arcpy.na.CopyTraversedSourceFeatures(input_network_analysis_layer, output_location, edge_feature_class_name, junction_feature_class_name, turn_table_name)
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名称
|
说明
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数据类型
|
|
input_network_analysis_layer
|
将复制遍历源要素的网络分析图层。 如果网络分析图层没有有效结果，则会通过求解图层以生成有效结果。
|
Network Analyst Layer
|
|
output_location
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用来保存输出表和两个要素类的工作空间。
|
Workspace; Feature Dataset
|
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edge_feature_class_name
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将包含遍历边源要素相关信息的要素类的名称。 如果求解的网络分析图层不遍历任何边要素，则将创建空要素类。
|
String
|
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junction_feature_class_name
|
将包含遍历交汇点源要素（包括输入网络分析图层中的系统交汇点和相关点）相关信息的要素类的名称。 如果求解的网络分析图层不遍历任何交汇点，则将创建空要素类。
|
String
|
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turn_table_name
|
将包含基础边成本按比例增加的遍历通用转弯和转弯要素相关信息的表的名称。 如果求解的网络分析图层不遍历任何转弯，则将创建空表。 因为始终不会遍历受限制的转弯，因此它们始终不会包含在输出中。
|
String
|
派生输出
|
名称
|
说明
|
数据类型
|
|
edge_features
|
包含网络分析中遍历的网络数据集边的要素类。
|
Feature Class
|
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junction_features
|
包含网络分析中遍历的网络数据集交汇点的要素类。
|
Feature Class
|
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turn_table
|
包含网络分析中遍历的网络数据集转弯的表。
|
Table
|
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modified_input_network_analysis_layer
|
已解决的网络分析图层。
|
Network Analyst Layer
|
代码示例
CopyTraversedSourceFeatures 示例 1（Python 窗口）
以下 Python 窗口脚本演示了如何使用 CopyTraversedSourceFeatures 函数在内存工作空间中将遍历的边、交汇点和转弯从“路径”网络分析图层写入到要素类和表中。
arcpy.na.CopyTraversedSourceFeatures("Route", "C:/Data/Output.gdb",
"TraversedEdges",
"TraversedJunctions",
"TraversedTurns")
CopyTraversedSourceFeatures 示例 2（工作流）
以下独立 Python 脚本演示了如何使用 CopyTraversedSourceFeatures 来查找从人口普查区域质心到最近消防站的路径的共有街道。 这些结果有助于确定在紧急情况下使用最为频繁的街道。
# Name: CopyTraversedSourceFeatures_ex02.py
# Description: The scenario shows how to find the streets that are common to the
# routes between the closest fire station and the census tract
# centroids. These streets can be used to identify critical points
# in case of an emergency.
# Requirements: Network Analyst extension
# Import system modules
import os
import arcpy
from arcpy import env
try:
# Set environment settings
output_dir = "C:/Data"
# The NA layer's data will be saved to the workspace specified here
env.workspace = os.path.join(output_dir, "Output.gdb")
env.overwriteOutput = True
env.qualifiedFieldNames = False
# Set local variables
input_gdb = "C:/Data/SanFrancisco.gdb"
output_gdb = "C:/Data/Output.gdb"
network = os.path.join(input_gdb, "Transportation", "Streets_ND")
layer_name = "EmergencyRoutes"
travel_mode = "Driving Time"
facilities = os.path.join(input_gdb, "Analysis", "FireStations")
incidents = os.path.join(input_gdb, "Analysis", "TractCentroids")
edge_frequency = os.path.join(output_gdb, "EdgeFrequency")
critical_streets = os.path.join(output_gdb, "CriticalStreets")
# Create a new closest facility analysis layer.
result_object = arcpy.na.MakeClosestFacilityAnalysisLayer(
network, layer_name, travel_mode, "FROM_FACILITIES"
)
# Get the layer object from the result object. The closest facility layer can
# now be referenced using the layer object.
layer_object = result_object.getOutput(0)
# Get the names of all the sublayers within the closest facility layer.
sublayer_names = arcpy.na.GetNAClassNames(layer_object)
# Stores the layer names that we will use later
facilities_layer_name = sublayer_names["Facilities"]
incidents_layer_name = sublayer_names["Incidents"]
# Load fire station features as facilities
arcpy.na.AddLocations(layer_object, facilities_layer_name, facilities)
# Load tract centroids as incidents. Map the ID field from Tract
# Centroids as the name for incidents using field mappings
field_mappings = arcpy.na.NAClassFieldMappings(
layer_object, incidents_layer_name
)
field_mappings['Name'].mappedFieldName = "ID"
arcpy.na.AddLocations(
layer_object, incidents_layer_name, incidents, field_mappings
)
# Solve the closest facility layer and copy the travered source features to
# the output geodatabase. Use default names for the output feature
# classes and table. Retrieve the first output, which is the traversed edges.
traversed_edges = arcpy.na.CopyTraversedSourceFeatures(
layer_object, output_gdb
).getOutput(0)
# Some streets might be traversed by more than one route. Streets traversed
# by many routes are the most critical emergency routes. Count the number of
# routes using each street.
arcpy.analysis.Frequency(
traversed_edges, edge_frequency, ["SourceOID", "SourceName"]
)
# The resulting edge features from CopyTraversedSourceFeatures may include
# clipped versions of the original street features because the Closest
# Facility route only traveled across part of the street feature. Select
# the complete street features from the original street feature class and
# copy them to output.
# Get the full path to the network dataset's streets feature class by
# describing the network dataset.
network_desc = arcpy.Describe(network)
edge_sources = network_desc.edgeSources
for es in edge_sources:
if es.name.lower() == "streets":
streets_source = os.path.join(os.path.dirname(network), es.name)
break
# Select the relevant streets based on overlap with the results from
# CopyTraversedSourceFeatures
streets_layer = arcpy.management.MakeFeatureLayer(
streets_source, "StreetsLayer"
)
arcpy.management.SelectLayerByLocation(
streets_layer, "SHARE_A_LINE_SEGMENT_WITH", traversed_edges
)
# Add the frequency information to the output feature class using JoinField
arcpy.management.JoinField(
streets_layer, "ObjectID", edge_frequency, "SourceOID", "FREQUENCY"
)
# Save the selected features to disk
arcpy.management.CopyFeatures(streets_layer, critical_streets)
# Delete the Frequency field from the street feature class
arcpy.management.DeleteField(streets_layer, "FREQUENCY")
print("Script completed successfully")
except Exception as e:
# If an error occurred, print line number and error message
import traceback, sys
tb = sys.exc_info()[2]
print("An error occurred on line %i" % tb.tb_lineno)
print(str(e))