Source code for pm4py.algo.filtering.pandas.prefixes.prefix_filter

import pandas as pd

from enum import Enum
from typing import Optional, Dict, Any

from pm4py.util import constants
from pm4py.util import exec_utils
from pm4py.util import xes_constants, pandas_utils




class Parameters(Enum):
    CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY
    ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
    INDEX_KEY = "index_key"
    INDEX_IN_TRACE_KEY = "index_in_trace_key"
    USE_EXTREMES_TIMESTAMP = "use_extremes_timestamp"
    TEMP_COLUMN = "temp_column"
    FIRST_OR_LAST = "first_or_last"
    STRICT = "strict"





def apply(
    df: pd.DataFrame,
    activity: str,
    parameters: Optional[Dict[Any, Any]] = None,
):
    """
    Filter all the prefixes to a given activity (first or last occurrence of the activity in the case).

    Parameters
    ----------------
    df
        Dataframe
    parameters
        Parameters of the algorithm:
        - Parameters.CASE_ID_KEY => the case identifier column.
        - Parameters.ACTIVITY_KEY => the activity column.
        - Parameters.INDEX_IN_TRACE_KEY => attribute that should act as container of the index of the event inside
                                            the case.
        - Parameters.TEMP_COLUMN => temporary column which is used for internal purposes.
        - Parameters.FIRST_OR_LAST => filter on the first or last occurrence of an activity in the dataframe.
        - Parameters.STRICT => applies the filter in a strict (<) or lean (<=) way (boolean).

    Returns
    ----------------
    df
        Dataframe filtered keeping the prefixes to a given activity (first or last occurrence of the activity in the case).
    """
    if parameters is None:
        parameters = {}

    case_id_key = exec_utils.get_param_value(
        Parameters.CASE_ID_KEY, parameters, constants.CASE_CONCEPT_NAME
    )
    activity_key = exec_utils.get_param_value(
        Parameters.ACTIVITY_KEY, parameters, xes_constants.DEFAULT_NAME_KEY
    )
    index_in_trace_key = exec_utils.get_param_value(
        Parameters.INDEX_IN_TRACE_KEY,
        parameters,
        constants.DEFAULT_INDEX_IN_TRACE_KEY,
    )
    temp_column = exec_utils.get_param_value(
        Parameters.TEMP_COLUMN, parameters, "@@temp_column"
    )
    first_or_last = exec_utils.get_param_value(
        Parameters.FIRST_OR_LAST, parameters, "first"
    )
    strict = exec_utils.get_param_value(Parameters.STRICT, parameters, True)

    if index_in_trace_key not in df.columns:
        df = pandas_utils.insert_ev_in_tr_index(
            df, column_name=index_in_trace_key, case_id=case_id_key
        )

    position_activity = df[df[activity_key] == activity].groupby(case_id_key)
    if first_or_last == "first":
        position_activity = position_activity.first()
    elif first_or_last == "last":
        position_activity = position_activity.last()
    position_activity = position_activity.reset_index()[
        [case_id_key, index_in_trace_key]
    ].to_dict("records")
    position_activity = {
        x[case_id_key]: x[index_in_trace_key] for x in position_activity
    }

    df[temp_column] = df[case_id_key].map(position_activity)
    if strict:
        df = df[df[index_in_trace_key] < df[temp_column]]
    else:
        df = df[df[index_in_trace_key] <= df[temp_column]]

    return df