import arcpy# 输入参数 input_features = arcpy.GetParameterAsText(0) # 连接要素 join_field = arcpy.GetParameterAsText(1) # 连接字段 target_feature = arcpy.GetParameterAsText(2) # 目标要素 target_field = arcpy.GetParameterAsText(3) # 目标字段 area_threshold = arcpy.GetParameterAsText(4) # 面积阈值 # 创建空间连接 arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 选择面积大于阈值的连接要素 arcpy.Select_analysis("in_memory/spatial_join", "in_memory/selected_features", "''Shape_Area' > ' + str(area_threshold) # 统计相同连接字段值的面积总和 arcpy.Statistics_analysis("in_memory/selected_features", "in_memory/summarized_features", "Shape_Area SUM", join_field) # 创建字典,存储连接字段值和对应的面积总和 sum_dict = {} with arcpy.da.SearchCursor("in_memory/summarized_features", [join_field, "SUM_Shape_Area"]) as cursor: for row in cursor: sum_dict[row[0]] = row # 更新目标要素中的字段值 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field]) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = str(area_sum) cursor.updateRow(row) # 导出结果 arcpy.CopyFeatures_management(target_feature, arcpy.GetParameterAsText(5))运行出错:SyntaxError: EOL while scanning string literal (空间连接.py, line 11) 执行(fzzz)失败。请改正代码

时间: 2023-12-03 17:45:44 浏览: 29
根据错误提示,是因为代码中第 11 行字符串结束符缺失。可以尝试在该行末尾添加一个单引号来修复该错误,代码修改如下: ```python arcpy.Select_analysis("in_memory/spatial_join", "in_memory/selected_features", "''Shape_Area' > '" + str(area_threshold) + "'") ``` 另外,代码中还有一个错误,第 22 行的 `row[0] = str(area_sum)` 应该修改为 `row[0] = str(area_sum[1])`,因为 `sum_dict[join_value]` 返回的是一个包含连接字段值和面积总和的元组,用索引 1 取出面积总和才是正确的。修改后的完整代码如下: ```python import arcpy # 输入参数 input_features = arcpy.GetParameterAsText(0) join_field = arcpy.GetParameterAsText(1) target_feature = arcpy.GetParameterAsText(2) target_field = arcpy.GetParameterAsText(3) area_threshold = arcpy.GetParameterAsText(4) # 创建空间连接 arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 选择面积大于阈值的连接要素 arcpy.Select_analysis("in_memory/spatial_join", "in_memory/selected_features", "''Shape_Area' > '" + str(area_threshold) + "'") # 统计相同连接字段值的面积总和 arcpy.Statistics_analysis("in_memory/selected_features", "in_memory/summarized_features", "Shape_Area SUM", join_field) # 创建字典,存储连接字段值和对应的面积总和 sum_dict = {} with arcpy.da.SearchCursor("in_memory/summarized_features", [join_field, "SUM_Shape_Area"]) as cursor: for row in cursor: sum_dict[row[0]] = row # 更新目标要素中的字段值 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field]) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = str(area_sum[1]) cursor.updateRow(row) # 导出结果 arcpy.CopyFeatures_management(target_feature, arcpy.GetParameterAsText(5)) ```

相关推荐

import arcpy# 输入参数 input_features = arcpy.GetParameterAsText(0) # 连接要素 join_field = arcpy.GetParameterAsText(1) # 连接字段 target_feature = arcpy.GetParameterAsText(2) # 目标要素 target_field = arcpy.GetParameterAsText(3) # 目标字段 area_threshold = arcpy.GetParameterAsText(4) # 面积阈值 # 创建空间连接 arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 选择面积大于阈值的连接要素 arcpy.Select_analysis("in_memory/spatial_join", "in_memory/selected_features", ""Shape_Area" > " + str(area_threshold)) # 统计相同连接字段值的面积总和 arcpy.Statistics_analysis("in_memory/selected_features", "in_memory/summarized_features", "Shape_Area SUM", join_field) # 创建字典,存储连接字段值和对应的面积总和 sum_dict = {} with arcpy.da.SearchCursor("in_memory/summarized_features", [join_field, "SUM_Shape_Area"]) as cursor: for row in cursor: sum_dict[row[0]] = row # 更新目标要素中的字段值 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field]) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = str(area_sum) cursor.updateRow(row) # 导出结果 arcpy.CopyFeatures_management(target_feature, arcpy.GetParameterAsText(5))运行上面代码出现错误:SyntaxError: invalid syntax (空间连接.py, line 11) 执行(fzzz)失败。请改正出完整的代码

