134 lines
5.1 KiB
Python
Executable file
134 lines
5.1 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
# This is free software for the public good of a permacomputer hosted at
|
|
# permacomputer.com, an always-on computer by the people, for the people.
|
|
# One which is durable, easy to repair, & distributed like tap water
|
|
# for machine learning intelligence.
|
|
#
|
|
# The permacomputer is community-owned infrastructure optimized around
|
|
# four values:
|
|
#
|
|
# TRUTH First principles, math & science, open source code freely distributed
|
|
# FREEDOM Voluntary partnerships, freedom from tyranny & corporate control
|
|
# HARMONY Minimal waste, self-renewing systems with diverse thriving connections
|
|
# LOVE Be yourself without hurting others, cooperation through natural law
|
|
#
|
|
# This software contributes to that vision by enabling code execution across 42+ programming languages through a unified interface, accessible to all.
|
|
# Code is seeds to sprout on any abandoned technology.
|
|
|
|
"""
|
|
Generate aggregated performance charts from multiple perf.json files.
|
|
Run via: build/un -a -f reports/4.2.0/perf.json -f reports/4.2.3/perf.json -f reports/4.2.4/perf.json scripts/generate-aggregated-charts.py
|
|
"""
|
|
import json
|
|
import os
|
|
from pathlib import Path
|
|
from statistics import mean
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
|
|
# Input files from /tmp/input/
|
|
input_dir = Path('/tmp/input')
|
|
output_dir = Path('/tmp/artifacts')
|
|
output_dir.mkdir(parents=True, exist_ok=True)
|
|
|
|
# Load all perf.json files
|
|
reports = {}
|
|
for json_file in sorted(input_dir.glob('*.json')):
|
|
data = json.loads(json_file.read_text())
|
|
tag = data.get('tag', json_file.stem)
|
|
reports[tag] = data
|
|
print(f"Loaded {tag}")
|
|
|
|
if not reports:
|
|
print("ERROR: No JSON files found")
|
|
exit(1)
|
|
|
|
print(f"\nAnalyzing {len(reports)} reports...")
|
|
|
|
# Extract data
|
|
versions = sorted(reports.keys())
|
|
avg_durations = [reports[v]['summary']['avg_duration_seconds'] for v in versions]
|
|
|
|
# Extract language timings
|
|
lang_timings = {}
|
|
for v in versions:
|
|
lang_timings[v] = {}
|
|
for lang_entry in reports[v]['languages']:
|
|
lang = lang_entry['language']
|
|
dur = lang_entry['duration_seconds']
|
|
lang_timings[v][lang] = dur
|
|
|
|
# Calculate variance
|
|
all_langs = set()
|
|
for langs in lang_timings.values():
|
|
all_langs.update(langs.keys())
|
|
|
|
lang_variance = {}
|
|
for lang in all_langs:
|
|
durs = []
|
|
for v in versions:
|
|
if lang in lang_timings.get(v, {}):
|
|
dur = lang_timings[v][lang]
|
|
if isinstance(dur, (int, float)) and dur > 0:
|
|
durs.append(dur)
|
|
if len(durs) >= 2:
|
|
pct = ((max(durs) - min(durs)) / min(durs) * 100) if min(durs) > 0 else 0
|
|
lang_variance[lang] = {'min': min(durs), 'max': max(durs), 'pct': pct}
|
|
|
|
# Set dark theme
|
|
plt.style.use('dark_background')
|
|
plt.rcParams['figure.facecolor'] = '#1a1a2e'
|
|
plt.rcParams['axes.facecolor'] = '#16213e'
|
|
|
|
# Chart 1: Duration Trend
|
|
fig, ax = plt.subplots(figsize=(10, 6))
|
|
ax.plot(versions, avg_durations, marker='o', linewidth=2, markersize=10, color='#e94560')
|
|
ax.fill_between(range(len(versions)), avg_durations, alpha=0.3, color='#e94560')
|
|
ax.set_xlabel('Release', fontsize=12)
|
|
ax.set_ylabel('Average Duration (seconds)', fontsize=12)
|
|
ax.set_title('Average Test Duration Degradation Over Releases', fontsize=14, fontweight='bold')
|
|
ax.grid(True, alpha=0.3)
|
|
for i, (v, d) in enumerate(zip(versions, avg_durations)):
|
|
ax.text(i, d + 1, f'{d}s', ha='center', fontsize=10)
|
|
plt.tight_layout()
|
|
plt.savefig(str(output_dir / 'aggregated-duration-trend.png'), dpi=150, facecolor='#1a1a2e')
|
|
print('✓ aggregated-duration-trend.png')
|
|
plt.close()
|
|
|
|
# Chart 2: Language Variance
|
|
top_langs = sorted(lang_variance.items(), key=lambda x: x[1]['pct'], reverse=True)[:15]
|
|
lang_names = [k.upper() for k, v in top_langs]
|
|
variances = [v['pct'] for k, v in top_langs]
|
|
colors = ['#e94560' if v > 200 else '#f39c12' if v > 100 else '#27ae60' for v in variances]
|
|
|
|
fig, ax = plt.subplots(figsize=(12, 8))
|
|
bars = ax.barh(lang_names, variances, color=colors, edgecolor='#fff', linewidth=1)
|
|
ax.set_xlabel('Variance %', fontsize=12)
|
|
ax.set_title('Top 15 Most Unstable Languages (% Variance)', fontsize=14, fontweight='bold')
|
|
for i, (bar, var) in enumerate(zip(bars, variances)):
|
|
ax.text(var + 5, bar.get_y() + bar.get_height()/2, f'{var:.0f}%', va='center', fontsize=9)
|
|
plt.tight_layout()
|
|
plt.savefig(str(output_dir / 'aggregated-language-variance.png'), dpi=150, facecolor='#1a1a2e')
|
|
print('✓ aggregated-language-variance.png')
|
|
plt.close()
|
|
|
|
# Chart 3: Ranking Changes
|
|
fig, ax = plt.subplots(figsize=(14, 8))
|
|
for v in versions:
|
|
sorted_langs = sorted(lang_timings[v].items(), key=lambda x: x[1], reverse=True)
|
|
slowest_10 = sorted_langs[:10]
|
|
for i, (lang, dur) in enumerate(slowest_10):
|
|
ax.scatter(versions.index(v), i, s=300, alpha=0.6)
|
|
|
|
ax.set_xlabel('Release', fontsize=12)
|
|
ax.set_ylabel('Rank (0=Slowest)', fontsize=12)
|
|
ax.set_title('Ranking Instability - Top 10 Slowest Languages Per Run', fontsize=14, fontweight='bold')
|
|
ax.set_xticks(range(len(versions)))
|
|
ax.set_xticklabels(versions)
|
|
plt.tight_layout()
|
|
plt.savefig(str(output_dir / 'aggregated-ranking-changes.png'), dpi=150, facecolor='#1a1a2e')
|
|
print('✓ aggregated-ranking-changes.png')
|
|
plt.close()
|
|
|
|
print('\n✓ All charts generated successfully')
|
|
print(f'✓ Saved to {output_dir}/')
|