v0.1.0

Pre-release with basic DeepSensor functionality for data processing, task loading, and neural process training/inference.

What's New

• DataProcessor for normalising xarray and pandas data + standardising coordinates
• TaskLoader for loading neural process meta-learning tasks from xarray and/or pandas data, outputting Task objects
• TaskLoader.__call__ provides sampling schemes for generating context and target sets. Options:
  • random sampling (xarray/pandas),
  • passing all observations (xarray/pandas),
  • randomly splitting into context & target (pandas only).
• ProbabilisticModel class providing blueprint for generic model interface
• DeepSensorModel(ProbabilisticModel) class for outputting unnormalised model predictions in xarray (grid) or pandas (off-grid)
• ConvNP(DeepSensorModel) model class wrapping around neuralprocesses (https://github.com/wesselb/neuralprocesses) for convolutional neural process modelling
• train_epoch method implementing simple training scheme on a list of Tasks

Contributors

• Thanks to @wesselb for support with backend-agnosticism!
• DataProcessor dimension validation + unit tests by @jonas-scholz123 in #2
• fix str of tensorflow backend by @acocac in #3
• Fix else level in set_gpu_default_device() by @polpel in #4
• Fix DataProcessor's validaiton of dimension ordering in xr.Dataset by @polpel in #5

Full Changelog: https://github.com/tom-andersson/deepsensor/commits/v0.1.0