def test_statetransition_immediate(self):
pta = PTA.from_json(example_json_1)
pta.set_random_energy_model()
pta.state["IDLE"].power.value = 9
cg = get_simulated_accountingmethod(
"static_statetransition_immediate")(pta, 1000000, "uint8_t",
"uint8_t", "uint8_t",
"uint8_t")
cg.current_state = pta.state["IDLE"]
cg.sleep(7)
self.assertEqual(cg.get_energy(), 9 * 7)
pta.transitions[1].energy.value = 123
cg.pass_transition(pta.transitions[1])
self.assertEqual(cg.get_energy(), 9 * 7 + 123)
cg.pass_transition(pta.transitions[1])
self.assertEqual(cg.get_energy(), (9 * 7 + 123 + 123) % 256)
cg = get_simulated_accountingmethod(
"static_statetransition_immediate")(pta, 100000, "uint8_t",
"uint8_t", "uint8_t",
"uint8_t")
cg.current_state = pta.state["IDLE"]
cg.sleep(7)
self.assertEqual(cg.get_energy(), 0)
cg.sleep(15)
self.assertEqual(cg.get_energy(), 90)
cg.sleep(90)
self.assertEqual(cg.get_energy(), 900 % 256)
cg = get_simulated_accountingmethod(
"static_statetransition_immediate")(pta, 100000, "uint8_t",
"uint8_t", "uint8_t",
"uint16_t")
cg.current_state = pta.state["IDLE"]
cg.sleep(7)
self.assertEqual(cg.get_energy(), 0)
cg.sleep(15)
self.assertEqual(cg.get_energy(), 90)
cg.sleep(90)
self.assertEqual(cg.get_energy(), 900)
pta.state["IDLE"].power.value = 9 # -> 90 uW
pta.transitions[1].energy.value = 1 # -> 100 pJ
cg = get_simulated_accountingmethod(
"static_statetransition_immediate")(pta, 1000000, "uint8_t",
"uint8_t", "uint8_t",
"uint8_t", 1e-5, 1e-5, 1e-10)
cg.current_state = pta.state["IDLE"]
cg.sleep(10) # 10 us
self.assertEqual(cg.get_energy(), 90 * 10)
cg.pass_transition(pta.transitions[1])
self.assertAlmostEqual(cg.get_energy(), 90 * 10 + 100, places=0)
cg.pass_transition(pta.transitions[1])
self.assertAlmostEqual(cg.get_energy(), 90 * 10 + 100 + 100, places=0)
def test_from_json(self):
pta = PTA.from_json(example_json_1)
self.assertEqual(pta.parameters, ["datarate", "txbytes", "txpower"])
self.assertEqual(pta.state["UNINITIALIZED"].name, "UNINITIALIZED")
self.assertEqual(pta.state["IDLE"].name, "IDLE")
self.assertEqual(pta.state["TX"].name, "TX")
self.assertEqual(len(pta.transitions), 5)
self.assertEqual(pta.transitions[0].name, "init")
self.assertEqual(pta.transitions[1].name, "init")
self.assertEqual(pta.transitions[2].name, "setTxPower")
self.assertEqual(pta.transitions[3].name, "send")
self.assertEqual(pta.transitions[4].name, "txComplete")
def test_state_immediate(self):
pta = PTA.from_json(example_json_1)
pta.set_random_energy_model()
pta.state["IDLE"].power.value = 9
cg = get_simulated_accountingmethod("static_state_immediate")(
pta, 1000000, "uint8_t", "uint8_t", "uint8_t", "uint8_t")
cg.current_state = pta.state["IDLE"]
cg.sleep(7)
self.assertEqual(cg.get_energy(), 9 * 7)
pta.transitions[1].energy.value = 123
cg.pass_transition(pta.transitions[1])
self.assertEqual(cg.get_energy(), 9 * 7)
cg.pass_transition(pta.transitions[1])
self.assertEqual(cg.get_energy(), 9 * 7)
def test_get_X_expensive_state(self):
pta = PTA.from_json(example_json_1)
self.assertEqual(pta.get_least_expensive_state(), pta.state["IDLE"])
