摘要
用于访问位置分配网络分析图层中的分析属性。GetSolverProperties 函数用于从位置分配网络分析图层中获取 LocationAllocationSolverProperties 对象。
讨论
LocationAllocationSolverProperties 对象提供对位置分配网络分析图层中所有分析属性的读取和写入权限。该对象可用于修改位置分配图层的分析属性，并可重新求解相应图层以确定合适结果。使用创建位置分配图层地理处理工具可创建新的位置分配图层。通过从新的位置分配图层获取 LocationAllocationSolverProperties 对象，可重新对现有图层进行后续分析，而无需每次分析都创建一个新图层，以节省时间。
修改 LocationAllocationSolverProperties 对象的属性后，可立即使用其他函数和地理处理工具分析相关图层。无需刷新或更新图层，通过上述对象进行的修改便可生效。
属性
| 属性 | 说明 | 数据类型 |
| accumulators (读写) | Provides the ability to get or set a list of network cost attributes that are accumulated as part of the analysis. An empty list, [], indicates that no cost attributes are accumulated. | String |
| attributeParameters (读写) | Provides the ability to get or set the parameterized attributes to be used in the analysis. The property returns a Python dictionary. The dictionary key is a two-value tuple consisting of the attribute name and the parameter name. The value for each item in the dictionary is the parameter value. Parameterized network attributes are used to model some dynamic aspect of an attribute's value. For example, a tunnel with a height restriction of 12 feet can be modeled using a parameter. In this case, the vehicle's height in feet should be specified as the parameter value. If the vehicle is taller than 12 feet, this restriction will then evaluate to true, thereby restricting travel through the tunnel. Similarly, a bridge could have a parameter to specify a weight restriction. Attempting to modify the attributeParameters property in place won't result in updated values. Instead, you should always use a new dictionary object to set values for the property. The following two code blocks demonstrate the difference between these two approaches. | Dictionary |
| defaultCapacity (读写) | 用于获取或设置当位置分配 problemType 参数设置为 MAXIMIZE_CAPACITATED_COVERAGE 时默认的设施点容量。对于所有其他问题类型，可忽略此参数。 设施点有容量属性，如果此属性设置为非空值，将覆盖该设施点的 defaultCapacity 参数。 | Double |
| facilitiesToFind (读写) | 用于获取或设置求解程序应定位的设施点数量。如果 problemType 属性设置为 MINIMIZE_FACILITIES，则属性值将被忽略，因为求解程序将确定最小数量的设施点进行定位，以将覆盖范围最大化。如果 problemType 属性设置为 TARGET_MARKET_SHARE，属性值也会被忽略，因为求解程序将搜索要占有指定市场份额所需的最小数量的设施点。 | Integer |
| impedance (读写) | 用于获取或设置用作阻抗的网络成本属性。 | String |
| impedanceCutoff (读写) | 用于获取或设置请求点可分配给设施点时的最大阻抗。 | Double |
| impedanceParameter (读写) | 用于获取或设置在 impedanceTransformation 属性中指定的方程的参数值。当 impedanceTransformation 属性设置为 LINEAR 时，该属性值将被忽略。该属性值不应为零。 | Double |
| impedanceTransformation (读写) | 用于获取或设置对设施点与请求点间网络成本进行变换的方程。该属性值与 ImpedanceParameter 属性值结合使用可指定设施点与请求点间的网络阻抗对于求解程序选择设施点的影响的严重程度。以下是可能值列表：
| String |
| outputPathShape (读写) | 控制是否用直线表示位置分配分析的结果。以下是可能值列表：
| String |
| problemType (读写) | 用于获取或设置将求解的问题类型。问题类型的选择取决于要定位的设施点种类。不同种类的设施点具有不同的优先级和约束。以下是可能值列表：
| String |
| restrictions (读写) | Provides the ability to get or set a list of restriction attributes that are applied for the analysis. An empty list, [], indicates that no restriction attributes are used for the analysis. | String |
| solverName (只读) | 返回被用于获取求解程序属性对象的 Network Analyst 图层所引用的求解程序的名称。从 LocationAllocationSolverProperties 对象访问时，该属性始终返回字符串值位置分配求解程序。 | String |
