preprocessor.steps package

Submodules

preprocessor.steps.browse_report module

preprocessor.steps.browse_report.apply_browse_report_georeference(input_filename: str, target_filename: str, browse: dict)

preprocessor.steps.browse_report.browse_georeference(source_dir: str, target_dir_data: str, target_dir_meta: str, browse_report: dict, browse: dict)

preprocessor.steps.browse_report.frange(start, stop=None, step=None)

preprocessor.steps.browse_report.generate_gsc(input_filename: str, target_filename: str, browse_report: dict, browse: dict)

preprocessor.steps.calc module

preprocessor.steps.calc.calc_formula(source_dir: str, target_dir: str, preprocessor_config: dict, inputs: Dict[str, dict], target_filename: str, formula: str, data_type: str = 'Float32', nodata_value: float | None = None, creationOptions: List[str] = [])

preprocessor.steps.calc.calc_step(source_dir: str, target_dir: str, preprocessor_config: dict, formulas: List[dict], group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None, ensure_no_data: int | float | complex | bool | None = None, data_file_globs: List[str] = [])

preprocessor.steps.calc.evaluate_formula(formula, filename, input_name, band)

Tries to replace a few common placeholders in the calc formula

preprocessor.steps.calc.set_default_no_data(input_filename: str, ensure_no_data=None)

preprocessor.steps.georeference module

preprocessor.steps.georeference.GetOgrEnvelope(geom)

preprocessor.steps.georeference.corner_georef(input_filename: str, target_filename: str, corner_names: List[str] | None = None, gcp_srid: int = 4326, warp: bool = False)

preprocessor.steps.georeference.correct_geo_transform(src_ds)

preprocessor.steps.georeference.fix_geotrans(input_filename: str, target_filename: str, warp_options: dict | None = None)

preprocessor.steps.georeference.gcp_georef(input_filename: str, target_filename: str, order: int = 1, projection: str = 'EPSG:4326', tps: bool = False, warp_options: dict | None = None)

preprocessor.steps.georeference.gcps_from_borders(size: Tuple[float, float], coords: Tuple[List[float], List[float], List[float], List[float]])

preprocessor.steps.georeference.georeference_step(source_dir: str, target_dir: str, preprocessor_config: dict, geotransforms: List[dict], data_file_globs: List[str] = [])

preprocessor.steps.georeference.gsc_footprint_georef(input_filename: str, target_filename: str, no_data: int | float | None = None)

preprocessor.steps.georeference.no_op(input_filename: str, target_filename: str)

preprocessor.steps.georeference.rpc_georef(input_filename: str, target_filename: str, rpc_file_template: str = '{fileroot}.RPC', warp_options: dict | None = None)

preprocessor.steps.georeference.set_gcps_from_gsc_footprint(ds, config, no_data=0)

preprocessor.steps.georeference.world_georef()

preprocessor.steps.output module

preprocessor.steps.output.output_step(source_dir: PathLike, target_dir: PathLike, preprocessor_config: dict, options: dict | None = None, data_file_globs: List[str] = [], group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None)

preprocessor.steps.stack module

preprocessor.steps.stack.create_groups(group_by, filenames)

Creates groups of files based on group_by configuration check if we have a group_by regex. If yes, use the first re-group to group by. Fallback is basename of file as the only groupname

preprocessor.steps.stack.handle_group_sort(sort_by, order, group, groupname)

preprocessor.steps.stack.intermediate_warp(src_ds, output_path=None, dst_SRS='EPSG:4326')

preprocessor.steps.stack.remove_rotated_geotransform(filenames, target_dir)

Unrotates geotransform to a common grid

preprocessor.steps.stack.stack_bands_step(source_dir: PathLike, target_dir: PathLike, preprocessor_config: dict, group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None, data_file_globs: List[str] = [])

Stack bands of the individual images

preprocessor.steps.subdataset module

preprocessor.steps.subdataset.extract_subdataset_step(source_dir: str, target_dir: str, preprocessor_config: dict, subdataset_types: Dict[str, str] | None = None, data_file_globs: List[str] = [])

preprocessor.steps.subdataset.extract_subdatasets(source_filename: str, target_dir: str, subdataset_types: Dict[str, str] | None = None)

Module contents

preprocessor.steps.calc_step(source_dir: str, target_dir: str, preprocessor_config: dict, formulas: List[dict], group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None, ensure_no_data: int | float | complex | bool | None = None, data_file_globs: List[str] = [])

preprocessor.steps.extract_subdataset_step(source_dir: str, target_dir: str, preprocessor_config: dict, subdataset_types: Dict[str, str] | None = None, data_file_globs: List[str] = [])

preprocessor.steps.georeference_step(source_dir: str, target_dir: str, preprocessor_config: dict, geotransforms: List[dict], data_file_globs: List[str] = [])

preprocessor.steps.output_step(source_dir: PathLike, target_dir: PathLike, preprocessor_config: dict, options: dict | None = None, data_file_globs: List[str] = [], group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None)

preprocessor.steps.stack_bands_step(source_dir: PathLike, target_dir: PathLike, preprocessor_config: dict, group_by: str | None = None, sort_by: str | None = None, order: List[str] | None = None, data_file_globs: List[str] = [])

Stack bands of the individual images