Resumen
Provides access to analysis properties from a location-allocation network analysis layer. The GetSolverProperties function is used to obtain a LocationAllocationSolverProperties object from a location-allocation network analysis layer.
Debate
The LocationAllocationSolverProperties object provides read and write access to all the analysis properties of a location-allocation network analysis layer. The object can be used to modify the desired analysis properties of the location-allocation layer, and the corresponding layer can be resolved to determine the appropriate results. A new location-allocation layer can be created using the Make Location-Allocation Analysis Layer geoprocessing tool. Obtaining the LocationAllocationSolverProperties object from a new location-allocation layer allows you to reuse the existing layer for subsequent analyses rather than create a layer for each analysis, which can be slow.
After modifying the properties on the LocationAllocationSolverProperties object, the corresponding layer can be immediately used with other functions and geoprocessing tools. There is no refresh or update of the layer required to honor the changes modified through the object.
Propiedades
| Propiedad | Explicación | Tipo de datos |
| accumulators (Lectura y escritura) | 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 (Lectura y escritura) | 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. Do not attempt to modify the attributeParameters property in place; this coding method will not work. Modify the attributeParameters property using a new dictionary object. | Dictionary |
| defaultCapacity (Lectura y escritura) | 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 (Lectura y escritura) | 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 (Lectura y escritura) | Provides the ability to get or set the network cost attribute used as impedance. | String |
| impedanceCutoff (Lectura y escritura) | Provides the ability to get or set the maximum impedance at which a demand point can be allocated to a facility. | Double |
| impedanceParameter (Lectura y escritura) | 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 (Lectura y escritura) | 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:
| String |
| outputPathShape (Lectura y escritura) | Controls whether straight lines are used to represent the results from the location-allocation analysis. The following is a list of possible values:
| String |
| problemType (Lectura y escritura) | 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:
| String |
| restrictions (Lectura y escritura) | 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 (Sólo lectura) | 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 (Lectura y escritura) | Provides the ability to get or set the target market share in percentage to solve 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 (Lectura y escritura) | 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:
For example, to specify that the departure should occur at 8:00 a.m. on Friday, specify the value as datetime.datetime(1900, 1, 5, 8,0,0). The timeZoneUsage parameter specifies whether the date and time refer to UTC or the time zone in which the facilities or demand points are located. | DateTime |
| timeZoneUsage (Lectura y escritura) | Specifies the time zone of the timeOfDay parameter.
When solving a location-allocation analysis that spans across multiple time zones, the following rules apply:
| String |
| travelDirection (Lectura y escritura) | Controls the direction of travel between facilities and demand points when calculating the network costs. The following is a list of possible values:
| String |
| travelMode (Sólo lectura) | Accesses the travel mode set on a network analysis layer as an arcpy.na.TravelMode object. | Object |
| useHierarchy (Lectura y escritura) | Controls the use of the hierarchy attribute while performing the analysis. The following is a list of possible values:
| String |
| uTurns (Lectura y escritura) | 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 |
Descripción general del método
| Método | Explicación |
| applyTravelMode (travel_mode) | Updates the analysis properties of a network analyst layer based on a travel mode object. The updated network analyst layer can then be solved to complete the analysis. |
Métodos
applyTravelMode (travel_mode)
| Parámetro | Explicación | Tipo de datos |
travel_mode | A variable that references a travel mode object derived from a network dataset. A list of travel mode objects can be obtained by calling the arcpy.na.GetTravelModes function. | Object |
When a network analyst layer is created, it is assigned default values for all of its analysis properties. The individual analysis properties can be updated using a solver properties object obtained from the network analyst layer. A travel mode stores a predefined set of analysis settings that help to perform a particular analysis, such as a walking time travel mode that stores the analysis settings required to perform a time-based walking analysis.
Using the applyTravelMode method, all the analysis settings that are defined in a travel mode can be applied at once. After the analysis properties are updated, the network analyst layer can be solved to complete the analysis.
If there is an error when updating the solver properties, such as when the provided travel mode references properties that don't exist on the current network dataset or references properties that are no longer applicable to the network dataset that was used to create the network analyst layer corresponding to the solver properties object, no exceptions are raised. The method will execute successfully, but you will get errors when you try to solve such a network analyst layer.
If the travel_mode parameter does not reference a travel mode object or a string, a TypeError exception is raised. If the travel_mode parameter references a string and the string cannot be internally converted to a valid string representation of a travel mode object, a ValueError exception is raised.
Muestra de código
The script shows how to choose optimal store locations that would generate the most business for a retail chain using location-allocation analysis. The script first creates a location-allocation layer with appropriate analysis settings. As a next step, the candidate store locations and the block group centroids are loaded as facilities and demand points, respectively. The analysis is solved and saved to a layer file. Two subsequent analyses are performed by modifying the analysis properties using the LocationAllocationSolverProperties object. After each solve, the layer is stored as a layer file. The script uses the tutorial data for the San Francisco region.
Heredado:
La función GetNASublayer se puede utilizar para recuperar las subcapas de una capa de análisis de red. Se introdujo en ArcGIS Pro 2.7. En versiones de software anteriores, la mejor forma de recuperar un objeto de subcapa de una capa de análisis de red era utilizar el método listLayers del objeto de análisis de red Layer utilizando el nombre de subcapa como comodín.
