def testNOACMetricForModelWithCrossingPoint(self):
self.assertEqual(
metrics.NOAC_metric(self.models['WITH_CROSSING_POINT']), 7
)
def testNOACMetricForModelWithCycles(self):
self.assertEqual(
metrics.NOAC_metric(self.models['WITH_CYCLES']), 16
)
def testNOACMetricForComplexModel(self):
self.assertEqual(
metrics.NOAC_metric(self.models['COMPLEX']), 21
)
def testNOACMetricForSimpleModel(self):
self.assertEqual(
metrics.NOAC_metric(self.models['SIMPLE']), 8
)
def check_diagrams_metics(diag_a, diag_b, do_print=True):
group = {}
try:
if do_print:
print("\n\tTNSE_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.TNSE_metric(diag_a), metrics.TNSE_metric(diag_b)))
group["TNSE_metric"] = {
"diag_a": metrics.TNSE_metric(diag_a),
"diag_b": metrics.TNSE_metric(diag_b)
}
except:
print("\nCan not calculate TNSE_metric for one or both diagrams")
try:
if do_print:
print("\n\tTNIE_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.TNIE_metric(diag_a), metrics.TNIE_metric(diag_b)))
group["TNIE_metric"] = {
"diag_a": metrics.TNIE_metric(diag_a),
"diag_b": metrics.TNIE_metric(diag_b)
}
except:
print("\nCan not calculate TNIE_metric for one or both diagrams")
try:
if do_print:
print("\n\tTNEE_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.TNEE_metric(diag_a), metrics.TNEE_metric(diag_b)))
group["TNEE_metric"] = {
"diag_a": metrics.TNEE_metric(diag_a),
"diag_b": metrics.TNEE_metric(diag_b)
}
except:
print("\nCan not calculate TNEE_metric for one or both diagrams")
try:
if do_print:
print("\n\tTNE_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.TNE_metric(diag_a), metrics.TNE_metric(diag_b)))
group["TNE_metric"] = {
"diag_a": metrics.TNE_metric(diag_a),
"diag_b": metrics.TNE_metric(diag_b)
}
except:
print("\nCan not calculate TNE_metric for one or both diagrams")
try:
if do_print:
print("\n\tNOA_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.NOA_metric(diag_a), metrics.NOA_metric(diag_b)))
group["NOA_metric"] = {
"diag_a": metrics.NOA_metric(diag_a),
"diag_b": metrics.NOA_metric(diag_b)
}
except:
print("\nCan not calculate NOA_metric for one or both diagrams")
try:
if do_print:
print("\n\tNOAC_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.NOAC_metric(diag_a), metrics.NOAC_metric(diag_b)))
group["NOAC_metric"] = {
"diag_a": metrics.NOAC_metric(diag_a),
"diag_b": metrics.NOAC_metric(diag_b)
}
except:
print("\nCan not calculate NOAC_metric for one or both diagrams")
try:
if do_print:
print("\n\tNOAJS_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.NOAJS_metric(diag_a), metrics.NOAJS_metric(diag_b)))
group["NOAJS_metric"] = {
"diag_a": metrics.NOAJS_metric(diag_a),
"diag_b": metrics.NOAJS_metric(diag_b)
}
except:
print("\nCan not calculate NOAJS_metric for one or both diagrams")
try:
if do_print:
print("\n\tNumberOfNodes_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.NumberOfNodes_metric(diag_a),
metrics.NumberOfNodes_metric(diag_b)))
group["NumberOfNodes_metric"] = {
"diag_a": metrics.NumberOfNodes_metric(diag_a),
"diag_b": metrics.NumberOfNodes_metric(diag_b)
}
except:
print(
"\nCan not calculate NumberOfNodes_metric for one or both diagrams"
)
try:
if do_print:
print("\n\tGatewayHeterogenity_metric: \ndiag_a:{}\ndiag_b:{}".
