CrossValidationResult

Resumen

The CrossValidationResult class is returned by the Cross Validation tool and contains access to the cross-validation results that can be generated for any geostatistical layer.

Debate

The CrossValidationResult class is similar to the Result class except for the additional read-only properties that it contains. For detailed help, see the Cross Validation tool.

Only the mean and root mean square error results are available for IDW, Global Polynomial Interpolation, Radial Basis Functions, Diffusion Interpolation With Barriers, and Kernel Interpolation With Barriers.

Percent in 90% Interval, Percent in 95% Interval, and Average CRPS are only available for Empirical Bayesian Kriging and EBK Regression Prediction models.

Propiedades

Propiedad	Explicación	Tipo de datos
averageCRPS (Sólo lectura)	The average of the Continuous Ranked Probability Scores (CRPS) for all points.	Double
averageStandard (Sólo lectura)	The average of the prediction standard errors.	Double
count (Sólo lectura)	The number of input samples.	Long
inputCount (Sólo lectura)	Returns the number of inputs.	Integer
maxSeverity (Sólo lectura)	Returns the maximum severity of the messages. 0 —If the tool produced only informative messages. 1 — If the tool produced a warning message, but no error messages. 2 — If the tool produced an error message.	Integer
meanError (Sólo lectura)	The averaged difference between the measured and the predicted values.	Double
meanStandardized (Sólo lectura)	Mean standardized error.	Double
messageCount (Sólo lectura)	Returns the number of messages.	Integer
outputCount (Sólo lectura)	Returns the number of outputs.	Integer
percentIn90Interval (Sólo lectura)	The percentage of points that are contained in a 90 percent cross validated confidence interval.	Double
percentIn95Interval (Sólo lectura)	The percentage of points that are contained in a 95 percent cross validated confidence interval.	Double
resultID (Sólo lectura)	Gets the job ID. If the tool is not a geoprocessing service, the resultID will be "".	String
rootMeanSquare (Sólo lectura)	The root mean square error.	Double
rootMeanSquareStandardized (Sólo lectura)	The root-mean-square-standardized error should be close to 1 if the prediction standard errors are valid. If the root-mean-square-standardized error is greater than 1, you are underestimating the variability in your predictions. If the root-mean-square-standardized error is less than 1, you are overestimating the variability in your predictions.	Double
status (Sólo lectura)	Gets the job status. 0 —New 1 —Submitted 2 —Waiting 3 —Executing 4 —Succeeded 5 —Failed 6 —Timed out 7 —Cancelling 8 —Cancelled 9 —Deleting 10 —Deleted	Integer

Descripción general del método

Método	Explicación
cancel ()	Cancels an associated job
getInput (index)	Returns a given input, either as a recordset or string.
getMapImageURL ({parameter_list}, {height}, {width}, {resolution})	Gets a map service image for a given output, if one exists.
getMessage (index)	Returns a specific message.
getMessages ({severity})	Returns messages.
getOutput (index)	Returns a given output, either as a string or a RecordSet. If the output of the tool, such as Make Feature Layer, is a layer, getOutput will return a Layer object.
getSeverity (index)	Returns the severity of a specific message.

Métodos

cancel ()

getInput (index)

Parámetro	Explicación	Tipo de datos
index	The index position of the input.	Integer

Valor de retorno

Tipo de datos	Explicación
Object	The input, either as a recordset or string.

getMapImageURL ({parameter_list}, {height}, {width}, {resolution})

Parámetro	Explicación	Tipo de datos
parameter_list	Parameter(s) on which the map service image will be based.	Integer
height	The height of the image.	Double
width	The width of the image.	Double
resolution	The resolution of the image.	Double

Valor de retorno

Tipo de datos	Explicación
String	The URL of the map image.

getMessage (index)

Parámetro	Explicación	Tipo de datos
index	The index position of the message.	Integer

Valor de retorno

Tipo de datos	Explicación
String	The geoprocessing message.

getMessages ({severity})

Parámetro	Explicación	Tipo de datos
severity	The type of messages to be returned: 0=message, 1=warning, 2=error. Not specifying a value returns all message types. 0 —informational message 1 —warning message 2 —error message (El valor predeterminado es 0)	Integer

Valor de retorno

Tipo de datos	Explicación
String	The geoprocessing messages.

getOutput (index)

Parámetro	Explicación	Tipo de datos
index	The index position of the outputs.	Integer

Valor de retorno

Tipo de datos	Explicación
Object	The output, either as a recordset or a string. If the output of the tool, such as Make Feature Layer, is a layer, getOutput will return a Layer object. Result outputs can also be accessed by index, so result.getOutput(0) and result[0] are equivalent.

getSeverity (index)

Parámetro	Explicación	Tipo de datos
index	The message index position.	Integer

Valor de retorno

Tipo de datos	Explicación
Integer	The severity of the specific message. 0 —informational message 1 —warning message 2 —error message

Muestra de código

CrossValidation (Python window)

Perform cross-validation on an input geostatistical layer.

import arcpy
arcpy.env.workspace = "C:/gapyexamples/data"
cvResult = arcpy.CrossValidation_ga("C:/gapyexamples/data/kriging.lyr")
print("Root Mean Square error = " + str(cvResult.rootMeanSquare))

CrossValidation (stand-alone script)

Perform cross-validation on an input geostatistical layer.

# Name: CrossValidation_Example_02.py
# Description: Perform cross validation on an input geostatistical layer.
# Requirements: Geostatistical Analyst Extension

# Import system modules
import arcpy

# Set environment settings
arcpy.env.workspace = "C:/gapyexamples/data"

# Set local variables
inLayer = "C:/gapyexamples/data/kriging.lyr"

# Execute CrossValidation
cvResult = arcpy.CrossValidation_ga(inLayer)
print("Root Mean Square error = " + str(cvResult.rootMeanSquare))