Package net.imglib2.histogram

Class HistogramNd<T>

java.lang.Object
net.imglib2.histogram.HistogramNd<T>
All Implemented Interfaces:
Iterable<LongType>, Dimensions, EuclideanSpace, Img<LongType>, Interval, IterableInterval<LongType>, IterableRealInterval<LongType>, RandomAccessible<LongType>, RandomAccessibleInterval<LongType>, RealInterval
public class HistogramNd<T> extends Object implements Img<LongType>
A HistogramNd is an n-dimensional histogram that tracks up to four kinds of values: 1) values in the center of the distribution 2) values to the left of the center of the distribution (lower tail) 3) values to the right of the center of the distribution (upper tail) 4) values outside the other areas

Note: the last three classifications may not be present depending upon the makeup of the input data.

Author:
Barry DeZonia

  • Constructor Summary

    Constructors
    Constructor
    Description
    HistogramNd(Iterable<List<T>> data, List<BinMapper1d<T>> mappers)
    Construct a histogram from an iterable set of data and a list of bin mapping algorithms.
    HistogramNd(List<Iterable<T>> data, List<BinMapper1d<T>> mappers)
    Construct a histogram from an iterable set of data and a list of bin mapping algorithms.
    HistogramNd(List<BinMapper1d<T>> mappers)
    Construct a histogram from a list of bin mapping algorithms.
    HistogramNd(HistogramNd<T> other)
    Construct a histogram whose bin mappings match another histogram.

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    addData(Iterable<List<T>> data)
    Counts additional data contained in a given iterable collection.
    void
    addData(List<Iterable<T>> data)
    Counts additional data contained in a given iterable collection.
    HistogramNd<T>
    copy()
     
    void
    countData(Iterable<List<T>> data)
    Counts the data contained in the given data source using the underlying bin distribution.
    void
    countData(List<Iterable<T>> data)
    Counts the data contained in the given data source using the underlying bin distribution.
    Cursor<LongType>
    cursor()
    Returns a RealCursor that iterates with optimal speed without calculating the location at each iteration step.
    void
    decrement(long[] binPos)
    Directly decrement a bin by position.
    void
    decrement(List<T> values)
    Directly decrement a bin by value,
    DiscreteFrequencyDistribution
    dfd()
    Get the discrete frequency distribution associated with this histogram.
    long
    dimension(int d)
    Return the size of the given dimension of the frequency distribution of this histogram.
    void
    dimensions(long[] dims)
    Fill the provided long[] with the sizes of all dimensions of the frequency distribution of this histogram.
    long
    distributionCount()
    Returns the frequency count of all values in the distribution: lower tail + middle + upper tail.
    long
    distributionCount(int dim, long dimVal)
    Returns the frequency count of all values in the specified dimension of the distribution: lower tail + middle + upper tail.
    ImgFactory<LongType>
    factory()
    Get a ImgFactory that creates Imgs of the same kind as this one.
    LongType
    firstElement()
    Get the first element of this IterableRealInterval.
    long
    frequency(long[] binPos)
    Returns the frequency count of the values within a bin.
    long
    frequency(List<T> values)
    Returns the frequency count of values within a bin using a set of representative values.
    long
    getBinCount()
    Returns the number of bins contained in the histogram.
    void
    getCenterValues(long[] binPos, List<T> values)
    Gets the values associated with the center of a bin.
    void
    getLowerBounds(long[] binPos, List<T> values)
    Gets the values associated with the left edge of a bin.
    void
    getUpperBounds(long[] binPos, List<T> values)
    Gets the values associated with the right edge of a bin.
    boolean
    hasTails()
    Returns true if the histogram has tail bins which count extreme values for one or more dimensions
    boolean
    hasTails(int dim)
    Returns true if the histogram has tail bins which count extreme values for the given dimension.
    long
    ignoredCount()
    Returns the frequency count of values that were ignored because they could not be mapped to any bin.
    boolean
    includesLowerBound(int dim, long binPos)
    Returns true if the given bin interval is closed on the left for the given dimension.
    boolean
    includesLowerBounds(long[] binPos)
    Returns true if the given bin interval is closed on the left
    boolean
    includesUpperBound(int dim, long binPos)
    Returns true if the given bin interval is closed on the right for the given dimension.
    boolean
    includesUpperBounds(long[] binPos)
    Returns true if the given bin interval is closed on the right
    void
    increment(long[] binPos)
    Directly increment a bin by position.
    void
    increment(List<T> values)
    Directly increment a bin by value.
    boolean
    isInLowerTail(int dim, T value)
    Returns true if a given value for a given dimension is mapped to the lower tail of the distribution.
    boolean
    isInLowerTail(List<T> values)
    Returns true if a given set of values are mapped to the lower tail of the distribution.
    boolean
    isInMiddle(int dim, T value)
    Returns true if a given value for a given dimension is mapped to the middle of the distribution.
    boolean
    isInMiddle(List<T> values)
    Returns true if a given set of values are mapped to the middle of the distribution.
    boolean
    isInUpperTail(int dim, T value)
    Returns true if a given value for a given dimension is mapped to the upper tail of the distribution.
    boolean
    isInUpperTail(List<T> values)
    Returns true if a given set of values are mapped to the upper tail of the distribution.
    boolean
    isOutside(int dim, T value)
    Returns true if a given value for a given dimension is outside the distribution.
    boolean
    isOutside(List<T> values)
    Returns true if a given set of values are outside the distribution.
    Object
    iterationOrder()
    Returns the iteration order of this IterableRealInterval.
    Iterator<LongType>
    iterator()
     
