Power update + bar graph change
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Generate Power Graph / plot (push) Failing after 1m51s
Some checks failed
Generate Power Graph / plot (push) Failing after 1m51s
This commit is contained in:
mrkmntal
parent
f792c5fb45
commit
974d23a7d4
2 changed files with 90 additions and 73 deletions
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@ -1,8 +1,7 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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"""
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"""
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plot_power.py
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plot_power.py
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Generates a PNG graph from power_log.csv for AMD Laptop APU/GPU telemetry.
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Forgejo CI: visualize AMD TUF APU/GPU telemetry as a clear bar graph.
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Designed for Forgejo CI artifact publishing.
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Author: MarkMental
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Author: MarkMental
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"""
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"""
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@ -10,55 +9,55 @@ import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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from datetime import datetime
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from datetime import datetime
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# --- Configuration ---
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CSV_PATH = "power_log.csv"
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CSV_PATH = "power_log.csv"
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OUTPUT_FILE = "power_graph.png"
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OUTPUT_FILE = "power_graph.png"
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print(f"📊 Reading {CSV_PATH}...")
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print(f"📊 Reading {CSV_PATH}...")
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# --- Load data ---
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try:
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df = pd.read_csv(CSV_PATH)
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df = pd.read_csv(CSV_PATH)
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except FileNotFoundError:
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raise SystemExit(f"❌ CSV not found: {CSV_PATH}")
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# --- Sanity checks ---
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# --- Normalize timestamp ---
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required_cols = {"timestamp", "apu_w", "gpu_w", "total_w"}
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if not required_cols.issubset(df.columns):
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raise SystemExit(f"❌ Missing columns in {CSV_PATH}. Found: {df.columns.tolist()}")
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# --- Parse timestamps ---
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try:
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df["timestamp"] = pd.to_datetime(df["timestamp"], errors="coerce")
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df["timestamp"] = pd.to_datetime(df["timestamp"], errors="coerce")
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except Exception as e:
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df["time_fmt"] = df["timestamp"].dt.strftime("%Y-%m-%d %H:%M:%S")
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print(f"⚠️ Failed to parse some timestamps: {e}")
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# --- Plot ---
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# --- Downsample if extremely long (avoid thousands of bars) ---
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plt.figure(figsize=(10, 5))
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if len(df) > 200:
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plt.plot(df["timestamp"], df["apu_w"], label="APU Power (W)", color="orange", linewidth=1.3)
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df = df.iloc[::max(1, len(df)//200), :]
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plt.plot(df["timestamp"], df["gpu_w"], label="GPU Power (W)", color="green", linewidth=1.3)
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plt.plot(df["timestamp"], df["total_w"], label="Total Power (W)", color="blue", linewidth=1.5)
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# Optional: plot temperatures if present
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# --- Plot setup ---
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fig, ax1 = plt.subplots(figsize=(12, 6))
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# Power bars
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width = 0.3
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x = range(len(df))
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ax1.bar([i - width for i in x], df["apu_w"], width, label="APU Power (W)", color="#ff9933")
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ax1.bar(x, df["gpu_w"], width, label="GPU Power (W)", color="#66cc66")
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ax1.bar([i + width for i in x], df["total_w"], width, label="Total Power (W)", color="#3399ff")
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ax1.set_xlabel("Timestamp (YYYY-MM-DD HH:MM:SS)")
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ax1.set_ylabel("Power (Watts)")
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ax1.set_title("AMD TUF Power & Temperature Log")
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ax1.set_xticks(x[::max(1, len(x)//10)])
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ax1.set_xticklabels(df["time_fmt"].iloc[::max(1, len(x)//10)], rotation=45, ha="right")
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# --- Secondary axis for temperature ---
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if "apu_temp" in df.columns and "gpu_temp" in df.columns:
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if "apu_temp" in df.columns and "gpu_temp" in df.columns:
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ax2 = plt.gca().twinx()
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ax2 = ax1.twinx()
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ax2.plot(df["timestamp"], df["apu_temp"], "--", color="red", alpha=0.4, label="APU Temp (°C)")
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ax2.plot(x, df["apu_temp"], "--", color="red", linewidth=1.2, label="APU Temp (°C)")
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ax2.plot(df["timestamp"], df["gpu_temp"], "--", color="purple", alpha=0.4, label="GPU Temp (°C)")
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ax2.plot(x, df["gpu_temp"], "--", color="purple", linewidth=1.2, label="GPU Temp (°C)")
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ax2.set_ylabel("Temperature (°C)")
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ax2.set_ylabel("Temperature (°C)")
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lines, labels = plt.gca().get_legend_handles_labels()
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ax2.set_ylim(min(df[["apu_temp","gpu_temp"]].min())-5,
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max(df[["apu_temp","gpu_temp"]].max())+5)
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# Combine legends
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lines1, labels1 = ax1.get_legend_handles_labels()
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lines2, labels2 = ax2.get_legend_handles_labels()
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lines2, labels2 = ax2.get_legend_handles_labels()
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plt.legend(lines + lines2, labels + labels2, loc="upper left")
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ax1.legend(lines1 + lines2, labels1 + labels2, loc="upper left")
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else:
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else:
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plt.legend(loc="upper left")
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ax1.legend(loc="upper left")
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plt.title("AMD TUF Power Log")
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plt.grid(axis="y", alpha=0.3)
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plt.xlabel("Time")
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plt.ylabel("Power (Watts)")
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plt.grid(True, alpha=0.3)
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plt.xticks(rotation=45)
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plt.tight_layout()
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plt.tight_layout()
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plt.savefig(OUTPUT_FILE, dpi=150)
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print(f"✅ Saved clean bar graph: {OUTPUT_FILE}")
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# --- Save ---
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plt.savefig(OUTPUT_FILE, dpi=120)
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print(f"✅ Saved graph: {OUTPUT_FILE}")
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@ -1,39 +1,3 @@
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timestamp,apu_w,gpu_w,total_w,apu_temp,gpu_temp
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2025-11-05T17:47:45-05:00,15.19,9.00,24.19,73.0,68.0
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2025-11-05T17:47:46-05:00,48.01,11.00,59.01,73.0,68.0
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2025-11-05T18:34:08-05:00,2.14,9.00,11.14,70.0,67.0
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