pm4py.algo.filtering.log.paths package#

PM4Py – A Process Mining Library for Python

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Submodules#

pm4py.algo.filtering.log.paths.paths_filter module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.algo.filtering.log.paths.paths_filter.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'#

DECREASING_FACTOR = 'decreasingFactor'#

POSITIVE = 'positive'#

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#

MIN_PERFORMANCE = 'min_performance'#

MAX_PERFORMANCE = 'max_performance'#

pm4py.algo.filtering.log.paths.paths_filter.apply(log: EventLog, paths: List[Tuple[str, str]], parameters: Dict[str | Parameters, Any] | None = None) → EventLog[source]#

Apply a filter on traces containing / not containing a path

Parameters#

log

Log

paths

Paths that we are looking for (expressed as tuple of 2 strings)

parameters

Parameters of the algorithm, including:: Parameters.ATTRIBUTE_KEY -> Attribute identifying the activity in the log Parameters.POSITIVE -> Indicate if events should be kept/removed

Returns#

filtered_log: Filtered log

pm4py.algo.filtering.log.paths.paths_filter.apply_performance(log: EventLog, provided_path: Tuple[str, str], parameters: Dict[str | Parameters, Any] | None = None) → EventLog[source]#

Filters the cases of an event log where there is at least one occurrence of the provided path occurring in the defined timedelta range.

Parameters#

log

Event log

provided_path

Path between two activities (expressed as tuple)

parameters

Parameters of the filter, including:: Parameters.ATTRIBUTE_KEY -> Attribute identifying the activity in the log Parameters.TIMESTAMP_KEY -> Attribute identifying the timestamp in the log Parameters.POSITIVE -> Indicate if events should be kept/removed Parameters.MIN_PERFORMANCE -> Minimal allowed performance of the provided path Parameters.MAX_PERFORMANCE -> Maximal allowed performance of the provided path

Returns#

filtered_log: Filtered event log

pm4py.algo.filtering.log.paths.paths_filter.get_paths_from_log(log, attribute_key='concept:name')[source]#

Get the paths of the log along with their count

Parameters#

log: Log
attribute_key: Attribute key (must be specified if different from concept:name)

Returns#

paths: Dictionary of paths associated with their count

pm4py.algo.filtering.log.paths.paths_filter.get_sorted_paths_list(paths)[source]#

Gets sorted paths list

Parameters#

paths: Dictionary of paths associated with their count

Returns#

listpaths: Sorted paths list

pm4py.algo.filtering.log.paths.paths_filter.get_paths_threshold(plist, decreasing_factor)[source]#

Get end attributes cutting threshold

Parameters#

plist: List of paths ordered by number of occurrences
decreasing_factor: Decreasing factor of the algorithm

Returns#

threshold: Paths cutting threshold

pm4py.algo.filtering.log.paths.paths_filter.filter_log_by_paths(log, paths, variants, vc, threshold, attribute_key='concept:name')[source]#

Keep only paths which number of occurrences is above the threshold (or they belong to the first variant)

Parameters#

log: Log
paths: Dictionary of paths associated with their count
variants: (If specified) Dictionary with variant as the key and the list of traces as the value
vc: List of variant names along with their count
threshold: Cutting threshold (remove paths which number of occurrences is below the threshold)
attribute_key: (If specified) Specify the attribute key to use (default concept:name)

Returns#

filtered_log: Filtered log