import arcpy # 输入参数 input_features = arcpy.GetParameterAsText(0) # 连接要素 join_field = arcpy.GetParameterAsText(1) # 连接字段 target_feature = arcpy.GetParameterAsText(2) # 目标要素 target_field = arcpy.GetParameterAsText(3) # 目标字段 area_threshold = arcpy.GetParameterAsText(4) # 面积阈值 # 创建空间连接 arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 选择面积大于阈值的连接要素 arcpy.Select_analysis("in_memory/spatial_join", "in_memory/selected_features", "Shape_Area > " + area_threshold) # 统计相同连接字段值的面积总和 arcpy.Statistics_analysis("in_memory/selected_features", "in_memory/summarized_features", "Shape_Area SUM", join_field) # 创建字典,存储连接字段值和对应的面积总和 sum_dict = {} with arcpy.da.SearchCursor("in_memory/summarized_features", [join_field, "SUM_Shape_Area"]) as cursor: for row in cursor: sum_dict[row[0]] = row[1] # 更新目标要素中的字段值 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field]) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = str(area_sum) cursor.updateRow(row) # 导出结果 arcpy.CopyFeatures_management(target_feature, arcpy.GetParameterAsText(5))运行出现错误Traceback (most recent call last): File "D:\实验2\空间连接.py", line 13, in <module> File "c:\program files (x86)\arcgis\desktop10.2\arcpy\arcpy\analysis.py", line 84, in Select raise e ExecuteError: ERROR 000358: 无效的表达式 "Shape_Area" > 600 执行(Select)失败。 执行(fzzz)失败。请改正代码并写出完整可复制的代码

import sys sys.tracebacklimit = 0 import os os.environ['PYTHONUNBUFFERED'] = '1'import arcpy # 获取参数 input_features = arcpy.GetParameterAsText(0) join_field = arcpy.GetParameterAsText(1) target_feature = arcpy.GetParameterAsText(2) target_field = arcpy.GetParameterAsText(3) area_threshold = arcpy.GetParameterAsText(4) # 创建空间连接 join_result = arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 使用MakeFeatureLayer创建要素图层,并使用AddFieldDelimiters处理字段名称 join_layer = arcpy.management.MakeFeatureLayer(join_result, "join_layer").getOutput(0) join_field_name = arcpy.AddFieldDelimiters(join_layer, join_field) # 使用SelectLayerByAttribute选择重叠面积大于阈值的要素 arcpy.management.SelectLayerByAttribute(join_layer, "NEW_SELECTION", "Shape_Area > " + str(area_threshold)) # 使用SummaryStatistics工具进行面积求和 summary_table = arcpy.Statistics_analysis(join_layer, "in_memory/summary_table", [["Shape_Area", "SUM"]], join_field_name) # 使用TableToNumPyArray将结果转换为字典 sum_dict = {} with arcpy.da.TableToNumPyArray(summary_table, [join_field, "SUM_Shape_Area"]) as arr: for row in arr: sum_dict[row[0]] = row[1] # 使用UpdateCursor更新目标要素类的目标字段 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field], sql_clause=(None, "ORDER BY OBJECTID")) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = area_sum cursor.updateRow(row) # 导出结果 output_feature = arcpy.GetParameterAsText(5) arcpy.CopyFeatures_management(target_feature, output_feature) # 删除游标对象和要素图层对象 del cursor, join_layer运行错误SyntaxError: invalid syntax (空间连接.py, line 4) 执行(ccc)失败。请改正代码

import arcpy # 获取参数 input_features = arcpy.GetParameterAsText(0) join_field = arcpy.GetParameterAsText(1) target_feature = arcpy.GetParameterAsText(2) target_field = arcpy.GetParameterAsText(3) area_threshold = arcpy.GetParameterAsText(4) # 创建空间连接 join_result = arcpy.SpatialJoin_analysis(input_features, target_feature, "in_memory/spatial_join", "JOIN_ONE_TO_ONE", "KEEP_ALL", "", "INTERSECT") # 使用MakeFeatureLayer创建要素图层,并使用AddFieldDelimiters处理字段名称 join_layer = arcpy.management.MakeFeatureLayer(join_result, "join_layer").getOutput(0) join_field_name = arcpy.AddFieldDelimiters(join_layer, join_field) # 使用SelectLayerByAttribute选择重叠面积大于阈值的要素 arcpy.management.SelectLayerByAttribute(join_layer, "NEW_SELECTION", "Shape_Area > " + str(area_threshold)) # 使用SummaryStatistics工具进行面积求和 summary_table = arcpy.Statistics_analysis(join_layer, "in_memory/summary_table", [["Shape_Area", "SUM"]], join_field_name) # 使用TableToNumPyArray将结果转换为字典 sum_dict = {} with arcpy.da.TableToNumPyArray(summary_table, [join_field, "SUM_Shape_Area"]) as arr: for row in arr: sum_dict[row[0]] = row[1] # 使用UpdateCursor更新目标要素类的目标字段 with arcpy.da.UpdateCursor(target_feature, [target_field, join_field], sql_clause=(None, "ORDER BY OBJECTID")) as cursor: for row in cursor: join_value = row[1] if join_value in sum_dict: area_sum = sum_dict[join_value] row[0] = area_sum cursor.updateRow(row) # 导出结果 output_feature = arcpy.GetParameterAsText(5) arcpy.CopyFeatures_management(target_feature, output_feature) # 删除游标对象 del cursor运行错误:Traceback (most recent call last): File "D:\实验2\空间连接.py", line 25, in <module> AttributeError: __exit__ 执行(ccc)失败。请改正代码

