def get_im_tree_from_variants(self, parameters=None):
variants = {
x["variant"]: x["count"]
for x in self.get_variants(parameters=parameters)["variants"]
}
tree = inductive_miner.apply_tree_variants(variants,
parameters=parameters)
return tree
def get_im_tree_from_variants(self, parameters=None):
if parameters is None:
parameters = {}
parameters["window_size"] = 1000000000000
variants = {x["variant"]: x["count"] for x in self.get_variants(parameters=parameters)["variants"]}
tree = inductive_miner.apply_tree_variants(variants, parameters=parameters)
return tree
def test_df_tree_variants_dfg_based(self):
df = pd.read_csv(os.path.join("input_data", "running-example.csv"))
df = dataframe_utils.convert_timestamp_columns_in_df(df)
tree = inductive_miner.apply_tree_variants(
pd_variants.get_variants_set(df),
variant=inductive_miner.DFG_BASED)
def test_log_tree_variants_dfg_based(self):
log = xes_importer.apply(
os.path.join("input_data", "running-example.xes"))
tree = inductive_miner.apply_tree_variants(
log_variants.get_variants(log), variant=inductive_miner.DFG_BASED)
log, parameters={"pm4py:param:activity_key": CLASSIFIER})
elif "parquet" in log_name:
from pm4py.statistics.attributes.pandas import get as attributes_get_pandas
dataframe = pd.read_parquet(log_path)
activities = set(
attributes_get_pandas.get_attribute_values(
dataframe, CLASSIFIER).keys())
variants = pm4py.get_variants(dataframe)
fp_log = pm4py.algo.discovery.footprints.log.variants.entire_dataframe.apply(
dataframe)
print("start tree_im_clean")
tree_im_clean = im_clean.apply_tree(
log, parameters={"pm4py:param:activity_key": CLASSIFIER})
print("end tree_im_clean")
tree_im = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IM,
parameters={"pm4py:param:activity_key": CLASSIFIER})
print(tree_im_clean)
print(tree_im)
tree_imf = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IMf,
parameters={"pm4py:param:activity_key": CLASSIFIER})
tree_imd = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IMd,
parameters={"pm4py:param:activity_key": CLASSIFIER})
fp_tree_clean = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
tree_im_clean)
fp_tree_im = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
tree_im)
dataframe, CLASSIFIER).keys())
variants = pm4py.get_variants_as_tuples(dataframe)
variants = {",".join(x): y for x, y in variants.items()}
fp_log = pm4py.algo.discovery.footprints.log.variants.entire_dataframe.apply(
dataframe)
print("start tree_im_clean")
tree_im_clean = im_clean.apply_tree(log,
parameters={
"pm4py:param:activity_key":
CLASSIFIER,
"noise_threshold":
NOISE_THRESHOLD
})
print("end tree_im_clean")
tree_im = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IM,
parameters={"pm4py:param:activity_key": CLASSIFIER})
print(tree_im_clean)
print(tree_im)
tree_imf = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IMf,
parameters={
"pm4py:param:activity_key": CLASSIFIER,
"noiseThreshold": NOISE_THRESHOLD
})
tree_imd = inductive_miner.apply_tree_variants(
variants,
variant=inductive_miner.Variants.IMd,
parameters={"pm4py:param:activity_key": CLASSIFIER})
fp_tree_clean = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
for log_name in os.listdir(LOGS_FOLDER):
if "xes" in log_name or "parquet" in log_name:
log_path = os.path.join(LOGS_FOLDER, log_name)
print("")
print(log_path)
if "xes" in log_name:
log = pm4py.read_xes(log_path)
variants = pm4py.get_variants(log)
fp_log = pm4py.algo.discovery.footprints.log.variants.entire_event_log.apply(
log)
elif "parquet" in log_name:
dataframe = pd.read_parquet(log_path)
variants = pm4py.get_variants(dataframe)
fp_log = pm4py.algo.discovery.footprints.log.variants.entire_dataframe.apply(
dataframe)
tree_im = inductive_miner.apply_tree_variants(
variants, variant=inductive_miner.Variants.IM)
tree_imf = inductive_miner.apply_tree_variants(
variants, variant=inductive_miner.Variants.IMf)
tree_imd = inductive_miner.apply_tree_variants(
variants, variant=inductive_miner.Variants.IMd)
fp_tree_im = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
tree_im)
fp_tree_imf = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
tree_imf)
fp_tree_imd = pm4py.algo.discovery.footprints.tree.variants.bottomup.apply(
tree_imd)
fp_conf_im = pm4py.algo.conformance.footprints.variants.log_extensive.apply(
fp_log, fp_tree_im)
fp_conf_imf = pm4py.algo.conformance.footprints.variants.log_extensive.apply(
fp_log, fp_tree_imf)
fp_conf_imd = pm4py.algo.conformance.footprints.variants.log_extensive.apply(