OpParallelization (SciJava Ops Tutorial 1.0.0 API)

java.lang.Object
- org.scijava.ops.tutorial.OpParallelization

All Implemented Interfaces:

OpCollection
```
public class OpParallelization
extends Object
implements OpCollection
```
SciJava Ops includes a mechanism for automatically introducing concurrency to Ops. Developers can utilize this mechanism by writing their Ops on the smallest element of the computation, be that a single pixel, or a Neighborhood. SciJava Ops will then "lift" these Ops, creating parallelized Ops that run on an entire RandomAccessibleInterval This tutorial showcases these lifting mechanisms.

Author:

Gabriel Selzer

Constructor Summary

Constructors
Constructor Description

OpParallelization()

Method Summary

All Methods Static Methods Concrete Methods
Modifier and Type	Method	Description
`static void`	`averageNeighborhood(Neighborhood<UnsignedByteType> input, UnsignedByteType output)`	This Op, which computes some algorithm over a neighborhood, also lets the framework assume the burden of parallelization
`static void`	`invertOp(UnsignedByteType input, UnsignedByteType output)`	This Op, which is really just a computation on a single pixel, lets the framework assume the burden of parallelization
`static void`	`main(String... args)`

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

- Constructor Detail
  - OpParallelization
```
public OpParallelization()
```
- Method Detail
  - invertOp
```
public static void invertOp(UnsignedByteType input,
                            UnsignedByteType output)
```
    This Op, which is really just a computation on a single pixel, lets the framework assume the burden of parallelization
    
    Parameters:
    
    input - the input pixel
    
    output - the preallocated output pixel (container)
    
    Implementation Note:
    
    op names="tutorial.invertPerPixel"
  - averageNeighborhood
```
public static void averageNeighborhood(Neighborhood<UnsignedByteType> input,
                                       UnsignedByteType output)
```
    This Op, which computes some algorithm over a neighborhood, also lets the framework assume the burden of parallelization
    
    Parameters:
    
    input - the input pixel
    
    output - the preallocated output pixel (container)
    
    Implementation Note:
    
    op names="tutorial.neighborhoodAverage"
  - main
```
public static void main(String... args)
```