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#!/usr/bin/env python3
from dfatool.automata import PTA
from dfatool.codegen import get_simulated_accountingmethod
import unittest
example_json_1 = {
"parameters": ["datarate", "txbytes", "txpower"],
"initial_param_values": [None, None, None],
"state": {
"IDLE": {"power": {"type": "static", "value": 5}},
"TX": {
"power": {
"type": "analytic",
"value": 100,
"functionStr": "regression_arg(0) + regression_arg(1) * parameter(txpower)",
"parameterNames": ["datarate", "txbytes", "txpower"],
"argCount": 0,
"regressionModel": [100, 2],
}
},
},
"transitions": [
{
"name": "init",
"origin": ["UNINITIALIZED", "IDLE"],
"destination": "IDLE",
"duration": {"type": "static", "value": 50000},
"set_param": {"txpower": 10},
},
{
"name": "setTxPower",
"origin": "IDLE",
"destination": "IDLE",
"duration": {"type": "static", "value": 120},
"energy ": {"type": "static", "value": 10000},
"arg_to_param_map": {0: "txpower"},
"argument_values": [[10, 20, 30]],
},
{
"name": "send",
"origin": "IDLE",
"destination": "TX",
"duration": {
"type": "analytic",
"value": 10,
"functionStr": "regression_arg(0) + regression_arg(1)"
" * function_arg(1)",
"parameterNames": ["datarate", "txbytes", "txpower"],
"argCount": 0,
"regressionModel": [48, 8],
},
"energy": {
"type": "analytic",
"value": 3,
"functionStr": "regression_arg(0) + regression_arg(1)"
" * function_arg(1)",
"parameterNames": ["datarate", "txbytes", "txpower"],
"argCount": 0,
"regressionModel": [3, 5],
},
"arg_to_param_map": {1: "txbytes"},
"argument_values": [['"foo"', '"hodor"'], [3, 5]],
"argument_combination": "zip",
},
{
"name": "txComplete",
"origin": "TX",
"destination": "IDLE",
"is_interrupt": 1,
"timeout": {
"type": "analytic",
"value": 2000,
"functionStr": "regression_arg(0) + regression_arg(1)"
" * parameter(txbytes)",
"parameterNames": ["datarate", "txbytes", "txpower"],
"argCount": 0,
"regressionModel": [500, 16],
},
},
],
}
class TestCG(unittest.TestCase):
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_statetransition(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")(
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)
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_state(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")(
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)
cg = get_simulated_accountingmethod("static_state")(
pta, 1000000, "uint8_t", "uint16_t", "uint16_t", "uint16_t"
)
if __name__ == "__main__":
unittest.main()
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