pm4py.algo.discovery.inductive.variants.im.util package

Submodules

pm4py.algo.discovery.inductive.variants.im.util.base_case module

pm4py.algo.discovery.inductive.variants.im.util.base_case.empty_log(log)[source]

Returns bool if log is empty

pm4py.algo.discovery.inductive.variants.im.util.base_case.single_activity(log, activity_key)[source]

Returns bool if log consists of single activity only

pm4py.algo.discovery.inductive.variants.im.util.constants module

pm4py.algo.discovery.inductive.variants.im.util.fall_through module

pm4py.algo.discovery.inductive.variants.im.util.fall_through.act_once_per_trace(l, activities, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.activity_concurrent(self, l, activities, activity_key, parameters=None)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.empty_trace(l)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.filter_activity_from_log(l, act, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.filter_activity_use_idx(l, act, activity_key, idx)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.index_containing(l, activities, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.show_nice_log(old_log)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.split_before_start(trace, start_activities, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.split_between_end_and_start(trace, start_activities, end_activities, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.strict_tau_loop(l, start_activities, end_activities, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.fall_through.tau_loop(l, start_activities, activity_key)[source]

pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain module

class pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain.Parameters(value)[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
CASE_ID_KEY = 'case_id_glue'
CONCURRENT_KEY = 'concurrent'
EMPTY_TRACE_KEY = 'empty_trace'
NOISE_THRESHOLD = 'noiseThreshold'
ONCE_PER_TRACE_KEY = 'once_per_trace'
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'
STRICT_TAU_LOOP_KEY = 'strict_tau_loop'
TAU_LOOP_KEY = 'tau_loop'
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain.check_loop_need(spec_tree_struct)[source]

Check whether a forced loop transitions shall be added

Parameters

spec_tree_struct – Internal tree structure (after application of Inductive Miner)

Returns

Checks if the loop on the subtree is needed

Return type

need_loop_on_subtree

pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain.get_new_hidden_trans()[source]

Create a hidden node (transition) in the process tree

pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain.get_repr(spec_tree_struct, rec_depth, contains_empty_traces=False)[source]

Get the representation of a process tree

Parameters
  • spec_tree_struct – Internal tree structure (after application of Inductive Miner)

  • rec_depth – Current recursion depth

  • contains_empty_traces – Boolean value that is True if the event log from which the DFG has been extracted contains empty traces

Returns

Representation of the tree (could be printed, transformed, viewed)

Return type

final_tree_repr

pm4py.algo.discovery.inductive.variants.im.util.get_tree_repr_implain.get_transition(label)[source]

Create a node (transition) with the specified label in the process tree

pm4py.algo.discovery.inductive.variants.im.util.splitting module

pm4py.algo.discovery.inductive.variants.im.util.splitting.split_loop(cut, l, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.splitting.split_parallel(cut, l, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.splitting.split_sequence(cut, l, activity_key)[source]
pm4py.algo.discovery.inductive.variants.im.util.splitting.split_xor(cut, l, activity_key)[source]

Module contents