refactor: 重构项目结构，将geo_tools重命名为app并更新相关引用
- 将主包名从geo_tools改为app - 更新所有模块中的引用路径 - 迁移并更新测试用例 - 添加项目规则文档 - 保持原有功能不变，仅进行结构调整
This commit is contained in:
188
scripts/其他工具/A耕作层厚度栅格制作_新1.py
Normal file
188
scripts/其他工具/A耕作层厚度栅格制作_新1.py
Normal file
@@ -0,0 +1,188 @@
|
||||
import os
|
||||
from pathlib import Path
|
||||
import time
|
||||
|
||||
import geopandas as gpd
|
||||
from geopandas.io import file
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
|
||||
def assign_gzchd_flexible_v2(soil_prop, point_path, polygon_path, output_path):
|
||||
print("正在读取数据...")
|
||||
points = gpd.read_file(point_path)
|
||||
polygons = gpd.read_file(polygon_path)
|
||||
|
||||
# 1. 坐标系转换
|
||||
if points.crs != polygons.crs:
|
||||
print(f"坐标系不一致，正在转换点数据...")
|
||||
points = points.to_crs(polygons.crs)
|
||||
|
||||
# 2. 预处理, 判断样点是否存在TZ字段，如果不存在，则用TDLYLX字段代替,并将其转为字符串类型,如果两个字段都不存在，则报错
|
||||
if 'TZ' not in points.columns:
|
||||
if 'TDLYLX' in points.columns:
|
||||
points['TZ'] = points['TDLYLX'].astype(str).str.strip()
|
||||
else:
|
||||
raise ValueError("点要素类中不存在TZ或TDLYLX字段，无法进行匹配！")
|
||||
else:
|
||||
points['TZ'] = points['TZ'].astype(str).str.strip()
|
||||
|
||||
polygons['TZ'] = polygons['TZ'].astype(str).str.strip()
|
||||
|
||||
# 确保 GZCHD 是数值类型，避免合并时类型冲突
|
||||
points[soil_prop] = pd.to_numeric(points[soil_prop], errors='coerce').fillna(0)
|
||||
|
||||
if soil_prop in polygons.columns:
|
||||
polygons = polygons.drop(columns=[soil_prop])
|
||||
|
||||
# 辅助函数：按指定字段分组进行最近点匹配
|
||||
def match_by_attribute(poly_gdf, pt_gdf, attr_name, suffix):
|
||||
if attr_name not in poly_gdf.columns or attr_name not in pt_gdf.columns:
|
||||
return None, []
|
||||
|
||||
poly_sub = poly_gdf[poly_gdf[attr_name].notna()].copy()
|
||||
point_sub = pt_gdf[pt_gdf[attr_name].notna()].copy()
|
||||
|
||||
if poly_sub.empty or point_sub.empty:
|
||||
return None, []
|
||||
|
||||
poly_sub[attr_name] = poly_sub[attr_name].astype(str).str.strip()
|
||||
point_sub[attr_name] = point_sub[attr_name].astype(str).str.strip()
|
||||
|
||||
common_values = set(poly_sub[attr_name].unique()) & set(point_sub[attr_name].unique())
|
||||
if not common_values:
|
||||
return None, []
|
||||
|
||||
matched_parts = []
|
||||
matched_ids = []
|
||||
for value in common_values:
|
||||
poly_part = poly_sub[poly_sub[attr_name] == value].copy()
|
||||
point_part = point_sub[point_sub[attr_name] == value][[soil_prop, 'geometry']].copy()
|
||||
if poly_part.empty or point_part.empty:
|
||||
continue
|
||||
|
||||
matched_part = gpd.sjoin_nearest(poly_part, point_part, how='left', rsuffix=suffix)
|
||||
matched_part = matched_part[~matched_part.index.duplicated(keep='first')]
|
||||
if not matched_part.empty:
|
||||
matched_parts.append(matched_part)
|
||||
matched_ids.extend(matched_part.index.tolist())
|
||||
|
||||
if matched_parts:
|
||||
return pd.concat(matched_parts), matched_ids
|
||||
return None, []
|
||||
|
||||
matched_results = []
|
||||
matched_indices = []
|
||||
|
||||
# --- 第一步：按相同 TZ 匹配 ---
|
||||
print("步骤 1: 正在匹配相同 TZ 的最近点...")
|
||||
first_matched, first_ids = match_by_attribute(polygons, points, 'TZ', '_p1')
|
||||
if first_matched is not None and not first_matched.empty:
|
||||
matched_results.append(first_matched)
|
||||
matched_indices.extend(first_ids)
|
||||
|
||||
# --- 第二步：按 TS 匹配未匹配面 ---
|
||||
unmatched_mask = ~polygons.index.isin(matched_indices)
|
||||
remaining_polygons = polygons[unmatched_mask].copy()
|
||||
print(f"步骤 2: 正在为 {len(remaining_polygons)} 个要素匹配 TS 最近点...")
|
||||
|
||||
if not remaining_polygons.empty:
|
||||
ts_matched, ts_ids = match_by_attribute(remaining_polygons, points, 'TS', '_p_ts')
|
||||
if ts_matched is not None and not ts_matched.empty:
|
||||
matched_results.append(ts_matched)
|
||||
matched_indices.extend(ts_ids)
|
||||
remaining_polygons = polygons[~polygons.index.isin(matched_indices)].copy()
|
||||
print(f"已匹配 TS: {len(ts_ids)} 个要素，剩余 {len(remaining_polygons)} 个。")
|
||||
else:
|
||||
print("未匹配到 TS 类型要素，继续下一步。")
|
||||
|
||||
# --- 第三步：按 YL 匹配未匹配面 ---
|
||||
if not remaining_polygons.empty:
|
||||
print(f"步骤 3: 正在为 {len(remaining_polygons)} 个要素匹配 YL 最近点...")
