Deepsensor

What's Changed
* Fix rounding errors in `DeepSensorModel.predict` coordinates from normalise-unnormalise operations by tom-andersson and polpel in https://github.com/tom-andersson/deepsensor/pull/25
* Support autoregressive (AR) sampling in `DeepSensorModel.predict`
* Support training with multiple non-overapping targets
* Support NaNs in context and target data for `ConvNP`
* `deepsensor.active_learning` enhancements
* Support numpy coordinates in `TaskLoader` context/target and `DeepSensorModel.predict` targets
* Switch default random sampling behaviour for `xarray` data to use linear interpolation rather than grid-cell wise to avoid prediction artifacts away from grid cells (thanks jonas-scholz123)


**Full Changelog**: https://github.com/tom-andersson/deepsensor/compare/v0.1.4...v0.1.5

* Fix decoder scale not being inferred from model discretisation density (ppu). Closes https://github.com/tom-andersson/deepsensor/issues/18
* Add `deepsensor.plot.feature_maps` method
* Provisional `deepsensor.active_learning` functionality with acquisition functions and greedy algorithm

**Breaking changes**
* `ConvNP` class moved from `deepsensor.model.models` to `deepsensor.model.convnp`

**Full Changelog**: https://github.com/tom-andersson/deepsensor/compare/v0.1.3...v0.1.4

Try to trigger PyPI upload with publisher set up on PyPI

**Full Changelog**: https://github.com/tom-andersson/deepsensor/compare/v0.1.2...v0.1.3

What's New
* Breaking change: Plotting module moved and methods renamed for nicer-looking imports. E.g. now `deepsensor.plot.plot.plot_context_encoding` is `deepsensor.plot.context_encoding`.
* Added `deepsensor.plot.receptive_field` method for plotting model's RF in unnormalised space with cartopy coastlines.

**Full Changelog**: https://github.com/tom-andersson/deepsensor/compare/v0.1.1...v0.1.2

What's New
* Published on PyPI
* `ConvNP` class defaults to CNP model
* More intuitive names for ConvCNP or ConvCNP: `ConvNP(..., likelihood="cnp")` and `ConvNP(..., likelihood="gnp")`

**Full Changelog**: https://github.com/tom-andersson/deepsensor/compare/v0.1.0...v0.1.1

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 `Task`s

Contributors
* Thanks to wesselb for support with backend-agnosticism!
* `DataProcessor` dimension validation + unit tests by jonas-scholz123 in https://github.com/tom-andersson/deepsensor/pull/2
* fix str of tensorflow backend by acocac in https://github.com/tom-andersson/deepsensor/pull/3
* Fix `else` level in set_gpu_default_device() by polpel in https://github.com/tom-andersson/deepsensor/pull/4
* Fix DataProcessor's validaiton of dimension ordering in xr.Dataset by polpel in https://github.com/tom-andersson/deepsensor/pull/5

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