v0.7.0

All changes

This release adds support for cropping a dataset using the convex hull of the lat/lon coordinates of another dataset, which can be used for creating boundary data in Limited Area Modelling setups.

v0.6.1

All changes

This release contains bugfixes to update tests to use newer version of pre-commit, use correct python version, and remove uses of incompatible typing notation.

Fixes

• use old union typing notation compatible with all required python versions #77 @SimonKamuk

Maintenance

• update pre-commit action to v3.0.1 #77 @SimonKamuk
• fix tests to use expected python version from test matrix #77 @SimonKamuk

v0.6.0

All changes

This release adds the ability to slice input data by any coordinate, derive variables from input datasets, and store config in created datasets. It also adds support for zarr 3.0.0 and above, and a mypy typing action to pre-commit hooks. In addition a number of bugs were fixed related to adding unwanted dimensions to the dataset, chunk size estimates, and derived functions. The release also includes a number of maintenance updates including updating the DANRA test dataset to v0.2.0 (which smaller, leading to faster test execution) and updating the dataclass-wizard dependency to at least v0.29.2.

Added

• add functionality to slice input data by any coordinate #55@matschreiner
• add ability to derive variables from input datasets #34, @ealerskans, @mafdmi
• add github PR template to guide development process on github #44, @leifdenby
• add support for zarr 3.0.0 and above #51, @kashif
• warn if the user tries to load a non-YAML file #50, @j6k4m8
• add mypy typing action to pre-commit hooks #67, @observingClouds
• add support for storing config in created datasets and option to only overwrite zarr dataset of config change #64, @leifdenby

Fixes

• fix bug which adds unwanted dimensions to the dataset #60, @ealerskans, @observingClouds
• correct chunk size estimate #59, @ealerskans
• fix bug arising when variables provided to derived functions are renamed #56, @leifdenby
• ensure config fields defaulting to None are typed as Optional and fields defaulting to {} are given a default-factory so that serialization with default values works correctly #63, @leifdenby
• fix reading of exported config files #67, @observingClouds

Maintenance

• update DANRA test dataset to v0.2.0 which uses a smaller cropped domain #62, @leifdenby
• update dataclass-wizard dependency to at least v0.29.2 allowing for use of Union types together with check for unmatched keys in config yaml #73, @leifdenby

v0.5.0

This release adds support for an optional extra section in the config file (for user-defined extra information that is ignored by mllam-data-prep) and fixes a few minor issues. Note that to use extra section in the config file the schema version in the config file must be increased to v0.5.0.

Added

• Add optional section called extra to config file to allow for user-defined extra information that is ignored by mllam-data-prep but can be used by downstream applications. , @leifdenby

Changed

• remove f-string from name_format in config examples #35
• replace global config for dataclass_wizard on mllam_data_prep.config.Config with config specific to that dataclass (to avoid conflicts with other uses of dataclass_wizard) #36
• Schema version bumped to v0.5.0 to match release version that supports optional extra section in config #18

v0.4.0

This release adds support for defining the output path in the command line interface and addresses bugs around optional dependencies for dask.distributed.

Added

• add optional output path argument to parser.

Changed

• fix bug by making dependency distributed optional
• change config example to call validation split val instead of validation #28
• fix typo in install dependency distributed
• add missing psutil requirement. #21.

v0.3.0

Added

• add support for parallel processing using dask.distributed with command line flags --dask-distributed-local-core-fraction and --dask-distributed-local-memory-fraction to control the number of cores and memory to use on the local machine.

v0.2.0

Added

• add support for creating dataset splits (e.g. train, validation, test) through output.splitting section in the config file, and support for optionally compute statistics for a given split (with output.splitting.splits.{split_name}.compute_statistics). .

• include units and long_name attributes for all stacked variables as {output_variable}_units and {output_variable}_long_name .

• include version of mllam-data-prep in output

Changed

• split dataset creation and storage to zarr into separate functions mllam_data_prep.create_dataset(...) and
  mllam_data_prep.create_dataset_zarr(...) respectively

• changes to spec from v0.1.0:

  • the architecture section has been renamed output to make it clearer that this section defines the properties of the output of mllam-data-prep
  • sampling_dim removed from output (previously architecture) section of spec, this is not needed to create the training data
  • the variables (and their dimensions) of the output definition has been renamed from architecture.input_variables to output.variables
  • coordinate value ranges for the dimensions of the output (i.e. what that the architecture expects as input) has been renamed from
    architecture.input_ranges to output.coord_ranges to make the use more clear
  • selection on variable coordinates values is now set with
    inputs.{dataset_name}.variables.{variable_name}.values rather than inputs.{dataset_name}.variables.{variable_name}.sel
  • when dimension-mapping method stack_variables_by_var_name is used the formatting string for the new variable is now called name_format rather than name
  • when dimension-mapping is done by simply renaming a dimension this configuration now needs to be set by providing the named method (rename) explicitly through the method key, i.e. rather than {to_dim}: {from_dim} it is now {to_dim}: {method: rename, dim: {from_dim}} to match the signature of the other dimension-mapping methods.
  • attribute inputs.{dataset_name}.name attribute has been removed, with the key dataset_name this is superfluous

• relax minimuim python version requirement to >3.8 to simplify downstream usage

v0.1.0

First tagged release of mllam-data-prep which includes functionality to declaratively (in a yaml-config file) describe how the variables and
coordinates of a set of zarr-based source datasets are mapped to a new set of variables with new coordinates to single a training dataset and write this resulting single dataset to a new zarr dataset. This explicit mapping gives the flexibility to target different different model architectures (which may require different inputs with different shapes between architectures).