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")