eogrow.pipelines.import_vector
Implements a pipeline for importing vector data from a file.
- class eogrow.pipelines.import_vector.ImportVectorPipeline(config, raw_config=None)[source]
Bases:
Pipeline
- Parameters:
config (Schema) – A dictionary with configuration parameters
raw_config (RawConfig | None) – The configuration parameters pre-validation, for logging purposes only
- pydantic model Schema[source]
Bases:
Schema
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- Fields:
clip (bool)
input_filename (str)
input_folder_key (str)
output_feature (Tuple[eolearn.core.constants.FeatureType, str])
output_folder_key (str)
reproject (bool)
- field clip: bool = True
Controls whether the polygons are clipped to the EOPatch boundaries.
- field input_filename: str [Required]
Filename of the vector file to be imported. Needs to be located in the input-data folder.
- field input_folder_key: str = 'input_data'
The folder key into which the EOPatch will be saved.
- Validated by:
validate_storage_key
- field output_feature: Feature [Required]
The EOPatch feature to which the vector will be imported.
- Validated by:
validate_feature
- field output_folder_key: str [Required]
The folder key into which the EOPatch will be saved.
- Validated by:
validate_storage_key
- field reproject: bool = True
Controls whether the vector file is reprojected to the EOPatch CRS.
- get_execution_arguments(workflow, patch_list)[source]
Prepares execution arguments for each eopatch from a list of patches.
The output should be a dictionary of form {execution_name: {node: node_kwargs}}. Execution names are usually names of EOPatches, but can be anything.
- Parameters:
workflow (EOWorkflow) – A workflow for which arguments will be prepared
patch_list (List[Tuple[str, BBox]]) –
- Return type:
Dict[str, Dict[EONode, Dict[str, object]]]