diff options
Diffstat (limited to 'lib')
| -rwxr-xr-x | lib/dfatool.py | 170 |
1 files changed, 151 insertions, 19 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index 7d6d5c9..6498176 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -361,6 +361,7 @@ def _preprocess_measurement(measurement): 'first_trig' : trigidx[0] * 10, 'calibration' : caldata, 'trace' : mim.analyze_states(charges, trigidx, vcalfunc), + 'expected_trace' : measurement['expected_trace'], 'has_mimosa_error' : mim.is_error, 'mimosa_errors' : mim.errors, } @@ -599,6 +600,21 @@ class RawData: Example: `[ {"id": 1, "trace": [ {"parameter": {...}, "isa": "state", "name": "UNINITIALIZED"}, ...] }, ... ] * At least one `*.mim` file. Each file corresponds to a single execution of the entire benchmark (i.e., all runs described in DriverLog.json) and starts with a MIMOSA Autocal calibration sequence. MIMOSA files are parsed by the `MIMOSA` class. + + Version 1: + + * `ptalog.json`: measurement setup and traces. Contents: + `.opt.sleep`: state duration + `.opt.pta`: PTA + `.opt.traces`: list of sub-benchmark traces (the benchmark may have been split due to code size limitations). Each item is a list of traces as returned by `harness.traces`: + `.opt.traces[]`: List of traces. Each trace has an 'id' (numeric, starting with 1) and 'trace' (list of states and transitions) element. + Each state/transition must have the members '`parameter` (dict with normalized parameter values), `.isa` ("state" or "transition") and `.name` + Each transition must additionally contain `.args` + `.opt.files`: list of coresponding MIMOSA measurements. + `.opt.files[]` = ['abc123.mim'] + `.opt.configs`: .... + + tbd """ self.filenames = filenames.copy() self.traces_by_fileno = [] @@ -607,6 +623,12 @@ class RawData: self.preprocessed = False self._parameter_names = None + with tarfile.open(filenames[0]) as tf: + for member in tf.getmembers(): + if member.name == 'ptalog.json': + self.version = 1 + break + def _state_is_too_short(self, online, offline, state_duration, next_transition): # We cannot control when an interrupt causes a state to be left if next_transition['plan']['level'] == 'epilogue': @@ -624,14 +646,48 @@ class RawData: # state_duration is stored as ms, not us return offline['us'] > state_duration * 1500 - def _measurement_is_valid(self, processed_data): + def _measurement_is_valid_01(self, processed_data, repeat = 0): + """ + Check if a dfatool v0 or v1 measurement is valid. + + processed_data layout: + 'fileno' : measurement['fileno'], + 'info' : measurement['info'], + 'triggers' : len(trigidx), + 'first_trig' : trigidx[0] * 10, + 'calibration' : caldata, + 'trace' : mim.analyze_states(charges, trigidx, vcalfunc) + 'expected_trace' : trace from PTA DFS (with parameter data) + mim.analyze_states returns a list of (alternating) states and transitions. + Each element is a dict containing: + - isa: 'state' oder 'transition' + - clip_rate: range(0..1) Anteil an Clipping im Energieverbrauch + - raw_mean: Mittelwert der Rohwerte + - raw_std: Standardabweichung der Rohwerte + - uW_mean: Mittelwert der (kalibrierten) Leistungsaufnahme + - uW_std: Standardabweichung der (kalibrierten) Leistungsaufnahme + - us: Dauer + + Nur falls isa == 'transition': + - timeout: Dauer des vorherigen Zustands + - uW_mean_delta_prev: Differenz zwischen uW_mean und uW_mean des vorherigen Zustands + - uW_mean_delta_next: Differenz zwischen uW_mean und uW_mean des Folgezustands + """ setup = self.setup_by_fileno[processed_data['fileno']] - traces = self.traces_by_fileno[processed_data['fileno']] + traces = processed_data['expected_trace'] state_duration = setup['state_duration'] + + # Check MIMOSA error + if processed_data['has_mimosa_error']: + processed_data['error'] = '; '.join(processed_data['mimosa_errors']) + return False + # Check trigger count sched_trigger_count = 0 for run in traces: sched_trigger_count += len(run['trace']) + if