pm4py.algo.organizational_mining.roles.common.algorithm module#

class pm4py.algo.organizational_mining.roles.common.algorithm.Parameters(*values)[source]#

Bases: Enum

ROLES_THRESHOLD_PARAMETER = 'roles_threshold_parameter'#
RESOURCE_KEY = 'pm4py:param:resource_key'#
ACTIVITY_KEY = 'pm4py:param:activity_key'#
pm4py.algo.organizational_mining.roles.common.algorithm.get_sum_from_dictio_values(dictio, parameters=None)[source]#

Get the sum of a dictionary values

Parameters:

  • dictio – Dictionary

  • parameters – Parameters of the algorithm

Returns:

Sum of the dictionary values

Return type:

sum_values

pm4py.algo.organizational_mining.roles.common.algorithm.normalize_role(role, parameters=None)[source]#

Normalize a role

Parameters:

  • role – Originators of the role

  • parameters – Parameters of the algorithm

Returns:

Normalized multiset of originators

Return type:

normalized_role

pm4py.algo.organizational_mining.roles.common.algorithm.find_multiset_intersection(role1, role2, normalize=False, parameters=None)[source]#

Finds the intersection of a multiset

Parameters:

  • role1 – First role originators

  • role2 – Second role originators

  • normalize – Do the normalization of the roles

  • parameters – Parameters of the algorithm

Returns:

Intersection of the multiset

Return type:

intersection

pm4py.algo.organizational_mining.roles.common.algorithm.find_multiset_union(role1, role2, normalize=False, parameters=None)[source]#

Finds the union of a multiset

Parameters:

  • role1 – First role originators

  • role2 – Second role originators

  • normalize – Do the normalization of the roles

  • parameters – Parameters of the algorithm

Returns:

Union of the multiset

Return type:

union

pm4py.algo.organizational_mining.roles.common.algorithm.find_role_similarity(roles, i, j, parameters=None)[source]#

Calculate a number of similarity between different roles

Parameters:

  • roles – List of roles

  • i – Index of the first role

  • j – Index of the second role

  • parameters – Parameters of the algorithm

Returns:

Similarity measure

Return type:

similarity

pm4py.algo.organizational_mining.roles.common.algorithm.aggregate_roles_iteration(roles, parameters=None)[source]#

Single iteration of the roles aggregation algorithm

Parameters:

  • roles – Roles

  • parameters – Parameters of the algorithm

Returns:

(Partially aggregated) roles

Return type:

agg_roles

pm4py.algo.organizational_mining.roles.common.algorithm.aggregate_roles_algorithm(roles, parameters=None)[source]#

Algorithm to aggregate similar roles

Parameters:

  • roles – Roles

  • parameters – Parameters of the algorithm

Returns:

(Aggregated) roles

Return type:

agg_roles

pm4py.algo.organizational_mining.roles.common.algorithm.get_initial_roles(res_act_couples, parameters=None)[source]#

Get the initial list of roles (each activity is a stand-alone role)

Parameters:

  • res_act_couples – (resource, activity) couples along with the number of occurrences

  • parameters – Parameters of the algorithm

Returns:

List of roles (set of activities + multiset of resources)

Return type:

roles

pm4py.algo.organizational_mining.roles.common.algorithm.apply(res_act_couples, parameters=None) → List[Role][source]#

Apply the roles detection, introduced by Burattin, Andrea, Alessandro Sperduti, and Marco Veluscek. “Business models enhancement through discovery of roles.” 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2013.

Parameters:

  • res_act_couples – (resource, activity) couples along with the number of occurrences

  • parameters – Parameters of the algorithm

Returns:

List of roles (set of activities + multiset of resources)

Return type:

roles