Subset Features (Geostatistical Analyst)

Disponible avec une licence Geostatistical Analyst.

Synthèse

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.

Utilisation

• 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.

  Remarque :

  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.

Paramètres

Boîte de dialogue

Étiquette	Explication	Type de données
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 (Facultatif)	The subset of test features to be created.	Feature Class; Table
Size of training feature subset (Facultatif)	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 (Facultatif)	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})

Nom	Explication	Type de données
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 (Facultatif)	The subset of test features to be created.	Feature Class; Table
size_of_training_dataset (Facultatif)	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 (Facultatif)	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

Exemple de code

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)

Environnements

Espace de travail courant, Étendue, Transformations géographiques, Système de coordonnées en sortie, Générateur de nombres aléatoires, Espace de travail temporaire

Cas particuliers

Informations de licence

• Basic: Nécessite Geostatistical Analyst
• Standard: Nécessite Geostatistical Analyst
• Advanced: Nécessite Geostatistical Analyst