From 18ed677ab66962f38337466e973d2d0ee9085bcb Mon Sep 17 00:00:00 2001
From: Hector van der Aa <hector@h3cx.dev>
Date: Thu, 4 Jun 2026 10:29:20 +0200
Subject: [PATCH] Added plot derivatives

---
 src/plot_derivatives_graph.py | 80 +++++++++++++++++++++++++++++++++++
 1 file changed, 80 insertions(+)
 create mode 100644 src/plot_derivatives_graph.py

diff --git a/src/plot_derivatives_graph.py b/src/plot_derivatives_graph.py
new file mode 100644
index 0000000..8fa334a
--- /dev/null
+++ b/src/plot_derivatives_graph.py
@@ -0,0 +1,80 @@
+# Copyright (C) 2026 Hector van der Aa <hector@h3cx.dev>
+# Copyright (C) 2026 Association Exergie <association.exergie@gmail.com>
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+from cProfile import label
+import pandas as pd
+from pathlib import Path
+import argparse
+from tqdm import tqdm
+import matplotlib.pyplot as plt
+
+parser = argparse.ArgumentParser()
+parser.add_argument("directory", type=Path, help="Source data directory")
+
+args = parser.parse_args()
+
+directory: Path = args.directory
+
+if not directory.is_dir():
+    parser.error(f"{directory} is not a valid directory")
+
+print(f"Processing data in: {directory}")
+
+files: list[Path] = []
+
+for path in directory.glob("*.csv"):
+    stem = path.stem
+
+    try:
+        base_name, channel = stem.rsplit("_", 1)
+    except ValueError:
+        print(f"Skipping badly named file: {path}")
+        continue
+
+    if channel != "trimmed":
+        print(f"Skipping unknown file: {path}")
+        continue
+
+    files.append(path)
+
+
+for file in files:
+    trimmed_df = pd.read_csv(file).set_index("time_us", drop=False)
+    base_name, _ = file.stem.rsplit("_", 1)
+    der_file = file.parent / f"{base_name}_derivative.csv"
+    der_df = pd.read_csv(der_file).set_index("time_us", drop=False)
+    fig, ax = plt.subplots(figsize=(12, 6))
+
+    # RPM
+    ax.plot(der_df["time_us"] / 1_000_000, der_df["d1"], label="d1")
+    ax.set_xlabel("Time (s)")
+    ax.set_ylabel("RPM")
+    ax.set_title(f"{base_name} RPM over Time")
+    ax.grid(True)
+
+    ax1 = ax.twinx()
+    ax1.plot(der_df["time_us"] / 1_000_000, der_df["d2"], label="d2", color="red")
+
+    # Crank on second y-axis
+    ax2 = ax.twinx()
+    ax2.plot(
+        trimmed_df["time_us"] / 1_000_000, trimmed_df["crank"], alpha=0.4, label="Crank"
+    )
+    ax2.set_ylabel("Crank")
+    ax2.set_ylim(-0.1, 1.1)
+
+    ax3 = ax.twinx()
+    ax3.plot(
+        trimmed_df["time_us"] / 1_000_000,
+        trimmed_df["cam"],
+        alpha=0.4,
+        label="Cam",
+        color="red",
+    )
+    ax3.set_ylabel("Cam")
+    ax3.set_ylim(-0.1, 1.1)
+
+    fig.tight_layout()
+    plt.show()
+    plt.close(fig)