diff options
Diffstat (limited to 'lib/lennart/DataProcessor.py')
| -rw-r--r-- | lib/lennart/DataProcessor.py | 57 |
1 files changed, 27 insertions, 30 deletions
diff --git a/lib/lennart/DataProcessor.py b/lib/lennart/DataProcessor.py index 27005b1..44fef0a 100644 --- a/lib/lennart/DataProcessor.py +++ b/lib/lennart/DataProcessor.py @@ -51,11 +51,12 @@ class DataProcessor: sync_start = 0 outliers = 0 pre_outliers_ts = None + # TODO only consider the first few and the last few seconds for sync points for i, energytrace_dataset in enumerate(self.energy_data): usedtime = energytrace_dataset[0] - last_data[0] # in microseconds timestamp = energytrace_dataset[0] usedenergy = energytrace_dataset[3] - last_data[3] - power = usedenergy / usedtime * 10 ** -3 # in watts + power = usedenergy / usedtime * 1e-3 # in watts if power > 0: if power > self.power_sync_watt: if sync_start is None: @@ -81,7 +82,7 @@ class DataProcessor: last_data = energytrace_dataset - self.plot_data_x.append(energytrace_dataset[0] / 1_000_000) + self.plot_data_x.append(timestamp / 1_000_000) self.plot_data_y.append(power) if power > self.power_sync_watt: @@ -90,8 +91,11 @@ class DataProcessor: (sync_start / 1_000_000, pre_outliers_ts / 1_000_000) ) - logger.debug(f"Synchronization areas: {datasync_timestamps}") - # print(time_stamp_data[2]) + # print(datasync_timestamps) + + # time_stamp_data contains an entry for each level change on the Logic Analyzer input. + # So, time_stamp_data[0] is the first low-to-high transition, time_stamp_data[2] the second, etc. + # -> time_stamp_data[-8] is the low-to-high transition indicating the first after-measurement sync pulse start_offset = datasync_timestamps[0][1] - time_stamp_data[2] start_timestamp = datasync_timestamps[0][1] @@ -99,7 +103,10 @@ class DataProcessor: end_offset = datasync_timestamps[-2][0] - (time_stamp_data[-8] + start_offset) end_timestamp = datasync_timestamps[-2][0] logger.debug( - f"Measurement area: LA timestamp range [{start_timestamp}, {end_timestamp}]" + f"Measurement area: ET timestamp range [{start_timestamp}, {end_timestamp}]" + ) + logger.debug( + f"Measurement area: LA timestamp range [{time_stamp_data[2]}, {time_stamp_data[-8]}]" ) logger.debug(f"Start/End offsets: {start_offset} / {end_offset}") @@ -108,7 +115,7 @@ class DataProcessor: f"synchronization end_offset == {end_offset}. It should be no more than a few seconds." ) - with_offset = self.addOffset(time_stamp_data, start_offset) + with_offset = np.array(time_stamp_data) + start_offset with_drift = self.addDrift( with_offset, end_timestamp, end_offset, start_timestamp @@ -116,20 +123,6 @@ class DataProcessor: self.modified_timestamps = with_drift - def addOffset(self, input_timestamps, start_offset): - """ - Add begin offset at start - - :param input_timestamps: List of timestamps (float list) - :param start_offset: Timestamp of last EnergyTrace datapoint at the first sync point - :return: List of modified timestamps (float list) - """ - modified_timestamps_with_offset = [] - for x in input_timestamps: - if x + start_offset >= 0: - modified_timestamps_with_offset.append(x + start_offset) - return modified_timestamps_with_offset - def removeTooFarDatasets(self, input_timestamps): """ Removing datasets, that are to far away at ethe end @@ -151,20 +144,22 @@ class DataProcessor: Add drift to datapoints :param input_timestamps: List of timestamps (float list) - :param end_timestamp: Timestamp of first EnergyTrace datapoint at the second last sync point + :param end_timestamp: Timestamp of first EnergyTrace datapoint at the second-to-last sync point :param end_offset: the time between end_timestamp and the timestamp of synchronisation signal :param start_timestamp: Timestamp of last EnergyTrace datapoint at the first sync point :return: List of modified timestamps (float list) """ endFactor = (end_timestamp + end_offset - start_timestamp) / ( end_timestamp - start_timestamp - ) - modified_timestamps_with_drift = [] - for x in input_timestamps: - modified_timestamps_with_drift.append( - ((x - start_timestamp) * endFactor) + start_timestamp - ) - + ) + 0.0001 + # print( + # f"({end_timestamp} + {end_offset} - {start_timestamp}) / ({end_timestamp} - {start_timestamp}) == {endFactor}" + # ) + # Manuelles endFactor += 0.0001 macht es merklich besser + # print(f"endFactor = {endFactor}") + modified_timestamps_with_drift = ( + (input_timestamps - start_timestamp) * endFactor + ) + start_timestamp return modified_timestamps_with_drift def plot(self, annotateData=None): @@ -345,11 +340,12 @@ class DataProcessor: "isa": "state", "W_mean": np.mean(power), "W_std": np.std(power), - "uW": power * 1e6, "s": ( start_transition_ts_timing - end_transition_ts_timing ), # * 10 ** 6, } + if with_traces: + state["uW"] = power * 1e6 energy_trace_new.append(state) energy_trace_new[-2]["W_mean_delta_next"] = ( @@ -369,12 +365,13 @@ class DataProcessor: "isa": "transition", "W_mean": np.mean(power), "W_std": np.std(power), - "uW": power * 1e6, "s": ( end_transition_ts_timing - start_transition_ts_timing ), # * 10 ** 6, "count_dp": len(power), } + if with_traces: + transition["uW"] = power * 1e6 if (end_transition_ts - start_transition_ts) * 10 ** 6 > 2_000_000: # TODO Last data set corrupted? HOT FIX!!!!!!!!!!!! REMOVE LATER |