Added into runner.py

1 files changed, 152 insertions, 6 deletions

diff --git a/lib/loader.py b/lib/loader.py
index c0a1694..38d59fc 100644
--- a/lib/loader.py
+++ b/lib/loader.py
@@ -1621,6 +1621,7 @@ class EnergyTraceWithLogicAnalyzer:
         transition_names: list,
         with_traces=False,
     ):
+
         """
         Create a new EnergyTraceWithLogicAnalyzer object.
 
@@ -1636,9 +1637,13 @@ class EnergyTraceWithLogicAnalyzer:
         self.errors = list()
 
     def load_data(self, log_data):
-        # TODO Daten laden
-        print("########################")
-        print(log_data[0].split("\n")[0])
+        from data.timing.SigrokInterface import SigrokResult
+        from data.energy.EnergyInterface import EnergyInterface
+
+        # Daten laden
+        self.sync_data = SigrokResult.fromString(log_data[0])
+        self.energy_data = EnergyInterface.getDataFromString(str(log_data[1]))
+
         pass
 
     def analyze_states(self, traces, offline_index: int):
@@ -1666,7 +1671,89 @@ class EnergyTraceWithLogicAnalyzer:
             * `W_mean_delta_next`: Differenz zwischen W_mean und W_mean des Folgezustands
         """
 
-        # TODO Tatsächlich Daten auswerten
+        # Tatsächlich Daten auswerten
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+        # remove Dirty Data from previously running program (happens if logic Analyzer Measurement starts earlier than
+        # the HW Reset from energytrace)
+        use_data_after_index = 0
+        for x in range(1, len(self.sync_data.timestamps)):
+            if self.sync_data.timestamps[x] - self.sync_data.timestamps[x - 1] > 1.3:
+                use_data_after_index = x
+                break
+
+        time_stamp_data = self.sync_data.timestamps[use_data_after_index:]
+
+        start_offset = None
+        start_timestamp = None
+        end_offset = None
+        end_timestamp = None
+
+        last_values = []  # maybe needed to flatten the data
+        plot_data_x = []
+        plot_data_y = []
+        last_data = [0, 0, 0, 0]
+
+        power_sync_watt = 0.0162
+
+        # MAIN ENERGY DATA ITERATION
+        for energytrace_dataset in self.energy_data:
+            usedtime = energytrace_dataset[0] - last_data[0]
+            usedenergy = energytrace_dataset[3] - last_data[3]
+            power = usedenergy / usedtime * 10 ** -3  # in watts
+
+            if power > 0:
+                if power > power_sync_watt and start_offset is None:
+                    # automatic START offset calculation
+                    start_offset = energytrace_dataset[0] / 1_000_000 - time_stamp_data[0]
+                    start_timestamp = energytrace_dataset[0] / 1_000_000
+                if power > power_sync_watt and start_offset is not None:  # TODO BETTER
+                    # automatic END offset calculation (Drift)
+                    end_offset = energytrace_dataset[0] / 1_000_000 - time_stamp_data[-1] - start_offset
+                    end_timestamp = energytrace_dataset[0] / 1_000_000
+                if len(last_values) > 10:
+                    last_values.pop(0)
+                last_values.append(power)
+                # print("%s \tUsed Energy: %i  \tUsed Time: %i  \tPower: %f \t l_10: %f" % (now_data[0], usedenergy, usedtime, power, sum(last_values) / len(last_values)))
+                plot_data_x.append(energytrace_dataset[0] / 1_000_000)
+                plot_data_y.append(power)
+
+                last_data = energytrace_dataset
+
+        # --------------------
+        # add start offset to the data
+        modified_timestamps_with_offset = []
+        for x in time_stamp_data:
+            if x + start_offset >= 0:
+                modified_timestamps_with_offset.append(x + start_offset)
+
+        # --------------------
+        # Add drift to datapoints
+        modified_timestamps_with_drift = []
+        endFactor = (end_timestamp + end_offset - start_timestamp) / (end_timestamp - start_timestamp)
+        for x in modified_timestamps_with_offset:
+            modified_timestamps_with_drift.append(((x - start_timestamp) * endFactor) + start_timestamp)
+
+        self.start_offset = 0
+        def getPowerBetween(start, end):
+            first_index = 0
+            all_power = 0
+            all_power_count = 0
+            for ind in range(self.start_offset, len(plot_data_x)):
+                first_index = ind
+                if plot_data_x[ind] > start:
+                    break
+
+            for ind in range(first_index, len(plot_data_x)):
+                all_power += plot_data_y[ind]
+                all_power_count += 1
+                if plot_data_x[ind] > end:
+                    self.start_offset = ind - 1
+                    break
+            return all_power / all_power_count
+
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 
         energy_trace = list()
 
