Version 1.5.7

• Remove numpy<2 restriction.

Version 1.5.6

• Limit geopandas version to < 1.0.0

Version 1.5.5

• SnowMaskTask now correctly handles temporally empty eopatches.

Version 1.5.4

• Minor fixes for documentation

Version 1.5.3

• Fix version numpy<2 in anticipation of numpy 2.0 release.

Version 1.5.2

• RayExecutor can now forward remote kwargs to ray jobs.
• ImportTiffTask no longer uses the use_vsi parameter. The IO part was fully off-loaded to rasterio.
• ImportTiffTask and ExportTiffTask parameter folder was renamed to path. The renaming is backwards compatible for now.

Version 1.5.1

• MorphologicalFilterTask adapted to work on boolean values.
• Added temporal_subset method to EOPatch, which can be used to extract a subset of an EOPatch by filtering out temporal slices. Also added a corresponding TemporalSubsetTask.
• EOExecutor now has an option to treat TemporalDimensionWarning as an exception.
• String representation of EOPatch objects was revisited to avoid edge cases where the output would print enormous objects.

Version 1.5.0

The release focuses on making eo-learn much simpler to install, reducing the number of dependencies, and improving validation of soundness of EOPatch data.

• eo-learn is now distributed as a single package. Installation of eo-learn-mask and similar is no longer necessary and users are warned when such installations are detected.
• Changes to timestamps and bbox attributes of EOPatch objects:
  • FeatureType.TIMESTAMPS and FeatureType.BBOX have been deprecated, data should be accessed via attributes. Feature parsers no longer return these values (for instance when calling EOPatch.get_features).
  • EOPatches without temporal information now have a timestamp value of None, whereas a timestamp value [] signifies that the EOPatch has a temporal dimension of 0.
  • Introduced a get_timestamps method that will fail if timestamps are None. This can be used in cases where timestamps are assumed to be present (to avoid issues with type-checking and ill formed inputs).
  • Loading, saving, and copying of EOPatches will take timestamps into account either when processing the full eopatch (i.e. features=...) or if the selection contains a temporal feature. The behavior can be controlled via the load_timestamps/save_timestamps/copy_timestamps parameter.
• Saving and loading of FeatureType.META_INFO now processes each feature as a separate file, allowing better filtering and preventing accidental overwriting.
• The default backend for SpatialResizeTask has been switched to cv2 to reduce the number of dependencies.
• eolearn.geometry.morphology tasks now use cv2 instead of scikit-image to reduce the number of dependencies. The task interfaces have been slightly adjusted.
• Improved reports:
  • Exception grouping is now done by exception origin instead of exception message, resulting in shorter reports.
  • Added execution time statistics per node
• CloudMaskTask has been restricted to mono-temporal predictions using the s2cloudless package. For the multi-temporal one check here.
• Certain tasks (for instance SaveTask and LoadTask) no longer pass arguments to the super-class via **kwargs in order to improve documentation and type-checking.
• SaveTask and LoadTask now raise OSError exceptions instead of IOError.
• Project-specific and outdated EOTasks were moved to extras or to the example repository eo-learn-examples/extra-tasks.
• The submodule eolearn.features.bands_extraction has been renamed to eolearn.features.ndi.
• The submodule eolearn.ml_tools.extra.plotting has been moved to eolearn.visualization.utils.
• Compression of EOPatch files has been hardcoded. The parameter compression_level has been deprecated and has no effect.
• Introduced experimental zarr support for loading/saving temporal slices of temporal features. The API might be changed in future releases.
• Limited rasterio to 1.3.7 due to an issue with importing rasters from AWS S3
• Updated examples, simplified tests, various improvements.

Version 1.4.2

Changelog:

• Introduced support for Python 3.11.
• Removed support for Python 3.7.
• Added T-Digest EOTask in the scope of the Global Earth Monitor Project, contributed by @meengel.
• Used evalscript generation utility from sentinelhub-py in SH related EOTasks.
• Deprecated the EOPatch.merge method and extracted it as a function.
• Deprecated the OVERWRITE_PATCH permission and enforcing the usage of explicit string permissions.
• Encapsulated FeatureDict class as Mapping, removed inheritance from dict.
• Switched to new-style typed annotations.
• Introduced the ruff python linter, removed flake8 and isort (covered by ruff).
• Fixed issue with occasionally failing scheduled builds on the master branch.
• Various refactoring efforts and dependency improvements.
• Various improvements to tests and code.

Version 1.4.1

The future direction of eo-learn will start prioritizing reliability and safety of code. After a lot of debate we decided that EOPatches must be well defined in the sense of geo-spatial information (bounding box) and, when using temporal features, temporal information (timestamps). In this light we decided to slowly adjust the code so that ill-formed EOPatches would occur less often. The end goal is to separate these patch-defining meta-information from other EOPatch features.

In this minor release we added a fair amount of deprecation warnings, that should help users to adapt their code ahead of any big codebreaking changes.

• The codebase is now fully annotated and type annotations are mandatory for all new code.
• In the future EOPatch objects will require a valid bbox. For now the users are warned when no such value is provided.
• SaveTask and LoadTask now automatically save/load the bounding box whenever possible, even if not specified in features parameter. CopyTask and MergeEOPatchesTask also always include the bounding box when possible.
• The EOPatch attribute bbox can no longer be deleted via the del command.
• The EOPatch attribute timestamp was renamed into timestamps. The old name still works, but the users are notified. Similarly for FeatureType.TIMESTAMP which was renamed to FeatureType.TIMESTAMPS.
• Feature parsers from eolearn.core.utils.parsers now support callables as input for allowed_feature_types, which are used for filtration over all feature types. Due to this improvement the class FeatureTypeSet was deprecated.
• Certain rarely used methods of FeatureType were deprecated. Method is_raster has been renamed to is_array and designates feature types that contain numpy arrays. We also added is_image for types that denote temporal and timeless imagery.
• Contributors are no longer listed in file headers, but are instead listed in the CREDITS.md file in the root of the repository.
• Updated CONTRIBUTING.md instructions.
• Various other minor improvements and deprecations.