|
||||
yl_matched, yl_ids = match_by_attribute(remaining_polygons, points, 'YL', '_p_yl')
|
||||
if yl_matched is not None and not yl_matched.empty:
|
||||
matched_results.append(yl_matched)
|
||||
matched_indices.extend(yl_ids)
|
||||
remaining_polygons = polygons[~polygons.index.isin(matched_indices)].copy()
|
||||
print(f"已匹配 YL: {len(yl_ids)} 个要素，剩余 {len(remaining_polygons)} 个。")
|
||||
else:
|
||||
print("未匹配到 YL 类型要素，继续下一步。")
|
||||
|
||||
# --- 第四步：按 TL 匹配未匹配面 ---
|
||||
if not remaining_polygons.empty:
|
||||
print(f"步骤 4: 正在为 {len(remaining_polygons)} 个要素匹配 TL 最近点...")
|
||||
tl_matched, tl_ids = match_by_attribute(remaining_polygons, points, 'TL', '_p_tl')
|
||||
if tl_matched is not None and not tl_matched.empty:
|
||||
matched_results.append(tl_matched)
|
||||
matched_indices.extend(tl_ids)
|
||||
remaining_polygons = polygons[~polygons.index.isin(matched_indices)].copy()
|
||||
print(f"已匹配 TL: {len(tl_ids)} 个要素，剩余 {len(remaining_polygons)} 个。")
|
||||
else:
|
||||
print("未匹配到 TL 类型要素，继续全局最近点。")
|
||||
|
||||
else:
|
||||
print("没有未匹配的面要素，跳过 TS/YL/TL 匹配。")
|
||||
|
||||
# --- 最后：全局最近点匹配剩余面 ---
|
||||
unmatched_mask = ~polygons.index.isin(matched_indices)
|
||||
remaining_polygons = polygons[unmatched_mask].copy()
|
||||
print(f"最后一步: 正在为 {len(remaining_polygons)} 个要素匹配全局最近点...")
|
||||
|
||||
if not remaining_polygons.empty:
|
||||
point_pool = points[[soil_prop, 'geometry']]
|
||||
step_final = gpd.sjoin_nearest(remaining_polygons, point_pool, how='left', rsuffix='_p2')
|
||||
step_final = step_final[~step_final.index.duplicated(keep='first')]
|
||||
matched_results.append(step_final)
|
||||
|
||||
# --- 第三步：稳健合并 ---
|
||||
print("正在合并数据...")
|
||||
# 过滤掉列表中可能的 None 或空 DataFrame，防止 FutureWarning
|
||||
to_concat = [res for res in matched_results if res is not None and not res.empty]
|
||||
|
||||
if to_concat:
|
||||
final_gdf = pd.concat(to_concat)
|
||||
else:
|
||||
# 如果没有任何匹配结果，返回带空 GZCHD 的原面要素
|
||||
final_gdf = polygons.copy()
|
||||
final_gdf[soil_prop] = 0
|
||||
|
||||
# --- 4. 清理与保存 ---
|
||||
# 删除临时列
|
||||
cols_to_drop = [
|
||||
c for c in final_gdf.columns
|
||||
if 'index_' in c
|
||||
or '_p1' in c
|
||||
or '_p2' in c
|
||||
or '_p_ts' in c
|
||||
or '_p_yl' in c
|
||||
or '_p_tl' in c
|
||||
]
|
||||
final_gdf = final_gdf.drop(columns=cols_to_drop)
|
||||
|
||||
# 强制去重复列名
|
||||
final_gdf = final_gdf.loc[:, ~final_gdf.columns.duplicated()]
|
||||
|
||||
# 填充空值并确保类型一致
|
||||
if soil_prop in final_gdf.columns:
|
||||
final_gdf[soil_prop] = final_gdf[soil_prop].fillna(0)
|
||||
else:
|
||||
final_gdf[soil_prop] = 0
|
||||
|
||||
print(f"正在保存结果至: {output_path}")
|
||||
final_gdf.to_file(output_path, encoding='utf-8')
|
||||
print("处理完成！")
|
||||
|
||||
return final_gdf
|
||||
|
||||
if __name__ == "__main__":
|
||||
# 遍历文件夹中所有样点shp文件，并进行处理
|
||||
shp_file = r"E:\@三普属性图出图\测试\YXTCHD.shp" # 样点数据文件夹
|
||||
dltb_file = r"E:\@三普属性图出图\广西天峨县\@基础数据\土壤类型图\土壤类型图.shp" # 耕地图斑
|
||||
output_folder = r"E:\@三普属性图出图\广西天峨县" # 输出文件夹
|
||||
|
||||
assign_gzchd_flexible_v2(
|
||||
soil_prop= "YXTCHD", # 耕地层厚度字段名
|
||||
point_path=shp_file, # 样点数据
|
||||
polygon_path= dltb_file,
|
||||
output_path=fr'{output_folder}\YXTCHD.shp' # 输出文件
|
||||
)
|
||||
time.sleep(2) # 防止文件读写冲突
|
||||
Reference in New Issue
Block a user