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"] })