AbstractGauss (ImgLib2 Javadocs 0-SNAPSHOT API)

java.lang.Object
- net.imglib2.algorithm.gauss.AbstractGauss<T>

Type Parameters:

T - - Defines the Type in which the actual computation is performed

Direct Known Subclasses:

GaussDouble, GaussFloat, GaussGeneral, GaussNativeType
```
public abstract class AbstractGauss<T extends NumericType<T>>
extends Object
```
Author:

Stephan Preibisch

Constructor Summary

Constructors
Constructor and Description
`AbstractGauss(double[] sigma, RandomAccessible<T> input, Interval inputInterval, RandomAccessible<T> output, Localizable outputOffset, ImgFactory<T> factory, T type)`

Method Summary

All Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`call()`
`protected void`	`computeKernel()` Compute the Gaussian Kernel for all dimensions
`protected SamplingLineIterator<T>`	`createInputLineSampler(int dim, Interval range)` An `Iterator` that samples a one dimensional line of input data for the current dimension.
`protected WritableLineIterator<T>`	`createOutputLineWriter(int dim, Interval range, SamplingLineIterator<T> inputLineSampler)` An `Iterator` that samples a one dimensional line of output data for the current dimension.
`ImgFactory<T>`	`getFactory()`
`RandomAccessible<T>`	`getInput()`
`Interval`	`getInputInterval()`
`double[][]`	`getKernel()`
`int`	`getNumThreads()`
`RandomAccessible<T>`	`getOutput()`
`Localizable`	`getOutputOffset()`
`protected abstract Img<T>`	`getProcessingLine(long size)`
`protected T`	`getProcessingType()`
`protected Interval`	`getRange(int dim)` The area for the output/temp that needs to be convolved, always relative to the input of the next convolution operation.
`RandomAccessible<T>`	`getResult()`
`double[]`	`getSigma()`
`protected Interval`	`getTemporaryImgSize()`
`Img<T>`	`getTmp1()`
`Img<T>`	`getTmp2()`
`int`	`numDimensions()`
`protected void`	`processLine(SamplingLineIterator<T> input, double[] kernel)` Compute the current line.
`void`	`setNumThreads(int numThreads)`
`T`	`type()`
`protected void`	`updateInputLineSampler(SamplingLineIterator<T> a, Interval range, long[] offset, Localizable originalLocation)` Updates the current `SamplingLineIterator` to the location of the new line that is processed and clears the processing line (set all values to zero)
`protected void`	`updateOutputLineWriter(WritableLineIterator<T> a, Interval range, long[] offset, Localizable originalLocation)` Updates the current `WritableLineIterator` to the location of the new line that is processed.
`protected void`	`writeLine(WritableLineIterator<T> a, SamplingLineIterator<T> inputLineSampler)` Writes the computed line back into the output/temp image.

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

- Constructor Detail
  - AbstractGauss
```
public AbstractGauss(double[] sigma,
                     RandomAccessible<T> input,
                     Interval inputInterval,
                     RandomAccessible<T> output,
                     Localizable outputOffset,
                     ImgFactory<T> factory,
                     T type)
```
- Method Detail
  - getSigma
```
public double[] getSigma()
```
  - getKernel
```
public double[][] getKernel()
```
  - numDimensions
```
public int numDimensions()
```
  - getInput
```
public RandomAccessible<T> getInput()
```
  - getOutput
```
public RandomAccessible<T> getOutput()
```
  - getFactory
```
public ImgFactory<T> getFactory()
```
  - getInputInterval
```
public Interval getInputInterval()
```
  - getOutputOffset
```
public Localizable getOutputOffset()
```
  - type
```
public T type()
```
  - getTmp1
```
public Img<T> getTmp1()
```
  - getTmp2
```
public Img<T> getTmp2()
```
  - getProcessingType
```
protected T getProcessingType()
```
  - getProcessingLine
```
protected abstract Img<T> getProcessingLine(long size)
```
  - getResult
```
public RandomAccessible<T> getResult()
```
    Returns:
    
    the result of the convolution
  - getRange
```
protected Interval getRange(int dim)
```
    The area for the output/temp that needs to be convolved, always relative to the input of the next convolution operation. The area is larger than the input, defined by the size of the kernel in each dimension.
    
