com.esri.arcgis.geoprocessing.tools.spatialanalysttools
Class MLClassify

java.lang.Object
  com.esri.arcgis.geoprocessing.AbstractGPTool
      com.esri.arcgis.geoprocessing.tools.spatialanalysttools.MLClassify

All Implemented Interfaces:

GPTool

public class MLClassify
extends AbstractGPTool

Performs a maximum likelihood classification on a set of raster bands. The Maximum Likelihood Classification tool is contained in the Spatial Analyst Tools tool box.
Learn more about how Maximum Likelihood Classification works

Software restrictions: none

Usage tips:

• Any signature file created by the Create Signature, Edit Signature, or Iso Cluster tools is a valid entry for the input signature file. These will have a ".gsg" extension.
• The input a priori probability file must be an ASCII file consisting of two columns. The values in the left column represent class IDs. The values in the right column represent the a priori probabilities for the respective classes. Valid values for class a priori probabilities must be greater than or equal to zero. If zero is specified as a probability, the class will not appear on the output raster. The sum of the specified a priori probabilities must be less than or equal to one. The format of the file is as follows: 1 .3 2 .1 4 .0 5 .15 7 .05 8 .2The classes omitted in the file will receive the average a priori probability of the remaining portion of the value of one. In the above example, all classes from 1 to 8 are represented in the signature file. The a priori probabilities of classes 3 and 6 are missing in the {in_a_priori_file}. Since the sum of all probabilities specified in the above file is equal to 0.8, the remaining portion of the probability (0.2) is divided by the number of classes not specified (two). Therefore, classes 3 and 6 will each be assigned a probability of 0.1.
• A specified reject fraction, which lies between any two valid values, will be assigned to the next upper valid value. For example, 0.02 will become 0.025.
• If the input is a layer created from a multiband raster with more than three bands, the operation will only consider the bands that were loaded (symbolized) by the layer.
• By default, all cells in the output raster will be classified, with each class having equal probability weights attached to their signatures.
• There is a direct relationship between the number of unclassified cells on the output raster resulting from the reject fraction and the number of cells represented by the sum of levels of confidence smaller than the respective value entered for the reject fraction.
• The extension for an input a priori probability file is ".txt".

Field Summary

Fields inherited from class com.esri.arcgis.geoprocessing.AbstractGPTool

vals

Constructor Summary

MLClassify()
Creates the Maximum Likelihood Classification tool with defaults.

MLClassify(Object inRasterBands, Object inSignatureFile, Object outClassifiedRaster)
Creates the Maximum Likelihood Classification tool with the required parameters.

Method Summary

String	getAPrioriProbabilities() Returns the A priori probability weighting parameter of this tool .
Object	getInAPrioriFile() Returns the Input a priori probability file parameter of this tool .
Object	getInRasterBands() Returns the Input raster bands parameter of this tool .
Object	getInSignatureFile() Returns the Input signature file parameter of this tool .
Object	getOutClassifiedRaster() Returns the Output classified raster parameter of this tool .
Object	getOutConfidenceRaster() Returns the Output confidence raster parameter of this tool .
String	getRejectFraction() Returns the Reject fraction parameter of this tool .
String	getToolboxAlias() Returns the alias of the tool box containing this tool.
String	getToolboxName() Returns the name of the tool box containing this tool.
String	getToolName() Returns the name of this tool.
void	setAPrioriProbabilities(String aPrioriProbabilities) Sets the A priori probability weighting parameter of this tool .
void	setInAPrioriFile(Object inAPrioriFile) Sets the Input a priori probability file parameter of this tool .
void	setInRasterBands(Object inRasterBands) Sets the Input raster bands parameter of this tool .
void	setInSignatureFile(Object inSignatureFile) Sets the Input signature file parameter of this tool .
void	setOutClassifiedRaster(Object outClassifiedRaster) Sets the Output classified raster parameter of this tool .
void	setOutConfidenceRaster(Object outConfidenceRaster) Sets the Output confidence raster parameter of this tool .
void	setRejectFraction(String rejectFraction) Sets the Reject fraction parameter of this tool .

Methods inherited from class com.esri.arcgis.geoprocessing.AbstractGPTool

getParameterValues, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

MLClassify

public MLClassify()

Creates the Maximum Likelihood Classification tool with defaults.

Initializes the array of tool parameters with the default values specified when the tool was created.

MLClassify

public MLClassify(Object inRasterBands,
                  Object inSignatureFile,
                  Object outClassifiedRaster)

Creates the Maximum Likelihood Classification tool with the required parameters.

