SearchNeighborhoodStandard3D—ArcGIS Pro

摘要

SearchNeighborhoodStandard3D 类可用于为 3D 经验贝叶斯克里金法工具定义三维搜索邻域。

语法

 SearchNeighborhoodStandard3D ({radius}, {nbrMax}, {nbrMin}, {sectorType})

参数	说明	数据类型
radius	以地图单位指定搜索邻域的半径长度的距离。	Double
nbrMax	要在进行预测时使用的搜索半径内的最大相邻要素数。	Long
nbrMin	要在进行预测时使用的搜索半径内的最小相邻要素数。	Long
sectorType	搜索邻域的扇区类型。搜索邻域可以划分为 1、4、6、8、12 或 20 个扇区。扇区类型均基于正多面体。 ONE_SECTOR—1 个扇区(球体) FOUR_SECTORS—4 个扇区(四面体) SIX_SECTORS—6 个扇区(六面体) EIGHT_SECTORS—8 个扇区(八面体) TWELVE_SECTORS—12 个扇区(十二面体) TWENTY_SECTORS—20 个扇区(二十面体)	String

属性

属性	说明	数据类型
nbrMax (只读)	搜索邻域的最大相邻要素数。	Long
nbrMin (只读)	搜索邻域的最小相邻要素数。	Long
radius (只读)	搜索邻域的半径。	Double
sectorType (只读)	搜索邻域的扇区类型。	String

代码示例

SearchNeighborhoodStandard3D（Python 窗口）

使用 SearchNeighborhoodStandard3D 和 Empirical Bayesian Kriging 3D 工具生成地统计图层。

import arcpy
arcpy.ga.EmpiricalBayesianKriging3D("my3DLayer", "Shape.Z", "myValueField", "myGALayer", "METER", "",
                                    "POWER", "NONE", 100, 1, 100, "NONE", "",
                                    "NBRTYPE=Standard3D RADIUS=10000 NBR_MAX=15 NBR_MIN=10 SECTOR_TYPE=ONE_SECTOR",
                                    "", "PREDICTION", 0.5, "EXCEED", "")

SearchNeighborhoodStandard3D（独立脚本）

使用 SearchNeighborhoodStandard3D 和 Empirical Bayesian Kriging 3D 工具生成地统计图层。

# Name: SearchNeighborhoodStandard3D_Example_02.py
# Description: Interpolates 3D points using a standard 3D neighborhood
# Requirements: Geostatistical Analyst Extension
# Author: Esri

# Import system modules
import arcpy

# Set local variables
in3DPoints = "C:/gapyexamples/input/my3DPoints.shp"
elevationField = "Shape.Z"
valueField = "myValueField"
outGALayer = "myGALayer"
elevationUnit = "METER"
measurementErrorField = "myMEField"
semivariogramModel = "LINEAR"
transformationType = "NONE"
subsetSize = 80
overlapFactor = 1.5
numSimulations = 200
trendRemoval = "FIRST"
elevInflationFactor = 20
radius = 10000
maxNeighbors = 15
minNeighbors = 10
sectorType = "FOUR_SECTORS"
searchNeighborhood = arcpy.SearchNeighborhoodStandard3D(radius, maxNeighbors, minNeighbors, sectorType)
outputElev = 1000
outputType = "PREDICTION"

# Check out the ArcGIS Geostatistical Analyst extension license
arcpy.CheckOutExtension("GeoStats")

# Execute Empirical Bayesian Kriging 3D
arcpy.ga.EmpiricalBayesianKriging3D(in3DPoints, elevationField, valueField, outGALayer, elevationUnit, myMEField,
                                    semivariogramModel, transformationType, subsetSize, overlapFactor, numSimulations,
                                    trendRemoval, elevInflationFactor, searchNeighborhood, outputElev, outputType)

有关此主题的反馈?

摘要

语法

属性

代码示例

在本主题中