    • a model class can now easily be plugged in into MLAir. #121
    • introduced new concept of workflows, #134
  • new features:
    • workflows are used to execute a sequence of run modules, #134
    • default workflows for standard and the Juelich HPC systems are available, custom workflows can be defined, #134
    • seasonal decomposition is available for conditional quantile plot, #112
    • map plot is created with coordinates, #108
    • flatten_tails are now more general and easier to customise, #114
    • model classes have custom compile options (replaces set_loss), #110
    • model can be set in ExperimentSetup from outside, #121
    • default experiment settings can be queried using get_defaults(), #123
    • training and model settings are reported as MarkDown and Tex tables, #145
  • technical
    • Juelich HPC systems are supported and installation scripts are available, #106
    • data store is tracked, I/O is saved and illustrated in a plot, #116
    • batch size, epoch parameter have to be defined in ExperimentSetup, #127, #122
    • automatic documentation with sphinx, #109
    • default experiment settings are updated, #123
    • refactoring of experiment path and its default naming, #124
    • refactoring of some parameter names, #146
    • preparation for package distribution with pip, #119
    • all run scripts are updated to run with workflows, #134
    • the experiment folder is restructured, #130