    Cursor<LongType>
    localizingCursor()
    Returns a RealLocalizable Iterator that calculates its location at each iteration step.
    long
    lowerTailCount()
    Returns the frequency count of values in all lower tail bins (if any).
    long
    lowerTailCount(int dim)
    Returns the frequency count of values in the lower tail bin (if any) for the given dimension.
    void
    map(List<T> values, long[] binPos)
    Fills a bin position by mapping from a set of representative values.
    long
    max(int d)
    Get the maximum in dimension d.
    void
    max(long[] max)
    Write the maximum of each dimension into long[].
    void
    max(Positionable max)
    Sets a Positionable to the maximum of this Interval
    long
    min(int d)
    Get the minimum in dimension d.
    void
    min(long[] min)
    Write the minimum of each dimension into long[].
    void
    min(Positionable min)
    Sets a Positionable to the minimum of this Interval
    int
    numDimensions()
    Return the number of dimensions of the frequency distribution of this histogram.
    RandomAccess<LongType>
    randomAccess()
    Create a random access sampler for integer coordinates.
    RandomAccess<LongType>
    randomAccess(Interval interval)
    Create a random access sampler for integer coordinates.
    void
    realMax(double[] max)
    Write the maximum of each dimension into double[].
    double
    realMax(int d)
    Get the maximum in dimension d.
    void
    realMax(RealPositionable max)
    Sets a RealPositionable to the maximum of this Interval
    void
    realMin(double[] min)
    Write the minimum of each dimension into double[].
    double
    realMin(int d)
    Get the minimum in dimension d.
    void
    realMin(RealPositionable min)
    Sets a RealPositionable to the minimum of this Interval
    double
    relativeFrequency(long[] binPos, boolean includeTails)
    Returns the relative frequency of values within a bin.
    double
    relativeFrequency(List<T> values, boolean includeTails)
    Returns the relative frequency of values within a bin using a set of representative values.
    void
    resetCounters()
    Resets all data counts to 0.
    long
    size()
    Returns the number of elements in this Function.
    void
    subtractData(Iterable<List<T>> data)
    Uncounts some original data contained in a given iterable collection.
    void
    subtractData(List<Iterable<T>> data)
    Uncounts some original data contained in a given iterable collection.
    long
    totalCount()
    Returns the total count of all values observed; both within and without the entire distribution.
    long
    upperTailCount()
    Returns the frequency count of values in all upper tail bins (if any).
    long
    upperTailCount(int dim)
    Returns the frequency count of values in the upper tail bin (if any) for the given dimension.
    long
    valueCount()
    Returns the frequency count of all values in the middle of the distribution.
    long
    valueCount(int dim)
    Returns the frequency count of all values in the middle of the distribution for a given dimension.

    Methods inherited from class java.lang.Object

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

    Methods inherited from interface java.lang.Iterable

    forEach, spliterator

  • Constructor Details

    • HistogramNd

      public HistogramNd(List<BinMapper1d<T>> mappers)
      Construct a histogram from a list of bin mapping algorithms. Use countData() to populate it.
      Parameters:
      mappers - The algorithms used to map values to bins

    • HistogramNd

      public HistogramNd(HistogramNd<T> other)
      Construct a histogram whose bin mappings match another histogram. After this construction the histogram bins are unpopulated.
      Parameters:
      other - The histogram to copy.

    • HistogramNd

      public HistogramNd(Iterable<List<T>> data, List<BinMapper1d<T>> mappers)
      Construct a histogram from an iterable set of data and a list of bin mapping algorithms. Must be given one iterable data source that returns multiple data values at each point.
      Parameters:
      data - The iterable set of values to calculate upon
      mappers - The algorithms used to map values to bins

    • HistogramNd

      public HistogramNd(List<Iterable<T>> data, List<BinMapper1d<T>> mappers)
      Construct a histogram from an iterable set of data and a list of bin mapping algorithms. Must be given multiple iterable data sources that each return a single data value at each point.
      Parameters:
      data - The iterable set of values to calculate upon
      mappers - The algorithms used to map values to bins

  • Method Details

    • hasTails

      public boolean hasTails(int dim)
      Returns true if the histogram has tail bins which count extreme values for the given dimension.

    • hasTails

      public boolean hasTails()
      Returns true if the histogram has tail bins which count extreme values for one or more dimensions

    • lowerTailCount

      public long lowerTailCount(int dim)
      Returns the frequency count of values in the lower tail bin (if any) for the given dimension.

