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Turf-MCP

by es3154
MIT License
  • Apple
  • Linux
classification.py2.89 kB
# 空间分类函数 from fastmcp import FastMCP from turf_mcp.utils import call_js_script classification_mcp = FastMCP("classification") @classification_mcp.tool async def nearestPoint(target_point: str, points: str) -> str: """ 查找距离目标点最近的点特征。 此功能从点集合中查找距离给定目标点最近的点特征,并返回该点及其距离信息。 Args: target_point: 目标点特征 - 类型: str (JSON 字符串格式的 GeoJSON Feature) - 格式: Feature with Point geometry - 示例: '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}' points: 点特征集合 - 类型: str (JSON 字符串格式的 GeoJSON FeatureCollection) - 格式: FeatureCollection with Point features - 示例: '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.833, 39.284]}}, ...]}' Returns: str: JSON 字符串格式的最近点特征 - 类型: GeoJSON Feature with Point geometry and distance property - 格式: {"type": "Feature", "geometry": {"type": "Point", "coordinates": [lng, lat]}, "properties": {"distance": 距离数值, ...}} - 示例: '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.833, 39.284]}, "properties": {"distance": 12.34, ...}}' Raises: Exception: 当 JavaScript 执行失败、超时或输入数据格式错误时抛出异常 Example: >>> import asyncio >>> target_point = '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.343, 39.984]}}' >>> points = '{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.833, 39.284]}}]}' >>> result = asyncio.run(nearestPoint(target_point, points)) >>> print(result) '{"type": "Feature", "geometry": {"type": "Point", "coordinates": [-75.833, 39.284]}, "properties": {"distance": 12.34, ...}}' Notes: - 输入参数 target_point 和 points 必须是有效的 JSON 字符串 - 坐标顺序为 [经度, 纬度] (WGS84 坐标系) - 计算的是球面距离,单位为千米 - 返回的点特征包含原始属性以及新增的 distance 属性 - 依赖于 Turf.js 库和 Node.js 环境 """ js_script = f""" const turf = require('@turf/turf'); const targetPoint = JSON.parse('{target_point}'); const points = JSON.parse('{points}'); const result = turf.nearestPoint(targetPoint, points); console.log(JSON.stringify(result)); """ try: return await call_js_script(js_script) except Exception as e: raise Exception(f"执行异常: {str(e)}")

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