Initializes the array of tool parameters with the values as specified for the required parameters and with the default values for the other parameters.

Parameters:

inRasterBands - Composite Geodataset, input raster bands.

inSignatureFile - File, a ".gsg" extension is required.

outClassifiedRaster - Raster Dataset, output classified raster dataset.

Method Detail

getInRasterBands

public Object getInRasterBands()

Returns the Input raster bands parameter of this tool . This parameter is Composite Geodataset, input raster bands. This is a required parameter.

Returns:

the Input raster bands

setInRasterBands

public void setInRasterBands(Object inRasterBands)

Sets the Input raster bands parameter of this tool . This parameter is Composite Geodataset, input raster bands. This is a required parameter.

Parameters:

inRasterBands - Composite Geodataset, input raster bands.

getInSignatureFile

public Object getInSignatureFile()

Returns the Input signature file parameter of this tool . This parameter is File, a ".gsg" extension is required. This is a required parameter.

Returns:

the Input signature file

setInSignatureFile

public void setInSignatureFile(Object inSignatureFile)

Sets the Input signature file parameter of this tool . This parameter is File, a ".gsg" extension is required. This is a required parameter.

Parameters:

inSignatureFile - File, a ".gsg" extension is required.

getOutClassifiedRaster

public Object getOutClassifiedRaster()

Returns the Output classified raster parameter of this tool . This parameter is Raster Dataset, output classified raster dataset. This is a required parameter.

Returns:

the Output classified raster

setOutClassifiedRaster

public void setOutClassifiedRaster(Object outClassifiedRaster)

Sets the Output classified raster parameter of this tool . This parameter is Raster Dataset, output classified raster dataset. This is a required parameter.

Parameters:

outClassifiedRaster - Raster Dataset, output classified raster dataset.

getRejectFraction

public String getRejectFraction()

Returns the Reject fraction parameter of this tool . This parameter is String, the 14 valid entries are: 0.0, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.975, 0.99, and 0.995. This is an optional parameter.

Returns:

the Reject fraction

setRejectFraction

public void setRejectFraction(String rejectFraction)

Sets the Reject fraction parameter of this tool . This parameter is String, the 14 valid entries are: 0.0, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.975, 0.99, and 0.995. This is an optional parameter.

Parameters:

rejectFraction - String, the 14 valid entries are: 0.0, 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.975, 0.99, and 0.995.

getAPrioriProbabilities

public String getAPrioriProbabilities()

Returns the A priori probability weighting parameter of this tool . This parameter is String, specifies how a priori probabilities will be determined. This is an optional parameter.

Returns:

the A priori probability weighting

setAPrioriProbabilities

public void setAPrioriProbabilities(String aPrioriProbabilities)

Sets the A priori probability weighting parameter of this tool . This parameter is String, specifies how a priori probabilities will be determined. This is an optional parameter.

Parameters:

aPrioriProbabilities - String, specifies how a priori probabilities will be determined.

getInAPrioriFile

public Object getInAPrioriFile()

Returns the Input a priori probability file parameter of this tool . This parameter is File, the extension for a priori files can be ".txt" or ".asc". This is an optional parameter.

Returns:

the Input a priori probability file

setInAPrioriFile

public void setInAPrioriFile(Object inAPrioriFile)

Sets the Input a priori probability file parameter of this tool . This parameter is File, the extension for a priori files can be ".txt" or ".asc". This is an optional parameter.

Parameters:

inAPrioriFile - File, the extension for a priori files can be ".txt" or ".asc".

getOutConfidenceRaster

public Object getOutConfidenceRaster()

Returns the Output confidence raster parameter of this tool . This parameter is Raster Dataset, output confidence raster dataset showing the certainty of the classification in 14 levels of confidence, with the lowest values representing the highest reliability. This is an optional parameter.

Returns:

the Output confidence raster

setOutConfidenceRaster

public void setOutConfidenceRaster(Object outConfidenceRaster)

Sets the Output confidence raster parameter of this tool . This parameter is Raster Dataset, output confidence raster dataset showing the certainty of the classification in 14 levels of confidence, with the lowest values representing the highest reliability. This is an optional parameter.

Parameters:

outConfidenceRaster - Raster Dataset, output confidence raster dataset showing the certainty of the classification in 14 levels of confidence, with the lowest values representing the highest reliability.

getToolName

public String getToolName()

Returns the name of this tool.

Returns:

the tool name

getToolboxName

public String getToolboxName()

Returns the name of the tool box containing this tool.

Returns:

the tool box name

getToolboxAlias

public String getToolboxAlias()

Returns the alias of the tool box containing this tool.

Returns:

the tool box alias