CrossValidationResult
Récapitulatif
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 Result class except for the additional read-only properties that it contains. For detailed help, see the Cross Validation tool help.
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.
Propriétés
Propriété | Explication | Type de données |
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 message. | 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 |
resultID (Lecture seule) |
Gets the job ID. | 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}) |
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 recordset or string. If the output of the tool, such as MakeFeatureLayer is a layer, getOutput will return a Layer object. |
getSeverity (index) |
Returns the severity of a specific message. |
Méthodes
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. |
Paramètre | Explication | Type de données |
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 |
Type de données | Explication |
String |
The URL of the map image. |
Paramètre | Explication | Type de données |
index |
The index position of the message. | Integer |
Type de données | Explication |
String |
The geoprocessing message. |
Paramètre | Explication | Type de données |
severity |
The type of messages to be returned: 0=message, 1=warning, 2=error. Not specifying a value returns all message types.
(La valeur par défaut est 0) | Integer |
Type de données | Explication |
String |
The geoprocessing messages. |
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 string. If the output of the tool, such as MakeFeatureLayer is a layer, getOutput will return a Layer object. |
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" # Check out the ArcGIS Geostatistical Analyst extension license arcpy.CheckOutExtension("GeoStats") # Execute CrossValidation cvResult = arcpy.CrossValidation_ga(inLayer) print "Root Mean Square error = " + str(cvResult.rootMeanSquare)