Add timeline visualization and fix resource profiling
- Save timeline data for each run (time, memory, CPU) - Create timelines directory structure - Add Python visualization script for charts - Fix integer comparison errors in profiling - Collect samples throughout program lifetime
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Ein Anderssono
Executable
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#!/usr/bin/env python3
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"""
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Visualize resource usage timelines from benchmark data.
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Generates SVG charts showing memory and CPU usage over time for each language.
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"""
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import os
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import sys
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import matplotlib.pyplot as plt
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import matplotlib
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matplotlib.use('Agg') # Non-interactive backend
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from pathlib import Path
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import numpy as np
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def read_timeline_data(filepath):
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"""Read timeline TSV file and return time, memory, cpu arrays."""
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times = []
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memories = []
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cpus = []
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with open(filepath, 'r') as f:
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for line in f:
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parts = line.strip().split()
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if len(parts) >= 3:
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try:
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times.append(int(parts[0]))
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memories.append(int(parts[1]) / 1024) # Convert KB to MB
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cpus.append(int(parts[2]))
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except ValueError:
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continue
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return np.array(times), np.array(memories), np.array(cpus)
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def create_timeline_chart(language, times, memories, cpus, output_dir):
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"""Create a dual-axis chart showing memory and CPU over time."""
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if len(times) == 0:
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print(f"No data for {language}")
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return
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fig, ax1 = plt.subplots(figsize=(10, 6))
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# Memory on left axis
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color1 = '#2E86AB' # Blue
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ax1.set_xlabel('Tid (ms)', fontsize=12)
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ax1.set_ylabel('Minne (MB)', color=color1, fontsize=12)
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ax1.plot(times, memories, color=color1, linewidth=2, label='Minne')
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ax1.tick_params(axis='y', labelcolor=color1)
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ax1.grid(True, alpha=0.3)
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# CPU on right axis
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ax2 = ax1.twinx()
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color2 = '#E94F37' # Red
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ax2.set_ylabel('CPU (%)', color=color2, fontsize=12)
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ax2.plot(times, cpus, color=color2, linewidth=2, linestyle='--', label='CPU')
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ax2.tick_params(axis='y', labelcolor=color2)
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# Title and legend
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plt.title(f'{language} - Resursanvändning över tid', fontsize=14, fontweight='bold')
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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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ax1.legend(lines1 + lines2, labels1 + labels2, loc='upper right')
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plt.tight_layout()
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# Save
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output_file = output_dir / f'{language}_timeline.svg'
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plt.savefig(output_file, format='svg', dpi=300)
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plt.close()
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print(f"Created {output_file}")
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def create_comparison_chart(languages_data, output_dir, metric='memory'):
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"""Create a comparison chart for multiple languages."""
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fig, ax = plt.subplots(figsize=(14, 8))
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colors = plt.cm.tab20(np.linspace(0, 1, len(languages_data)))
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for idx, (language, times, values) in enumerate(languages_data):
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if len(times) > 0:
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ax.plot(times, values, label=language, linewidth=2, color=colors[idx])
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if metric == 'memory':
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ax.set_ylabel('Minne (MB)', fontsize=12)
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ax.set_title('Minnesanvändning över tid - Jämförelse', fontsize=14, fontweight='bold')
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else:
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ax.set_ylabel('CPU (%)', fontsize=12)
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ax.set_title('CPU-användning över tid - Jämförelse', fontsize=14, fontweight='bold')
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ax.set_xlabel('Tid (ms)', fontsize=12)
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ax.grid(True, alpha=0.3)
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ax.legend(loc='upper right', fontsize=10)
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plt.tight_layout()
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output_file = output_dir / f'comparison_{metric}.svg'
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plt.savefig(output_file, format='svg', dpi=300)
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plt.close()
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print(f"Created {output_file}")
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def main():
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if len(sys.argv) < 2:
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print("Usage: python visualize_timelines.py <timelines_dir> [output_dir]")
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print("Example: python visualize_timelines.py timelines charts")
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sys.exit(1)
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timelines_dir = Path(sys.argv[1])
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output_dir = Path(sys.argv[2]) if len(sys.argv) > 2 else Path('charts')
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if not timelines_dir.exists():
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print(f"Error: Directory {timelines_dir} does not exist")
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sys.exit(1)
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output_dir.mkdir(exist_ok=True)
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# Collect data for all languages
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all_languages = []
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# Process each language
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for lang_dir in sorted(timelines_dir.iterdir()):
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if lang_dir.is_dir():
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language = lang_dir.name
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# Find the best run (usually run_2.tsv)
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timeline_file = lang_dir / 'run_2.tsv'
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if timeline_file.exists():
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times, memories, cpus = read_timeline_data(timeline_file)
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if len(times) > 0:
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# Create individual chart
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create_timeline_chart(language, times, memories, cpus, output_dir)
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# Store for comparison
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all_languages.append((language, times, memories))
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# Create comparison charts (top 10 fastest languages)
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if len(all_languages) > 0:
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# Sort by execution time and take top 10
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all_languages.sort(key=lambda x: x[1][-1] if len(x[1]) > 0 else float('inf'))
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top_10 = all_languages[:10]
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create_comparison_chart(top_10, output_dir, 'memory')
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# Create comparison for slowest languages
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if len(all_languages) > 10:
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slowest = all_languages[-5:]
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create_comparison_chart(slowest, output_dir, 'memory')
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print(f"\nAll charts saved to {output_dir}/")
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if __name__ == '__main__':
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main()
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