| targetMarketShare (读写) | 用于获取或设置当 problemType 属性设置为 TARGET_MARKET_SHARE 时要求解的目标市场份额百分数。它是您希望设施点解占总请求权重的百分比。求解程序会求出为占有该值指定的目标市场份额所需的最小设施点数。为 facilitiesToFind 属性设置的任何值都将被忽略。 | Double |
| timeOfDay (读写) | 用于获取或设置离开的时间和日期。可以从设施点或请求点离开，取决于是从请求点向设施点行驶还是从设施点向请求点行驶。可以用值 None 指定不应使用任何日期和时间。 可使用以下日期来指定一周中的每一天，而无需使用特定的日期：
例如，要指定应该在星期五 8:00 a.m. 离开，则将值指定为 datetime.datetime(1900, 1, 5, 8,0,0)。 timeZoneUsage 参数指定该日期和时间是 UTC 还是设施点或请求点所在时区。 | DateTime |
| timeZoneUsage (读写) | 指定 timeOfDay 参数的时区。
在求解跨多个时区的位置分配分析问题时，以下规则适用：
| String |
| travelDirection (读写) | 控制计算网络成本时设施点与请求点之间的行驶方向。以下是可能值列表：
| String |
| useHierarchy (读写) | Controls the use of the hierarchy attribute while performing the analysis. The following is a list of possible values:
| String |
| uTurns (读写) | Provides the ability to get or set the policy that indicates how the U-turns at junctions that could occur during network traversal between stops are being handled by the solver. The following is a list of possible values:
| String |
方法概述
| 方法 | 说明 |
| applyTravelMode (travel_mode) | 根据出行模式对象更新网络分析图层的分析属性。随后可对更新的网络分析图层进行求解以完成分析。 |
方法
applyTravelMode (travel_mode)
| 参数 | 说明 | 数据类型 |
travel_mode | 该变量引用一个源自网络数据集的出行模式对象。可通过调用 arcpy.na.GetTravelModes 函数获得出行模式对象的列表。 | Object |
创建网络分析图层后，将为其分配所有分析属性的默认值。可使用从网络分析图层获得的求解程序属性对象更新各个分析属性。出行模式存储了一组预定义的分析设置，用于帮助执行特定分析，例如，步行时间出行模式存储了执行基于时间的步行分析所需的分析设置。
使用 applyTravelMode 方法，可一次性应用在一个出行模式中定义的所有分析设置。在分析属性完成更新后，可对网络分析图层进行求解以完成分析。
如果在更新求解程序属性时出错，例如，当提供的出行模式所引用的属性在当前网络数据集中不存在，或不再适用于创建求解程序属性对象的相应网络分析图层所使用的网络数据集时，不会产生任何异常。此方法将成功执行，但当您尝试求解此类网络分析图层时会出现错误。
如果 travel_mode 参数不引用出行模式对象或字符串，则将产生 TypeError 异常。如果 travel_mode 参数引用字符串并且该字符串无法在内部转换成出行模式对象的有效字符串表示，将产生 ValueError 异常。
代码实例
LocationAllocationSolverProperties 示例 1（Python 窗口）
该脚本显示如何更新位置分配网络分析图层的问题类型，以“最小化设施点数”并将幂阻抗变换的阻抗参数设置为 2。它假设已经在新地图文档中根据旧金山地区的网络数据集创建名为 Stores Coverage 的位置分配图层。
#Get the location-allocation layer object from a layer named "Stores Coverage" in
#the table of contents
laLayer = arcpy.mapping.Layer("Stores Coverage")
#Get the solver properties object from the location-allocation layer
solverProps = arcpy.na.GetSolverProperties(laLayer)
#Update the properties for the location-allocation layer using the solver properties
#object
solverProps.problemType = "MINIMIZE_FACILITIES"
solverProps.impedanceTransformation = "POWER"
solverProps.impedanceParameter = 2
LocationAllocationSolverProperties 示例 2（工作流）
该脚本显示如何使用位置分配分析为连锁零售店选择可以获得最大业务量的商店位置。该脚本首先使用相应的分析设置创建一个新位置分配图层。接下来，将候选商店位置和区块组中心分别加载为设施点和需求点。对分析进行求解并保存至图层文件。使用 LocationAllocationSolverProperties 对象修改分析属性以执行两个后续分析。每次求解之后，图层均以文件格式储存。该脚本使用旧金山地区的数据。示例详细描述参照“网络分析教程”的练习 9。在帮助您在 ArcMap 用户界面下演练此流程的同时，该教程提供了使用 Python 脚本自动处理类似场景的示例。
import arcpy
#Set up the environment
arcpy.env.overwriteOutput = True
arcpy.env.workspace = "C:/data/SanFrancisco.gdb"
arcpy.CheckOutExtension("network")
#Set up variables
networkDataset = "Transportation/Streets_ND"
outNALayerName = "NewStoreLocations"
inFacilities = "Analysis/CandidateStores"
requiredFacility = "Analysis/ExistingStore"
