def analyze_simulation_outputs(path):
golden_output, fault_outputs = load_outputs([path])
golden_output = golden_output[0]
fault_outputs = fault_outputs[0]
global_faults_count = 0
global_nans_count = 0
global_zeros_count = 0
global_diff = np.zeros((0))
global_bit_classes = {}
for fault_output in fault_outputs:
faults_count, nans_count, zeros_count, diff, bit_classes = count_faults(golden_output, fault_output)
global_faults_count += faults_count
global_nans_count += nans_count
global_zeros_count += zeros_count
global_diff = np.concatenate((global_diff, diff))
for bit_class_key, bit_class_count in bit_classes.items():
if bit_class_key not in global_bit_classes:
global_bit_classes[bit_class_key] = 0
global_bit_classes[bit_class_key] += bit_class_count
return global_faults_count, global_nans_count, global_zeros_count, global_diff, global_bit_classes
def main():
paths = get_data_paths()
counters = {}
diffs = {}
nans = {}
for path in paths:
golden_output, fault_outputs = load_outputs([path])
golden_output = golden_output[0]
fault_outputs = fault_outputs[0]
for fault_output in fault_outputs:
faults, nan, values_diff = count_faults(golden_output, fault_output)
if faults not in counters:
counters[int(faults)] = 0
counters[int(faults)] += faults
if faults not in nans:
nans[int(faults)] = 0
nans[int(faults)] += nan
if faults not in diffs:
diffs[int(faults)] = np.zeros((0))
diffs[int(faults)] = np.concatenate((diffs[faults], values_diff))
dd = np.zeros((0))
for faults in sorted(counters.keys()):
nan_p = nans[faults] / counters[faults]
print("Faults: {}".format(faults))
print("NaN percentage: {:.5f}".format(nan_p))
print("Min value: {:.5f}".format(diffs[faults].min()))
print("Max value: {:.5f}".format(diffs[faults].max()))
stat, p = shapiro(diffs[faults])
print("Gaussian test (Saphiro-Wilk): {}".format(True if p > 0.05 else False))
stat, p = normaltest(diffs[faults])
print("Gaussian test (D'agostino): {}".format(True if p > 0.05 else False))
print("\n")
dd = np.concatenate((diffs[faults], dd))
#np.save("counters", counters)
#np.save("diffs", diffs)
#np.save("nans", nans)
to_json(counters, "counters.json")
to_json(nans, "nans.json")
#to_json(diffs, "diffs.json")
np.save("global_diffs", dd)