Add DFATOOL_EXPORT_LASYNC variable for ET+LA / ET+Timer sync eval

3 files changed, 36 insertions, 1 deletions

diff --git a/lib/lennart/DataProcessor.py b/lib/lennart/DataProcessor.py
index 07d2a2b..b46315a 100644
--- a/lib/lennart/DataProcessor.py
+++ b/lib/lennart/DataProcessor.py
@@ -171,6 +171,23 @@ class DataProcessor:
         ) * endFactor + start_timestamp
         return modified_timestamps_with_drift
 
+    def export_sync(self):
+        # [1st trans start, 1st trans stop, 2nd trans start, 2nd trans stop, ...]
+        sync_timestamps = list()
+
+        for i in range(4, len(self.modified_timestamps) - 8, 2):
+            sync_timestamps.append(
+                (self.modified_timestamps[i], self.modified_timestamps[i + 1])
+            )
+
+        # EnergyTrace timestamps
+        timestamps = self.plot_data_x
+
+        # EnergyTrace power values
+        power = self.plot_data_y
+
+        return {"sync": sync_timestamps, "timestamps": timestamps, "power": power}
+
     def plot(self, annotateData=None):
         """
         Plots the power usage and the timestamps by logic analyzer
diff --git a/lib/loader.py b/lib/loader.py
index 0e1e8c9..0c7ad91 100644
--- a/lib/loader.py
+++ b/lib/loader.py
@@ -12,7 +12,7 @@ import tarfile
 import hashlib
 from multiprocessing import Pool
 
-from .utils import running_mean, soft_cast_int
+from .utils import NpEncoder, running_mean, soft_cast_int
 
 logger = logging.getLogger(__name__)
 
@@ -1714,6 +1714,11 @@ class EnergyTraceWithLogicAnalyzer:
             dp.plot()  # <- plot traces with sync annotatons
             # dp.plot(names) # <- plot annotated traces (with state/transition names)
             pass
+        if os.getenv("DFATOOL_EXPORT_LASYNC") is not None:
+            filename = os.getenv("DFATOOL_EXPORT_LASYNC") + f"_{offline_index}.json"
+            with open(filename, "w") as f:
+                json.dump(dp.export_sync(), f, cls=NpEncoder)
+            logger.info("Exported data and LA sync timestamps to {filename}")
         energy_trace_new = energy_trace_new[4:]
 
         energy_trace = list()
diff --git a/lib/utils.py b/lib/utils.py
index d28ecda..adcb534 100644
--- a/lib/utils.py
+++ b/lib/utils.py
@@ -1,3 +1,4 @@
+import json
 import numpy as np
 import re
 import logging
@@ -6,6 +7,18 @@ arg_support_enabled = True
 logger = logging.getLogger(__name__)
 
 
+class NpEncoder(json.JSONEncoder):
+    def default(self, obj):
+        if isinstance(obj, np.integer):
+            return int(obj)
+        elif isinstance(obj, np.floating):
+            return float(obj)
+        elif isinstance(obj, np.ndarray):
+            return obj.tolist()
+        else:
+            return super(NpEncoder, self).default(obj)
+
+
 def running_mean(x: np.ndarray, N: int) -> np.ndarray:
     """
     Compute `N` elements wide running average over `x`.