de.erichseifert.gral.data.filters

Class Kernel

java.lang.Object

de.erichseifert.gral.data.filters.Kernel

All Implemented Interfaces:

java.io.Serializable

public class Kernel
extends java.lang.Object
implements java.io.Serializable

Class that represents an one dimensional array of coefficients for a weighted filtering.

Functionality includes:

• Adding of other kernels or scalars
• Multiplication with other kernels or scalars
• Normalization
• Negation

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Kernel(double... values) Creates a new kernel object with the specified values and an offset being half the size of this kernel (rounded down).
Kernel(int offset, double[] values) Creates a new Kernel object with the specified offset and values.

Method Summary

Modifier and Type	Method and Description
Kernel	add(double v) Returns a new Kernel, where the specified value was added to each of the items.
Kernel	add(Kernel k) Returns a new Kernel, where the specified kernel was added.
double	get(int i) Returns the value at the specified position of this kernel.
static Kernel	getBinomial(double variance) Returns a Kernel of specified variance with binomial coefficients.
static Kernel	getBinomial(int size) Returns a Kernel of specified size with binomial coefficients.
int	getMaxIndex() Returns the index of the "rightmost" value.
int	getMinIndex() Returns the index of the "leftmost" value.
int	getOffset() Returns the offset of this kernel.
static Kernel	getUniform(int size, int offset, double value) Returns a Kernel with the specified size and offset, filled with a single value.
Kernel	mul(double v) Returns a new Kernel, where the specified value was multiplied with each of the items.
Kernel	mul(Kernel k) Returns a new Kernel, where the specified kernel was multiplied.
Kernel	negate() Returns a Kernel with all values being negated.
Kernel	normalize() Returns a normalized Kernel so that the sum of all values equals 1.
int	size() Returns the number of values in this kernel.

Methods inherited from class java.lang.Object

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

Constructor Detail

Kernel

public Kernel(int offset,
              double[] values)

Creates a new Kernel object with the specified offset and values.

Parameters:

offset - Offset to the first item in the kernel.

values - Array of values in the kernel.

Kernel

public Kernel(double... values)

Creates a new kernel object with the specified values and an offset being half the size of this kernel (rounded down).

Parameters:

values - Data values for the kernel.

Method Detail

getBinomial

public static Kernel getBinomial(double variance)

Returns a Kernel of specified variance with binomial coefficients.

Parameters:

variance - Variance.

Returns:

Kernel.

getBinomial

public static Kernel getBinomial(int size)

Returns a Kernel of specified size with binomial coefficients.

Parameters:

size - Size of the Kernel.

Returns:

Kernel.

getUniform

public static Kernel getUniform(int size,
                                int offset,
                                double value)

Returns a Kernel with the specified size and offset, filled with a single value.

Parameters:

size - Size.

offset - Offset.

value - Value the Kernel is filled with.

Returns:

Kernel.

get

public double get(int i)

Returns the value at the specified position of this kernel. If the position exceeds the minimum or maximum index, 0.0 is returned.

Parameters:

i - Index to be returned.

Returns:

Value at the specified index.

getOffset

public int getOffset()

Returns the offset of this kernel.

Returns:

Offset.

size

public int size()

Returns the number of values in this kernel.

Returns:

Number of values.

getMinIndex

public int getMinIndex()

Returns the index of the "leftmost" value.

Returns:

Minimal index.

getMaxIndex

public int getMaxIndex()

Returns the index of the "rightmost" value.

Returns:

Maximal index.

add

public Kernel add(double v)

Returns a new Kernel, where the specified value was added to each of the items.

Parameters:

v - Value to be added.

Returns:

Kernel with new values.

add

public Kernel add(Kernel k)

Returns a new Kernel, where the specified kernel was added.

Parameters:

k - Kernel to be added.

Returns:

Kernel with new values.

mul

public Kernel mul(double v)

Returns a new Kernel, where the specified value was multiplied with each of the items.

Parameters:

v - Value to be multiplied.

Returns:

Kernel with new values.

mul

public Kernel mul(Kernel k)

Returns a new Kernel, where the specified kernel was multiplied.

Parameters:

k - Kernel to be multiplied.

Returns:

Kernel with new values.

normalize

public Kernel normalize()

Returns a normalized Kernel so that the sum of all values equals 1.

Returns:

Normalized Kernel.

negate

public Kernel negate()

Returns a Kernel with all values being negated.

Returns:

Negated Kernel.