weka.core
Class SparseInstance

java.lang.Object
  weka.core.Instance
      weka.core.SparseInstance

All Implemented Interfaces:

java.io.Serializable, Copyable

public class SparseInstance
extends Instance

Class for storing an instance as a sparse vector. A sparse instance only requires storage for those attribute values that are non-zero. Since the objective is to reduce storage requirements for datasets with large numbers of default values, this also includes nominal attributes -- the first nominal value (i.e. that which has index 0) will not require explicit storage, so rearrange your nominal attribute value orderings if necessary. Missing values will be stored explicitly.

See Also:

Serialized Form

Constructor Summary

SparseInstance(double weight, double[] attValues)
Constructor that generates a sparse instance from the given parameters.

SparseInstance(double weight, double[] attValues, int[] indices, int maxNumValues)
Constructor that inititalizes instance variable with given values.

SparseInstance(Instance instance)
Constructor that generates a sparse instance from the given instance.

SparseInstance(int numAttributes)
Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.

SparseInstance(SparseInstance instance)
Constructor that copies the info from the given instance.

Method Summary

Attribute	attributeSparse(int indexOfIndex) Returns the attribute associated with the internal index.
java.lang.Object	copy() Produces a shallow copy of this instance.
int	index(int position) Returns the index of the attribute stored at the given position.
boolean	isMissing(int attIndex) Tests if a specific value is "missing".
int	locateIndex(int index) Locates the greatest index that is not greater than the given index.
static void	main(java.lang.String[] options) Main method for testing this class.
Instance	mergeInstance(Instance inst) Merges this instance with the given instance and returns the result.
int	numAttributes() Returns the number of attributes.
int	numValues() Returns the number of values in the sparse vector.
void	replaceMissingValues(double[] array) Replaces all missing values in the instance with the values contained in the given array.
void	setValue(int attIndex, double value) Sets a specific value in the instance to the given value (internal floating-point format).
void	setValueSparse(int indexOfIndex, double value) Sets a specific value in the instance to the given value (internal floating-point format).
double[]	toDoubleArray() Returns the values of each attribute as an array of doubles.
java.lang.String	toString() Returns the description of one instance in sparse format.
double	value(int attIndex) Returns an instance's attribute value in internal format.

Methods inherited from class weka.core.Instance

attribute, classAttribute, classIndex, classIsMissing, classValue, dataset, deleteAttributeAt, enumerateAttributes, equalHeaders, insertAttributeAt, isMissing, isMissingSparse, isMissingValue, missingValue, numClasses, setClassMissing, setClassValue, setClassValue, setDataset, setMissing, setMissing, setValue, setValue, setValue, setWeight, stringValue, stringValue, toString, toString, value, valueSparse, weight

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SparseInstance

public SparseInstance(Instance instance)

Constructor that generates a sparse instance from the given instance. Reference to the dataset is set to null. (ie. the instance doesn't have access to information about the attribute types)

Parameters:

instance - the instance from which the attribute values and the weight are to be copied

SparseInstance

public SparseInstance(SparseInstance instance)

Constructor that copies the info from the given instance. Reference to the dataset is set to null. (ie. the instance doesn't have access to information about the attribute types)

Parameters:

instance - the instance from which the attribute info is to be copied

SparseInstance

public SparseInstance(double weight,
                      double[] attValues)

Constructor that generates a sparse instance from the given parameters. Reference to the dataset is set to null. (ie. the instance doesn't have access to information about the attribute types)

Parameters:

weight - the instance's weight

attValues - a vector of attribute values

SparseInstance

public SparseInstance(double weight,
                      double[] attValues,
                      int[] indices,
                      int maxNumValues)

Constructor that inititalizes instance variable with given values. Reference to the dataset is set to null. (ie. the instance doesn't have access to information about the attribute types)

Parameters:

weight - the instance's weight

attValues - a vector of attribute values (just the ones to be stored)

indices - the indices of the given values in the full vector

maxNumValues - the maximium number of values that can be stored

SparseInstance

public SparseInstance(int numAttributes)

Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null. (ie. the instance doesn't have access to information about the attribute types)

Parameters:

numAttributes - the size of the instance

Method Detail

attributeSparse

public Attribute attributeSparse(int indexOfIndex)

Returns the attribute associated with the internal index.