# Name: LocationAllocationSolverProperties_workflow_01.py
# Description: Test three different scenarios for optimizing the locations of
# new stores based on customer and competitor locations. Use the
# LocationAllocationSolverProperties object to update an existing
# Location-Allocation layer before re-running the analysis.
# Requirements: Network Analyst Extension
# Import system modules
import arcpy
from arcpy import env
import os
try:
# Check out Network Analyst license if available. Fail if the Network Analyst license is not available.
if arcpy.CheckExtension("network") == "Available":
arcpy.CheckOutExtension("network")
else:
raise arcpy.ExecuteError("Network Analyst Extension license is not available.")
# 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
# Set local variables
input_gdb = "C:/Data/SanFrancisco.gdb"
network = os.path.join(input_gdb, "Transportation", "Streets_ND")
layer_name = "Location_Allocation"
scenario1_output = "NewStoreLocations"
scenario2_output = "StoreExpansionScenario"
scenario3_output = "MaximizedMarketShareStoreLocations"
facilities = os.path.join(input_gdb, "Analysis", "CandidateStores")
required_facility = os.path.join(input_gdb, "Analysis", "ExistingStore")
competitor_facility = os.path.join(input_gdb, "Analysis", "CompetitorStores")
demand_points = os.path.join(input_gdb, "Analysis", "TractCentroids")
# --- Scenario 1: Select the best three locations for stores
# 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.
result_object = arcpy.na.MakeLocationAllocationAnalysisLayer(network,
layer_name, "Driving Time",
"TO_FACILITIES",
"MAXIMIZE_ATTENDANCE", cutoff=5,
number_of_facilities_to_find=3,
decay_function_type="LINEAR")
# Get the layer object from the result object. The Location-Allocation layer
# can now be referenced using the layer object.
layer_object = result_object.getOutput(0)
# Get the names of all the sublayers within the location-allocation layer.
sublayer_names = arcpy.na.GetNAClassNames(layer_object)
# Store the layer names that we will use later
facilities_layer_name = sublayer_names["Facilities"]
demand_points_layer_name = sublayer_names["DemandPoints"]
# Get the facilities sublayer object to use later
facilities_sublayer = arcpy.na.GetNASublayer(layer_object, "Facilities")
# Load the candidate store locations as facilities using default search
# tolerance and field mappings.
arcpy.na.AddLocations(layer_object, facilities_layer_name, facilities, "",
"")
# Load the tract centroids as demand points using default search tolerance.
# Use the field mappings to map the Weight property from POP2000 field.
demand_field_mappings = arcpy.na.NAClassFieldMappings(layer_object,
demand_points_layer_name)
demand_field_mappings["Weight"].mappedFieldName = "POP2000"
arcpy.na.AddLocations(layer_object, demand_points_layer_name, demand_points,
demand_field_mappings, "")
# Solve the location-allocation layer
arcpy.na.Solve(layer_object)
# Save the facilities sublayer of the solved Location-Allocation layer as a
# feature class
arcpy.management.CopyFeatures(facilities_sublayer, scenario1_output)
# --- Scenario 2: Assuming the three stores selected previously have already
# been built, select the best locations for two more stores
# 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.
field_mappings = arcpy.na.NAClassFieldMappings(layer_object,
facilities_layer_name)
field_mappings["FacilityType"].defaultValue = 1
field_mappings["Name"].mappedFieldName = "Name"
arcpy.na.AddLocations(layer_object, facilities_layer_name, required_facility,
field_mappings, "", append="APPEND")
# Solve the location-allocation layer
arcpy.na.Solve(layer_object)
# Save the facilities sublayer of the solved Location-Allocation layer as a
# feature class
arcpy.management.CopyFeatures(facilities_sublayer, scenario2_output)
# --- Scenario 3: Re-run the previous scenario with additional information:
# the locations 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.
field_mappings["FacilityType"].defaultValue = 2
arcpy.na.AddLocations(layer_object, facilities_layer_name,
competitor_facility, field_mappings, "",
append="APPEND")
# Get the LocationAllocationSolverProperties object from the
# Location-Allocation layer to modify the analysis settings for the layer.
solver_props = arcpy.na.GetSolverProperties(layer_object)
# Set the problem type to Maximize Market Share, and impedance transformation
# to Power with an impedance parameter value of 2.
solver_props.problemType = "MAXIMIZE_MARKET_SHARE"
solver_props.impedanceTransformation = "POWER"
solver_props.impedanceParameter = 2
# Solve the location-allocation layer
arcpy.na.Solve(layer_object)
# print the market share that was obtained
print(arcpy.GetMessage(0))
# Save the facilities sublayer of the solved Location-Allocation layer as a
# feature class
arcpy.management.CopyFeatures(facilities_sublayer, scenario3_output)
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 occured on line %i" % tb.tb_lineno)
print(str(e))This script shows how to apply the TruckingTime travel mode to an existing layer.
#Get the location-allocation layer object from a layer named
#"Location-Allocation" in the map
doc = arcpy.mp.ArcGISProject('current')
map_obj = doc.listMaps()[0]
la_layer = map_obj.listLayers('Location-Allocation')[0]
#Get the Trucking Time travel mode from the network dataset
desc = arcpy.Describe(la_layer)
travel_modes = arcpy.na.GetTravelModes(desc.network.catalogPath)
trucking_mode = travel_modes["Trucking Time"]
#Apply the travel mode to the analysis layer
solver_properties = arcpy.na.GetSolverProperties(la_layer)
solver_properties.applyTravelMode(trucking_mode)