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