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

PropiedadExplicaciónTipo 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.

  • 0If 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.

  • 0New
  • 1Submitted
  • 2Waiting
  • 3Executing
  • 4Succeeded
  • 5Failed
  • 6Timed out
  • 7Cancelling
  • 8Cancelled
  • 9Deleting
  • 10Deleted
Integer

Descripción general del método

MétodoExplicación
cancel ()

Cancels an associated job

getInput (index)

Returns a given input, either as a recordset or string.

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

Returns a map service image for a given output, if one exists.

getMessage (index)

Returns a specific message by index position.

getMessages ({severity})

Returns the geoprocessing tool 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)
ParámetroExplicaciónTipo de datos
index

The index position of the input.

Integer
Valor de retorno
Tipo de datosExplicación
Object

The input, either as a recordset or string.

getMapImageURL ({parameter_list}, {height}, {width}, {resolution})
ParámetroExplicaciónTipo de datos
parameter_list

The parameters 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 datosExplicación
String

The URL of the map image.

getMessage (index)
ParámetroExplicaciónTipo de datos
index

The index position of the message.

Integer
Valor de retorno
Tipo de datosExplicación
String

The geoprocessing message.

getMessages ({severity})
ParámetroExplicaciónTipo de datos
severity

The type of messages to be returned.

  • 0Informative, warning, and error messages are returned.
  • 1Only warning messages are returned.
  • 2Only error messages are returned.

Not specifying a severity level will return all types of messages.

(El valor predeterminado es 0)

Integer
Valor de retorno
Tipo de datosExplicación
String

The geoprocessing tool messages.

getOutput (index)
ParámetroExplicaciónTipo de datos
index

The index position of the outputs.

Integer
Valor de retorno
Tipo de datosExplicación
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)
ParámetroExplicaciónTipo de datos
index

The message index position.

Integer
Valor de retorno
Tipo de datosExplicación
Integer

The severity of the specific message.

  • 0Informative, warning, and error messages are returned.
  • 1Only warning messages are returned.
  • 2Only error messages are returned.

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))