oasislmf.preparation.il_inputs

Functions

get_calc_rule_ids(il_inputs_calc_rules_df, calc_rule_type)	Merges IL inputs with the correct calc_rule table and returns calc rule IDs.
get_il_input_items(gul_inputs_df, exposure_data, ...)	Generates and returns a Pandas dataframe of IL input items.

Module Contents

oasislmf.preparation.il_inputs.get_calc_rule_ids(il_inputs_calc_rules_df, calc_rule_type)

Merges IL inputs with the correct calc_rule table and returns calc rule IDs.

Args:

il_inputs_calc_rules_df (pandas.DataFrame): IL input items dataframe. calc_rule_type (str): Type of calc_rule to look for.

Returns:

pandas.Series: Series of calculation rule IDs.

oasislmf.preparation.il_inputs.get_il_input_items(gul_inputs_df, exposure_data, target_dir, logger, exposure_profile=get_default_exposure_profile(), accounts_profile=get_default_accounts_profile(), fm_aggregation_profile=get_default_fm_aggregation_profile(), do_disaggregation=True, oasis_files_prefixes=OASIS_FILES_PREFIXES['il'], chunksize=2 * 10**5)

Generates and returns a Pandas dataframe of IL input items.

Also writes FM files (fm_policytc, fm_profile, fm_programme, fm_xref) to target_dir.

Args:

gul_inputs_df (pandas.DataFrame): GUL input items. exposure_data: Object containing all information about the insurance policies. target_dir (str): Path to the directory used to write the FM files. logger: Logger object to trace progress. exposure_profile (dict, optional): Source exposure profile. accounts_profile (dict, optional): Source accounts profile. fm_aggregation_profile (dict, optional): FM aggregation profile. do_disaggregation (bool, optional): Whether to split terms and conditions

for aggregate exposure.

oasis_files_prefixes (dict, optional): Dictionary of file prefixes for FM output files. chunksize (int, optional): Number of rows to write per chunk when writing CSV files.

Returns:

pandas.DataFrame: IL inputs dataframe with output_id, layer_id, and other

FM-related columns.