    Parameters:
    
    dim - - The dimension that is currently processed
    
    Returns:
    
    - the Interval defining the output size for the current dimension that is processed
  - createInputLineSampler
```
protected SamplingLineIterator<T> createInputLineSampler(int dim,
                                                         Interval range)
```
    An Iterator that samples a one dimensional line of input data for the current dimension.
    
    Parameters:
    
    dim - - The current dimension
    
    range - - the size of the output/temp image
    
    Returns:
    
    - A SamplingLineIterator which provides the input
  - createOutputLineWriter
```
protected WritableLineIterator<T> createOutputLineWriter(int dim,
                                                         Interval range,
                                                         SamplingLineIterator<T> inputLineSampler)
```
    An Iterator that samples a one dimensional line of output data for the current dimension.
    
    Parameters:
    
    dim - - The current dimension
    
    range - - the size of the output/temp image
    
    inputLineSampler - - the input line sampler which knows all the stuff already
    
    Returns:
    
    - A SamplingLineIterator which provides the output
  - processLine
```
protected void processLine(SamplingLineIterator<T> input,
                           double[] kernel)
```
    Compute the current line. It is up to the implementation howto really do that. The idea is to only iterate over the input once (that's why it is an Iterator) as it is potentially an expensive operation (e.g. a Converter might be involved or we are computing on a rendered input)
    
    Parameters:
    
    input - - the Iterator/Sampler over the current input line.
  - writeLine
```
protected void writeLine(WritableLineIterator<T> a,
                         SamplingLineIterator<T> inputLineSampler)
```
    Writes the computed line back into the output/temp image. The idea is to only iterate over the output once (that's why it is an Iterator) as it is potentially an expensive operation (e.g. a Converter might be involved)
    
    Parameters:
    
    a - - the Iterator/Sampler over the current output line.
  - updateInputLineSampler
```
protected void updateInputLineSampler(SamplingLineIterator<T> a,
                                      Interval range,
                                      long[] offset,
                                      Localizable originalLocation)
```
    Updates the current SamplingLineIterator to the location of the new line that is processed and clears the processing line (set all values to zero)
    
    Parameters:
    
    a - - the SamplingLineIterator
    
    range - - the size of the output/temp image
    
    offset - - the new position
    
    originalLocation - - the location where is was put initially, all movements are relative to that
  - updateOutputLineWriter
```
protected void updateOutputLineWriter(WritableLineIterator<T> a,
                                      Interval range,
                                      long[] offset,
                                      Localizable originalLocation)
```
    Updates the current WritableLineIterator to the location of the new line that is processed.
    
    Parameters:
    
    a - - the WritableLineIterator
    
    range - - the size of the output/temp image
    
    offset - - the new position
    
    originalLocation - - the location where is was put initially, all movements are relative to that
  - computeKernel
```
protected void computeKernel()
```
    Compute the Gaussian Kernel for all dimensions
  - getTemporaryImgSize
```
protected Interval getTemporaryImgSize()
```
    Returns:
    
    - the size the input images need to have
  - getNumThreads
```
public int getNumThreads()
```
  - setNumThreads
```
public void setNumThreads(int numThreads)
```
  - call
```
public void call()
```

Class AbstractGauss<T extends NumericType<T>>

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

AbstractGauss

Method Detail

getSigma

getKernel

numDimensions

getInput

getOutput

getFactory

getInputInterval

getOutputOffset

type

getTmp1

getTmp2

getProcessingType

getProcessingLine

getResult

getRange

createInputLineSampler

createOutputLineWriter

processLine

writeLine

updateInputLineSampler

updateOutputLineWriter

computeKernel

getTemporaryImgSize

getNumThreads

setNumThreads

call