57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
|
"""
|
|||
|
|
Optimize orbit data by downsampling excessively detailed orbits
|
|||
|
|
灶神星(Vesta)的轨道数据被过度采样了（31,825个点），降采样到合理的数量
|
|||
|
|
"""
|
|||
|
|
import asyncio
|
|||
|
|
from sqlalchemy import text
|
|||
|
|
from app.database import engine
|
|||
|
|
|
|||
|
|
|
|||
|
|
async def optimize_vesta_orbit():
|
|||
|
|
"""Downsample Vesta orbit from 31,825 points to ~1,326 points (every 24th point)"""
|
|||
|
|
async with engine.begin() as conn:
|
|||
|
|
# Get current Vesta orbit data
|
|||
|
|
result = await conn.execute(text("""
|
|||
|
|
SELECT points, num_points
|
|||
|
|
FROM orbits
|
|||
|
|
WHERE body_id = '2000004'
|
|||
|
|
"""))
|
|||
|
|
row = result.fetchone()
|
|||
|
|
|
|||
|
|
if not row:
|
|||
|
|
print("❌ Vesta orbit not found")
|
|||
|
|
return
|
|||
|
|
|
|||
|
|
points = row[0] # JSONB array
|
|||
|
|
current_count = row[1]
|
|||
|
|
|
|||
|
|
print(f"当前Vesta轨道点数: {current_count}")
|
|||
|
|
print(f"实际数组长度: {len(points)}")
|
|||
|
|
|
|||
|
|
# Downsample: take every 24th point (0.04 days * 24 ≈ 1 day per point)
|
|||
|
|
downsampled = points[::24]
|
|||
|
|
new_count = len(downsampled)
|
|||
|
|
|
|||
|
|
print(f"降采样后点数: {new_count}")
|
|||
|
|
print(f"数据大小减少: {current_count - new_count} 点")
|
|||
|
|
print(f"降采样比例: {current_count / new_count:.1f}x")
|
|||
|
|
|
|||
|
|
# Calculate size reduction
|
|||
|
|
import json
|
|||
|
|
old_size = len(json.dumps(points))
|
|||
|
|
new_size = len(json.dumps(downsampled))
|
|||
|
|
print(f"JSON大小: {old_size:,} -> {new_size:,} bytes ({old_size/new_size:.1f}x)")
|
|||
|
|
|
|||
|
|
# Update database
|
|||
|
|
await conn.execute(text("""
|
|||
|
|
UPDATE orbits
|
|||
|
|
SET points = :points, num_points = :num_points
|
|||
|
|
WHERE body_id = '2000004'
|
|||
|
|
"""), {"points": json.dumps(downsampled), "num_points": new_count})
|
|||
|
|
|
|||
|
|
print("✅ Vesta轨道数据已优化")
|
|||
|
|
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
asyncio.run(optimize_vesta_orbit())
|