format(metrics.GatewayHeterogenity_metric(diag_a),
metrics.GatewayHeterogenity_metric(diag_b)))
group["GatewayHeterogenity_metric"] = {
"diag_a": metrics.GatewayHeterogenity_metric(diag_a),
"diag_b": metrics.GatewayHeterogenity_metric(diag_b)
}
except:
print(
"\nCan not calculate GatewayHeterogenity_metric for one or both diagrams"
)
try:
if do_print:
print(
"\n\tCoefficientOfNetworkComplexity_metric: \ndiag_a:{}\ndiag_b:{}"
.format(metrics.CoefficientOfNetworkComplexity_metric(diag_a),
metrics.CoefficientOfNetworkComplexity_metric(diag_b)))
group["CoefficientOfNetworkComplexity_metric"] = {
"diag_a": metrics.CoefficientOfNetworkComplexity_metric(diag_a),
"diag_b": metrics.CoefficientOfNetworkComplexity_metric(diag_b)
}
except:
print(
"\nCan not calculate CoefficientOfNetworkComplexity_metric for one or both diagrams"
)
try:
if do_print:
print("\n\tAverageGatewayDegree_metric: \ndiag_a:{}\ndiag_b:{}".
format(metrics.AverageGatewayDegree_metric(diag_a),
metrics.AverageGatewayDegree_metric(diag_b)))
group["AverageGatewayDegree_metric"] = {
"diag_a": metrics.AverageGatewayDegree_metric(diag_a),
"diag_b": metrics.AverageGatewayDegree_metric(diag_b)
}
except:
print(
"\nCan not calculate AverageGatewayDegree_metric for one or both diagrams"
)
try:
if do_print:
print("\n\tDurfeeSquare_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.DurfeeSquare_metric(diag_a),
metrics.DurfeeSquare_metric(diag_b)))
group["DurfeeSquare_metric"] = {
"diag_a": metrics.DurfeeSquare_metric(diag_a),
"diag_b": metrics.DurfeeSquare_metric(diag_b)
}
except:
print(
"\nCan not calculate DurfeeSquare_metric for one or both diagrams")
try:
if do_print:
print("\n\tPerfectSquare_metric: \ndiag_a:{}\ndiag_b:{}".format(
metrics.PerfectSquare_metric(diag_a),
metrics.PerfectSquare_metric(diag_b)))
group["PerfectSquare_metric"] = {
"diag_a": metrics.PerfectSquare_metric(diag_a),
"diag_b": metrics.PerfectSquare_metric(diag_b)
}
except:
print(
"\nCan not calculate PerfectSquare_metric for one or both diagrams"
)
return group
def test_thesis_models(self):
format_three_dec = "{0:.3f}"
format_two_dec = "{0:.2f}"
names = [
"model1",
"model2",
"model3",
"model4",
"model5",
"model6",
"model7",
"model8",
"model9",
"model10",
"model11",
"model12",
"model13",
"model14",
"model15",
"model16",
"model17",
"model18",
"model19",
"model20",
"model21",
"model22",
"model23",
"model24",
"model25",
"model26",
"model27",
"model28",
"model29",
"model30",
"model31",
"model32"
]
with open("./output/metrics_part1.csv", "w") as file_one:
with open("./output/metrics_part2.csv", "w") as file_two:
with open("./output/metrics_min_max.csv", "w") as file_three:
# write header
file_one.write("Model name,NOA-H,NOA-G,NOA-diff,NOA-prop,NOC-H,NOC-G,NOC-diff,NOC-prop\n")
file_two.write("Model name,CNC-H,CNC-G,CNC-diff,Avg-H,Avg-G,Avg-diff,Heter-H,Heter-G,Heter-diff\n")
counter = 1
noa_max_diff = None
noa_max_diff_index = 0
noa_max_prop = None
noa_max_prop_index = 0
noa_min_diff = None
noa_min_diff_index = 0
noa_min_prop = None
noa_min_prop_index = 0
noa_sum = 0
noc_max_diff = None
noc_max_diff_index = 0
noc_max_prop = None
noc_max_prop_index = 0
noc_min_diff = None
noc_min_diff_index = 0
noc_min_prop = None
noc_min_prop_index = 0
