diff options
Diffstat (limited to 'lib')
| -rwxr-xr-x | lib/dfatool.py | 19 |
1 files changed, 10 insertions, 9 deletions
diff --git a/lib/dfatool.py b/lib/dfatool.py index 85ba7c9..6c3f322 100755 --- a/lib/dfatool.py +++ b/lib/dfatool.py @@ -101,6 +101,7 @@ def _preprocess_measurement(measurement): processed_data = { 'info' : measurement['info'], + 'setup' : measurement['setup'], 'triggers' : len(trigidx), 'first_trig' : trigidx[0] * 10, 'calibration' : caldata, @@ -115,24 +116,25 @@ class AEMRAnalyzer: self.filename = filename self.version = 0 - def _state_is_too_short(self, online, offline, next_transition): + 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': return False # Note: state_duration is stored as ms, not us - return offline['us'] < self.setup['state_duration'] * 500 + return offline['us'] < state_duration * 500 - def _state_is_too_long(self, online, offline, prev_transition): + def _state_is_too_long(self, online, offline, state_duration, prev_transition): # If the previous state was left by an interrupt, we may have some # waiting time left over. So it's okay if the current state is longer # than expected. if prev_transition['plan']['level'] == 'epilogue': return False # state_duration is stored as ms, not us - return offline['us'] > self.setup['state_duration'] * 1500 + return offline['us'] > state_duration * 1500 def _measurement_is_valid(self, processed_data): + state_duration = processed_data['setup']['state_duration'] # Check trigger count if self.sched_trigger_count != processed_data['triggers']: processed_data['error'] = 'got {got:d} trigger edges, expected {exp:d}'.format( @@ -164,14 +166,14 @@ class AEMRAnalyzer: if online_trace_part['isa'] == 'state' and online_trace_part['name'] != 'UNINITIALIZED': online_prev_transition = self.traces[online_run_idx]['trace'][online_trace_part_idx-1] online_next_transition = self.traces[online_run_idx]['trace'][online_trace_part_idx+1] - if self._state_is_too_short(online_trace_part, offline_trace_part, online_next_transition): + if self._state_is_too_short(online_trace_part, offline_trace_part, state_duration, online_next_transition): processed_data['error'] = 'Offline #{off_idx:d} (online {on_name:s} @ {on_idx:d}/{on_sub:d}) is too short (duration = {dur:d} us)'.format( off_idx = offline_idx, on_idx = online_run_idx, on_sub = online_trace_part_idx, on_name = online_trace_part['name'], dur = offline_trace_part['us']) return False - if self._state_is_too_long(online_trace_part, offline_trace_part, online_prev_transition): + if self._state_is_too_long(online_trace_part, offline_trace_part, state_duration, online_prev_transition): processed_data['error'] = 'Offline #{off_idx:d} (online {on_name:s} @ {on_idx:d}/{on_sub:d}) is too long (duration = {dur:d} us)'.format( off_idx = offline_idx, on_idx = online_run_idx, on_sub = online_trace_part_idx, @@ -203,15 +205,14 @@ class AEMRAnalyzer: # be analyzed. def preprocess_0(self): with tarfile.open(self.filename) as tf: - self.setup = json.load(tf.extractfile('setup.json')) + setup = json.load(tf.extractfile('setup.json')) self.traces = json.load(tf.extractfile('src/apps/DriverEval/DriverLog.json')) - print(self.setup) mim_files = [] for member in tf.getmembers(): _, extension = os.path.splitext(member.name) if extension == '.mim': mim_files.append({ - 'setup' : self.setup, + 'setup' : setup, 'info' : member, 'content' : tf.extractfile(member).read() }) |