最新推荐

recommend-type

ansys maxwell

ansys maxwell
recommend-type

matlab基于不确定性可达性优化的自主鲁棒操作.zip

matlab基于不确定性可达性优化的自主鲁棒操作.zip
recommend-type

pytest-2.8.0.zip

文件操作、数据分析和网络编程等。Python社区提供了大量的第三方库,如NumPy、Pandas和Requests,极大地丰富了Python的应用领域,从数据科学到Web开发。Python库的丰富性是Python成为最受欢迎的编程语言之一的关键原因之一。这些库不仅为初学者提供了快速入门的途径,而且为经验丰富的开发者提供了强大的工具,以高效率、高质量地完成复杂任务。例如,Matplotlib和Seaborn库在数据可视化领域内非常受欢迎,它们提供了广泛的工具和技术,可以创建高度定制化的图表和图形,帮助数据科学家和分析师在数据探索和结果展示中更有效地传达信息。
recommend-type

信息安全课程实验C++实现DES等算法源代码

信息安全课程实验C++实现DES等算法源代码
recommend-type

基于知识图谱的医疗诊断知识问答系统python源码+项目说明.zip

环境 python >= 3.6 pyahocorasick==1.4.2 requests==2.25.1 gevent==1.4.0 jieba==0.42.1 six==1.15.0 gensim==3.8.3 matplotlib==3.1.3 Flask==1.1.1 numpy==1.16.0 bert4keras==0.9.1 tensorflow==1.14.0 Keras==2.3.1 py2neo==2020.1.1 tqdm==4.42.1 pandas==1.0.1 termcolor==1.1.0 itchat==1.3.10 ahocorasick==0.9 flask_compress==1.9.0 flask_cors==3.0.10 flask_json==0.3.4 GPUtil==1.4.0 pyzmq==22.0.3 scikit_learn==0.24.1 效果展示 为能最简化使用该系统,不需要繁杂的部署各种七七八八的东西,当前版本使用的itchat将问答功能集成到微信做演示,这需要你的微信能登入网页微信才能使用itchat;另外对话上下文并没
recommend-type

zigbee-cluster-library-specification

最新的zigbee-cluster-library-specification说明文档。
recommend-type

管理建模和仿真的文件

管理Boualem Benatallah引用此版本:布阿利姆·贝纳塔拉。管理建模和仿真。约瑟夫-傅立叶大学-格勒诺布尔第一大学,1996年。法语。NNT:电话:00345357HAL ID:电话:00345357https://theses.hal.science/tel-003453572008年12月9日提交HAL是一个多学科的开放存取档案馆,用于存放和传播科学研究论文,无论它们是否被公开。论文可以来自法国或国外的教学和研究机构,也可以来自公共或私人研究中心。L’archive ouverte pluridisciplinaire
recommend-type

实现实时数据湖架构:Kafka与Hive集成

![实现实时数据湖架构:Kafka与Hive集成](https://img-blog.csdnimg.cn/img_convert/10eb2e6972b3b6086286fc64c0b3ee41.jpeg) # 1. 实时数据湖架构概述** 实时数据湖是一种现代数据管理架构,它允许企业以低延迟的方式收集、存储和处理大量数据。与传统数据仓库不同,实时数据湖不依赖于预先定义的模式,而是采用灵活的架构,可以处理各种数据类型和格式。这种架构为企业提供了以下优势: - **实时洞察:**实时数据湖允许企业访问最新的数据,从而做出更明智的决策。 - **数据民主化:**实时数据湖使各种利益相关者都可
recommend-type

2. 通过python绘制y=e-xsin(2πx)图像

可以使用matplotlib库来绘制这个函数的图像。以下是一段示例代码: ```python import numpy as np import matplotlib.pyplot as plt def func(x): return np.exp(-x) * np.sin(2 * np.pi * x) x = np.linspace(0, 5, 500) y = func(x) plt.plot(x, y) plt.xlabel('x') plt.ylabel('y') plt.title('y = e^{-x} sin(2πx)') plt.show() ``` 运行这段
recommend-type

JSBSim Reference Manual

JSBSim参考手册,其中包含JSBSim简介,JSBSim配置文件xml的编写语法,编程手册以及一些应用实例等。其中有部分内容还没有写完,估计有生之年很难看到完整版了,但是内容还是很有参考价值的。