pm4py.algo.discovery.log_skeleton.variants package

Submodules

pm4py.algo.discovery.log_skeleton.variants.classic module

class pm4py.algo.discovery.log_skeleton.variants.classic.Outputs(value)[source]

Bases: enum.Enum

An enumeration.

ACTIV_FREQ = 'activ_freq'
ALWAYS_AFTER = 'always_after'
ALWAYS_BEFORE = 'always_before'
DIRECTLY_FOLLOWS = 'directly_follows'
EQUIVALENCE = 'equivalence'
NEVER_TOGETHER = 'never_together'
class pm4py.algo.discovery.log_skeleton.variants.classic.Parameters(value)[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
CASE_ID_KEY = 'case_id_glue'
CONSIDERED_CONSTRAINTS = 'considered_constraints'
DEFAULT_CONSIDERED_CONSTRAINTS = ['equivalence', 'always_after', 'always_before', 'never_together', 'directly_follows', 'activ_freq']
NOISE_THRESHOLD = 'noise_threshold'
PARAMETER_VARIANT_DELIMITER = 'variant_delimiter'
pm4py.algo.discovery.log_skeleton.variants.classic.activ_freq(logs_traces, all_activs, len_log, noise_threshold=0)[source]

Gets the allowed activities frequencies given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • len_log – Length of the log

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.always_after(logs_traces, all_activs, noise_threshold=0)[source]

Gets the always-after relations given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.always_before(logs_traces, all_activs, noise_threshold=0)[source]

Gets the always-before relations given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.apply(log, parameters=None)[source]

Discover a log skeleton from an event log

Parameters
  • log – Event log

  • parameters

    Parameters of the algorithm, including:
    • the activity key (Parameters.ACTIVITY_KEY)

    • the noise threshold (Parameters.NOISE_THRESHOLD)

Returns

Log skeleton model

Return type

model

pm4py.algo.discovery.log_skeleton.variants.classic.apply_from_variants_list(var_list, parameters=None)[source]

Discovers the log skeleton from the variants list

Parameters
  • var_list – Variants list

  • parameters – Parameters

Returns

Log skeleton model

Return type

model

pm4py.algo.discovery.log_skeleton.variants.classic.directly_follows(logs_traces, all_activs, noise_threshold=0)[source]

Gets the allowed directly-follows relations given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.equivalence(logs_traces, all_activs, noise_threshold=0)[source]

Gets the equivalence relations given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.never_together(logs_traces, all_activs, len_log, noise_threshold=0)[source]

Gets the never-together relations given the traces of the log

Parameters
  • logs_traces – Traces of the log

  • all_activs – All the activities

  • len_log – Length of the log

  • noise_threshold – Noise threshold

Returns

List of relations in the log

Return type

rel

pm4py.algo.discovery.log_skeleton.variants.classic.prepare_encode(log_skeleton)[source]

Prepares the log skeleton for encoding

Parameters

log_skeleton – Log skeleton

Returns

Log skeleton (with lists instead of sets)

Return type

log_skeleton

Module contents