本文整理了Java中net.imglib2.util.Intervals.translate()方法的一些代码示例，展示了Intervals.translate()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Intervals.translate()方法的具体详情如下：
包路径：net.imglib2.util.Intervals
类名称：Intervals
方法名：translate

Intervals.translate介绍

[英]Translate an interval in one dimension. Create a FinalInterval , which is the input interval shifted by t in dimension d.
[中]在一维中平移间隔。创建一个FinalInterval，它是在维度d中按t移位的输入间隔。

代码示例

代码示例来源：origin: imglib/imglib2

/**
 * Translate the source view by the given translation vector. Pixel
 * <em>x</em> in the source view has coordinates <em>(x + translation)</em>
 * in the resulting view.
 *
 * @param interval
 *            the source
 * @param translation
 *            translation vector of the source view. The pixel at <em>x</em>
 *            in the source view becomes <em>(x + translation)</em> in the
 *            resulting view.
 */
public static < T > IntervalView< T > translate( final RandomAccessibleInterval< T > interval, final long... translation )
{
  return Views.interval(
      Views.translate( ( RandomAccessible< T > ) interval, translation ),
      Intervals.translate( interval, translation ) );
}

代码示例来源：origin: net.imglib2/imglib2

/**
 * Translate the source view by the given translation vector. Pixel
 * <em>x</em> in the source view has coordinates <em>(x + translation)</em>
 * in the resulting view.
 *
 * @param interval
 *            the source
 * @param translation
 *            translation vector of the source view. The pixel at <em>x</em>
 *            in the source view becomes <em>(x + translation)</em> in the
 *            resulting view.
 */
public static < T > IntervalView< T > translate( final RandomAccessibleInterval< T > interval, final long... translation )
{
  return Views.interval(
      Views.translate( ( RandomAccessible< T > ) interval, translation ),
      Intervals.translate( interval, translation ) );
}

代码示例来源：origin: net.imglib2/imglib2-algorithm

/**
 * Compute the partial derivative (central difference approximation) of source
 * in a particular dimension:
 * {@code d_f( x ) = ( f( x + e ) - f( x - e ) ) / 2},
 * where {@code e} is the unit vector along that dimension.
 *
 * @param source
 *            source image, has to provide valid data in the interval of the
 *            gradient image plus a one pixel border in dimension.
 * @param result
 *            output image
 * @param dimension
 *            along which dimension the partial derivatives are computed
 */
public static < T extends NumericType< T > > void gradientCentralDifference( final RandomAccessible< T > source,
    final RandomAccessibleInterval< T > result, final int dimension )
{
  final RandomAccessibleInterval< T > back = Views.interval( source, Intervals.translate( result, -1, dimension ) );
  final RandomAccessibleInterval< T > front = Views.interval( source, Intervals.translate( result, 1, dimension ) );
  LoopBuilder.setImages( result, back, front ).forEachPixel( ( r, b, f ) -> {
    r.set( f );
    r.sub( b );
    r.mul( 0.5 );
  } );
}

代码示例来源：origin: net.imglib2/imglib2-algorithm

/**
 * Compute the backward difference of source in a particular dimension:
 * {@code d_f( x ) = ( f( x ) - f( x - e ) )}
 * where {@code e} is the unit vector along that dimension
 *
 * @param source source image, has to provide valid data in the interval of
 *            the gradient image plus a one pixel border in dimension.
 * @param result output image
 * @param dimension along which dimension the partial derivatives are computed
 */
public static < T extends NumericType< T > > void gradientBackwardDifference( final RandomAccessible< T > source,
    final RandomAccessibleInterval< T > result, final int dimension )
{
  final RandomAccessibleInterval< T > back = Views.interval( source, Intervals.translate( result, -1, dimension ) );
  final RandomAccessibleInterval< T > front = Views.interval( source, result );
  LoopBuilder.setImages( result, back, front ).forEachPixel( ( r, b, f ) -> {
    r.set( f );
    r.sub( b );
  } );
}

