SparseDoubleVector (java-string-similarity 0.17 API)

java.lang.Object
- info.debatty.java.utils.SparseDoubleVector

All Implemented Interfaces:

Serializable
```
public class SparseDoubleVector
extends Object
implements Serializable
```
Sparse vector of double, implemented using two arrays.

Author:

Thibault Debatty

See Also:
Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected int[] keys

protected int size

protected double[] values

Fields
Modifier and Type	Field and Description
`protected int[]`	`keys`
`protected int`	`size`
`protected double[]`	`values`

Constructor Summary

Constructors
Constructor and Description
`SparseDoubleVector()`
`SparseDoubleVector(double[] array)`
`SparseDoubleVector(HashMap<Integer,Double> hashmap)`
`SparseDoubleVector(int size)`

Method Summary

Methods
Modifier and Type	Method and Description
`double`	`cosineSimilarity(SparseDoubleVector other)` Return the cosine similarity between the vectors.
`double`	`dotProduct(double[] other)`
`double`	`dotProduct(SparseDoubleVector other)`
`int`	`intersection(SparseDoubleVector other)` Return the number of non-zero values these two vectors have in common, \|A inter B\|.
`double`	`jaccard(SparseDoubleVector other)` Computes and return the Jaccard index with other SparseVector.
`double`	`norm()` Compute and return the L2 norm of the vector
`double`	`qgram(SparseDoubleVector other)` Compute and return the qgram similarity with other vector.
`void`	`sampleDIMSUM(double threshold, int count, int size)`
`int`	`size()` Return the number of non-zero elements in this vector.
`double[]`	`toArray(int size)` Return the array corresponding to this sparse vector.
`String`	`toString()`
`int`	`union(SparseDoubleVector other)`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - keys
```
protected int[] keys
```
  - values
```
protected double[] values
```
  - size
```
protected int size
```
- Constructor Detail
  - SparseDoubleVector
```
public SparseDoubleVector(int size)
```
    Parameters:
    size -
  - SparseDoubleVector
```
public SparseDoubleVector()
```
  - SparseDoubleVector
```
public SparseDoubleVector(HashMap<Integer,Double> hashmap)
```
    Parameters:
    hashmap -
  - SparseDoubleVector
```
public SparseDoubleVector(double[] array)
```
    Parameters:
    array -
- Method Detail
  - dotProduct
```
public double dotProduct(SparseDoubleVector other)
```
    Parameters:
    other -
    
    Returns:
  - dotProduct
```
public double dotProduct(double[] other)
```
    Parameters:
    other -
    
    Returns:
  - jaccard
```
public double jaccard(SparseDoubleVector other)
```
    Computes and return the Jaccard index with other SparseVector. |A inter B| / |A union B| It is actually computed as |A inter B| / (|A| +|B| - | A inter B|) using a single loop over A and B
    
    Parameters:
    other -
    
    Returns:
  - union
```
public int union(SparseDoubleVector other)
```
    Parameters:
    other -
    
    Returns:
  - intersection
```
public int intersection(SparseDoubleVector other)
```
    Return the number of non-zero values these two vectors have in common, |A inter B|. E.g: A = {0 1 2 3} and B = {1 2 3 0} have non-zero values at positions 1 and 2, hence A.intersection(B) = 2
    
    Parameters:
    other -
    
    Returns:
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - qgram
```
public double qgram(SparseDoubleVector other)
```
    Compute and return the qgram similarity with other vector. Sum(|a_i - b_i|)
    
    Parameters:
    other -
    
    Returns:
  - size
```
public int size()
```
    Return the number of non-zero elements in this vector.
    
    Returns:
  - norm
```
public double norm()
```
    Compute and return the L2 norm of the vector
    
    Returns:
  - cosineSimilarity
```
public double cosineSimilarity(SparseDoubleVector other)
```
    Return the cosine similarity between the vectors. Similarity = cos(theta) = A . B / (|A|.|B|)
    
    Parameters:
    other -
    
    Returns:
  - sampleDIMSUM
```
public void sampleDIMSUM(double threshold,
                int count,
                int size)
```
    Parameters:
    threshold -
    count -
    size -
  - toArray
```
public double[] toArray(int size)
```
    Return the array corresponding to this sparse vector.
    
    Parameters:
    size -
    
    Returns:

Class SparseDoubleVector

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

keys

values

size

Constructor Detail

SparseDoubleVector

SparseDoubleVector

SparseDoubleVector

SparseDoubleVector

Method Detail

dotProduct

dotProduct

jaccard

union

intersection

toString

qgram

size

norm

cosineSimilarity

sampleDIMSUM

toArray