introduce Feature type alias

eolearn/core/core_tasks.py

@@ -25,7 +25,7 @@
 from .eodata_merge import merge_eopatches
 from .eotask import EOTask
 from .exceptions import EODeprecationWarning
-from .types import EllipsisType, FeaturesSpecification
+from .types import EllipsisType, Feature, FeaturesSpecification
 from .utils.fs import get_filesystem, pickle_fs, unpickle_fs
 
 
@@ -227,7 +227,7 @@ def execute(
 class AddFeatureTask(EOTask):
     """Adds a feature to the given EOPatch."""
 
-    def __init__(self, feature: tuple[FeatureType, str]):
+    def __init__(self, feature: Feature):
         """
         :param feature: Feature to be added
         """
@@ -335,7 +335,7 @@ class InitializeFeatureTask(EOTask):
     def __init__(
         self,
         features: FeaturesSpecification,
-        shape: tuple[int, ...] | tuple[FeatureType, str],
+        shape: tuple[int, ...] | Feature,
         init_value: int = 0,
         dtype: np.dtype | type = np.uint8,
     ):
@@ -530,7 +530,7 @@ def zip_method(self, *f):
     def __init__(
         self,
         input_features: FeaturesSpecification,
-        output_feature: tuple[FeatureType, str],
+        output_feature: Feature,
         zip_function: Callable | None = None,
         **kwargs: Any,
     ):
@@ -597,8 +597,8 @@ class ExplodeBandsTask(EOTask):
 
     def __init__(
         self,
-        input_feature: tuple[FeatureType, str],
-        output_mapping: dict[tuple[FeatureType, str], int | Iterable[int]],
+        input_feature: Feature,
+        output_mapping: dict[Feature, int | Iterable[int]],
     ):
         """
         :param input_feature: A source feature from which to take the subset of bands.

eolearn/core/eodata.py

@@ -40,7 +40,7 @@
 from .constants import FEATURETYPE_DEPRECATION_MSG, TIMESTAMP_COLUMN, FeatureType, OverwritePermission
 from .eodata_io import FeatureIO, load_eopatch_content, save_eopatch
 from .exceptions import EODeprecationWarning, TemporalDimensionWarning
-from .types import EllipsisType, FeaturesSpecification
+from .types import EllipsisType, Feature, FeaturesSpecification
 from .utils.common import deep_eq, is_discrete_type
 from .utils.fs import get_filesystem
 from .utils.parsing import parse_features
@@ -394,7 +394,7 @@ def __setitem__(self, key: FeatureType | tuple[FeatureType, str | None | Ellipsi
         else:
             setattr(self, ftype_attr, value)
 
-    def __delitem__(self, feature: FeatureType | tuple[FeatureType, str]) -> None:
+    def __delitem__(self, feature: FeatureType | Feature) -> None:
         """Deletes the selected feature type or feature."""
         if isinstance(feature, tuple):
             feature_type, feature_name = feature
@@ -585,12 +585,12 @@ def get_spatial_dimension(self, feature_type: FeatureType, feature_name: str) ->
 
         raise ValueError(f"Features of type {feature_type} do not have a spatial dimension or are not arrays.")
 
-    def get_features(self) -> list[tuple[FeatureType, str]]:
+    def get_features(self) -> list[Feature]:
         """Returns a list of all non-empty features of EOPatch.
 
         :return: List of non-empty features
         """
-        feature_list: list[tuple[FeatureType, str]] = []
+        feature_list: list[Feature] = []
         with warnings.catch_warnings():
             warnings.filterwarnings("ignore", message=FEATURETYPE_DEPRECATION_MSG.format(".*?", ".*?"))
             removed_ftypes = {FeatureType.BBOX, FeatureType.TIMESTAMPS}  # list comprehensions make ignoring hard
@@ -748,7 +748,7 @@ def consolidate_timestamps(self, timestamps: list[dt.datetime]) -> set[dt.dateti
 
     def plot(
         self,
-        feature: tuple[FeatureType, str],
+        feature: Feature,
         *,
         times: list[int] | slice | None = None,
         channels: list[int] | slice | None = None,

eolearn/core/eodata_io.py

@@ -55,7 +55,7 @@
 
 from .constants import TIMESTAMP_COLUMN, FeatureType, OverwritePermission
 from .exceptions import EODeprecationWarning
-from .types import EllipsisType, FeaturesSpecification
+from .types import EllipsisType, Feature, FeaturesSpecification
 from .utils.fs import get_full_path, split_all_extensions
 from .utils.parsing import FeatureParser
 
@@ -92,7 +92,7 @@ class FilesystemDataInfo:
     old_meta_info: str | None = None
     features: dict[FeatureType, dict[str, str]] = field(default_factory=lambda: defaultdict(dict))
 
