oasislmf.preparation.gul_inputs¶

Functions¶

`get_gul_input_items`(location_df, keys_df[, ...])	Generates and returns a Pandas dataframe of GUL input items.
`write_complex_items_file`(gul_inputs_df, complex_items_fp)	Writes a complex model items file.
`write_sections_file`(gul_inputs_df, sections_fp[, ...])	Writes a section id file based on the input location area perils.
`write_amplifications_file`(gul_inputs_df, amplifications_fp)	Writes an amplifications file. This is the mapping between item IDs and
`write_items_file`(gul_inputs_df, items_fp[, chunksize])	Writes an items file.
`write_coverages_file`(gul_inputs_df, coverages_fp[, ...])	Writes a coverages file.
`write_gul_input_files`(gul_inputs_df, target_dir, ...)	Writes the standard Oasis GUL input files to a target directory, using a

Module Contents¶

oasislmf.preparation.gul_inputs.get_gul_input_items(location_df, keys_df, correlations=False, peril_correlation_group_df=None, exposure_profile=get_default_exposure_profile(), damage_group_id_cols=None, hazard_group_id_cols=None, do_disaggregation=True)[source]¶

Generates and returns a Pandas dataframe of GUL input items.

Parameters:

exposure_df (pandas.DataFrame) – Exposure dataframe
keys_df (pandas.DataFrame) – Keys dataframe
output_dir (str) – the output directory where input files are stored
exposure_profile (dict) – Exposure profile
damage_group_id_cols (list[str]) – Columns to be used to generate a hashed damage group id.
hazard_group_id_cols (list[str]) – Columns to be used to generate a hashed hazard group id.
do_disaggregation (bool) – If True, disaggregates by the number of buildings

Returns:

GUL inputs dataframe

Return type:

pandas.DataFrame

oasislmf.preparation.gul_inputs.write_complex_items_file(gul_inputs_df, complex_items_fp, chunksize=100000)[source]¶

Writes a complex model items file.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
complex_items_fp (str) – Complex/custom model items file path

Returns:

Complex/custom model items file path

Return type:

str

oasislmf.preparation.gul_inputs.write_sections_file(gul_inputs_df, sections_fp, chunksize=100000)[source]¶

Writes a section id file based on the input location area perils.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
dynamic_events_fp – events file path to output

oasislmf.preparation.gul_inputs.write_amplifications_file(gul_inputs_df, amplifications_fp, chunksize=100000)[source]¶

Writes an amplifications file. This is the mapping between item IDs and amplifications IDs.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
amplifications_fp (str) – amplifications file path

Returns:

amplifications file path

Return type:

str

oasislmf.preparation.gul_inputs.write_items_file(gul_inputs_df, items_fp, chunksize=100000)[source]¶

Writes an items file.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
items_fp (str) – Items file path

Returns:

Items file path

Return type:

str

oasislmf.preparation.gul_inputs.write_coverages_file(gul_inputs_df, coverages_fp, chunksize=100000)[source]¶

Writes a coverages file.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
coverages_fp (str) – Coverages file path

Returns:

Coverages file path

Return type:

str

oasislmf.preparation.gul_inputs.write_gul_input_files(gul_inputs_df, target_dir, correlations_df, output_dir, oasis_files_prefixes=OASIS_FILES_PREFIXES['gul'], chunksize=2 * 10**5)[source]¶

Writes the standard Oasis GUL input files to a target directory, using a pre-generated dataframe of GUL input items. The files written are

items.csv
coverages.csv

and optionally a complex items file in case of a complex/custom model.

Parameters:

gul_inputs_df (pandas.DataFrame) – GUL inputs dataframe
target_dir (str) – Target directory in which to write the files
oasis_files_prefixes – Oasis GUL input file name prefixes
oasis_files_prefixes – dict
chunksize (int) – The chunk size to use when writing out the input files

Returns:

GUL input files dict

Return type:

dict