NeSy4PPM.Data_preprocessing package

Submodules

NeSy4PPM.Data_preprocessing.data_preprocessing module

NeSy4PPM.Data_preprocessing.data_preprocessing.encode_prefixes(log_data: LogData, prefixes, encoder: Encodings = Encodings.Index_based, resource: bool = False) tuple
NeSy4PPM.Data_preprocessing.data_preprocessing.end_to_end_process(log_path: Path, log_name=None, train_ratio=0.8, train_log=None, test_log=None, case_name_key='case:concept:name', act_name_key='concept:name', res_name_key='org:resource', timestamp_key='time:timestamp', encoder: Encodings = Encodings.Index_based, resource: bool = False)
NeSy4PPM.Data_preprocessing.data_preprocessing.extract_encode_prefixes(log_data: LogData, encoder: Encodings = Encodings.Index_based, resource: bool = False)
NeSy4PPM.Data_preprocessing.data_preprocessing.extract_trace_prefixes(log_data: LogData, resource: bool = False)

Extract activity and resource sequences starting from a list of trace ids (i.e. trace_names).

NeSy4PPM.Data_preprocessing.log_utils module

class NeSy4PPM.Data_preprocessing.log_utils.LogData(log_path: Path, log_name=None, train_ratio=0.8, train_log=None, test_log=None, case_name_key='case:concept:name', act_name_key='concept:name', res_name_key='org:resource', timestamp_key='time:timestamp')

Bases: object

act_enc_mapping: {<class 'str'>}
act_name_key: str
case_name_key: str
compliance_th: float
encode_log(resource: bool, ascii_offset=161)
evaluation_prefix_end: int
evaluation_prefix_start: int
evaluation_th: float
evaluation_trace_ids = [<class 'str'>]
label_name_key: str
label_neg_val: str
label_pos_val: str
log: DataFrame
log_name: str
max_len: int
read_log(log_path, log_name)
res_enc_mapping: {<class 'str'>}
res_name_key: str
test_log_name: str
timestamp_key: str
timestamp_key2: str
timestamp_key3: str
timestamp_key4: str
train_log_name: str
training_trace_ids = [<class 'str'>]

NeSy4PPM.Data_preprocessing.shared_variables module

This file was created in order to bring common variables and functions into one file to make code more clear

NeSy4PPM.Data_preprocessing.utils module

class NeSy4PPM.Data_preprocessing.utils.BK_type(value)

Bases: Enum

An enumeration.

Declare = '(MP)Declare'
Declare_End = 'Declare_At_end'
ProbDeclare = 'ProbDeclare'
Procedural = 'Procedural'
Procedural_End = 'Procedural_At_end'
class NeSy4PPM.Data_preprocessing.utils.Encodings(value)

Bases: Enum

An enumeration.

Index_based = 'index-based'
Multi_encoders = 'multi-encoders'
One_hot = 'one-hot'
Shrinked_based = 'shrinked index-based'
class NeSy4PPM.Data_preprocessing.utils.NN_model(value)

Bases: Enum

An enumeration.

LSTM = 'LSTM'
Transformer = 'keras_trans'
NeSy4PPM.Data_preprocessing.utils.discover_Petri_nets(log_data: LogData, pn_folder: Path = WindowsPath('C:/Users/JOukharijane/Desktop/PostDoc/NeSy4PPM/docs/source/data/input/petrinets'))
NeSy4PPM.Data_preprocessing.utils.extract_last_model_checkpoint(log_name: str, models_folder: str, model_type: str, ckeckpoint_folder=WindowsPath('C:/Users/JOukharijane/Desktop/PostDoc/NeSy4PPM/docs/source/data/output')) Path
NeSy4PPM.Data_preprocessing.utils.load_bk(BK_file: Path)
NeSy4PPM.Data_preprocessing.utils.prepare_encoded_data(log_data: LogData, resource: bool)

Get all possible symbols for activities and resources and annotate them with integers.

Module contents