Overrides:

attributeSparse in class Instance

Parameters:

indexOfIndex - the index of the attribute's index

Returns:

the attribute at the given position

Throws:

UnassignedDatasetException - if instance doesn't have access to a dataset

copy

public java.lang.Object copy()

Produces a shallow copy of this instance. The copy has access to the same dataset. (if you want to make a copy that doesn't have access to the dataset, use new SparseInstance(instance)

Specified by:

copy in interface Copyable

Overrides:

copy in class Instance

Returns:

the shallow copy

index

public int index(int position)

Returns the index of the attribute stored at the given position.

Overrides:

index in class Instance

Parameters:

position - the position

Returns:

the index of the attribute stored at the given position

isMissing

public boolean isMissing(int attIndex)

Tests if a specific value is "missing".

Overrides:

isMissing in class Instance

Parameters:

attIndex - the attribute's index

locateIndex

public int locateIndex(int index)

Locates the greatest index that is not greater than the given index.

Returns:

the internal index of the attribute index. Returns -1 if no index with this property couldn't be found

mergeInstance

public Instance mergeInstance(Instance inst)

Merges this instance with the given instance and returns the result. Dataset is set to null.

Overrides:

mergeInstance in class Instance

Parameters:

inst - the instance to be merged with this one

Returns:

the merged instances

numAttributes

public int numAttributes()

Returns the number of attributes.

Overrides:

numAttributes in class Instance

Returns:

the number of attributes as an integer

numValues

public int numValues()

Returns the number of values in the sparse vector.

Overrides:

numValues in class Instance

Returns:

the number of values

replaceMissingValues

public void replaceMissingValues(double[] array)

Replaces all missing values in the instance with the values contained in the given array. A deep copy of the vector of attribute values is performed before the values are replaced.

Overrides:

replaceMissingValues in class Instance

Parameters:

array - containing the means and modes

Throws:

java.lang.IllegalArgumentException - if numbers of attributes are unequal

setValue

public void setValue(int attIndex,
                     double value)

Sets a specific value in the instance to the given value (internal floating-point format). Performs a deep copy of the vector of attribute values before the value is set.

Overrides:

setValue in class Instance

Parameters:

attIndex - the attribute's index

value - the new attribute value (If the corresponding attribute is nominal (or a string) then this is the new value's index as a double).

setValueSparse

public void setValueSparse(int indexOfIndex,
                           double value)

Sets a specific value in the instance to the given value (internal floating-point format). Performs a deep copy of the vector of attribute values before the value is set.

Overrides:

setValueSparse in class Instance

Parameters:

indexOfIndex - the index of the attribute's index

value - the new attribute value (If the corresponding attribute is nominal (or a string) then this is the new value's index as a double).

toDoubleArray

public double[] toDoubleArray()

Returns the values of each attribute as an array of doubles.

Overrides:

toDoubleArray in class Instance

Returns:

an array containing all the instance attribute values

toString

public java.lang.String toString()

Returns the description of one instance in sparse format. If the instance doesn't have access to a dataset, it returns the internal floating-point values. Quotes string values that contain whitespace characters.

Overrides:

toString in class Instance

Returns:

the instance's description as a string

value

public double value(int attIndex)

Returns an instance's attribute value in internal format.

Overrides:

value in class Instance

Parameters:

attIndex - the attribute's index

Returns:

the specified value as a double (If the corresponding attribute is nominal (or a string) then it returns the value's index as a double).

main

public static void main(java.lang.String[] options)

Main method for testing this class.