@@ -1697,7 +1784,65 @@ class EnergyTraceWithLogicAnalyzer:
                         )
                         return energy_trace
 
-        for name, duration in expected_transitions:
+
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+        end_transition_ts = None
+        timestamps_sync_start = 0
+        energy_trace_new = list()
+
+        for ts_index in range(0 + timestamps_sync_start, int(len(modified_timestamps_with_drift) / 2)):
+            start_transition_ts = modified_timestamps_with_drift[ts_index * 2]
+            if end_transition_ts is not None:
+                power = getPowerBetween(end_transition_ts, start_transition_ts)
+                #print("STATE", end_transition_ts * 10 ** 6, start_transition_ts * 10 ** 6, (start_transition_ts - end_transition_ts) * 10 ** 6, power)
+                if (start_transition_ts - end_transition_ts) * 10 ** 6 > 900_000 and power > power_sync_watt * 0.9 and ts_index > 10:
+                    #remove last transition and stop (upcoming data only sync)
+                    del energy_trace_new[-1]
+                    break
+                    pass
+
+                state = {
+                    "isa": "state",
+                    "W_mean": power,
+                    "W_std": 0.0001,
+                    "s": (start_transition_ts - end_transition_ts), #* 10 ** 6,
+                }
+                energy_trace_new.append(state)
+
+                energy_trace_new[-2]["W_mean_delta_next"] = (
+                        energy_trace_new[-2]["W_mean"] - energy_trace_new[-1]["W_mean"]
+                )
+
+                # get energy end_transition_ts
+            end_transition_ts = modified_timestamps_with_drift[ts_index * 2 + 1]
+            power = getPowerBetween(start_transition_ts, end_transition_ts)
+            #print("TRANS", start_transition_ts * 10 ** 6, end_transition_ts * 10 ** 6, (end_transition_ts - start_transition_ts) * 10 ** 6, power)
+            transition = {
+                "isa": "transition",
+                "W_mean": power,
+                "W_std": 0.0001,
+                "s": (end_transition_ts - start_transition_ts), #* 10 ** 6,
+            }
+
+            if (end_transition_ts - start_transition_ts) * 10 ** 6 > 2_000_000:
+                # TODO Last data set corrupted? HOT FIX!!!!!!!!!!!! REMOVE LATER
+                for x in range(4):
+                    del energy_trace_new[-1]
+                break
+                pass
+
+            energy_trace_new.append(transition)
+            # print(start_transition_ts, "-", end_transition_ts, "-", end_transition_ts - start_transition_ts)
+
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+        # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+        energy_trace_new = energy_trace_new[4:]
+
+        for number, item in enumerate(expected_transitions):
+            name, duration = item
             transition = {
                 "isa": "transition",
                 "W_mean": max(np.random.normal(0.023, 0.002), 0),
@@ -1725,7 +1870,8 @@ class EnergyTraceWithLogicAnalyzer:
                 energy_trace[-2]["W_mean"] - energy_trace[-1]["W_mean"]
             )
 
-        return energy_trace
+        #print(len(energy_trace_new), " - ", len(energy_trace), " - ", ",".join([str(x["s"]) for x in energy_trace_new[-6:]]), " - ", ",".join([str(x["s"]) for x in energy_trace[-6:]]))
+        return energy_trace_new
 
 
 class EnergyTraceWithTimer(EnergyTraceWithLogicAnalyzer):