105 lines
5.2 KiB
Python
105 lines
5.2 KiB
Python
"""
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scripts/example_workflow.py
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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端到端示例：演示 geo_tools 的完整工作流。
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运行方式
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--------
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cd F:\\@Project\\python\\geo_tools
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python scripts/example_workflow.py
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"""
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from __future__ import annotations
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from pathlib import Path
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# 添加项目根目录到路径（开发模式未安装时使用）
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import sys
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import geo_tools
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from geo_tools.utils.logger import get_logger
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logger = get_logger("example_workflow")
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DATA_DIR = Path(__file__).parent.parent / "data" / "sample"
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OUTPUT_DIR = Path(__file__).parent.parent / "output"
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OUTPUT_DIR.mkdir(exist_ok=True)
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def main() -> None:
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logger.info("=" * 60)
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logger.info("geo_tools 端到端工作流示例 v%s", geo_tools.__version__)
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logger.info("=" * 60)
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# ── 1. 读取示例点数据 ──────────────────────────────────────────
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logger.info("\n[步骤 1] 读取示例点数据（GeoJSON）")
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points = geo_tools.read_vector(DATA_DIR / "sample_points.geojson")
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logger.info(" 读取完成：%d 条要素，CRS=%s", len(points), points.crs)
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logger.info(" 字段：%s", list(points.columns))
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# ── 2. 读取示例面数据 ──────────────────────────────────────────
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logger.info("\n[步骤 2] 读取示例区域多边形（GeoJSON）")
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regions = geo_tools.read_vector(DATA_DIR / "sample_regions.geojson")
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logger.info(" 区域列表：%s", regions["name"].tolist())
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# ── 3. 数据校验 ───────────────────────────────────────────────
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logger.info("\n[步骤 3] 几何有效性校验")
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stats = geo_tools.validate_geometry(points)
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logger.info(" 点数据校验结果：%s", stats)
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stats = geo_tools.validate_geometry(regions)
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logger.info(" 面数据校验结果：%s", stats)
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# ── 4. 坐标系信息 ─────────────────────────────────────────────
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logger.info("\n[步骤 4] 查询 CRS 信息")
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crs_info = geo_tools.get_crs_info("EPSG:4326")
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logger.info(" WGS84 信息：%s", crs_info)
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proj_crs = geo_tools.suggest_projected_crs(116.4, 39.9)
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logger.info(" 北京适合的投影 CRS：%s", proj_crs)
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# ── 5. 重投影 ─────────────────────────────────────────────────
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logger.info("\n[步骤 5] 重投影到 Web Mercator（用于可视化）")
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points_3857 = geo_tools.reproject(points, "EPSG:3857")
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logger.info(" 重投影完成：CRS=%s", points_3857.crs)
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# ── 6. 面积加权均值 ───────────────────────────────────────────
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logger.info("\n[步骤 6] 面积加权均值计算（示例：用 buffer 生成面数据）")
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# 先将点缓冲生成面数据
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points_buffered = points.to_crs("EPSG:3857").copy()
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points_buffered["geometry"] = points_buffered.geometry.buffer(100_000) # 100km缓冲
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points_buffered = points_buffered.to_crs("EPSG:4326")
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from geo_tools.analysis.stats import area_weighted_mean
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aw_result = area_weighted_mean(points_buffered, value_col="value")
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logger.info(" 全局面积加权均值：%.4f", aw_result["area_weighted_mean"])
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# ── 7. 按位置选择 ─────────────────────────────────────────────
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logger.info("\n[步骤 7] 按位置选择：筛选华南区域内的城市")
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hua_nan = regions[regions["name"] == "华南"]
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points_in_huanan = geo_tools.select_by_location(points, hua_nan, predicate="intersects")
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logger.info(" 华南区域内的城市：%s", points_in_huanan["name"].tolist())
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# ── 8. 统计汇总 ───────────────────────────────────────────────
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logger.info("\n[步骤 8] 属性统计汇总")
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from geo_tools.analysis.stats import summarize_attributes
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summary = summarize_attributes(points, columns=["value"], group_col="category")
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logger.info(" 按分类汇总：\n%s", summary.to_string(index=False))
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# ── 9. 写出结果 ───────────────────────────────────────────────
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logger.info("\n[步骤 9] 写出处理结果")
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out_geojson = OUTPUT_DIR / "result_points_3857.geojson"
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geo_tools.write_vector(points_3857, out_geojson)
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logger.info(" GeoJSON 写出：%s", out_geojson)
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out_gpkg = OUTPUT_DIR / "results.gpkg"
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geo_tools.write_gpkg(points, out_gpkg, layer="original_points")
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geo_tools.write_gpkg(regions, out_gpkg, layer="regions", mode="a")
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logger.info(" GPKG 写出（2 图层）：%s", out_gpkg)
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logger.info("\n" + "=" * 60)
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logger.info("工作流演示完成！输出目录：%s", OUTPUT_DIR)
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logger.info("=" * 60)
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if __name__ == "__main__":
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main()
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