LocationAllocationSolverProperties (arcpy.na)

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 Make Location-Allocation Layer 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. #Don't attempt to modify the attributeParameters property in place. #This coding method won't work. solverProps.attributeParameters[('HeightRestriction', 'RestrictionUsage')] = "PROHIBITED" #Modify the attributeParameters property using a new dictionary object. #This coding method works. params = solverProps.attributeParameters params[('HeightRestriction', 'RestrictionUsage')] = "PROHIBITED" solverProps.attributeParameters = params If the network analysis layer does not have parameterized attributes, this property returns None.	Dictionary
defaultCapacity (读写)	Provides the ability to get or set the default capacity of facilities when the location-allocation problemType parameter is set to MAXIMIZE_CAPACITATED_COVERAGE. This parameter is ignored for all other problem types. Facilities have a Capacity property, which, if set to a nonnull value, overrides the defaultCapacity parameter for that facility.	Double
facilitiesToFind (读写)	Provides the ability to get or set the number of facilities that the solver should locate. The property value is ignored if the problemType property is set to MINIMIZE_FACILITIES, since the solver determines the minimum number of facilities to locate to maximize coverage. The property value is also ignored if the problemType property is set to TARGET_MARKET_SHARE, because the solver searches for the minimum number of facilities required to capture the specified market share.	Integer
impedance (读写)	Provides the ability to get or set the network cost attribute used as impedance.	String
impedanceCutoff (读写)	Provides the ability to get or set the maximum impedance at which a demand point can be allocated to a facility.	Double
impedanceParameter (读写)	Provides the ability to get or set a parameter value for the equations specified in the impedanceTransformation property. The property value is ignored when the impedanceTransformation property is set to LINEAR. The property value should not be zero.	Double
impedanceTransformation (读写)	Provides the ability to get or set the equation for transforming the network cost between facilities and demand points. This property value, coupled with the impedanceParameter property value, specifies how severely the network impedance between facilities and demand points influences the solver's choice of facilities. The following is a list of possible values: LINEAR —The transformed network impedance between the facility and the demand point is the same as the shortest-path network impedance between them. With this value set, the impedanceParameter property value is always set to one and any value set for impedanceParameter property is ignored. POWER —The transformed network impedance between the facility and the demand point is equal to the shortest-path network impedance raised to the power specified by the impedanceParameter property value. Use this property value with a positive impedanceParameter property value to give higher weight to nearby facilities. EXPONENTIAL —The transformed network impedance between the facility and the demand point is equal to the mathematical constant e raised to the power specified by the shortest-path network impedance multiplied by the impedanceParameter property value. Use this property value with a positive impedanceParameter property value to give a very high weight to nearby facilities.	String
outputPathShape (读写)	Controls whether straight lines are used to represent the results from the location-allocation analysis. The following is a list of possible values: NO_LINES —No shape will be generated for the output of the analysis. This is useful when you have a large number of demand points or facilities and are interested only in the tabular output. STRAIGHT_LINES —Straight lines connecting the solution facilities to their allocated demand points are generated.	String
problemType (读写)	Provides the ability to get or set the problem type that will be solved. The choice of the problem type depends on the kind of facility being located. Different kinds of facilities have different priorities and constraints. The following is a list of possible values: MINIMIZE_IMPEDANCE —This option solves the warehouse location problem. It selects a set of facilities such that the total sum of weighted impedances (demand at a location times the impedance to the closest facility) is minimized. This problem type is often known as the P-Median problem. MAXIMIZE_COVERAGE —This option solves the fire station location problem. It chooses facilities such that all or the greatest amount of demand is within a specified impedance cutoff. MINIMIZE_FACILITIES —This option solves the fire station location problem. It chooses the minimum number of facilities needed to cover all or the greatest amount of demand within a specified impedance cutoff. MAXIMIZE_ATTENDANCE —This option solves the neighborhood store location problem where the proportion of demand allocated to the nearest chosen facility falls with increasing distance. The set of facilities that maximize the total allocated demand is chosen. Demand further than the specified impedance cutoff does not affect the chosen set of facilities. MAXIMIZE_MARKET_SHARE —This option solves the competitive facility location problem. It chooses facilities to maximize market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The set of facilities that maximizes the total allocated demand is chosen. TARGET_MARKET_SHARE —This option solves the competitive facility location problem. It chooses facilities to reach a specified target market share in the presence of competitive facilities. Gravity model concepts are used to determine the proportion of demand allocated to each facility. The minimum number of facilities needed to reach the specified target market share is chosen.	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)	Returns the name of the solver being referenced by the Network Analyst layer used to obtain the solver properties object. The property always returns the string value Location-Allocation Solver when accessed from a LocationAllocationSolverProperties object.	String
targetMarketShare (读写)	Provides the ability to get or set the target market share in percentage to solve for when the problemType property is set to TARGET_MARKET_SHARE. It is the percentage of the total demand weight that you want your solution facilities to capture. The solver chooses the minimum number of facilities required to capture the target market share specified by this numeric value. Any value set for facilitiesToFind property is ignored.	Double
timeOfDay (读写)	Provides the ability to get or set the time and date of departure. The departure can be from facilities or demand points, depending on whether travel is from demand to facility or facility to demand. A value of None can be used to specify that no date and time should be used. Instead of using a particular date, a day of the week can be specified using the following dates: 今天 - 12/30/1899 星期日 - 12/31/1899 星期一 - 1/1/1900 星期二 - 1/2/1900 星期三 - 1/3/1900 星期四 - 1/4/1900 星期五 - 1/5/1900 星期六 - 1/6/1900 For example, to specify that the departure should occur at 8:00 AM on Friday, specify the value as datetime.datetime(1900, 1, 5, 8,0,0).	DateTime
travelDirection (读写)	Controls the direction of travel between facilities and demand points when calculating the network costs. The following is a list of possible values: FACILITY_TO_DEMAND —Direction of travel is from facilities to demand points. DEMAND_TO_FACILITY —Direction of travel is from demand points to facilities.	String
useHierarchy (读写)	Controls the use of the hierarchy attribute while performing the analysis. The following is a list of possible values: USE_HIERARCHY — Use the hierarchy attribute for the analysis. Using a hierarchy results in the solver preferring higher-order edges to lower-order edges. Hierarchical solves are faster, and they can be used to simulate the preference of a driver who chooses to travel on freeways over local roads when possible—even if that means a longer trip. This option is applicable only if the network dataset referenced by the Network Analyst layer has a hierarchy attribute. A value of True can also be used to specify this option. NO_HIERARCHY —Do not use the hierarchy attribute for the analysis. Not using a hierarchy yields an exact route for the network dataset. A value of False can also be used to specify this option.	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: ALLOW_UTURNS —U-turns are permitted at junctions with any number of connected edges. NO_UTURNS —U-turns are prohibited at all junctions, regardless of junction valency. Note, however, that U-turns are still permitted at network locations even when this setting is chosen; however, you can set the individual network locations' CurbApproach property to prohibit U-turns there as well. ALLOW_DEAD_ENDS_ONLY —U-turns are prohibited at all junctions, except those that have only one adjacent edge (a dead end). ALLOW_DEAD_ENDS_AND_INTERSECTIONS_ONLY —U-turns are prohibited at junctions where exactly two adjacent edges meet but are permitted at intersections (junctions with three or more adjacent edges) and dead ends (junctions with exactly one adjacent edge). Oftentimes, networks have extraneous junctions in the middle of road segments. This option prevents vehicles from making U-turns at these locations.	String

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")