sampo.userinput.parser.history#

Overview#

Function#

get_all_connections(graph_df, use_mapper, mapper)

-

get_delta_between_dates(first, second)

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find_min_without_outliers(lst)

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gather_links_types_statistics(s1, f1, s2, f2)

Count statistics on the occurrence of different mutual arrangement of tasks

get_all_seq_statistic(history_data, graph_df, use_model_name, mapper)

-

set_connections_info(graph_df, history_data, use_model_name, mapper, change_connections_info, expert_connections_info)

Restore tasks’ connection based on history data

Functions#

sampo.userinput.parser.history.get_all_connections(graph_df: pandas.DataFrame, use_mapper: bool = False, mapper: sampo.utilities.task_name.NameMapper = None) → Tuple[dict[str, list], dict[str, list]]#
sampo.userinput.parser.history.get_delta_between_dates(first: str, second: str) → int#
sampo.userinput.parser.history.find_min_without_outliers(lst: list[float]) → float#

Count statistics on the occurrence of different mutual arrangement of tasks

Parameters:

  • s1 – start of first work

  • f1 – finish of first work

  • s2 – start of second work

  • f2 – finish of second work

Returns:

Statistics on the occurrence of different mutual arrangement of tasks

sampo.userinput.parser.history.get_all_seq_statistic(history_data, graph_df, use_model_name=False, mapper=None)#
sampo.userinput.parser.history.set_connections_info(graph_df: pandas.DataFrame, history_data: pandas.DataFrame, use_model_name: bool = False, mapper=None, change_connections_info: bool = False, expert_connections_info: bool = False) → pandas.DataFrame#

Restore tasks’ connection based on history data

Param:

change_connections_info - whether existing connections should be modified based on connection history data

Param:

expert_connections_info - whether existing connections should not be modified based on connection history data

Returns:

repaired DataFrame