def test_pandas(self): # to avoid static method warnings in tests, # that by construction of the unittest package have to be expressed in such way self.dummy_variable = "dummy_value" log = csv_import_adapter.import_dataframe_from_path( os.path.join("..", "tests", "input_data", "running-example.csv")) hw_values = sna_factory.apply(log, variant="handover") wt_values = sna_factory.apply(log, variant="working_together") sub_values = sna_factory.apply(log, variant="subcontracting")
def test_1(self): # to avoid static method warnings in tests, # that by construction of the unittest package have to be expressed in such way self.dummy_variable = "dummy_value" log = xes_importer.apply( os.path.join("..", "tests", "input_data", "running-example.xes")) hw_values = sna_factory.apply(log, variant="handover") wt_values = sna_factory.apply(log, variant="working_together") sub_values = sna_factory.apply(log, variant="subcontracting") ja_values = sna_factory.apply(log, variant="jointactivities")
def apply(log, variant="handover", parameters=None): """ Gets the Social Network according to the specified metric and arc threshold Parameters ------------- log Log variant Variant of the algorithm to use parameters Possible parameters of the algorithm (arc threshold) Returns ------------- sna Social Network representation """ if parameters is None: parameters = {} parameters["metric_normalization"] = True metric = sna_factory.apply(log, variant=variant, parameters=parameters) pyvis_repr = sna_vis_factory.apply(metric, variant="pyvis", parameters=parameters) return open(pyvis_repr).read()
def execute_script(): log = xes_importer.apply( os.path.join("..", "tests", "input_data", "running-example.xes")) hw_values = sna_factory.apply(log, variant="handover") wt_values = sna_factory.apply(log, variant="working_together") sub_values = sna_factory.apply(log, variant="subcontracting") ja_values = sna_factory.apply(log, variant="jointactivities") gviz_sub = pn_vis_factory.apply(sub_values, variant="networkx", parameters={"format": "svg"}) gviz_hw = pn_vis_factory.apply(hw_values, variant="pyvis") gviz_wt = pn_vis_factory.apply(wt_values, variant="networkx", parameters={"format": "svg"}) gviz_ja = pn_vis_factory.apply(ja_values, variant="pyvis") pn_vis_factory.view(gviz_sub, variant="networkx") pn_vis_factory.view(gviz_hw, variant="pyvis") pn_vis_factory.view(gviz_wt, variant="networkx") pn_vis_factory.view(gviz_ja, variant="pyvis")
def work_handover(): try: print( "Kindly enter the name of your formatted file\n" "Note: please include .csv file extension and make sure that input file has no blank rows or columns" ) filename = str(input()) dataframe = csv_import_adapter.import_dataframe_from_path(filename, sep=",") from pm4py.objects.conversion.log import factory as conversion_factory # lib to convert csv to xes log = conversion_factory.apply(dataframe) from pm4py.algo.enhancement.sna import factory as sna_factory hw_values = sna_factory.apply(log, variant="handover") from pm4py.visualization.sna import factory as sna_vis_factory gviz_hw_py = sna_vis_factory.apply(hw_values, variant="pyvis") sna_vis_factory.view(gviz_hw_py, variant="pyvis") except FileNotFoundError: print("Please check your file name")