remotior_sensus.core.multiprocess_manager module

class remotior_sensus.core.multiprocess_manager.Multiprocess(n_processes: int | None = None, multiprocess_module=None)

Bases: object

__init__(n_processes: int | None = None, multiprocess_module=None)

create_warped_vrt(raster_path, output_path, output_wkt=None, align_raster_path=None, same_extent=False, n_processes: int | None = None, src_nodata=None, dst_nodata=None, extra_params=None)

find_minimum_dn()

gdal_copy_raster(input_raster, output, output_format='GTiff', compress=None, compress_format='DEFLATE', additional_params='', n_processes=1, available_ram: int | None = None, min_progress=None, max_progress=None)

gdal_warping(input_raster, output, output_format='GTiff', s_srs=None, t_srs=None, resample_method=None, raster_data_type=None, compression=None, compress_format='DEFLATE', additional_params='', n_processes: int | None = None, available_ram: int | None = None, src_nodata=None, dst_nodata=None, min_progress=None, max_progress=None)

get_dictionary_sum()

join_tables_multiprocess(table1, table2, field1_name, field2_name, nodata_value=None, join_type=None, postfix=None, n_processes: int | None = None, progress_message=None, min_progress=None, max_progress=None)

Parameters:

• table1 – input numpy table 1

• table2 – input numpy table 2

• field1_name – input field table 1

• field2_name – input field table 2

• nodata_value – input nodata value

• join_type – join type

• postfix – postfix string

• n_processes – number of parallel processes.

• progress_message – progress message

• min_progress – minimum progress value

• max_progress – maximum progress value

multi_download_file(url_list, output_path_list, authentication_uri=None, user=None, password=None, proxy_host=None, proxy_port=None, proxy_user=None, proxy_password=None, progress=None, message=None, min_progress=0, max_progress=100, retried=False, timeout=20, copernicus=False, access_token=None)

multiprocess_pixel_value()

multiprocess_raster_sieve(raster_path, n_processes: int | None = None, sieve_size=None, connected=None, output_nodata_value=None, output=None, output_data_type=None, compress=None, compress_format=None, available_ram: int | None = None, min_progress=0, max_progress=100)

multiprocess_raster_to_vector(raster_path, output_vector_path, field_name=None, n_processes: int | None = None, dissolve_output=False, min_progress=0, max_progress=100, available_ram: int | None = None)

multiprocess_raster_to_vector_old(raster_path, output_vector_path, field_name=None, n_processes: int | None = None, dissolve_output=True, min_progress=0, max_progress=100, available_ram: int | None = None)

multiprocess_region_growing()

multiprocess_roi_arrays()

multiprocess_scatter_values()

multiprocess_spectral_signature()

multiprocess_sum_array(nodata=None)

multiprocess_unique_values()

multiprocess_vector_to_raster(vector_path, field_name=None, output_path=None, reference_raster_path=None, output_format=None, nodata_value=None, background_value=None, burn_values=None, minimum_extent=None, x_y_size=None, all_touched=None, compress=None, compress_format=None, available_ram: int | None = None, min_progress=0, max_progress=100)

run(raster_path, function=None, function_argument=None, function_variable=None, calculation_datatype=None, use_value_as_nodata=None, any_nodata_mask=True, output_raster_path=None, output_data_type=None, output_nodata_value=None, compress=None, compress_format='LZW', n_processes: int | None = None, available_ram: int | None = None, dummy_bands=1, output_band_number=1, boundary_size=None, unique_section=False, keep_output_array=False, keep_output_argument=False, delete_array=True, scale=None, offset=None, input_nodata_as_value=None, classification=False, classification_confidence=False, signature_raster=False, virtual_raster=False, multi_add_factors=None, separate_bands=False, progress_message=None, device=None, multiple_block=None, specific_output=None, min_progress=None, max_progress=None)

Parameters:

• device – processing device ‘cpu’ or ‘cuda’ if available.

• classification_confidence – if True, write also additional classification confidence rasters as output.

• signature_raster – if True, write additional rasters for each spectral signature as output.

• raster_path – input path.

• multi_add_factors – list of multiplicative and additive factors.

• virtual_raster – if True, create virtual raster output.

• offset – integer number of output offset.

• scale – integer number of output scale.

• delete_array – if True delete output array.

• keep_output_argument – if True keep output argument for post processing.

• keep_output_array – if True keep output array for post processing.

• unique_section – if True consider the whole raster as unique section.

• dummy_bands – integer number of dummy bands to be counted for calculating block size

• available_ram – integer value of RAM in MB.

• any_nodata_mask – True to apply the nodata where any input is nodata, False to apply nodata where all inputs are nodata, None not apply nodata

• input_nodata_as_value – consider nodata as value in calculation

• output_data_type – string of data type for output raster such as Float32 or Int16

• output_band_number – number of bands of the output

• output_nodata_value – output nodata value

• compress_format – string of format of raster compression

• compress – True to compress the output raster or False not to compress

• boundary_size – integer number of pixels used to extend the boundary of calculations

• output_raster_path – list of output path strings

• calculation_datatype – datatype use during calculation

• function_variable – list of variables for function

• function_argument – arguments of function

• n_processes – number of parallel processes.

• function – function name

• specific_output – dictionary of values for specific output raster

• classification – if True, settings are defined for a classification output

• use_value_as_nodata – integer value as nodata in calculation

• separate_bands – if True, calculate a section for each raster range

• progress_message – progress message

• multiple_block – allows for setting block size as a multiple of the pixel count here defined

• min_progress – minimum progress value

• max_progress – maximum progress value

run_iterative_process(function_list, argument_list, min_progress=None, max_progress=None, n_processes=None)

run_scikit(function, classifier_list=None, list_train_argument_dictionaries=None, n_processes=None, available_ram: int | None = None, min_progress=None, max_progress=None)

run_separated(raster_path_list, function=None, function_argument=None, function_variable=None, calculation_datatype=None, use_value_as_nodata=None, any_nodata_mask=True, output_raster_list=None, output_data_type=None, output_nodata_value=None, compress=None, compress_format='LZW', n_processes: int | None = None, available_ram: int | None = None, output_band_number_list=None, boundary_size=None, dummy_bands=0, keep_output_array=False, keep_output_argument=False, scale=None, offset=None, input_nodata_as_value=None, multi_add_factors=None, progress_message=None, min_progress=None, max_progress=None)

Parameters:

• multi_add_factors – list of multiplicative and additive factors

• offset – list integer number of output offset

• scale – list of integer number of output scale

• keep_output_argument – if True keep output argument for post-processing

• dummy_bands – integer number of dummy bands to be counted for calculating block size

• keep_output_array – if True keep output array for post-processing

• available_ram – integer value of RAM in MB

• any_nodata_mask – True to apply the nodata where any input is nodata, False to apply nodata where all inputs are nodata, None not apply nodata

• input_nodata_as_value – consider nodata as value in calculation

• output_data_type – list of data type string for output raster such as Float32 or Int16

• output_band_number_list – list of number of bands of the output

• output_nodata_value – nodata value of the output

• compress_format – string of format of raster compression

• compress – True to compress the output raster or False not to compress

• boundary_size – integer number of pixels used to extend the boundary of calculations

• output_raster_list – list of output path strings

• calculation_datatype – datatype use during calculation

• function_variable – list of variables for function

• function_argument – arguments of function

• n_processes – number of parallel processes.

• function – function name

• raster_path_list – input path

• use_value_as_nodata – list of integer values as nodata in calculation

• progress_message – progress message

• min_progress – minimum progress value

• max_progress – maximum progress value

start(n_processes, multiprocess_module=None)

stop()