oasislmf.preparation.il_inputs

Functions

get_calc_rule_ids(il_inputs_calc_rules_df, calc_rule_type)

merge selected il_inputs with the correct calc_rule table and return a pandas Series of 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)[source]

merge selected il_inputs with the correct calc_rule table and return a pandas Series of calc. rule IDs

Args:

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

Returns:

pandas Series of calc. 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)[source]

Generates and returns a Pandas dataframe of IL input items.

Parameters:

  • gul_inputs_df (pandas.DataFrame) – GUL input items

  • exposure_data – object containing all information about the insurance policies

  • target_dir – path to the directory used to write the fm files

  • logger – logger object to trace progress

  • exposure_profile (dict) – Source exposure profile (optional)

  • accounts_profile (dict) – Source accounts profile (optional)

  • fm_aggregation_profile – FM aggregation profile (optional)

  • fm_aggregation_profile – dict

  • do_disaggregation – whether to split terms and conditions for aggregate exposure (optional)

  • do_disaggregation – bool

Returns:

IL inputs dataframe

Return type:

pandas.DataFrame

:return Accounts dataframe :rtype: pandas.DataFrame