Added plot derivatives

src/derivatives.py

@@ -0,0 +1,66 @@
+# Copyright (C) 2026 Hector van der Aa <hector@h3cx.dev>
+# Copyright (C) 2026 Pierre Barbier <pierrebarbier741@gmail.com>
+# Copyright (C) 2026 Association Exergie <association.exergie@gmail.com>
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import argparse
+from pathlib import Path
+
+import pandas as pd
+from tqdm import tqdm
+
+
+def filter_data(file: Path) -> pd.DataFrame:
+    df = pd.read_csv(file, usecols=["time_us", "crank", "cam"])
+
+    crank_df = df.loc[df["crank"] == 1, ["time_us"]].copy()
+
+    crank_df["d1"] = crank_df["time_us"].diff()
+    crank_df["prev_d1"] = crank_df["d1"].shift(1)
+    crank_df["d2"] = crank_df["d1"] - crank_df["prev_d1"]
+    crank_df["ratio"] = crank_df["d2"] / crank_df["d1"]
+
+    crank_df = crank_df.dropna(subset=["d1", "d2", "ratio"])
+
+    return crank_df[["time_us", "d1", "d2", "ratio"]]
+
+
+def main() -> None:
+    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}")
+
+    concat_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
+
+        concat_files.append(path)
+
+    for file in tqdm(concat_files, desc="Files"):
+        base_name, _ = file.stem.rsplit("_", 1)
+        output = file.parent / f"{base_name}_derivative.csv"
+
+        out_df = filter_data(file)
+        out_df.to_csv(output, index=False)
+
+
+if __name__ == "__main__":
+    main()

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)

src/plot_rpm_graphs.py

@@ -0,0 +1,76 @@
+# 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
+
+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)
+    rpm_file = file.parent / f"{base_name}_rpm.csv"
+    rpm_df = pd.read_csv(rpm_file).set_index("time_us", drop=False)
+    fig, ax = plt.subplots(figsize=(12, 6))
+
+    # RPM
+    ax.plot(rpm_df["time_us"] / 1_000_000, rpm_df["rpm"], label="RPM")
+    ax.set_xlabel("Time (s)")
+    ax.set_ylabel("RPM")
+    ax.set_title(f"{base_name} RPM over Time")
+    ax.grid(True)
+
+    # 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)

src/rpm_graph.py

@@ -0,0 +1,75 @@
+# 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
+
+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:
+    print(f"Processing {file.name}")
+    df = pd.read_csv(file).set_index("time_us", drop=False)
+    rows = []
+    current_time_us: int = 0
+    current_crank: int = 0
+    last_crank: int = -1
+    for _, row in tqdm(df.iterrows(), total=len(df)):
+        current_time_us = row["time_us"]
+        current_crank = row["crank"]
+
+        if current_crank == 1:
+            if last_crank != -1:
+                rpm = 30_000_000 / (current_time_us - last_crank)
+                rows.append({"time_us": current_time_us, "rpm": rpm})
+            last_crank = current_time_us
+
+    out_df = pd.DataFrame(rows)
+    base_name, _ = file.stem.rsplit("_", 1)
+    output = file.parent / f"{base_name}_rpm.csv"
+    image_output = file.parent / f"{base_name}_rpm.png"
+    out_df.to_csv(output)
+
+    fig, ax = plt.subplots(figsize=(12, 6))
+
+    ax.plot(out_df["time_us"] / 1_000_000, out_df["rpm"])
+    ax.set_xlabel("Time (s)")
+    ax.set_ylabel("RPM")
+    ax.set_title(f"{base_name} RPM over Time")
+    ax.grid(True)
+
+    fig.tight_layout()
+    fig.savefig(image_output, dpi=300)
+
+    plt.close(fig)