Bump version to 1.4.2 (#671)

* tdigest fixes

* add changelog

* bump version to 1.4.2

* update types of tdigest

CHANGELOG.md

@@ -1,3 +1,18 @@
+## [Version 1.4.2] - 2023-3-14
+
+- 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] - 2023-3-14
 
 - The codebase is now fully annotated and type annotations are mandatory for all new code.

core/eolearn/core/__init__.py

@@ -33,4 +33,4 @@
 from .utils.parallelize import execute_with_mp_lock, join_futures, join_futures_iter, parallelize
 from .utils.parsing import FeatureParser
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

coregistration/eolearn/coregistration/__init__.py

@@ -4,4 +4,4 @@
 
 from .coregistration import ECCRegistrationTask, get_gradient
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

features/eolearn/features/__init__.py

@@ -38,4 +38,4 @@
     AddSpatioTemporalFeaturesTask,
 )
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

geometry/eolearn/geometry/__init__.py

@@ -11,4 +11,4 @@
 )
 from .transformations import RasterToVectorTask, VectorToRasterTask
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

io/eolearn/io/__init__.py

@@ -13,4 +13,4 @@
     get_available_timestamps,
 )
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

mask/eolearn/mask/__init__.py

@@ -8,4 +8,4 @@
 from .snow_mask import SnowMaskTask, TheiaSnowMaskTask
 from .utils import resize_images
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

ml_tools/eolearn/ml_tools/__init__.py

@@ -5,4 +5,4 @@
 from .sampling import BlockSamplingTask, FractionSamplingTask, GridSamplingTask, sample_by_values
 from .train_test_split import TrainTestSplitTask
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"

ml_tools/eolearn/ml_tools/tdigest.py

@@ -1,5 +1,6 @@
 """
 The module provides an EOTask for the computation of a T-Digest representation of an EOPatch.
+Requires installation of `eolearn.ml_tools[TDIGEST]`.
 
 Copyright (c) 2017- Sinergise and contributors
 For the full list of contributors, see the CREDITS file in the root directory of this source tree.
@@ -16,7 +17,7 @@
 from eolearn.core import EOPatch, EOTask, FeatureType
 from eolearn.core.types import FeatureSpec, FeaturesSpecification
 
-ModeTypes = Literal["standard", "timewise", "monthly", "total"]
+ModeTypes = Union[Literal["standard", "timewise", "monthly", "total"], Callable]
 
 
 class TDigestTask(EOTask):
@@ -47,7 +48,7 @@ def __init__(
             * | `'total'` computes the total T-Digest representation of the whole feature accumulating all timestamps,
               | bands and pixels. Cannot be used with `pixelwise=True`.
             * | Callable computes the T-Digest representation defined by the processing function given as mode. Receives
-              | the input_array of the feature, the timestamps, the shape and the pixelwise and filternan keywords as an input.
+              | the input_array of the feature, timestamps, shape and pixelwise and filternan keywords as an input.
         :param pixelwise: Decider whether to compute the T-Digest representation accumulating pixels or per pixel.
             Cannot be used with `mode='total'`.
         :param filternan: Decider whether to filter out nan-values before computing the T-Digest.
@@ -83,8 +84,13 @@ def execute(self, eopatch: EOPatch) -> EOPatch:
         for in_feature_, out_feature_, shape in _looper(
             in_feature=self.in_feature, out_feature=self.out_feature, eopatch=eopatch
         ):
-            eopatch[out_feature_] = _processing_function.get(self.mode, self.mode)(
-                input_array=eopatch[in_feature_], timestamps=eopatch.timestamps, shape=shape, pixelwise=self.pixelwise, filternan=self.filternan
+            processing_func = self.mode if callable(self.mode) else _processing_function[self.mode]
+            eopatch[out_feature_] = processing_func(
+                input_array=eopatch[in_feature_],
+                timestamps=eopatch.timestamps,
+                shape=shape,
+                pixelwise=self.pixelwise,
+                filternan=self.filternan,
             )
 
         return eopatch
@@ -120,7 +126,9 @@ def _looper(
         yield in_feature_, out_feature_, shape
 
 
-def _process_standard(input_array: np.ndarray, shape: np.ndarray, pixelwise: bool, filternan: bool, **_: Any) -> np.ndarray:
+def _process_standard(
+    input_array: np.ndarray, shape: np.ndarray, pixelwise: bool, filternan: bool, **_: Any
+) -> np.ndarray:
     if pixelwise:
         array = np.empty(shape[-3:], dtype=object)
         for i, j, k in product(range(shape[-3]), range(shape[-2]), range(shape[-1])):
@@ -134,7 +142,9 @@ def _process_standard(input_array: np.ndarray, shape: np.ndarray, pixelwise: boo
     return array
 
 
-def _process_timewise(input_array: np.ndarray, shape: np.ndarray, pixelwise: bool, filternan: bool, **_: Any) -> np.ndarray:
+def _process_timewise(
+    input_array: np.ndarray, shape: np.ndarray, pixelwise: bool, filternan: bool, **_: Any
+) -> np.ndarray:
     if pixelwise:
         array = np.empty(shape, dtype=object)
         for time_, i, j, k in product(range(shape[0]), range(shape[1]), range(shape[2]), range(shape[3])):

setup.py

@@ -21,7 +21,7 @@ def parse_requirements(file):
 setup(
     name="eo-learn",
     python_requires=">=3.8",
-    version="1.4.1",
+    version="1.4.2",
     description="Earth observation processing framework for machine learning in Python",
     long_description=get_long_description(),
     long_description_content_type="text/markdown",
@@ -38,14 +38,14 @@ def parse_requirements(file):
     packages=[],
     include_package_data=True,
     install_requires=[
-        "eo-learn-core==1.4.1",
-        "eo-learn-coregistration==1.4.1",
-        "eo-learn-features==1.4.1",
-        "eo-learn-geometry==1.4.1",
-        "eo-learn-io==1.4.1",
-        "eo-learn-mask==1.4.1",
-        "eo-learn-ml-tools==1.4.1",
-        "eo-learn-visualization==1.4.1",
+        "eo-learn-core==1.4.2",
+        "eo-learn-coregistration==1.4.2",
+        "eo-learn-features==1.4.2",
+        "eo-learn-geometry==1.4.2",
+        "eo-learn-io==1.4.2",
+        "eo-learn-mask==1.4.2",
+        "eo-learn-ml-tools==1.4.2",
+        "eo-learn-visualization==1.4.2",
     ],
     extras_require={"DEV": parse_requirements("requirements-dev.txt")},
     zip_safe=False,

visualization/eolearn/visualization/__init__.py

@@ -4,4 +4,4 @@
 
 from .eopatch import PlotBackend, PlotConfig
 
-__version__ = "1.4.1"
+__version__ = "1.4.2"