代码示例来源：origin: net.imglib2/imglib2-algorithms

/**
 * Compute the partial derivative of source in a particular dimension.
 *
 * @param source
 *            source image, has to provide valid data in the interval of the
 *            gradient image plus a one pixel border in dimension.
 * @param gradient
 *            output image
 * @param dimension
 *            along which dimension the partial derivatives are computed
 */
public static < T extends NumericType< T > > void gradientCentralDifference2( final RandomAccessible< T > source, final RandomAccessibleInterval< T > gradient, final int dimension )
{
  final Cursor< T > front = Views.flatIterable( Views.interval( source, Intervals.translate( gradient, 1, dimension ) ) ).cursor();
  final Cursor< T > back = Views.flatIterable( Views.interval( source, Intervals.translate( gradient, -1, dimension ) ) ).cursor();
  for( final T t : Views.flatIterable( gradient ) )
  {
    t.set( front.next() );
    t.sub( back.next() );
    t.mul( 0.5 );
  }
}

代码示例来源：origin: net.imglib2/imglib2-algorithm

/**
   * Compute the forward difference of source in a particular dimension:
   * {@code d_f( x ) = ( f( x + e ) - f( x ) )}
   * where {@code e} is the unit vector along that dimension
   
   * @param source source image, has to provide valid data in the interval of
   *            the gradient image plus a one pixel border in dimension.
   * @param result output image
   * @param dimension along which dimension the partial derivatives are computed
   */
  public static < T extends NumericType< T > > void gradientForwardDifference( final RandomAccessible< T > source,
      final RandomAccessibleInterval< T > result, final int dimension )
  {
    final RandomAccessibleInterval< T > back = Views.interval( source, result );
    final RandomAccessibleInterval< T > front = Views.interval( source, Intervals.translate( result, 1, dimension ) );

    LoopBuilder.setImages( result, back, front ).forEachPixel( ( r, b, f ) -> {
      r.set( f );
      r.sub( b );
    } );
  }
}

代码示例来源：origin: net.imglib2/imglib2-algorithm

/**
 * Compute the partial derivative (central difference approximation) of source
 * in a particular dimension:
 * {@code d_f( x ) = ( f( x + e ) - f( x - e ) ) / 2},
 * where {@code e} is the unit vector along that dimension.
 *
 * @param source
 *            source image, has to provide valid data in the interval of the
 *            gradient image plus a one pixel border in dimension.
 * @param gradient
 *            output image
 * @param dimension
 *            along which dimension the partial derivatives are computed
 */
public static < T extends NumericType< T > > void gradientCentralDifference2( final RandomAccessible< T > source, final RandomAccessibleInterval< T > gradient, final int dimension )
{
  final Cursor< T > front = Views.flatIterable( Views.interval( source, Intervals.translate( gradient, 1, dimension ) ) ).cursor();
  final Cursor< T > back = Views.flatIterable( Views.interval( source, Intervals.translate( gradient, -1, dimension ) ) ).cursor();
  for ( final T t : Views.flatIterable( gradient ) )
  {
    t.set( front.next() );
    t.sub( back.next() );
    t.mul( 0.5 );
  }
}

代码示例来源：origin: imglib/imglib2

@Benchmark
public void gradient_niceAndFast()
{
  final RandomAccessibleInterval< DoubleType > backSource = Views.interval( in, Intervals.translate( out, -1, 0 ) );
  final RandomAccessibleInterval< DoubleType > frontSource = Views.interval( in, Intervals.translate( out, 1, 0 ) );
  LoopBuilder.setImages( out, backSource, frontSource ).forEachPixel(
      ( result, back, front ) -> {
        result.set( front );
        result.sub( back );
        result.mul( 0.5 );
      } );
}

代码示例来源：origin: imglib/imglib2

@Benchmark
public void gradient_niceAndSlow()
{
  final Cursor< DoubleType > front = Views.flatIterable( Views.interval( in, Intervals.translate( out, 1, 0 ) ) ).cursor();
  final Cursor< DoubleType > back = Views.flatIterable( Views.interval( in, Intervals.translate( out, -1, 0 ) ) ).cursor();
  for ( final DoubleType t : Views.flatIterable( out ) )
  {
    t.set( front.next() );
    t.sub( back.next() );
    t.mul( 0.5 );
  }
}

代码示例来源：origin: net.imglib2/imglib2-algorithms

final RandomAccess< T > back = source.randomAccess( Intervals.translate( gradient, 1, dimension ) );
final RandomAccess< T > front = source.randomAccess( Intervals.translate( gradient, -1, dimension ) );