-    def iterate_features(self) -> Iterator[tuple[tuple[FeatureType, str], str]]:
+    def iterate_features(self) -> Iterator[tuple[Feature, str]]:
         """Yields `(ftype, fname), path` tuples from `features`."""
         for ftype, ftype_dict in self.features.items():
             for fname, path in ftype_dict.items():
@@ -342,7 +342,7 @@ def _load_features(
     temporal_selection: None | slice | list[int] | list[bool],
     err_msg: str,
     file_information: FilesystemDataInfo,
-) -> dict[tuple[FeatureType, str], FeatureIO]:
+) -> dict[Feature, FeatureIO]:
     features_dict = {}
     if file_information.old_meta_info is not None and any(ftype is FeatureType.META_INFO for ftype, _ in feature_specs):
         msg = (

eolearn/core/eodata_merge.py

@@ -23,7 +23,7 @@
 from .constants import FeatureType
 from .eodata import EOPatch
 from .exceptions import EORuntimeWarning
-from .types import FeaturesSpecification
+from .types import Feature, FeaturesSpecification
 from .utils.parsing import FeatureParser
 
 OperationInputType = Union[Literal[None, "concatenate", "min", "max", "mean", "median"], Callable]
@@ -161,7 +161,7 @@ def _check_if_optimize(eopatches: Sequence[EOPatch], operation_input: OperationI
 
 def _merge_time_dependent_raster_feature(
     eopatches: Sequence[EOPatch],
-    feature: tuple[FeatureType, str],
+    feature: Feature,
     operation: Callable,
     order_mask_per_eopatch: Sequence[np.ndarray],
     optimize: bool,
@@ -204,7 +204,7 @@ def _merge_time_dependent_raster_feature(
 
 def _extract_and_join_time_dependent_feature_values(
     eopatches: Sequence[EOPatch],
-    feature: tuple[FeatureType, str],
+    feature: Feature,
     order_mask_per_eopatch: Sequence[np.ndarray],
     optimize: bool,
 ) -> tuple[np.ndarray, np.ndarray]:
@@ -237,9 +237,7 @@ def _is_strictly_increasing(array: np.ndarray) -> bool:
     return (np.diff(array) > 0).all().astype(bool)
 
 
-def _merge_timeless_raster_feature(
-    eopatches: Sequence[EOPatch], feature: tuple[FeatureType, str], operation: Callable
-) -> np.ndarray:
+def _merge_timeless_raster_feature(eopatches: Sequence[EOPatch], feature: Feature, operation: Callable) -> np.ndarray:
     """Merges numpy arrays of a timeless raster feature with a given operation."""
     arrays = _extract_feature_values(eopatches, feature)
 
@@ -255,7 +253,7 @@ def _merge_timeless_raster_feature(
         ) from exception
 
 
-def _merge_vector_feature(eopatches: Sequence[EOPatch], feature: tuple[FeatureType, str]) -> GeoDataFrame:
+def _merge_vector_feature(eopatches: Sequence[EOPatch], feature: Feature) -> GeoDataFrame:
     """Merges GeoDataFrames of a vector feature."""
     dataframes = _extract_feature_values(eopatches, feature)
 
@@ -299,7 +297,7 @@ def _get_common_bbox(eopatches: Sequence[EOPatch]) -> BBox | None:
     raise ValueError("Cannot merge EOPatches because they are defined for different bounding boxes.")
 
 
-def _extract_feature_values(eopatches: Sequence[EOPatch], feature: tuple[FeatureType, str]) -> list[Any]:
+def _extract_feature_values(eopatches: Sequence[EOPatch], feature: Feature) -> list[Any]:
     """A helper function that extracts a feature values from those EOPatches where a feature exists."""
     feature_type, feature_name = feature
     return [eopatch[feature] for eopatch in eopatches if feature_name in eopatch[feature_type]]

eolearn/core/eotask.py

@@ -24,7 +24,7 @@
 from .constants import FeatureType
 from .eodata import EOPatch
 from .exceptions import EODeprecationWarning
-from .types import EllipsisType, FeaturesSpecification, SingleFeatureSpec
+from .types import EllipsisType, Feature, FeaturesSpecification, SingleFeatureSpec
 from .utils.parsing import FeatureParser, parse_feature, parse_features, parse_renamed_feature, parse_renamed_features
 
 LOGGER = logging.getLogger(__name__)
@@ -84,7 +84,7 @@ def parse_feature(
         feature: SingleFeatureSpec,
         eopatch: EOPatch | None = None,
         allowed_feature_types: EllipsisType | Iterable[FeatureType] | Callable[[FeatureType], bool] = ...,
-    ) -> tuple[FeatureType, str]:
+    ) -> Feature:
         """See `eolearn.core.utils.parse_feature`."""
         return parse_feature(feature, eopatch, allowed_feature_types)
 
