forked from eden-emu/eden
155 lines
4.8 KiB
Python
Executable file
155 lines
4.8 KiB
Python
Executable file
#!/usr/bin/env python3
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# SPDX-FileCopyrightText: Copyright 2025 DraVee
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# SPDX-License-Identifier: GPL-3.0-or-later
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import sys
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import pandas as pd
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import matplotlib.pyplot as plt
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import glob
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import os
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import re
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# Check required Python modules
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required_modules = ["pandas", "matplotlib"]
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missing_modules = []
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for mod in required_modules:
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try:
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__import__(mod)
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except ImportError:
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missing_modules.append(mod)
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if missing_modules:
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print(f"Error: Missing required Python modules: {', '.join(missing_modules)}")
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print("Please install them, e.g.:")
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print(f" python3 -m pip install {' '.join(missing_modules)}")
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sys.exit(1)
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# Get log folder from command-line argument
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if len(sys.argv) < 2:
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print("Usage: python3 compare_logs.py <log_folder>")
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sys.exit(1)
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log_base_folder = os.path.expanduser(sys.argv[1])
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if not os.path.isdir(log_base_folder):
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print(f"Error: '{log_base_folder}' is not a valid folder")
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sys.exit(1)
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# Find all CSV files recursively (ignore summary CSVs)
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csv_files = sorted(glob.glob(os.path.join(log_base_folder, "**/eden_*.csv"), recursive=True))
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csv_files = [f for f in csv_files if not f.endswith("_summary.csv")]
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if not csv_files:
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print(f"No CSV files found in {log_base_folder} or its subfolders")
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sys.exit(0)
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# Prepare plotting
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plt.figure(figsize=(14, 7))
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colors = plt.colormaps['tab10']
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stats = []
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for i, csv_file in enumerate(csv_files):
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# Relative path from base folder
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relative_path = os.path.relpath(csv_file, log_base_folder)
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# Read eden-cli version if exists
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log_dir = os.path.dirname(csv_file)
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version_file = os.path.join(log_dir, "eden-cli-version.txt")
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if os.path.exists(version_file):
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with open(version_file, "r") as f:
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eden_version = f.read().strip()
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else:
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eden_version = "unknown version"
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# Corresponding summary file
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summary_file = csv_file.replace(".csv", "_summary.csv")
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# Skip empty CSVs
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if os.path.getsize(csv_file) == 0:
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print(f"Skipping {relative_path}: file is empty")
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continue
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# Read main CSV (skip system info lines)
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df = pd.read_csv(csv_file, skiprows=2)
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df.columns = df.columns.str.strip()
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if 'fps' not in df.columns:
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print(f"Skipping {relative_path}: no 'fps' column found")
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continue
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y = df['fps']
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# --- FILTRAR OUTLIERS ---
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mean_y = y.mean()
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std_y = y.std()
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y_filtered = y[(y >= mean_y - 3*std_y) & (y <= mean_y + 3*std_y)]
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x_filtered = range(len(y_filtered))
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# ------------------------
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# Compute statistics from filtered data
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mean_fps = y_filtered.mean()
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min_fps = y_filtered.min()
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max_fps = y_filtered.max()
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# Read summary CSV if exists
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summary_text = ""
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if os.path.exists(summary_file):
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try:
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df_sum = pd.read_csv(summary_file)
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avg = float(df_sum['Average FPS'][0])
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p0_1 = float(df_sum['0.1% Min FPS'][0])
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p1 = float(df_sum['1% Min FPS'][0])
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p97 = float(df_sum['97% Percentile FPS'][0])
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summary_text = f" | summary avg={avg:.1f}, 0.1%={p0_1:.1f}, 1%={p1:.1f}, 97%={p97:.1f}"
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except Exception as e:
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print(f"Could not read summary for {summary_file}: {e}")
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# Store stats including version
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stats.append((relative_path, mean_fps, min_fps, max_fps, summary_text, eden_version))
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# Plot FPS line with filtered data
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plt.plot(
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x_filtered, y_filtered,
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label=f"{relative_path} (avg={mean_fps:.1f}) [{eden_version}]{summary_text}",
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color=colors(i % 10)
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)
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# Configure plot
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plt.xlabel('Frame')
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plt.ylabel('FPS')
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plt.title('FPS Comparison Across All Builds (Outliers Removed)')
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plt.legend()
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plt.grid(True)
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plt.tight_layout()
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# Save plot
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png_file = os.path.join(os.getcwd(), "fps_comparison_all_builds.png")
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plt.savefig(png_file, dpi=200)
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plt.show()
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# Print concise statistics grouped by build folder
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print("\nFPS Summary by build folder (concise):")
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for name, mean_fps, min_fps, max_fps, summary_text, eden_version in stats:
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log_folder = os.path.dirname(name) # pasta do CSV (_timestamp_)
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build_folder = os.path.basename(os.path.dirname(log_folder)) # pasta do build*
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version_short = eden_version.split()[0] if eden_version != "unknown version" else "unknown"
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print(f"{build_folder} | {version_short} | mean={mean_fps:.1f}, min={min_fps:.1f}, max={max_fps:.1f}")
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print("\n----------------------------")
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print(f"Total CSV files processed: {len(stats)}")
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# Track build folders (without timestamps)
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build_folders = set()
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for csv_file in csv_files:
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run_folder = os.path.dirname(csv_file)
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build_folder = os.path.dirname(run_folder)
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build_folders.add(build_folder)
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print("\nBuild folders containing CSVs:")
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for folder in sorted(build_folders):
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print(f" - {folder}")
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print(f"Graph saved as: {png_file}")
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