competitorFacility = "Analysis/CompetitorStores"
inDemandPoints = "Analysis/TractCentroids"
outputFolder = "C:/data/output/"
#Create a new location-allocation layer. In this case the demand travels to
#the facility. We wish to find 3 potential store locations out of all the
#candidate store locations using the maximize attendance model.
outNALayer = arcpy.na.MakeLocationAllocationLayer(networkDataset, outNALayerName,
"TravelTime","DEMAND_TO_FACILITY",
"MAXIMIZE_ATTENDANCE",3,5,
"LINEAR")
#Get the layer object from the result object. The location-allocation layer
#can now be referenced using the layer object.
outNALayer = outNALayer.getOutput(0)
#Get the names of all the sublayers within the location-allocation layer.
subLayerNames = arcpy.na.GetNAClassNames(outNALayer)
#Stores the layer names that we will use later
facilitiesLayerName = subLayerNames["Facilities"]
demandPointsLayerName = subLayerNames["DemandPoints"]
#Load the candidate store locations as facilities using default search
#tolerance and field mappings.
arcpy.na.AddLocations(outNALayer, facilitiesLayerName, inFacilities, "", "",
exclude_restricted_elements = "EXCLUDE")
#Load the tract centroids as demand points using default search tolerance. Use
#the field mappings to map the Weight property from POP2000 field.
demandFieldMappings = arcpy.na.NAClassFieldMappings(outNALayer,
demandPointsLayerName)
demandFieldMappings["Weight"].mappedFieldName = "POP2000"
arcpy.na.AddLocations(outNALayer,demandPointsLayerName ,inDemandPoints,
demandFieldMappings, "",
exclude_restricted_elements = "EXCLUDE")
#Solve the location-allocation layer
arcpy.na.Solve(outNALayer)
#Save the solved location-allocation layer as a layer file on disk with
#relative paths
outLayerFile = outputFolder + outNALayerName + ".lyr"
arcpy.management.SaveToLayerFile(outNALayer,outLayerFile,"RELATIVE")
#We need to re-solve the previous scenario as a store-expansion scenario, in
#which we will start with an existing store and optimally locate two additional
#stores.
#Load the existing store location as the required facility. Use the field
#mappings to set the facility type to requried. We need to append this
#required facility to existing facilities.
fieldMappings = arcpy.na.NAClassFieldMappings(outNALayer, facilitiesLayerName)
fieldMappings["FacilityType"].defaultValue = 1
fieldMappings["Name"].mappedFieldName = "Name"
arcpy.na.AddLocations(outNALayer, facilitiesLayerName, requiredFacility,
fieldMappings, "", append = "APPEND",
exclude_restricted_elements = "EXCLUDE")
#Solve the location-allocation layer
arcpy.na.Solve(outNALayer)
#Save the solved location-allocation layer as a layer file on disk with
#relative paths
updatedNALayerName = "StoreExpansionScenario"
outNALayer.name = updatedNALayerName
outLayerFile = outputFolder + updatedNALayerName + ".lyr"
arcpy.management.SaveToLayerFile(outNALayer,outLayerFile,"RELATIVE")
#We need to resolve the previous scenario and locate new stores to
#maximize market share in light of competing stores.