@@ -93,7 +93,7 @@ def parse_features(
         features: FeaturesSpecification,
         eopatch: EOPatch | None = None,
         allowed_feature_types: EllipsisType | Iterable[FeatureType] | Callable[[FeatureType], bool] = ...,
-    ) -> list[tuple[FeatureType, str]]:
+    ) -> list[Feature]:
         """See `eolearn.core.utils.parse_features`."""
         return parse_features(features, eopatch, allowed_feature_types)
 

eolearn/core/types.py

@@ -27,8 +27,9 @@
 
 
 # DEVELOPER NOTE: the #: comments are applied as docstrings
+Feature: TypeAlias = Tuple[FeatureType, str]
 
-SingleFeatureSpec: TypeAlias = Union[Tuple[FeatureType, str], Tuple[FeatureType, str, str]]
+SingleFeatureSpec: TypeAlias = Union[Feature, Tuple[FeatureType, str, str]]
 
 SequenceFeatureSpec: TypeAlias = Sequence[Union[SingleFeatureSpec, FeatureType, Tuple[FeatureType, EllipsisType]]]
 DictFeatureSpec: TypeAlias = Dict[FeatureType, Union[EllipsisType, Iterable[Union[str, Tuple[str, str]]]]]

eolearn/core/utils/parsing.py

@@ -16,6 +16,7 @@
 from ..types import (
     DictFeatureSpec,
     EllipsisType,
+    Feature,
     FeaturesSpecification,
     SequenceFeatureSpec,
     SingleFeatureSpec,
@@ -238,7 +239,7 @@ def get_feature_specifications(self) -> list[tuple[FeatureType, str | EllipsisTy
         """
         return [(ftype, ... if fname is None else fname) for ftype, fname, _ in self._feature_specs]
 
-    def get_features(self, eopatch: EOPatch | None = None) -> list[tuple[FeatureType, str]]:
+    def get_features(self, eopatch: EOPatch | None = None) -> list[Feature]:
         """Returns a list of `(feature_type, feature_name)` pairs.
 
         For features that specify renaming, the new name of the feature is ignored.
@@ -285,7 +286,7 @@ def parse_feature(
     feature: SingleFeatureSpec,
     eopatch: EOPatch | None = None,
     allowed_feature_types: EllipsisType | Iterable[FeatureType] | Callable[[FeatureType], bool] = ...,
-) -> tuple[FeatureType, str]:
+) -> Feature:
     """Parses input describing a single feature into a `(feature_type, feature_name)` pair.
 
     See :class:`FeatureParser<eolearn.core.utilities.FeatureParser>` for viable inputs.
@@ -317,7 +318,7 @@ def parse_features(
     features: FeaturesSpecification,
     eopatch: EOPatch | None = None,
     allowed_feature_types: EllipsisType | Iterable[FeatureType] | Callable[[FeatureType], bool] = ...,
-) -> list[tuple[FeatureType, str]]:
+) -> list[Feature]:
     """Parses input describing features into a list of `(feature_type, feature_name)` pairs.
 
     See :class:`FeatureParser<eolearn.core.utilities.FeatureParser>` for viable inputs.

eolearn/core/utils/testing.py

@@ -23,6 +23,7 @@
 
 from ..constants import FeatureType
 from ..eodata import EOPatch
+from ..types import Feature
 from ..utils.parsing import FeatureParser
 
 DEFAULT_BBOX = BBox((0, 0, 100, 100), crs=CRS("EPSG:32633"))
@@ -45,7 +46,7 @@ def __post_init__(self) -> None:
 
 
 def generate_eopatch(
-    features: list[tuple[FeatureType, str]] | None = None,
+    features: list[Feature] | None = None,
     bbox: BBox = DEFAULT_BBOX,
     timestamps: list[dt.datetime] | None = None,
     seed: int = 42,

eolearn/coregistration/coregistration.py

@@ -16,7 +16,7 @@
 
 from eolearn.core import EOPatch, EOTask, FeatureType
 from eolearn.core.exceptions import EORuntimeWarning
-from eolearn.core.types import FeaturesSpecification
+from eolearn.core.types import Feature, FeaturesSpecification
 
 LOGGER = logging.getLogger(__name__)
 
