def get_mvp_visualization(self):
parameters = {}
parameters["format"] = "svg"
parameters["min_act_count"] = self.selected_min_acti_count
parameters["min_dfg_occurrences"] = self.selected_min_edge_freq_count
if self.selected_model_type == "mvp_performance":
parameters["performance"] = True
else:
parameters["performance"] = False
model = mvp_discovery.apply(self.exploded_dataframe, parameters=parameters)
gviz = mvp_vis_factory.apply(model, parameters=parameters)
tfilepath = tempfile.NamedTemporaryFile(suffix='.svg')
tfilepath.close()
mvp_vis_factory.save(gviz, tfilepath.name)
self.model_view = base64.b64encode(open(tfilepath.name, "rb").read()).decode('utf-8')
from pm4pymdl.objects.mdl.importer import importer as mdl_importer
from pm4pymdl.algo.mvp.discovery import algorithm as mvp_disc_factory
from pm4pymdl.visualization.mvp import visualizer as mvp_vis_factory
df = mdl_importer.apply("../example_logs/mdl/order_management.mdl")
model = mvp_disc_factory.apply(df)
gviz = mvp_vis_factory.apply(model, parameters={"format": "svg"})
mvp_vis_factory.view(gviz)
mapping["WRX"] = "Account determination for GR/IR clearing account"
mapping["GBB"] = "Offsetting entry for inventory posting"
mapping["MB1B"] = "Enter Transfer Posting"
df["event_activity"] = df["event_activity"].apply(lambda x: mapping[x])
from pm4pymdl.objects.mdl.exporter import exporter as mdl_exporter
mdl_exporter.apply(df, "bkpf_bseg.mdl")
#print(df["event_activity"].unique())
#input()
#print(df)
model = mvp_disc_factory.apply(df,
parameters={
"min_dfg_occurrences": 3,
"performance": False,
"decreasing_factor_sa_ea": 0.0,
"dependency_thresh": 0.3,
"perspectives": ["belnr", "xblnr", "hkont"]
})
gviz = mvp_vis_factory.apply(model, parameters={"format": "svg"})
mvp_vis_factory.save(gviz, "bkpf_caseid_frequency.svg")
model = mvp_disc_factory.apply(df,
parameters={
"min_dfg_occurrences": 3,
"performance": True,
"decreasing_factor_sa_ea": 0.0,
"dependency_thresh": 0.3,
"perspectives": ["belnr", "xblnr", "hkont"]
})