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

Submodules

pm4py.algo.discovery.inductive.variants.im.data_structures.subtree_plain module

class pm4py.algo.discovery.inductive.variants.im.data_structures.subtree_plain.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'
class pm4py.algo.discovery.inductive.variants.im.data_structures.subtree_plain.SubtreePlain(log, dfg, master_dfg, initial_dfg, activities, counts, rec_depth, noise_threshold=0, start_activities=None, end_activities=None, initial_start_activities=None, initial_end_activities=None, parameters=None, real_init=True)[source]

Bases: object

apply_fall_through(parameters=None)[source]
check_for_cut(test_log, deleted_activity=None, parameters=None)[source]
contains_empty_trace()[source]
create_dfg(parameters=None)[source]
detect_concurrent()[source]
detect_cut(second_iteration=False, parameters=None)[source]
detect_loop()[source]
detect_xor(conn_components)[source]

Detects xor cut :Parameters: * conn_components – Connected components

  • this_nx_graph – NX graph calculated on the DFG

  • strongly_connected_components – Strongly connected components

find_set_with_x(x, list_of_sets)[source]
get_index_of_x_in_list(x, li)[source]
initialize_tree(dfg, log, initial_dfg, activities, second_iteration=False, end_call=True, parameters=None)[source]

Initialize the tree

Parameters
  • dfg – Directly follows graph of this subtree

  • log – the event log

  • initial_dfg – Referral directly follows graph that should be taken in account adding hidden/loop transitions

  • activities – Activities of this subtree

  • second_iteration – Boolean that indicates if we are executing this method for the second time

is_followed_by(dfg, activity_a, activity_b)[source]

check if Activity A is followed by Activity B in the dfg of self, returns bool.

pm4py.algo.discovery.inductive.variants.im.data_structures.subtree_plain.make_tree(log, dfg, master_dfg, initial_dfg, activities, c, recursion_depth, noise_threshold, start_activities, end_activities, initial_start_activities, initial_end_activities, parameters=None)[source]

Module contents