@@ -36,10 +36,10 @@ class ECCRegistrationTask(EOTask):
 
     def __init__(
         self,
-        registration_feature: tuple[FeatureType, str],
-        reference_feature: tuple[FeatureType, str],
+        registration_feature: Feature,
+        reference_feature: Feature,
         channel: int,
-        valid_mask_feature: tuple[FeatureType, str] | None = None,
+        valid_mask_feature: Feature | None = None,
         apply_to_features: FeaturesSpecification = ...,
         interpolation_mode: int = cv2.INTER_LINEAR,
         warp_mode: int = cv2.MOTION_TRANSLATION,

eolearn/features/bands_extraction.py

@@ -10,7 +10,8 @@
 
 import numpy as np
 
-from eolearn.core import FeatureType, MapFeatureTask
+from eolearn.core import MapFeatureTask
+from eolearn.core.types import Feature
 
 
 class EuclideanNormTask(MapFeatureTask):
@@ -23,8 +24,8 @@ class EuclideanNormTask(MapFeatureTask):
 
     def __init__(
         self,
-        input_feature: tuple[FeatureType, str],
-        output_feature: tuple[FeatureType, str],
+        input_feature: Feature,
+        output_feature: Feature,
         bands: list[int] | None = None,
     ):
         """
@@ -55,8 +56,8 @@ class NormalizedDifferenceIndexTask(MapFeatureTask):
 
     def __init__(
         self,
-        input_feature: tuple[FeatureType, str],
-        output_feature: tuple[FeatureType, str],
+        input_feature: Feature,
+        output_feature: Feature,
         bands: tuple[int, int],
         acorvi_constant: float = 0,
         undefined_value: float = np.nan,

eolearn/features/clustering.py

@@ -15,6 +15,7 @@
 from sklearn.feature_extraction.image import grid_to_graph
 
 from eolearn.core import EOPatch, EOTask, FeatureType
+from eolearn.core.types import Feature
 
 
 class ClusteringTask(EOTask):
@@ -28,7 +29,7 @@ class ClusteringTask(EOTask):
 
     def __init__(
         self,
-        features: tuple[FeatureType, str],
+        features: Feature,
         new_feature_name: str,
         distance_threshold: float | None = None,
         n_clusters: int | None = None,

eolearn/features/doubly_logistic_approximation.py

@@ -14,6 +14,7 @@
 from scipy.optimize import curve_fit
 
 from eolearn.core import EOPatch, EOTask, FeatureType
+from eolearn.core.types import Feature
 
 
 def doubly_logistic(middle, initial_value, scale, a1, a2, a3, a4, a5) -> np.ndarray:  # type: ignore[no-untyped-def]
@@ -35,10 +36,10 @@ class DoublyLogisticApproximationTask(EOTask):
 
     def __init__(
         self,
-        feature: tuple[FeatureType, str],
-        new_feature: tuple[FeatureType, str] = (FeatureType.DATA_TIMELESS, "DOUBLY_LOGISTIC_PARAM"),
+        feature: Feature,
+        new_feature: Feature = (FeatureType.DATA_TIMELESS, "DOUBLY_LOGISTIC_PARAM"),
         initial_parameters: list[float] | None = None,
-        valid_mask: tuple[FeatureType, str] | None = None,
+        valid_mask: Feature | None = None,
     ):
         self.initial_parameters = initial_parameters
         self.feature = self.parse_feature(feature)

eolearn/features/feature_manipulation.py

@@ -19,9 +19,9 @@
 
 from sentinelhub import bbox_to_dimensions
 
-from eolearn.core import EOPatch, EOTask, FeatureType, MapFeatureTask
+from eolearn.core import EOPatch, EOTask, MapFeatureTask
 from eolearn.core.constants import TIMESTAMP_COLUMN
-from eolearn.core.types import FeaturesSpecification
+from eolearn.core.types import Feature, FeaturesSpecification
 from eolearn.core.utils.parsing import parse_renamed_features
 
 from .utils import ResizeLib, ResizeMethod, ResizeParam, spatially_resize_image
@@ -39,7 +39,7 @@ class SimpleFilterTask(EOTask):
 
     def __init__(
         self,
-        feature: tuple[FeatureType, str] | Literal["timestamps"],
+        feature: Feature | Literal["timestamps"],
         filter_func: Callable[[np.ndarray], bool] | Callable[[dt.datetime], bool],
         filter_features: FeaturesSpecification = ...,
     ):
@@ -49,7 +49,7 @@ def __init__(
         :param filter_features: A collection of features which will be filtered into a new EOPatch
         """
         if feature == "timestamps":
-            self.feature: tuple[FeatureType, str] | Literal["timestamps"] = "timestamps"
+            self.feature: Feature | Literal["timestamps"] = "timestamps"
         else:
             self.feature = self.parse_feature(
                 feature, allowed_feature_types=lambda fty: fty.is_temporal() and fty.is_array()
@@ -132,7 +132,7 @@ class ValueFilloutTask(EOTask):
 
     def __init__(
         self,
-        feature: tuple[FeatureType, str],
+        feature: Feature,
         operations: Literal["f", "b", "fb", "bf"] = "fb",
         value: float = np.nan,
         axis: int = 0,