diff options
| -rwxr-xr-x | bin/eval-online-model-accuracy.py | 2 | ||||
| -rwxr-xr-x | lib/automata.py | 9 | ||||
| -rw-r--r-- | lib/harness.py | 2 |
3 files changed, 9 insertions, 4 deletions
diff --git a/bin/eval-online-model-accuracy.py b/bin/eval-online-model-accuracy.py index 49157e5..b4c137e 100755 --- a/bin/eval-online-model-accuracy.py +++ b/bin/eval-online-model-accuracy.py @@ -164,7 +164,7 @@ if __name__ == '__main__': real_durations = list() model_energies = list() # duration in µs - # Bei kurzer Dauer (z.B. nur [1e2]) performt auc uint32_t für Energie gut, sonst nicht so (weil overflow) + # Bei kurzer Dauer (z.B. nur [1e2]) performt auch uint32_t für Energie gut, sonst nicht so (weil overflow) for sleep_duration in [1e2, 1e3, 1e4, 1e5, 1e6]: runs = pta.dfs(opt['depth'], with_arguments=True, with_parameters=True, trace_filter=opt['trace-filter'], sleep=sleep_duration) for run in runs: diff --git a/lib/automata.py b/lib/automata.py index d36acd7..a80796c 100755 --- a/lib/automata.py +++ b/lib/automata.py @@ -575,6 +575,8 @@ class PTA: kwargs['is_interrupt'] = transition['is_interrupt'] if 'return_value' in transition: kwargs['return_value_handlers'] = transition['return_value'] + if 'codegen' in transition: + kwargs['codegen'] = transition['codegen'] if 'loop' in transition: for state_name in transition['loop']: pta.add_transition(state_name, state_name, trans_name, @@ -784,7 +786,7 @@ class PTA: ret.append((transition, arguments, param)) yield ret - def bfs(self, depth: int = 10, orig_state: str = 'UNINITIALIZED', transition_filter=None, state_filter=None): + def bfs(self, depth: int = 10, orig_state: str = 'UNINITIALIZED', param_dict: dict = None, with_parameters: bool = False, transition_filter=None, state_filter=None): """ Return a generator object for breadth-first search of traces starting at orig_state. @@ -804,6 +806,9 @@ class PTA: :param orig_state: initial state for breadth-first search :param depth: search depth, default 10 + :param param_dict: initial parameter values + :param with_arguments: perform dfs with argument values + :param with_parameters: include parameters in trace? :param transition_filter: If set, only follow a transition if transition_filter(transition object) returns true. Default None. :param state_iflter: If set, only follow a state if state_filter(state_object) returns true. Default None. """ @@ -935,4 +940,4 @@ class PTA: transition.timeout_function = param_model(transition.name, 'timeout')['function'] except KeyError: print('[W] skipping model update of transition {} due to missing data'.format(state.name)) - pass
\ No newline at end of file + pass diff --git a/lib/harness.py b/lib/harness.py index 7a336e5..59b5fa0 100644 --- a/lib/harness.py +++ b/lib/harness.py @@ -330,7 +330,7 @@ class OnboardTimerHarness(TransitionHarness): log_data_target['parameter'][parameter_name].append(parameter_value) def parser_cb(self, line): - #print('[HARNESS] got line {}'.format(line)) + # print('[HARNESS] got line {}'.format(line)) res = re.match(r'\[PTA\] nop=(\S+)/(\S+)', line) if res: self.nop_cycles = int(res.group(1)) |