diff options
| -rwxr-xr-x | lib/automata.py | 11 | ||||
| -rw-r--r-- | lib/functions.py | 14 | ||||
| -rw-r--r-- | lib/parameters.py | 9 |
3 files changed, 20 insertions, 14 deletions
diff --git a/lib/automata.py b/lib/automata.py index 5849daa..c59f47a 100755 --- a/lib/automata.py +++ b/lib/automata.py @@ -1108,6 +1108,7 @@ class PTA: for i in range(len(self.parameters)) ] ) + param_list = dict_to_list(param_dict) for function in trace: if isinstance(function[0], Transition): function_name = function[0].name @@ -1120,7 +1121,7 @@ class PTA: total_energy += state.get_energy(duration, param_dict) if state.power.value_error is not None: total_energy_error += ( - duration * state.power.eval_mae(param_dict, function_args) + duration * state.power.eval_mae(param_list + function_args) ) ** 2 total_duration += duration # assumption: sleep is near-exact and does not contribute to the duration error @@ -1128,17 +1129,15 @@ class PTA: accounting.sleep(duration) else: transition = state.get_transition(function_name) - total_duration += transition.duration.eval( - dict_to_list(param_dict) + function_args - ) + total_duration += transition.duration.eval(param_list + function_args) if transition.duration.value_error is not None: total_duration_mae += ( - transition.duration.eval_mae(param_dict, function_args) ** 2 + transition.duration.eval_mae(param_list + function_args) ** 2 ) total_energy += transition.get_energy(param_dict, function_args) if transition.energy.value_error is not None: total_energy_error += ( - transition.energy.eval_mae(param_dict, function_args) ** 2 + transition.energy.eval_mae(param_list + function_args) ** 2 ) param_dict = transition.get_params_after_transition( param_dict, function_args diff --git a/lib/functions.py b/lib/functions.py index df74903..da9ad48 100644 --- a/lib/functions.py +++ b/lib/functions.py @@ -168,10 +168,10 @@ class ModelFunction: def is_predictable(self, param_list): raise NotImplementedError - def eval(self, param_list, arg_list): + def eval(self, param_list): raise NotImplementedError - def eval_mae(self, param_list, arg_list): + def eval_mae(self, param_list): if self.is_predictable(param_list): return self.function_error["mae"] return self.value_error["mae"] @@ -231,7 +231,7 @@ class StaticFunction(ModelFunction): """ return True - def eval(self, param_list=None, arg_list=None): + def eval(self, param_list=None): """ Evaluate model function with specified param/arg values. @@ -275,9 +275,9 @@ class SplitFunction(ModelFunction): return False return self.child[param_value].is_predictable(param_list) - def eval(self, param_list, arg_list=list()): + def eval(self, param_list): param_value = param_list[self.param_index] - return self.child[param_value].eval(param_list, arg_list) + return self.child[param_value].eval(param_list) def to_json(self): ret = super().to_json() @@ -485,7 +485,7 @@ class AnalyticFunction(ModelFunction): return False return True - def eval(self, param_list, arg_list=[]): + def eval(self, param_list): """ Evaluate model function with specified param/arg values. @@ -493,8 +493,6 @@ class AnalyticFunction(ModelFunction): corresponds to lexically first parameter, etc. :param arg_list: argument values (list of float), if arguments are used. """ - if len(self.model_args) == 0: - return self._function(param_list, arg_list) return self._function(self.model_args, param_list) def to_json(self): diff --git a/lib/parameters.py b/lib/parameters.py index aedb6cd..5fd44c3 100644 --- a/lib/parameters.py +++ b/lib/parameters.py @@ -567,6 +567,15 @@ class ParamStats: class ModelAttribute: + """ + A ModelAttribute instance handles a single model attribute, e.g. TX state power or something() function call duration, and corresponding benchmark data. + + It provides three models: + - a static model (`mean`, `median`) as lower bound of model accuracy + - a LUT model (`by_param`) as upper bound of model accuracy + - a fitted model (`model_function`, a `ModelFunction` instance) + """ + def __init__(self, name, attr, data, param_values, param_names, arg_count=0): # Data for model generation |