repeat: + sched_trigger_count *= repeat if sched_trigger_count != processed_data['triggers']: processed_data['error'] = 'got {got:d} trigger edges, expected {exp:d}'.format( got = processed_data['triggers'], @@ -654,7 +710,7 @@ class RawData: self._parameter_names = sorted(online_trace_part['parameter'].keys()) if sorted(online_trace_part['parameter'].keys()) != self._parameter_names: - processed_data['error'] = 'Offline #{off_idx:d} (online {on_name:s} @ {on_idx:d}/{on_sub:d}) has inconsistent paramete set: should be {param_want:s}, is {param_is:s}'.format( + processed_data['error'] = 'Offline #{off_idx:d} (online {on_name:s} @ {on_idx:d}/{on_sub:d}) has inconsistent parameter set: should be {param_want:s}, is {param_is:s}'.format( off_idx = offline_idx, on_idx = online_run_idx, on_sub = online_trace_part_idx, on_name = online_trace_part['name'], @@ -683,7 +739,7 @@ class RawData: return False - if online_trace_part['isa'] == 'state' and online_trace_part['name'] != 'UNINITIALIZED': + if online_trace_part['isa'] == 'state' and online_trace_part['name'] != 'UNINITIALIZED' and len(traces[online_run_idx]['trace']) > online_trace_part_idx+1: online_prev_transition = traces[online_run_idx]['trace'][online_trace_part_idx-1] online_next_transition = traces[online_run_idx]['trace'][online_trace_part_idx+1] try: @@ -706,9 +762,9 @@ class RawData: # TODO es gibt next_transitions ohne 'plan' return True - def _merge_measurement_into_online_data(self, measurement): + def _merge_online_and_offline(self, measurement): online_datapoints = [] - traces = self.traces_by_fileno[measurement['fileno']] + traces = measurement['expected_trace'].copy() for run_idx, run in enumerate(traces): for trace_part_idx in range(len(run['trace'])): online_datapoints.append((run_idx, trace_part_idx)) @@ -767,14 +823,16 @@ class RawData: offline_trace_part['uW_mean_delta_next'] * (offline_trace_part['us'] - 20)) online_trace_part['offline_aggregates']['timeout'].append( offline_trace_part['timeout']) + return traces - def _concatenate_analyzed_traces(self): - self.traces = [] - for trace in self.traces_by_fileno: - self.traces.extend(trace) - for i, trace in enumerate(self.traces): + def _concatenate_traces(self, list_of_traces): + trace_output = list() + for trace in list_of_traces: + trace_output.extend(trace.copy()) + for i, trace in enumerate(trace_output): trace['orig_id'] = trace['id'] trace['id'] = i + return trace_output def get_preprocessed_data(self, verbose = True): """ @@ -833,6 +891,8 @@ class RawData: return self.traces if self.version == 0: self._preprocess_0() + elif self.version == 1: + self._preprocess_1() self.preprocessed = True return self.traces @@ -851,15 +911,20 @@ class RawData: 'fileno' : i, 'info' : member, 'setup' : self.setup_by_fileno[i], - 'traces' : self.traces_by_fileno[i], + 'expected_trace' : self.traces_by_fileno[i], }) with Pool() as pool: measurements = pool.map(_preprocess_measurement, mim_files) num_valid = 0 + valid_traces = list() for measurement in measurements: - if self._measurement_is_valid(measurement): - self._merge_measurement_into_online_data(measurement) + + # Strip the last state (it is not part of the scheduled measurement) + measurement['trace'].pop() + + if self._measurement_is_valid_01(measurement): + valid_traces.append(self._merge_online_and_offline(measurement)) num_valid += 1 else: vprint(self.verbose, '[W] Skipping {ar:s}/{m:s}: {e:s}'.format( @@ -869,7 +934,62 @@ class RawData: vprint(self.verbose, '[I] {num_valid:d}/{num_total:d} measurements are valid'.format( num_valid = num_valid, num_total = len(measurements))) - self._concatenate_analyzed_traces() + self.traces = self._concatenate_traces(valid_traces) + self.preprocessing_stats = { + 'num_runs' : len(measurements), + 'num_valid' : num_valid + } + + def _preprocess_1(self): + """Load raw MIMOSA data.""" + mim_files = list() + for i, filename in enumerate(self.filenames): + traces_by_file = list() + mim_files_by_file = list() + with tarfile.open(filename) as tf: + for member in tf.getmembers(): + _, extension = os.path.splitext(member.name) + if extension == '.mim': + mim_files_by_file.append({ + 'content' : tf.extractfile(member).read(), + 'info' : member, + }) + elif extension == '.json': + ptalog = json.load(tf.extractfile(member)) + traces_by_file.extend(ptalog['traces']) + self.traces_by_fileno.append(self._concatenate_traces(traces_by_file)) + self.setup_by_fileno.append({ + 'mimosa_voltage' : ptalog['configs'][0]['voltage'], + 'mimosa_shunt' : ptalog['configs'][0]['shunt'], + 'state_duration' : ptalog['opt']['sleep'] + }) + for j, mim_file in enumerate(mim_files_by_file): + mim_file['setup'] = self.setup_by_fileno[i] + mim_file['expected_trace'] = ptalog['traces'][j] + mim_file['fileno'] = i + mim_files.extend(mim_files_by_file) + + with Pool() as pool: + measurements = pool.map(_preprocess_measurement, mim_files) + + num_valid = 0 + valid_traces = list() + for measurement in measurements: + # The first online measurement is the UNINITIALIZED state. In v1, + # it is not part of the expected PTA trace -> remove it. + measurement['trace'].pop(0) + if self._measurement_is_valid_01(measurement, ptalog['opt']['repeat']): + valid_traces.append(self._merge_online_and_offline(measurement)) + num_valid += 1 + else: + vprint(self.verbose, '[W] Skipping {ar:s}/{m:s}: {e:s}'.format( + ar = self.filenames[measurement['fileno']], + m = measurement['info'].name, + e = measurement['error'])) + vprint(self.verbose, '[I] {num_valid:d}/{num_total:d} measurements are valid'.format( + num_valid = num_valid, + num_total = len(measurements))) + self.traces = self._concatenate_traces(valid_traces) self.preprocessing_stats = { 'num_runs' : len(measurements), 'num_valid' : num_valid @@ -1892,7 +2012,7 @@ class MIMOSA: return charges, triggers - def load_data(self, raw_data, first_is_state = True): + def load_data(self, raw_data): u""" Load MIMOSA log data from a MIMOSA log file passed as raw byte string @@ -1900,7 +2020,6 @@ class MIMOSA: :returns: (numpy array of charges (pJ per 10µs), numpy array of triggers (0/1 int, per 10µs)) """ - self.first_is_state = first_is_state with io.BytesIO(raw_data) as data_object: with tarfile.open(fileobj = data_object) as tf: return self._load_tf(tf) @@ -1948,6 +2067,13 @@ class MIMOSA: self.is_error = True self.errors.append('Unable to find start of first transition (log starts with trigger == {} != 0)'.format(prevtrig)) + # if the last trigger is high (i.e., trigger/buzzer pin is active when the benchmark ends), + # it terminated in the middle of a transition -- meaning that it was not + # measured in its entirety. + if triggers[-1] != 0: + self.is_error = True + self.errors.append('Log ends during a transition'.format(prevtrig)) + # the device is reset for MIMOSA calibration in the first 10s and may # send bogus interrupts -> bogus triggers for i in range(1000000, triggers.shape[0]): @@ -2124,7 +2250,7 @@ class MIMOSA: :param trigidx: "charges" indexes corresponding to a trigger edge, see `trigger_edges` :param ua_func: charge(pJ) -> current(µA) function as returned by `calibration_function` - :returns: list of states and transitions, starting with a state and ending with a transition. + :returns: list of states and transitions, both starting andending with a state. Each element is a dict containing: * `isa`: 'state' or 'transition' * `clip_rate`: range(0..1) Anteil an Clipping im Energieverbrauch @@ -2141,7 +2267,13 @@ class MIMOSA: previdx = 0 is_state = True iterdata = [] - for idx in trigidx: + + # The last state (between the last transition and end of file) may also + # be important. Pretend it ends when the log ends. + trigger_indices = trigidx.copy() + trigger_indices.append(len(charges)) + + for idx in trigger_indices: range_raw = charges[previdx:idx] range_ua = ua_func(range_raw) substates = {} |