SearchNeighborhoodStandard
Zusammenfassung
The SearchNeighborhoodStandard class can be used to define the search neighborhood for IDW, Local Polynomial Interpolation, and Radial Basis Functions.
Syntax
SearchNeighborhoodStandard({majorSemiaxis}, {minorSemiaxis}, {angle}, {nbrMax}, {nbrMin}, {sectorType})
| Name | Erläuterung | Datentyp |
|---|---|---|
|
majorSemiaxis (Optional) |
The distance, in map units, specifying the length of the major semi axis of the ellipse within which data is selected from. |
Double |
|
minorSemiaxis (Optional) |
The distance, in map units, specifying the length of the minor semi axis of the ellipse within which data is selected from. |
Double |
|
angle (Optional) |
The angle of the search ellipse. |
Double |
|
nbrMax (Optional) |
Maximum number of neighbors, within the search ellipse, to use when making the prediction. |
Long |
|
nbrMin (Optional) |
Minimum number of neighbors, within the search ellipse, to use when making the prediction. |
Long |
|
sectorType (Optional) |
The searching ellipse can be divided into 1, 4, 4 with an offset of 45º, or 8 sectors. |
String |
Eigenschaften
| Name | Erläuterung | Datentyp |
|---|---|---|
|
angle (Lesen und schreiben) |
The angle of the search ellipse. |
Double |
|
majorSemiaxis (Lesen und schreiben) |
The distance, in map units, specifying the length of the major semi axis of the ellipse within which data is selected. |
Double |
|
minorSemiaxis (Lesen und schreiben) |
The distance, in map units, specifying the length of the minor semi axis of the ellipse within which data is selected. |
Double |
|
nbrMax (Lesen und schreiben) |
Maximum number of neighbors, within the search ellipse, to use when making the prediction. |
Long |
|
nbrMin (Lesen und schreiben) |
Minimum number of neighbors, within the search ellipse, to use when making the prediction. |
Long |
|
nbrType (Schreibgeschützt) |
The neighborhood type: Smooth or Standard. |
String |
|
sectorType (Lesen und schreiben) |
The searching ellipse can be divided into 1, 4, 4 with an offset of 45º, or 8 sectors. |
String |
Codebeispiel
SearchNeighborhoodStandard with IDW to produce an output raster.
import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
arcpy.ga.IDW("ca_ozone_pts", "OZONE", "outIDW", "C:/gapyexamples/output/idwout", "2000", "2",
arcpy.SearchNeighborhoodStandard(300000, 300000, 0, 15, 10, "ONE_SECTOR"), "")
SearchNeighborhoodStandard with IDW to produce an output raster.
# Name: InverseDistanceWeighting_Example_02.py
# Description: Interpolate a series of point features onto a rectangular raster
# using Inverse Distance Weighting (IDW).
# 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 = "outIDW"
outRaster = "C:/gapyexamples/output/idwout"
cellSize = 2000.0
power = 2
# Set variables for search neighborhood
majSemiaxis = 300000
minSemiaxis = 300000
angle = 0
maxNeighbors = 15
minNeighbors = 10
sectorType = "ONE_SECTOR"
searchNeighbourhood = arcpy.SearchNeighborhoodStandard(majSemiaxis, minSemiaxis,
angle, maxNeighbors,
minNeighbors, sectorType)
# Run IDW
arcpy.ga.IDW(inPointFeatures, zField, outLayer, outRaster, cellSize,
power, searchNeighbourhood)