remove "whether to" from docs (#776)

Co-authored-by: Matic Lubej <matic.lubej@sinergise.com>

Author: mlubej

eolearn/core/core_tasks.py

@@ -119,7 +119,7 @@ def __init__(
             all features will be saved.
         :param overwrite_permission: A level of permission for overwriting an existing EOPatch
             to 9 (highest compression).
-        :save_timestamps: Whether to save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
+        :save_timestamps: Save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
             if `features=...` or if other temporal features are being saved.
         :param use_zarr: Saves numpy-array based features into Zarr files. Requires ZARR extra dependencies.
         :param temporal_selection: Writes all of the data to the chosen temporal indices of preexisting arrays. Can be
@@ -191,7 +191,7 @@ def __init__(
             default configuration will be taken.
         :param features: A collection of features to be loaded. By default, all features will be loaded.
         :param lazy_loading: If `True` features will be lazy loaded.
-        :load_timestamps: Whether to load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
+        :load_timestamps: Load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
             if `features=...` or if other temporal features are being loaded.
         :param temporal_selection: Only loads data corresponding to the chosen indices. Can also be a callable that,
             given a list of timestamps, returns a list of booleans declaring which temporal slices to load.

eolearn/core/eodata.py

@@ -499,7 +499,7 @@ def __copy__(
         """Returns a new EOPatch with shallow copies of given features.
 
         :param features: A collection of features or feature types that will be copied into new EOPatch.
-        :param copy_timestamps: Whether to copy timestamps to the new EOPatch. By default copies them over if all
+        :param copy_timestamps: Copy timestamps to the new EOPatch. By default copies them over if all
             features are copied or if any temporal features are getting copied.
         """
         if not features:  # For some reason deepcopy and copy pass {} by default
@@ -526,7 +526,7 @@ def __deepcopy__(
 
         :param memo: built-in parameter for memoization
         :param features: A collection of features or feature types that will be copied into new EOPatch.
-        :param copy_timestamps: Whether to copy timestamps to the new EOPatch. By default copies them over if all
+        :param copy_timestamps: Copy timestamps to the new EOPatch. By default copies them over if all
             features are copied or if any temporal features are getting copied.
         """
         if not features:  # For some reason deepcopy and copy pass {} by default
@@ -564,7 +564,7 @@ def copy(
         :param features: Features to be copied into a new `EOPatch`. By default, all features will be copied.
         :param deep: If `True` it will make a deep copy of all data inside the `EOPatch`. Otherwise, only a shallow copy
             of `EOPatch` will be made. Note that `BBOX` and `TIMESTAMPS` will be copied even with a shallow copy.
-        :param copy_timestamps: Whether to copy timestamps to the new EOPatch. By default copies them over if all
+        :param copy_timestamps: Copy timestamps to the new EOPatch. By default copies them over if all
             features are copied or if any temporal features are getting copied.
         :return: An EOPatch copy.
         """
@@ -620,7 +620,7 @@ def save(
         :param overwrite_permission: A level of permission for overwriting an existing EOPatch
         :param filesystem: An existing filesystem object. If not given it will be initialized according to the `path`
             parameter.
-        :save_timestamps: Whether to save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
+        :save_timestamps: Save the timestamps of the EOPatch. With the `"auto"` setting timestamps are saved
             if `features=...` or if other temporal features are being saved.
         :param use_zarr: Saves numpy-array based features into Zarr files. Requires ZARR extra dependencies.
         :param temporal_selection: Writes all of the data to the chosen temporal indices of preexisting arrays. Can be
@@ -666,7 +666,7 @@ def load(
         :param lazy_loading: If `True` features will be lazy loaded.
         :param filesystem: An existing filesystem object. If not given it will be initialized according to the `path`
             parameter.
-        :load_timestamps: Whether to load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
+        :load_timestamps: Load the timestamps of the EOPatch. With the `"auto"` setting timestamps are loaded
             if `features=...` or if other temporal features are being loaded.
         :param temporal_selection: Only loads data corresponding to the chosen indices. Can also be a callable that,
             given a list of timestamps, returns a list of booleans declaring which temporal slices to load.

eolearn/core/eoexecution.py

@@ -114,7 +114,7 @@ def __init__(
               object.
 
             The 2nd option is chosen only if `filesystem` parameter exists in the signature.
-        :param raise_on_temporal_mismatch: Whether to treat `TemporalDimensionWarning` as an exception.
+        :param raise_on_temporal_mismatch: Treat `TemporalDimensionWarning` as an exception.
         """
         self.workflow = workflow
         self.execution_kwargs = self._parse_and_validate_execution_kwargs(execution_kwargs)
@@ -326,7 +326,7 @@ def get_failed_executions(self) -> list[int]:
     def get_report_path(self, full_path: bool = True) -> str:
         """Returns the filename and file path of the report.
 
-        :param full_path: Whether to return full absolute paths or paths relative to the filesystem object.
+        :param full_path: Return full absolute paths or paths relative to the filesystem object.
         :return: Report filename
         """
         if self.report_folder is None:
@@ -354,7 +354,7 @@ def make_report(self, include_logs: bool = True) -> None:
     def get_log_paths(self, full_path: bool = True) -> list[str]:
         """Returns a list of file paths containing logs.
 
-        :param full_path: Whether to return full absolute paths or paths relative to the filesystem object.
+        :param full_path: Return full absolute paths or paths relative to the filesystem object.
         :return: A list of paths to log files.
         """
         if self.report_folder is None:

eolearn/ml_tools/sampling.py

@@ -54,7 +54,7 @@ def sample_by_values(
     :param n_samples_per_value: A dictionary specifying the amount of samples per value. Values that are not in the
         dictionary will not be sampled.
     :param rng: A random numbers generator. If not provided it will be initialized without a seed.
-    :param replace: Whether to sample with replacement. False means each value can only be chosen once.
+    :param replace: Sample with replacement. False means each value can only be chosen once.
     :return: A pair of numpy arrays first one containing row indices and second one containing column indices of sampled
         points.
     """
@@ -190,7 +190,7 @@ def __init__(
         :param sampling_feature: A timeless mask feature according to which points will be sampled.
         :param fraction: Fraction of points to sample. Can be dictionary mapping values of mask to fractions.
         :param exclude_values: Skips points that have these values in `sampling_mask`
-        :param replace: Whether to sample with replacement. False means each value can only be chosen once.
+        :param replace: Sample with replacement. False means each value can only be chosen once.
         :param mask_of_samples: An output mask timeless feature of counts how many times each pixel has been sampled.
         """
         super().__init__(features_to_sample, mask_of_samples=mask_of_samples)
@@ -275,7 +275,7 @@ def __init__(
         :param amount: The number of points to sample if integer valued and the fraction of all points if `float`
         :param sample_size: A tuple describing a size of sampled blocks. The size is defined as a tuple of number of
             rows and number of columns.
-        :param replace: Whether to sample with replacement. False means each value can only be chosen once.
+        :param replace: Sample with replacement. False means each value can only be chosen once.
         :param mask_of_samples: An output mask timeless feature of counts how many times each pixel has been sampled.
         """
         super().__init__(features_to_sample, mask_of_samples=mask_of_samples)