diff options
| -rwxr-xr-x | lib/automata.py | 12 |
1 files changed, 12 insertions, 0 deletions
diff --git a/lib/automata.py b/lib/automata.py index 4cd694d..30634ab 100755 --- a/lib/automata.py +++ b/lib/automata.py @@ -2,6 +2,7 @@ from functions import AnalyticFunction, NormalizationFunction import itertools +import numpy as np def _dict_to_list(input_dict: dict) -> list: return [input_dict[x] for x in sorted(input_dict.keys())] @@ -51,6 +52,9 @@ class State: return self.power_function.eval(_dict_to_list(param_dict)) * duration return self.power * duration + def set_random_energy_model(self, static_model = True): + self.power = np.random.sample() * 50000 + def get_transition(self, transition_name: str) -> object: """Return Transition object for outgoing transtion transition_name.""" return self.outgoing_transitions[transition_name] @@ -213,6 +217,9 @@ class Transition: return self.energy_function.eval(_dict_to_list(param_dict), args) return self.energy + def set_random_energy_model(self, static_model = True): + self.energy = np.random.sample() * 50000 + def get_timeout(self, param_dict: dict = {}) -> float: u""" Return transition timeout in µs. @@ -533,6 +540,11 @@ class PTA: def get_initial_param_dict(self): return dict([[self.parameters[i], self.initial_param_values[i]] for i in range(len(self.parameters))]) + def set_random_energy_model(self, static_model = True): + for state in self.state.values(): + state.set_random_energy_model(static_model) + for transition in self.transitions: + transition.set_random_energy_model(static_model) def _dfs_with_param(self, generator, param_dict): for trace in generator: |