def test_generate_network_evolution_condition():
t_start = time.time()
T = 100
# gpath = os.path.abspath(os.path.dirname(os.getcwd()) + os.path.sep + '.') + os.sep + ''
gpath = networkEvolutionObjectModel.test()
evol = generate_network_evolution_condition(gpath, T)
t_end = time.time()
print(t_end - t_start)
evol.to_excel('e.xlsx')
return evol
def test_generate_failure_state_single_component_single_failuremode():
T = 100
g = networkEvolutionObjectModel.test()
ndf = g.graph["node_info"]
fdf = g.graph["fail_info"]
ndf = pd.merge(ndf, fdf, on="Type")
ndf = ndf.rename(columns={'NodeID': "ID"})
T, cdf = read_data(g, T)
x = cdf.iloc[0]
return generate_failure_state_single_component_single_failuremode(
x, T, ndf)
def test_single_componet_multi_failmode_multitimes():
T = 10000
N = 10
g = networkEvolutionObjectModel.test()
T, cdf = read_data(g, T)
mtbf_df = pd.DataFrame(columns=list(range(N)))
component_df = cdf[['ID', 'Type', 'MTBF', 'MTTR']]
for i in range(N):
test_component_info = generate_failure_state_multi_component_single_failuremode(
cdf, T)
temp = test_component_info.apply(lambda x: test_MTBF(x, T), axis=1)
mtbf_df[i] = temp
component_df['MTBF_CAL'] = mtbf_df.apply(np.mean, axis=1)
print(component_df)
def test_read_data():
g = networkEvolutionObjectModel.test()
t, cdf = read_data(g, 10)
print(t)
print(cdf)
def test_update_application_to_components():
g = networkEvolutionObjectModel.test()
cdf = update_application_to_components(g)
return cdf
def test_network_evolutin_rules_analysis_for_evolution_condition():
g = networkEvolutionObjectModel.test()
evol = pd.DataFrame()
network_evolutin_rules_analysis_for_evolution_condition(g, evol_input=evol)