diff options
Diffstat (limited to 'lib/loader/keysight.py')
| -rw-r--r-- | lib/loader/keysight.py | 155 |
1 files changed, 3 insertions, 152 deletions
diff --git a/lib/loader/keysight.py b/lib/loader/keysight.py index 9f9623a..2243361 100644 --- a/lib/loader/keysight.py +++ b/lib/loader/keysight.py @@ -6,7 +6,7 @@ import numpy as np import struct import xml.etree.ElementTree as ET -from bisect import bisect_right +from dfatool.loader.generic import ExternalTimerSync class KeysightCSV: @@ -49,7 +49,7 @@ class DLogChannel: return f"""<DLogChannel(slot={self.slot}, smu="{self.smu}", unit="{self.unit}", data={self.data})>""" -class DLog: +class DLog(ExternalTimerSync): def __init__( self, voltage: float, @@ -168,156 +168,7 @@ class DLog: self.slots[channel.slot - 1][channel.unit] = channel assert "A" in self.slots[0] - self.data = self.slots[0]["A"].data + self.data = self.slots[0]["A"].data * self.voltage def observed_duration_equals_expectation(self): return int(self.observed_duration) == self.planned_duration - - # very similar to DataProcessor.getStatesdfatool - def analyze_states(self, expected_trace, repeat_id): - sync_start = None - sync_timestamps = list() - above_count = 0 - below_count = 0 - for i, timestamp in enumerate(self.timestamps): - power = self.voltage * self.data[i] - if power > self.sync_power: - above_count += 1 - below_count = 0 - else: - above_count = 0 - below_count += 1 - - if above_count > 2 and sync_start is None: - sync_start = timestamp - elif below_count > 2 and sync_start is not None: - if timestamp - sync_start > self.sync_min_duration: - sync_end = timestamp - sync_timestamps.append((sync_start, sync_end)) - sync_start = None - print(sync_timestamps) - - if len(sync_timestamps) != 3: - self.errors.append( - f"Found {len(sync_timestamps)} synchronization pulses, expected three." - ) - self.errors.append(f"Synchronization pulses == {sync_timestamps}") - return list() - - start_ts = sync_timestamps[0][1] - end_ts = sync_timestamps[1][0] - - # start and end of first state - online_timestamps = [0, expected_trace[0]["start_offset"][repeat_id]] - - # remaining events from the end of the first transition (start of second state) to the end of the last observed state - for trace in expected_trace: - for word in trace["trace"]: - online_timestamps.append( - online_timestamps[-1] - + word["online_aggregates"]["duration"][repeat_id] - ) - - online_timestamps = np.array(online_timestamps) * 1e-6 - online_timestamps = ( - online_timestamps * ((end_ts - start_ts) / online_timestamps[-1]) + start_ts - ) - - trigger_edges = list() - for ts in online_timestamps: - trigger_edges.append(bisect_right(self.timestamps, ts)) - - energy_trace = list() - - for i in range(2, len(online_timestamps), 2): - prev_state_start_index = trigger_edges[i - 2] - prev_state_stop_index = trigger_edges[i - 1] - transition_start_index = trigger_edges[i - 1] - transition_stop_index = trigger_edges[i] - state_start_index = trigger_edges[i] - state_stop_index = trigger_edges[i + 1] - - # If a transition takes less time than the measurement interval, its start and stop index may be the same. - # In this case, self.data[transition_start_index] is the only data point affected by the transition. - # We use the self.data slice [transition_start_index, transition_stop_index) to determine the mean power, so we need - # to increment transition_stop_index by 1 to end at self.data[transition_start_index] - # (self.data[transition_start_index : transition_start_index+1 ] == [self.data[transition_start_index]) - if transition_stop_index == transition_start_index: - transition_stop_index += 1 - - prev_state_duration = online_timestamps[i + 1] - online_timestamps[i] - transition_duration = online_timestamps[i] - online_timestamps[i - 1] - state_duration = online_timestamps[i + 1] - online_timestamps[i] - - # some states are followed by a UART dump of log data. This causes an increase in CPU energy - # consumption and is not part of the peripheral behaviour, so it should not be part of the benchmark results. - # If a case is followed by a UART dump, its duration is longer than the sleep duration between two transitions. - # In this case, we re-calculate the stop index, and calculate the state duration from coarse energytrace data - # instead of high-precision sync data - if ( - self.timestamps[prev_state_stop_index] - - self.timestamps[prev_state_start_index] - > self.state_duration - ): - prev_state_stop_index = bisect_right( - self.timestamps, - self.timestamps[prev_state_start_index] + self.state_duration, - ) - prev_state_duration = ( - self.timestamps[prev_state_stop_index] - - self.timestamps[prev_state_start_index] - ) - - if ( - self.timestamps[state_stop_index] - self.timestamps[state_start_index] - > self.state_duration - ): - state_stop_index = bisect_right( - self.timestamps, - self.timestamps[state_start_index] + self.state_duration, - ) - state_duration = ( - self.timestamps[state_stop_index] - - self.timestamps[state_start_index] - ) - - prev_state_power = self.data[prev_state_start_index:prev_state_stop_index] - - transition_timestamps = self.timestamps[ - transition_start_index:transition_stop_index - ] - transition_power = self.data[transition_start_index:transition_stop_index] - - state_timestamps = self.timestamps[state_start_index:state_stop_index] - state_power = self.data[state_start_index:state_stop_index] - - transition = { - "isa": "transition", - "W_mean": np.mean(transition_power), - "W_std": np.std(transition_power), - "s": transition_duration, - } - if self.with_traces: - transition["plot"] = ( - transition_timestamps - transition_timestamps[0], - transition_power, - ) - - state = { - "isa": "state", - "W_mean": np.mean(state_power), - "W_std": np.std(state_power), - "s": state_duration, - } - if self.with_traces: - state["plot"] = (state_timestamps - state_timestamps[0], state_power) - - transition["W_mean_delta_prev"] = transition["W_mean"] - np.mean( - prev_state_power - ) - transition["W_mean_delta_next"] = transition["W_mean"] - state["W_mean"] - - energy_trace.append(transition) - energy_trace.append(state) - - return energy_trace |