#Load the competitor store locations as the competitor facilities. Use the field
#mappings to set the facility type to Competitor. We need to append these
#competitor facilities to existing facilities.
fieldMappings["FacilityType"].defaultValue = 2
arcpy.na.AddLocations(outNALayer, facilitiesLayerName, competitorFacility,
fieldMappings, "", append = "APPEND",
exclude_restricted_elements = "EXCLUDE")
#Get the LocationAllocationSolverProperties object from the location-allocation
#layer to modify the analysis settings for the layer.
solverProps = arcpy.na.GetSolverProperties(outNALayer)
#Set the problem type to Maximize Market Share, and impedance transformation to
#Power with an impedance parameter value of 2.
solverProps.problemType = "MAXIMIZE_MARKET_SHARE"
solverProps.impedanceTransformation = "POWER"
solverProps.impedanceParameter = 2
#Solve the location-allocation layer
arcpy.na.Solve(outNALayer)
#print the market share that was obtained
arcpy.AddMessage(arcpy.GetMessage(0))
#Change the name of the NA Layer
updatedNALayerName = "MaximizedMarketShareStoreLocations"
outNALayer.name = updatedNALayerName
#Save the solved location-allocation layer as a layer file on disk with
#relative paths
outLayerFile = outputFolder + updatedNALayerName + ".lyr"
arcpy.management.SaveToLayerFile(outNALayer,outLayerFile,"RELATIVE")
arcpy.AddMessage("Completed")
ApplyTravelMode 示例 3（工作流）
此脚本显示基于“货运时间”出行模式查找最佳设施点位置的方法。
#Import modules
import os
import arcpy
#Define variables
workspace = "C:/data/SanDiego.gdb"
output_folder = "C:/data/output"
nds = os.path.join(workspace, "Transportation", "Streets_ND")
facilities = os.path.join(workspace, "Warehouses")
demand_points = os.path.join(workspace, "TruckDepots")
analysis_layer_name = "NewWarehouseLocation"
#Set environment variables
arcpy.env.overwriteOutput = True
#Check out the network analyst extension
arcpy.CheckOutExtension("network")
#Create a new closest facility analysis layer
make_layer_result = arcpy.na.MakeLocationAllocationLayer(nds, analysis_layer_name,
"TravelTime")
analysis_layer = make_layer_result.getOutput(0)
#Add facilities and demand points to the analysis layer using default field mappings
sub_layer_names = arcpy.na.GetNAClassNames(analysis_layer)
facility_layer_name = sub_layer_names["Facilities"]
demand_points_layer_name = sub_layer_names["DemandPoints"]
arcpy.na.AddLocations(analysis_layer, facility_layer_name, facilities, "#", "#")
arcpy.na.AddLocations(analysis_layer, demand_points_layer_name, demand_points ,
"#", "#")
#Get the Trucking Time travel mode from the network dataset
travel_modes = arcpy.na.GetTravelModes(nds)
trucking_mode = travel_modes["Trucking Time"]
#Apply the travel mode to the analysis layer
solver_properties = arcpy.na.GetSolverProperties(analysis_layer)
solver_properties.applyTravelMode(trucking_mode)
#Solve the analysis layer and save the result as a layer file
arcpy.na.Solve(analysis_layer)
output_layer = os.path.join(output_folder, analysis_layer_name + ".lyr")
arcpy.management.SaveToLayerFile(analysis_layer, output_layer, "RELATIVE")
arcpy.AddMessage("Completed")