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python_scripts/plot_script.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Fri Jun 12 21:31:53 2026
+
+@author: chris
+"""
+import json
+import time
+from collections import defaultdict, deque
+
+import numpy as np
+import paho.mqtt.client as mqtt
+import matplotlib.pyplot as plt
+
+MQTT_BROKER = "s960411f.ala.eu-central-1.emqxsl.com"
+MQTT_PORT = 8883
+MQTT_USER = "cma"
+MQTT_PASS = "cmatest"
+
+TOPIC = "can/raw"
+
+# store last N samples per CAN ID
+history = defaultdict(lambda: deque(maxlen=200))
+
+# candidate sensor signals
+candidates = defaultdict(list)
+
+# ----------------------------
+# MQTT callback
+# ----------------------------
+def on_message(client, userdata, msg):
+    try:
+        data = json.loads(msg.payload.decode())
+
+        can_id = data["id"]
+        dlc = data["dlc"]
+        payload = data["data"]
+
+        timestamp = data.get("ts", time.time())
+
+        history[can_id].append((timestamp, payload))
+
+    except Exception as e:
+        print("Parse error:", e)
+
+
+# ----------------------------
+# Find best "sensor-like" byte index
+# ----------------------------
+def detect_sensor_like_signals():
+    sensor_map = {}
+
+    for can_id, samples in history.items():
+        if len(samples) < 20:
+            continue
+
+        arr = np.array([s[1][:8] for s in samples])
+
+        # check each byte position
+        for i in range(arr.shape[1]):
+            series = arr[:, i]
+
+            # ignore constant / noisy bytes
+            if np.std(series) < 0.5:
+                continue
+
+            # sensor heuristic:
+            # - slowly varying
+            # - not binary toggling
+            # - not full random noise
+            diff = np.abs(np.diff(series))
+            stability_score = np.mean(diff)
+
+            if 0.01 < stability_score < 5.0:
+                sensor_map.setdefault(can_id, []).append((i, stability_score))
+
+    return sensor_map
+
+
+# ----------------------------
+# Print likely sensors
+# ----------------------------
+def print_candidates():
+    sensors = detect_sensor_like_signals()
+
+    print("\n=== SENSOR CANDIDATES ===")
+
+    idx = 1
+    for can_id, signals in sensors.items():
+        for byte_index, score in signals:
+            print(f"Sensor{idx}: CAN ID {hex(can_id)} byte[{byte_index}] score={score:.3f}")
+            idx += 1
+
+
+# ----------------------------
+# Live plotting (simple)
+# ----------------------------
+def plot_sensor(can_id, byte_index):
+    samples = history[can_id]
+
+    if len(samples) < 10:
+        return
+
+    y = [s[1][byte_index] for s in samples]
+    x = list(range(len(y)))
+
+    plt.clf()
+    plt.title(f"CAN {hex(can_id)} byte[{byte_index}]")
+    plt.plot(x, y)
+    plt.pause(0.1)
+
+
+# ----------------------------
+# MQTT setup
+# ----------------------------
+client = mqtt.Client()
+client.username_pw_set(MQTT_USER, MQTT_PASS)
+client.on_message = on_message
+
+client.connect(MQTT_BROKER, MQTT_PORT, 60)
+client.subscribe(TOPIC)
+
+client.loop_start()
+
+print("Listening for CAN frames...\n")
+
+# ----------------------------
+# Main loop
+# ----------------------------
+plt.ion()
+
+while True:
+    time.sleep(5)
+
+    print_candidates()
+
+    # try plotting strongest candidate (if any)
+    sensors = detect_sensor_like_signals()
+
+    for can_id, signals in sensors.items():
+        if signals:
+            byte_index = signals[0][0]
+            plot_sensor(can_id, byte_index)
+            break