Mid progress

plot.py

@@ -1,45 +1,58 @@
 import os
 import matplotlib.pyplot as plt
-import matplotlib.dates as mdates
 import numpy as np
 
-from datetime import datetime
-
 DATA_DIR = "data"
 
-# Find the latest data file
-files = [f for f in os.listdir(DATA_DIR) if f.startswith("voltages_") and f.endswith(".csv")]
+# Find the newest summary CSV
+files = [f for f in os.listdir(DATA_DIR) if f.startswith("summary_") and f.endswith(".csv")]
 if not files:
-    raise FileNotFoundError("No voltage data files found in 'data/'")
+    raise FileNotFoundError("No summary files found in 'data/'")
 
 latest_file = max(files, key=lambda f: os.path.getmtime(os.path.join(DATA_DIR, f)))
 filepath = os.path.join(DATA_DIR, latest_file)
 print(f"Plotting data from {filepath}")
 
-# Load CSV data
-timestamps = []
-voltages = []
+# Load CSV
+start_ms = []
+end_ms = []
+vals = []  # rows of [max, mean+std, mean, mean-std, min]
 
 with open(filepath, "r") as f:
     next(f)  # skip header
     for line in f:
-        ts_str, v_str = line.strip().split(",")
-        ts = datetime.strptime(ts_str, "%Y-%m-%d %H:%M:%S.%f")
-        timestamps.append(ts)
-        voltages.append(float(v_str))
+        parts = line.strip().split(",")
+        if len(parts) != 7:
+            continue
+        s_ms, e_ms, *rest = parts
+        start_ms.append(float(s_ms))
+        end_ms.append(float(e_ms))
+        vals.append([float(x) for x in rest])
+
+vals = np.array(vals)
+
+# Time axis: relative seconds since first interval start
+start_ms = np.array(start_ms)
 
 # Plot
-plt.figure(figsize=(12, 5))
-plt.scatter(timestamps, voltages, marker='o', linestyle='-', s=0.2)
+plt.figure(figsize=(12, 6))
 
-plt.xlabel("Time (CET)")
-plt.ylabel("Voltage (V)")
-plt.title(f"Voltage Measurements ({latest_file})")
+max_tot = vals[:, 1].mean()
+min_tot = vals[:, 3].mean()
+
+print(max_tot, min_tot)
+plt.scatter(start_ms, vals[:, 0], label="max", s=3)
+plt.scatter(start_ms, vals[:, 1], label="mean+std", s=3)
+plt.scatter(start_ms, vals[:, 2], label="mean", s=3)
+plt.scatter(start_ms, vals[:, 3], label="mean-std", s=3)
+plt.scatter(start_ms, vals[:, 4], label="min", s=3 )
+
+plt.xlabel("Time since start (s)")
+plt.ylabel("Voltage summary (V)")
+plt.title(f"Voltage Summary ({latest_file})")
 plt.grid(True)
-
-# Format x-axis for readable time
-plt.gcf().autofmt_xdate()
-plt.gca().xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S"))
+plt.legend()
 
 plt.tight_layout()
 plt.show()
+