pm4py.algo.filtering.pandas.variants package¶

Submodules¶

pm4py.algo.filtering.pandas.variants.variants_filter module¶

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

class pm4py.algo.filtering.pandas.variants.variants_filter.Parameters[source]¶

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'¶

CASE_ID_KEY = 'pm4py:param:case_id_key'¶

DECREASING_FACTOR = 'decreasingFactor'¶

POSITIVE = 'positive'¶

pm4py.algo.filtering.pandas.variants.variants_filter.apply(df: pandas.core.frame.DataFrame, admitted_variants: List[List[str]], parameters: Optional[Dict[Union[str, pm4py.algo.filtering.pandas.variants.variants_filter.Parameters], Any]] = None) → pandas.core.frame.DataFrame[source]¶

Apply a filter on variants

Parameters:	df – Dataframe admitted_variants – List of admitted variants (to include/exclude) parameters – Parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Column that contains the Case ID Parameters.ACTIVITY_KEY -> Column that contains the activity Parameters.POSITIVE -> Specifies if the filter should be applied including traces (positive=True) or excluding traces (positive=False) variants_df -> If provided, avoid recalculation of the variants dataframe
Returns:	Filtered dataframe
Return type:	df

pm4py.algo.filtering.pandas.variants.variants_filter.apply_auto_filter(df, parameters=None)[source]¶

Apply an automatic filter on variants

Parameters:	df – Dataframe parameters – Parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Column that contains the Case ID Parameters.ACTIVITY_KEY -> Column that contains the activity variants_df -> If provided, avoid recalculation of the variants dataframe Parameters.DECREASING_FACTOR -> Decreasing factor that should be passed to the algorithm
Returns:	Filtered dataframe
Return type:	df

Deprecated since version 2.2.11: This will be removed in 3.0.0. Removed

pm4py.algo.filtering.pandas.variants.variants_filter.filter_variants_by_coverage_percentage(log, min_coverage_percentage, parameters=None)[source]¶

Filters the variants of the log by a coverage percentage (e.g., if min_coverage_percentage=0.4, and we have a log with 1000 cases, of which 500 of the variant 1, 400 of the variant 2, and 100 of the variant 3, the filter keeps only the traces of variant 1 and variant 2).

Parameters:	log – Event log min_coverage_percentage – Minimum allowed percentage of coverage parameters – Parameters
Returns:	Filtered log
Return type:	filtered_log

pm4py.algo.filtering.pandas.variants.variants_filter.filter_variants_top_k(log, k, parameters=None)[source]¶

Keeps the top-k variants of the log

Parameters:	log – Event log k – Number of variants that should be kept parameters – Parameters
Returns:	Filtered log
Return type:	filtered_log

Module contents¶

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.