摘要
SearchNeighborhoodStandardCircular 类可用于定义以下邻域搜索方法：经验贝叶斯克里金法、反距离权重法、局部多项式插值法和径向基函数插值法。
语法
SearchNeighborhoodStandardCircular ({radius}, {angle}, {nbrMax}, {nbrMin}, {sectorType})| 参数 | 说明 | 数据类型 |
radius | The distance, in map units, specifying the length of the radius of the searching circle. | Double |
angle | The angle of the search circle. This parameter will only affect the angle of the sectors. | Double |
nbrMax | Maximum number of neighbors, within the search ellipse, to use when making the prediction. | Long |
nbrMin | Minimum number of neighbors, within the search ellipse, to use when making the prediction. | Long |
sectorType | The searching ellipse can be divided into 1, 4, 4 with an offset of 45º, or 8 sectors. | String |
属性
| 属性 | 说明 | 数据类型 |
| angle (读写) | The angle of the search ellipse. | Double |
| radius (读写) | The distance, in map units, specifying the length of the radius of the searching circle. | Double |
| nbrMax (读写) | 要在进行预测时使用的搜索椭圆内的最大相邻要素数。 | Long |
| nbrMin (读写) | 要在进行预测时使用的搜索椭圆内的最小相邻要素数。 | Long |
| nbrType (只读) | 邻域类型：平滑或标准。 | String |
| sectorType (读写) | The searching ellipse can be divided into 1, 4, 4 with an offset of 45º, or 8 sectors. | String |
代码实例
SearchNeighborhoodSmoothCircular（Python 窗口）
SearchNeighborhoodStandardCircular 与经验贝叶斯克里金法相结合生成输出栅格的示例。
import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
arcpy.LocalPolynomialInterpolation_ga(
"ca_ozone_pts", "OZONE", "outLPI", "C:/gapyexamples/output/lpiout", "2000",
"2", arcpy.SearchNeighborhoodSmooth(300000, 300000, 0, 0.5), "QUARTIC",
"", "", "", "", "PREDICTION")
SearchNeighborhoodSmoothCircular（独立脚本）
SearchNeighborhoodStandardCircular 与经验贝叶斯克里金法相结合生成输出栅格的示例。
# Name: LocalPolynomialInterpolation_Example_02.py
# Description: Local Polynomial interpolation fits many polynomials, each
# within specified overlapping neighborhoods.
# Requirements: Geostatistical Analyst Extension
# Import system modules
import arcpy
# Set environment settings
arcpy.env.workspace = "C:/gapyexamples/data"
# Set local variables
inPointFeatures = "ca_ozone_pts.shp"
zField = "ozone"
outLayer = "outLPI"
outRaster = "C:/gapyexamples/output/lpiout"
cellSize = 2000.0
power = 2
kernelFunction = "QUARTIC"
bandwidth = ""
useConNumber = ""
conNumber = ""
weightField = ""
outSurface = "PREDICTION"
# Set variables for search neighborhood
majSemiaxis = 300000
minSemiaxis = 300000
angle = 0
smoothFactor = 0.5
searchNeighbourhood = arcpy.SearchNeighborhoodSmooth(majSemiaxis, minSemiaxis,
angle, smoothFactor)
# Check out the ArcGIS Geostatistical Analyst extension license
arcpy.CheckOutExtension("GeoStats")
# Execute LocalPolynomialInterpolation
arcpy.LocalPolynomialInterpolation_ga(inPointFeatures, zField, outLayer, outRaster,
cellSize, power, searchNeighbourhood,
kernelFunction, bandwidth, useConNumber,
conNumber, weightField, outSurface)