filterd incoming data with timestamp conditioning

mainplot.py

@@ -146,12 +146,18 @@ def update_SI(value: SD.ReturnDecoder):
         file.write(f"{value.timestamp},{value.log_message}\n")
     print(f"\033[F\033[2Ktime:{value.timestamp}, SI:{value.log_message}", end="\n")
 
+Last_history_call: int = 0
 
 def append_history(adc_values: list, timestamp: int):
     """Store the new sample in the rolling history (derived units)."""
-    if len(history_x)> 0 and timestamp < history_x[-1]:
+    global Last_history_call
+    if len(history_x) > 0 and timestamp < history_x[-1]:
         return  # discard out-of-order samples
+    if len(history_x) > 0 and (history_x[-1] + (int(time.time_ns() / 1000000) - Last_history_call)*2) < timestamp:
+        print(f"Discarding future sample: {timestamp} > {history_x[-1]} + {(int(time.time_ns() / 1000000) - Last_history_call)*2}")
+        return  # discard samples too far in future
     history_x.append(timestamp)
+    Last_history_call = int(time.time_ns() / 1000000)  # in ms
 
     # 0: Thrust (average of load cells 0 and 1)
     lc_avg = (adc_values[0] + adc_values[1]) / 2
@@ -169,6 +175,7 @@ def append_history(adc_values: list, timestamp: int):
         history_y[i - 1].append(pres)  # 8→7, 15→14
     
 
+
 def update_plot():
     """Redraw plot based on selected derived channels and available history."""
     ax.clear()