Subset Features (Geostatistical Analyst)

Available with Geostatistical Analyst license.

Summary

Divides the original dataset into two parts: one part to be used to model the spatial structure and produce a surface, the other to be used to compare and validate the output surface.

Usage

• If multipart features are used as input, the output will be a subset of multipart features and not individual features.

• If you want the random sequence used to create the subsets to be repeatable, you need to specify a nonzero seed value in the Random number generator environment variable.

  Note:

  Only the Mersenne Twister random number generator type is supported; if ACM collected algorithm 599 or Standard C Rand is chosen, Mersenne Twister will be used instead.

• The test feature class is often used in validation of a model created using the training feature class.

Parameters

Dialog

Label	Explanation	Data Type
Input features	Points, lines, polygon features, or table from which to create a subset.	Table View
Output training feature class	The subset of training features to be created.	Feature Class; Table
Output test feature class (Optional)	The subset of test features to be created.	Feature Class; Table
Size of training feature subset (Optional)	The size of the output training feature class, entered either as a percentage of the input features or as an absolute number of features.	Double
Subset size units (Optional)	Type of subset size. Percentage of input— The percentage of the input features that will be in the training dataset. Absolute value— The number of features that will be in the training dataset.	Boolean

Python

arcpy.ga.SubsetFeatures(in_features, out_training_feature_class, {out_test_feature_class}, {size_of_training_dataset}, {subset_size_units})

Name	Explanation	Data Type
in_features	Points, lines, polygon features, or table from which to create a subset.	Table View
out_training_feature_class	The subset of training features to be created.	Feature Class; Table
out_test_feature_class (Optional)	The subset of test features to be created.	Feature Class; Table
size_of_training_dataset (Optional)	The size of the output training feature class, entered either as a percentage of the input features or as an absolute number of features.	Double
subset_size_units (Optional)	Type of subset size. PERCENTAGE_OF_INPUT— The percentage of the input features that will be in the training dataset. ABSOLUTE_VALUE— The number of features that will be in the training dataset.	Boolean

Code sample

SubsetFeatures example 1 (Python window)

Randomly split the features into two feature classes.

import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
arcpy.SubsetFeatures_ga("ca_ozone_pts", "C:/gapyexamples/output/training", 
                        "", "", "PERCENTAGE_OF_INPUT")

SubsetFeatures example 2 (stand-alone script)

Randomly split the features into two feature classes.

# Name: SubsetFeatures_Example_02.py
# Description: Randomly split the features into two feature classes.
# 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"
outtrainPoints = "C:/gapyexamples/output/training.shp"
outtestPoints = ""
trainData = ""
subsizeUnits = "PERCENTAGE_OF_INPUT"

# Execute SubsetFeatures
arcpy.SubsetFeatures_ga(inPointFeatures, outtrainPoints, outtestPoints, 
                        trainData, subsizeUnits)

Environments

Current Workspace, Extent, Geographic Transformations, Output Coordinate System, Random number generator, Scratch Workspace

Licensing information

• Basic: Requires Geostatistical Analyst
• Standard: Requires Geostatistical Analyst
• Advanced: Requires Geostatistical Analyst