diff options
Diffstat (limited to 'lib')
| -rwxr-xr-x | lib/automata.py | 54 | ||||
| -rwxr-xr-x | lib/dfatool.py | 3 |
2 files changed, 54 insertions, 3 deletions
diff --git a/lib/automata.py b/lib/automata.py index 5779fe1..a947a61 100755 --- a/lib/automata.py +++ b/lib/automata.py @@ -10,6 +10,17 @@ def _parse_function(input_function): def _dict_to_list(input_dict): return [input_dict[x] for x in sorted(input_dict.keys())] +def _attribute_to_json(static_value, param_function): + ret = { + 'static' : static_value + } + if param_function: + ret['function'] = { + 'raw' : param_function._model_str, + 'regression_args' : list(param_function._regression_args) + } + return ret + class Transition: def __init__(self, orig_state, dest_state, name, energy = 0, energy_function = None, @@ -19,8 +30,8 @@ class Transition: arguments = [], param_update_function = None, arg_to_param_map = None, set_param = None): self.name = name - self.origin = orig_state - self.destination = dest_state + self.origin = orig_state.name + self.destination = dest_state.name self.energy = energy self.energy_function = energy_function self.duration = duration @@ -60,6 +71,21 @@ class Transition: ret[k] = v return ret + def to_json(self): + ret = { + 'name' : self.name, + 'origin' : self.origin, + 'destination' : self.destination, + 'is_interrupt' : self.is_interrupt, + 'arguments' : self.arguments, + 'arg_to_param_map' : self.arg_to_param_map, + 'set_param' : self.set_param, + 'duration' : _attribute_to_json(self.duration, self.duration_function), + 'energy' : _attribute_to_json(self.energy, self.energy_function), + 'timeout' : _attribute_to_json(self.timeout, self.timeout_function), + } + return ret + class State: def __init__(self, name, power = 0, power_function = None): self.name = name @@ -100,6 +126,13 @@ class State: new_suffix.extend(suffix) yield new_suffix + def to_json(self): + ret = { + 'name' : self.name, + 'power' : _attribute_to_json(self.power, self.power_function) + } + return ret + def _json_function_to_analytic_function(base, attribute, parameters): if attribute in base and 'function' in base[attribute]: base = base[attribute]['function'] @@ -158,6 +191,15 @@ class PTA: return pta + def to_json(self): + ret = { + 'parameters' : self.parameters, + 'initial_param_values' : self.initial_param_values, + 'states' : dict([[state.name, state.to_json()] for state in self.states.values()]), + 'transitions' : [trans.to_json() for trans in self.transitions] + } + return ret + def add_state(self, state_name, **kwargs): if 'power_function' in kwargs and type(kwargs['power_function']) != AnalyticFunction: kwargs['power_function'] = AnalyticFunction(kwargs['power_function'], @@ -205,3 +247,11 @@ class PTA: state = transition.destination return total_energy, total_duration, state, param_dict + + def update(self, static_model, param_model): + for state in self.states.values(): + if state.name != 'UNINITIALIZED': + state.power = static_model(state.name, 'power') + if param_model(state.name, 'power'): + state.power_function = param_model(state.name, 'power')['function'] + print(state.name, state.power, state.power_function.__dict__) diff --git a/lib/dfatool.py b/lib/dfatool.py index e2c0cb8..705902a 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -907,9 +907,10 @@ class EnergyModel: return model_getter, info_getter def to_json(self): + static_model = self.get_static() _, param_info = self.get_fitted() pta = PTA.from_json(self.hwmodel) - pta.update(param_info) + pta.update(static_model, param_info) return pta.to_json() def states(self): |