noc_sum = 0
cnc_max = None
cnc_max_diff = None
cnc_max_index = 0
cnc_min = None
cnc_min_diff = None
cnc_min_index = 0
cnc_diff_sum = 0
avg_max_diff = None
avg_max_index = 0
avg_min_diff = None
avg_min_index = 0
avg_diff_sum = 0
heter_max_diff = None
heter_max_index = 0
heter_min_diff = None
heter_min_index = 0
for model_name in names:
print(model_name)
hand_made_bpmn = diagram.BpmnDiagramGraph()
hand_made_bpmn.load_diagram_from_xml_file(self.hand_made_models + model_name + ".bpmn")
hand_made_noa = metrics.NOA_metric(hand_made_bpmn)
hand_made_noc = metrics.NOAC_metric(hand_made_bpmn) - hand_made_noa
hand_made_cnc = metrics.CoefficientOfNetworkComplexity_metric(hand_made_bpmn)
if metrics.all_gateways_count(hand_made_bpmn) > 0:
hand_made_avg = metrics.AverageGatewayDegree_metric(hand_made_bpmn)
else:
hand_made_avg = 0
hand_made_heter = int(metrics.GatewayHeterogenity_metric(hand_made_bpmn))
gen_bpmn = diagram.BpmnDiagramGraph()
gen_bpmn.load_diagram_from_xml_file(self.generated_models + model_name + ".bpmn")
gen_noa = metrics.NOA_metric(gen_bpmn)
gen_noc = metrics.NOAC_metric(gen_bpmn) - gen_noa
gen_cnc = metrics.CoefficientOfNetworkComplexity_metric(gen_bpmn)
if cnc_max is None:
cnc_max = gen_cnc
elif cnc_max < gen_cnc:
cnc_max = gen_cnc
if cnc_min is None:
cnc_min = gen_cnc
elif cnc_min > gen_cnc:
cnc_min = gen_cnc
if metrics.all_gateways_count(gen_bpmn) > 0:
gen_avg = metrics.AverageGatewayDegree_metric(gen_bpmn)
else:
gen_avg = 0
gen_heter = int(metrics.GatewayHeterogenity_metric(gen_bpmn))
noa_diff = hand_made_noa - gen_noa
noa_prop = (noa_diff * 100.0) / hand_made_noa
noa_sum += noa_prop
if noa_max_diff is None:
noa_max_diff = noa_diff
noa_max_diff_index = counter
elif noa_diff > noa_max_diff:
noa_max_diff = noa_diff
noa_max_diff_index = counter
if noa_max_prop is None:
noa_max_prop = noa_diff
noa_max_prop_index = counter
elif noa_prop > noa_max_prop:
noa_max_prop = noa_prop
noa_max_prop_index = counter
if noa_min_diff is None:
noa_min_diff = noa_diff
noa_min_diff_index = counter
elif noa_diff < noa_min_diff:
noa_min_diff = noa_diff
noa_min_diff_index = counter
if noa_min_prop is None:
noa_min_prop = noa_diff
noa_min_prop_index = counter
elif noa_prop < noa_min_prop:
noa_min_prop = noa_prop
noa_min_prop_index = counter
noc_diff = hand_made_noc - gen_noc
noc_prop = (noc_diff * 100.0) / hand_made_noc
noc_sum += noc_prop
if noc_max_diff is None:
noc_max_diff = noc_diff
noc_max_diff_index = counter
elif noc_diff > noc_max_diff:
noc_max_diff = noc_diff
noc_max_diff_index = counter
if noc_max_prop is None:
noc_max_prop = noc_prop
noc_max_prop_index = counter
elif noc_prop > noc_max_prop:
noc_max_prop = noc_prop
noc_max_prop_index = counter
if noc_min_diff is None:
noc_min_diff = noc_diff
noc_min_diff_index = counter
elif noc_diff < noc_min_diff:
noc_min_diff = noc_diff
noc_min_diff_index = counter
if noc_min_prop is None:
noc_min_prop = noc_prop
noc_min_prop_index = counter
elif noc_prop < noc_min_prop:
noc_min_prop = noc_prop
noc_min_prop_index = counter
cnc_diff = hand_made_cnc - gen_cnc
cnc_diff_sum += cnc_diff
if cnc_max_diff is None:
cnc_max_diff = cnc_diff
elif cnc_diff > cnc_max_diff:
cnc_max_diff = cnc_diff
cnc_max_index = counter
if cnc_min_diff is None:
cnc_min_diff = cnc_diff
elif cnc_diff < cnc_min_diff:
cnc_min_diff = cnc_diff
cnc_min_index = counter
avg_diff = hand_made_avg - gen_avg
avg_diff_sum += avg_diff
if avg_max_diff is None:
avg_max_diff = avg_diff
elif avg_diff > avg_max_diff:
avg_max_diff = avg_diff
avg_max_index = counter
if avg_min_diff is None:
avg_min_diff = avg_diff
elif avg_diff < avg_min_diff:
avg_min_diff = avg_diff
avg_min_index = counter
heter_diff = hand_made_heter - gen_heter
if heter_max_diff is None:
heter_max_diff = heter_diff
elif heter_diff > heter_max_diff:
heter_max_diff = heter_diff
heter_max_index = counter
if heter_min_diff is None:
heter_min_diff = heter_diff
elif heter_diff < heter_min_diff:
heter_min_diff = heter_diff
heter_min_index = counter
file_one.write("Model " + str(counter) + "," + str(hand_made_noa) + "," + str(gen_noa) + ","
+ str(noa_diff) + "," + format_two_dec.format(noa_prop) + "\%,"
+ str(hand_made_noc) + "," + str(gen_noc) + "," + str(noc_diff) + ","
+ format_two_dec.format(noc_prop) + "\%\n")
file_two.write("Model " + str(counter) + "," + format_three_dec.format(hand_made_cnc) + ","
+ format_three_dec.format(gen_cnc) + "," + format_three_dec.format(cnc_diff)
+ "," + format_three_dec.format(hand_made_avg) + ","
+ format_three_dec.format(gen_avg) + "," + format_three_dec.format(avg_diff)
+ "," + str(hand_made_heter) + "," + str(gen_heter) + "," + str(heter_diff)
+ "\n")
counter += 1
file_three.write(
"CNC metric: avg=" + format_three_dec.format(cnc_diff_sum / counter)
+ ", min=" + format_three_dec.format(cnc_min_diff)
+ ", model: " + str(cnc_min_index)
+ ", max=" + format_three_dec.format(cnc_max_diff)
+ ", model: " + str(cnc_max_index)
+ ", global min: " + format_three_dec.format(cnc_min)
+ ", global max: " + format_three_dec.format(cnc_max) + "\n")
file_three.write(
"Average Gateway Degree metric: avg=" + format_three_dec.format(avg_diff_sum / counter)
+ ", min=" + format_three_dec.format(avg_min_diff)
+ ", model: " + str(avg_min_index)
+ ", max=" + format_three_dec.format(avg_max_diff)
+ ", model: " + str(avg_max_index) + "\n")
file_three.write(
"Gateway Heterogenity metric: "
+ "min=" + str(heter_min_diff)
+ ", model: " + str(heter_min_index)
+ ", max=" + str(heter_max_diff)
+ ", model: " + str(heter_max_index) + "\n")
file_three.write(
"NOA metric (diff): "
+ "min=" + str(noa_min_diff)
+ ", model: " + str(noa_min_diff_index)
+ ", max=" + str(noa_max_diff)
+ ", model: " + str(noa_max_diff_index) + "\n")
file_three.write(
"NOA metric (prop): "
+ "min=" + format_two_dec.format(noa_min_prop)
+ ", model: " + str(noa_min_prop_index)
+ ", max=" + format_two_dec.format(noa_max_prop)
+ ", model: " + str(noa_max_prop_index)
+ ", average: " + format_two_dec.format(noa_sum / counter) + "\n")
file_three.write(
"NOC metric (diff): "
+ "min=" + str(noc_min_diff)
+ ", model: " + str(noc_min_diff_index)
+ ", max=" + str(noc_max_diff)
+ ", model: " + str(noc_max_diff_index) + "\n")
file_three.write(
"NOC metric (prop): "
+ "min=" + format_two_dec.format(noc_min_prop)
+ ", model: " + str(noc_min_prop_index)
+ ", max=" + format_two_dec.format(noc_max_prop)
+ ", model: " + str(noc_max_prop_index)
+ ", average: " + format_two_dec.format(noc_sum / counter) + "\n")