diff options
| -rwxr-xr-x | lib/dfatool.py | 88 |
1 files changed, 86 insertions, 2 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index 8f2e9e6..43e5c9e 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -521,6 +521,86 @@ class ParamStats: else: return self.arg_dependence_ratio(state_or_trans, attribute, arg_index) > 0.5 +class TimingData: + """ + Loader for timing model traces measured with on-board timers. + + Excpets a specific trace format and UART log output (as produced by + generate-dfa-benchmark.py). Prunes states from output. (TODO) + """ + + def __init__(self, filenames): + """ + Create a new TimingData object. + + Each filenames element corresponds to a measurement run. + """ + self.filenames = filenames.copy() + self.traces_by_fileno = [] + self.setup_by_fileno = [] + self.preprocessed = False + self._parameter_names = None + self.version = 0 + + def _concatenate_analyzed_traces(self): + self.traces = [] + for trace_group in self.traces_by_fileno: + for trace in trace_group: + # TimingHarness logs states, but does not aggregate any data for them at the moment -> throw all states away + transitions = list(filter(lambda x: x['isa'] == 'transition', trace['trace'])) + self.traces.append({ + 'id' : trace['id'], + 'trace': transitions, + }) + for i, trace in enumerate(self.traces): + trace['orig_id'] = trace['id'] + trace['id'] = i + for log_entry in trace['trace']: + paramkeys = sorted(log_entry['parameter'].keys()) + paramvalues = [soft_cast_int(log_entry['parameter'][x]) for x in paramkeys] + if not 'param' in log_entry['offline_aggregates']: + log_entry['offline_aggregates']['param'] = list() + if 'duration' in log_entry['offline_aggregates']: + for i in range(len(log_entry['offline_aggregates']['duration'])): + log_entry['offline_aggregates']['param'].append(paramvalues) + + def _preprocess_0(self): + for filename in self.filenames: + with open(filename, 'r') as f: + log_data = json.load(f) + self.traces_by_fileno.append(log_data['traces']) + self._concatenate_analyzed_traces() + + def get_preprocessed_data(self, verbose = True): + """ + Return a list of DFA traces annotated with timing, and parameter data. + + Suitable for the PTAModel constructor. + See PTAModel(...) docstring for format details. + """ + self.verbose = verbose + if self.preprocessed: + return self.traces + if self.version == 0: + self._preprocess_0() + self.preprocessed = True + return self.traces + +def sanity_check_aggregate(aggregate): + for key in aggregate: + if not 'param' in aggregate[key]: + raise RuntimeError('aggregate[{}][param] does not exist'.format(key)) + if not 'attributes' in aggregate[key]: + raise RuntimeError('aggregate[{}][attributes] does not exist'.format(key)) + for attribute in aggregate[key]['attributes']: + if not attribute in aggregate[key]: + raise RuntimeError('aggregate[{}][{}] does not exist, even though it is contained in aggregate[{}][attributes]'.format(key, attribute, key)) + param_len = len(aggregate[key]['param']) + attr_len = len(aggregate[key][attribute]) + if param_len != attr_len: + raise RuntimeError('parameter mismatch: len(aggregate[{}][param]) == {} != len(aggregate[{}][{}]) == {}'.format(key, param_len, key, attribute, attr_len)) + + class RawData: """ Loader for hardware model traces measured with MIMOSA. @@ -1138,8 +1218,12 @@ def _add_trace_data_to_aggregate(aggregate, key, element): else: # TODO do not hardcode values aggregate[key]['attributes'] = ['duration', 'energy', 'rel_energy_prev', 'rel_energy_next'] - if element['plan']['level'] == 'epilogue': + if 'plan' in element and element['plan']['level'] == 'epilogue': aggregate[key]['attributes'].insert(0, 'timeout') + attributes = aggregate[key]['attributes'].copy() + for attribute in attributes: + if attribute not in element['offline_aggregates']: + aggregate[key]['attributes'].remove(attribute) for datakey, dataval in element['offline_aggregates'].items(): aggregate[key][datakey].extend(dataval) @@ -1251,7 +1335,7 @@ class PTAModel: parameters -- list of parameter names, as returned by pta_trace_to_aggregate arg_count -- function arguments, as returned by pta_trace_to_aggregate traces -- list of preprocessed DFA traces, as returned by RawData.get_preprocessed_data() - ignore_trace_indexes -- list of trace indexes. The corresponding taces will be ignored. + ignore_trace_indexes -- list of trace indexes. The corresponding traces will be ignored. discard_outliers -- currently not supported: threshold for outlier detection and removel (float). Outlier detection is performed individually for each state/transition in each trace, so it only works if the benchmark ran several times. |