self.assertEqual(pta.get_most_expensive_state(), pta.state["TX"])
# self.assertAlmostEqual(pta.min_duration_until_energy_overflow(), (2**32 - 1) * 1e-12 / 10e-3, places=9)
# self.assertAlmostEqual(pta.min_duration_until_energy_overflow(energy_granularity=1e-9), (2**32 - 1) * 1e-9 / 10e-3, places=9)
self.assertAlmostEqual(
pta.max_duration_until_energy_overflow(),
(2**32 - 1) * 1e-12 / 5e-6,
places=9,
)
self.assertAlmostEqual(
pta.max_duration_until_energy_overflow(energy_granularity=1e-9),
(2**32 - 1) * 1e-9 / 5e-6,
places=9,
)
def test_from_json_dfs_arg(self):
pta = PTA.from_json(example_json_1)
self.assertEqual(
sorted(dfs_tran_to_name(pta.dfs(1), False)),
[["init", "init"], ["init", "send"], ["init", "setTxPower"]],
)
self.assertEqual(
sorted(dfs_tran_to_name(pta.dfs(1, with_arguments=True), True)),
[
[("init", ()), ("init", ())],
[("init", ()), ("send", ('"foo"', 3))],
[("init", ()), ("send", ('"hodor"', 5))],
[("init", ()), ("setTxPower", (10, ))],
[("init", ()), ("setTxPower", (20, ))],
[("init", ()), ("setTxPower", (30, ))],
],
)
def test_from_json_function(self):
pta = PTA.from_json(example_json_1)
self.assertEqual(
pta.state["TX"].get_energy(1000, {
"datarate": 10,
"txbytes": 6,
"txpower": 10
}),
1000 * (10000 + 2 * 10),
)
self.assertEqual(
pta.transitions[4].get_timeout({
"datarate": 10,
"txbytes": 6,
"txpower": 10
}),
500 + 16 * 6,
)
def test_from_json_dfs_param(self):
pta = PTA.from_json(example_json_1)
no_param = {"datarate": None, "txbytes": None, "txpower": 10}
param_tx3 = {"datarate": None, "txbytes": 3, "txpower": 10}
param_tx5 = {"datarate": None, "txbytes": 5, "txpower": 10}
param_txp10 = {"datarate": None, "txbytes": None, "txpower": 10}
param_txp20 = {"datarate": None, "txbytes": None, "txpower": 20}
param_txp30 = {"datarate": None, "txbytes": None, "txpower": 30}
self.assertEqual(
sorted(
dfs_tran_to_name(
pta.dfs(1, with_arguments=True, with_parameters=True),
True, True)),
[
[("init", (), no_param), ("init", (), no_param)],
[("init", (), no_param), ("send", ('"foo"', 3), param_tx3)],
[("init", (), no_param), ("send", ('"hodor"', 5), param_tx5)],
[("init", (), no_param), ("setTxPower", (10, ), param_txp10)],
[("init", (), no_param), ("setTxPower", (20, ), param_txp20)],
[("init", (), no_param), ("setTxPower", (30, ), param_txp30)],
],
)
k, v = kv.split("=")
try:
arg_dict[k] = float(v)
except ValueError:
arg_dict[k] = v
args.with_substates = arg_dict
if args.plot_traces:
plot_traces(preprocessed_data, args.plot_traces)
if raw_data.preprocessing_stats["num_valid"] == 0:
print("No valid data available. Abort.", file=sys.stderr)
sys.exit(2)
if pta is None and raw_data.pta is not None:
pta = PTA.from_json(raw_data.pta)
by_name, parameters, arg_count = pta_trace_to_aggregate(
preprocessed_data, ignored_trace_indexes
)
filter_aggregate_by_param(by_name, parameters, args.filter_param)
if args.param_shift:
param_shift = dfatool.cli.parse_param_shift(args.param_shift)
shift_param_in_aggregate(by_name, parameters, param_shift)
detect_outliers_in_aggregate(
by_name, z_limit=args.z_score, remove_outliers=args.remove_outliers
)
