diff options
Diffstat (limited to 'lib/loader.py')
| -rw-r--r-- | lib/loader.py | 137 |
1 files changed, 133 insertions, 4 deletions
diff --git a/lib/loader.py b/lib/loader.py index c35eb4c..65d497b 100644 --- a/lib/loader.py +++ b/lib/loader.py @@ -107,7 +107,14 @@ def _preprocess_mimosa(measurement): def _preprocess_etlog(measurement): setup = measurement["setup"] - etlog = EnergyTraceLog( + + energytrace_class = EnergyTraceWithBarcode + if measurement["sync_mode"] == "la": + energytrace_class = EnergyTraceWithLogicAnalyzer + elif measurement["sync_mode"] == "timer": + energytrace_class = EnergyTraceWithTimer + + etlog = energytrace_class( float(setup["voltage"]), int(setup["state_duration"]), measurement["transition_names"], @@ -406,7 +413,7 @@ class RawData: processed_data["error"] = "; ".join(processed_data["datasource_errors"]) return False - # Note that the low-level parser (EnergyTraceLog) already checks + # Note that the low-level parser (EnergyTraceWithBarcode) already checks # whether the transition count is correct return True @@ -909,6 +916,10 @@ class RawData: new_filenames = list() with tarfile.open(filename) as tf: ptalog = self.ptalog + if "sync" in ptalog["opt"]["energytrace"]: + sync_mode = ptalog["opt"]["energytrace"]["sync"] + else: + sync_mode = "bar" # Benchmark code may be too large to be executed in a single # run, so benchmarks (a benchmark is basically a list of DFA runs) @@ -968,6 +979,7 @@ class RawData: offline_data.append( { "content": tf.extractfile(member).read(), + "sync_mode": sync_mode, "fileno": j, "info": member, "setup": self.setup_by_fileno[j], @@ -1161,7 +1173,7 @@ def pta_trace_to_aggregate(traces, ignore_trace_indexes=[]): return by_name, parameter_names, arg_count -class EnergyTraceLog: +class EnergyTraceWithBarcode: """ EnergyTrace log loader for DFA traces. @@ -1184,7 +1196,7 @@ class EnergyTraceLog: with_traces=False, ): """ - Create a new EnergyTraceLog object. + Create a new EnergyTraceWithBarcode object. :param voltage: supply voltage [V], usually 3.3 V :param state_duration: state duration [ms] @@ -1599,6 +1611,123 @@ class EnergyTraceLog: return None, None, None, None +class EnergyTraceWithLogicAnalyzer: + def __init__( + self, + voltage: float, + state_duration: int, + transition_names: list, + with_traces=False, + ): + """ + Create a new EnergyTraceWithLogicAnalyzer object. + + :param voltage: supply voltage [V], usually 3.3 V + :param state_duration: state duration [ms] + :param transition_names: list of transition names in PTA transition order. + Needed to map barcode synchronization numbers to transitions. + """ + self.voltage = voltage + self.state_duration = state_duration * 1e-3 + self.transition_names = transition_names + self.with_traces = with_traces + self.errors = list() + + def load_data(self, log_data): + # TODO Daten laden + pass + + def analyze_states(self, traces, offline_index: int): + u""" + Split log data into states and transitions and return duration, energy, and mean power for each element. + + :param traces: expected traces, needed to synchronize with the measurement. + traces is a list of runs, traces[*]['trace'] is a single run + (i.e. a list of states and transitions, starting with a transition + and ending with a state). + :param offline_index: This function uses traces[*]['trace'][*]['online_aggregates']['duration'][offline_index] to find sync codes + + :param charges: raw charges (each element describes the charge in pJ transferred during 10 µs) + :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: returns list of states and transitions, starting with a transition and ending with astate + Each element is a dict containing: + * `isa`: 'state' or 'transition' + * `W_mean`: Mittelwert der Leistungsaufnahme + * `W_std`: Standardabweichung der Leistungsaufnahme + * `s`: Dauer + if isa == 'transition, it also contains: + * `W_mean_delta_prev`: Differenz zwischen W_mean und W_mean des vorherigen Zustands + * `W_mean_delta_next`: Differenz zwischen W_mean und W_mean des Folgezustands + """ + + # TODO Tatsächlich Daten auswerten + + energy_trace = list() + + expected_transitions = list() + for trace_number, trace in enumerate(traces): + for state_or_transition_number, state_or_transition in enumerate( + trace["trace"] + ): + if state_or_transition["isa"] == "transition": + try: + expected_transitions.append( + ( + state_or_transition["name"], + state_or_transition["online_aggregates"]["duration"][ + offline_index + ] + * 1e-6, + ) + ) + except IndexError: + self.errors.append( + 'Entry #{} ("{}") in trace #{} has no duration entry for offline_index/repeat_id {}'.format( + state_or_transition_number, + state_or_transition["name"], + trace_number, + offline_index, + ) + ) + return energy_trace + + for name, duration in expected_transitions: + transition = { + "isa": "transition", + "W_mean": max(np.random.normal(0.023, 0.002), 0), + "W_std": 0.0001, + "s": duration, + } + + energy_trace.append(transition) + + if len(energy_trace) > 1: + energy_trace[-1]["W_mean_delta_prev"] = ( + energy_trace[-1]["W_mean"] - energy_trace[-2]["W_mean"] + ) + + state = { + "isa": "state", + "W_mean": max(np.random.normal(0.023, 0.002), 0), + "W_std": 0.0001, + "s": self.state_duration, + } + + energy_trace.append(state) + + energy_trace[-2]["W_mean_delta_next"] = ( + energy_trace[-2]["W_mean"] - energy_trace[-1]["W_mean"] + ) + + return energy_trace + + +class EnergyTraceWithTimer(EnergyTraceWithLogicAnalyzer): + pass + + class MIMOSA: """ MIMOSA log loader for DFA traces with auto-calibration. |