Résumé
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.
Discussion
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.
Propriétés
| Propriété | Explication | Type de données |
| averageCRPS (Lecture seule) | The average of the Continuous Ranked Probability Scores (CRPS) for all points. | Double |
| averageStandard (Lecture seule) | The average of the prediction standard errors. | Double |
| count (Lecture seule) | The number of input samples. | Long |
| inputCount (Lecture seule) | Returns the number of inputs. | Integer |
| maxSeverity (Lecture seule) | Returns the maximum severity of the messages.
| Integer |
| meanError (Lecture seule) | The averaged difference between the measured and the predicted values. | Double |
| meanStandardized (Lecture seule) | Mean standardized error. | Double |
| messageCount (Lecture seule) | Returns the number of messages. | Integer |
| outputCount (Lecture seule) | Returns the number of outputs. | Integer |
| percentIn90Interval (Lecture seule) | The percentage of points that are contained in a 90 percent cross validated confidence interval. | Double |
| percentIn95Interval (Lecture seule) | The percentage of points that are contained in a 95 percent cross validated confidence interval. | Double |
| resultID (Lecture seule) | Gets the job ID. If the tool is not a geoprocessing service, the resultID will be "". | String |
| rootMeanSquare (Lecture seule) | The root mean square error. | Double |
| rootMeanSquareStandardized (Lecture seule) | 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 (Lecture seule) | Gets the job status.
| Integer |
Vue d’ensemble des méthodes
| Méthode | Explication |
| 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. |
Méthodes
cancel ()
getInput (index)
| Paramètre | Explication | Type de données |
index | The index position of the input. | Integer |
| Type de données | Explication |
| Object | The input, either as a recordset or string. |
getMapImageURL ({parameter_list}, {height}, {width}, {resolution})| Paramètre | Explication | Type de données |
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 |
| Type de données | Explication |
| String | The URL of the map image. |
getMessage (index)
| Paramètre | Explication | Type de données |
index | The index position of the message. | Integer |
| Type de données | Explication |
| String | The geoprocessing message. |
getMessages ({severity})| Paramètre | Explication | Type de données |
severity | The type of messages to be returned.
Not specifying a severity level will return all types of messages. (La valeur par défaut est 0) | Integer |
| Type de données | Explication |
| String | The geoprocessing tool messages. |
getOutput (index)
| Paramètre | Explication | Type de données |
index | The index position of the outputs. | Integer |
| Type de données | Explication |
| 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)
| Paramètre | Explication | Type de données |
index | The message index position. | Integer |
| Type de données | Explication |
| Integer | The severity of the specific message.
|
Exemple de code
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))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))Vous avez un commentaire à formuler concernant cette rubrique ?