cars.orchestrator.registry.saver_registry

This module contains the saver registry class

Classes

CarsDatasetsRegistrySaver	CarsDatasetsRegistrySaver
SingleCarsDatasetSaver	SingleCarsDatasetSaver

Module Contents

class cars.orchestrator.registry.saver_registry.CarsDatasetsRegistrySaver(id_generator)

Bases: cars.orchestrator.registry.abstract_registry.AbstractCarsDatasetRegistry

CarsDatasetsRegistrySaver This registry manages the saving of arriving future results

registered_cars_datasets_savers = []

get_cars_ds(future_result)

Get a list of registered CarsDataset

Parameters:

obj – object to get cars dataset from

:return corresponding CarsDataset :rtype: CarsDataset

get_cars_datasets_list()

Get a list of registered CarsDataset

:return list of CarsDataset :rtype: list(CarsDataset)

cars_dataset_in_registry(cars_ds)

Check if a CarsDataset is already registered, return id if exists

Parameters:

cars_ds (CarsDataset) – cars dataset

:return : True if in registry, if of cars dataset :rtype : Tuple(bool, int)

get_cars_ds_saver_corresponding_cars_dataset(cars_ds)

Get the SingleCarsDatasetSaver corresponding to given cars dataset

Parameters:

cars_ds – cars dataset

:return : single cars dataset saver :rtype : SingleCarsDatasetSaver

get_cars_ds_saver_corresponding_id(obj_id)

Get the SingleCarsDatasetSaver corresponding to given id

Parameters:

obj_id (int) – cars dataset id

:return : single cars dataset saver :rtype : SingleCarsDatasetSaver

save(future_result)

Save future result

Parameters:

future_result – xr.Dataset or pd.DataFrame

add_file_to_save(file_name, cars_ds, tag=None, dtype=None, nodata=None, optional_data=False, save_by_pair=False, rio_tags=None, rio_band_description=None, nbits=None)

Add file corresponding to cars_dataset to registered_cars_datasets

Parameters:

• file_name (str) – file name to save futures to

• cars_ds (CarsDataset) – CarsDataset to register

• tag (str) – tag to save

• dtype (str) – dtype

• nodata (float) – no data value

• optional_data (bool) – True if the data is optionnal

• save_by_pair (bool)

• rio_tags – rasterio tags list((band, tag))

• rio_band_description – rasterio description list((band, tag))

cleanup()

Cleanup function.

Close correctly all opened files.

class cars.orchestrator.registry.saver_registry.SingleCarsDatasetSaver(obj_id, cars_ds)

SingleCarsDatasetSaver

Structure managing the descriptors of each CarsDataset.

obj_id

cars_ds

file_names = []

optional_data_list = []

tags = []

dtypes = []

nodatas = []

descriptors = []

save_pc_by_pair_list = []

nbits = []

already_seen = False

count = 0

folder_name = None

rio_tags = []

rio_band_description = []

add_file(file_name, tag=None, dtype=None, nodata=None, optional_data=False, save_by_pair=False, rio_tags=None, rio_band_description=None, nbits=None)

Add file to current CarsDatasetSaver

Parameters:

• file_name (str) – file name to save futures to

• tag (str) – tag to save

• dtype (str) – dtype

• nodata (float) – no data value

• optional_data (bool) – True if the data is optionnal

• rio_tags – rasterio tags list((band, tag))

• rio_band_description – rasterio description list((band, tag))

save(future_result)

Save future result

Parameters:

future_result – xr.Dataset or pandas.DataFrame

cleanup()

Cleanup function

Close properly all opened files