    • lowerTailCount

      public long lowerTailCount()
      Returns the frequency count of values in all lower tail bins (if any).

    • upperTailCount

      public long upperTailCount(int dim)
      Returns the frequency count of values in the upper tail bin (if any) for the given dimension.

    • upperTailCount

      public long upperTailCount()
      Returns the frequency count of values in all upper tail bins (if any).

    • valueCount

      public long valueCount(int dim)
      Returns the frequency count of all values in the middle of the distribution for a given dimension.

    • valueCount

      public long valueCount()
      Returns the frequency count of all values in the middle of the distribution.

    • distributionCount

      public long distributionCount(int dim, long dimVal)
      Returns the frequency count of all values in the specified dimension of the distribution: lower tail + middle + upper tail. Does not include ignored values.

    • distributionCount

      public long distributionCount()
      Returns the frequency count of all values in the distribution: lower tail + middle + upper tail. Does not include ignored values.

    • ignoredCount

      public long ignoredCount()
      Returns the frequency count of values that were ignored because they could not be mapped to any bin.

    • totalCount

      public long totalCount()
      Returns the total count of all values observed; both within and without the entire distribution. Thus it includes ignored values. One should decide carefully between using distributionCount() and totalCount().

    • frequency

      public long frequency(List<T> values)
      Returns the frequency count of values within a bin using a set of representative values. Note that multiple values can be mapped to one bin so this is NOT the frequency count of this exact set of values in the distribution.
      Parameters:
      values - A set of representative values of interest

    • frequency

      public long frequency(long[] binPos)
      Returns the frequency count of the values within a bin.

    • relativeFrequency

      public double relativeFrequency(List<T> values, boolean includeTails)
      Returns the relative frequency of values within a bin using a set of representative values. Note that multiple values can be mapped to one bin so this is NOT the relative frequency of this exact set of values in the distribution.

      This calculation is of the number of values in the bin divided by either the number of values in the distribution or the number of values in the center of the distribution (tails ignored).

      One can devise other ways to count relative frequencies that consider ignored values also. If needed one can use the various count methods and frequency methods to calculate any relative frequency desired.

      Parameters:
      values - A representative set of values of interest
      includeTails - Flag for determining whether to include tails in calculation.

    • relativeFrequency

      public double relativeFrequency(long[] binPos, boolean includeTails)
      Returns the relative frequency of values within a bin.

      This calculation is of the number of values in the bin divided by either the number of values in the distribution or the number of values in the center of the distribution (tails ignored).

      One can devise other ways to count relative frequencies that consider ignored values also. If needed one can use the various count methods and frequency methods to calculate any relative frequency desired.

      Parameters:
      binPos - The position of the bin of interest
      includeTails - Flag for determining whether to include tails in calculation.

    • getBinCount

      public long getBinCount()
      Returns the number of bins contained in the histogram.

    • map

      public void map(List<T> values, long[] binPos)
      Fills a bin position by mapping from a set of representative values.

    • getCenterValues

      public void getCenterValues(long[] binPos, List<T> values)
      Gets the values associated with the center of a bin.
      Parameters:
      binPos - The bin index of interest
      values - The outputs to fill with the center values

    • getLowerBounds

      public void getLowerBounds(long[] binPos, List<T> values)
      Gets the values associated with the left edge of a bin.
      Parameters:
      binPos - The bin index of interest
      values - The outputs to fill with the left edge values

    • getUpperBounds

      public void getUpperBounds(long[] binPos, List<T> values)
      Gets the values associated with the right edge of a bin.
      Parameters:
      binPos - The bin index of interest
      values - The outputs to fill with the right edge values

    • includesUpperBounds

      public boolean includesUpperBounds(long[] binPos)
      Returns true if the given bin interval is closed on the right
      Parameters:
      binPos - The bin number of the interval of interest

    • includesLowerBounds

      public boolean includesLowerBounds(long[] binPos)
      Returns true if the given bin interval is closed on the left
      Parameters:
      binPos - The bin number of the interval of interest

    • includesUpperBound

      public boolean includesUpperBound(int dim, long binPos)
      Returns true if the given bin interval is closed on the right for the given dimension.
      Parameters:
      dim - The dimension of interest
      binPos - The bin number of the interval of interest

    • includesLowerBound

      public boolean includesLowerBound(int dim, long binPos)
      Returns true if the given bin interval is closed on the left for the given dimension.
      Parameters:
      dim - The dimension of interest
      binPos - The bin number of the interval of interest

    • isInLowerTail

      public boolean isInLowerTail(List<T> values)
      Returns true if a given set of values are mapped to the lower tail of the distribution.
      Parameters:
      values - The set of values to determine the location of

    • isInLowerTail

      public boolean isInLowerTail(int dim, T value)
      Returns true if a given value for a given dimension is mapped to the lower tail of the distribution.
      Parameters:
      dim - The dimension number of the axis of interest
      value - The value to determine the location of

    • isInUpperTail

      public boolean isInUpperTail(List<T> values)
      Returns true if a given set of values are mapped to the upper tail of the distribution.
      Parameters:
      values - The set of values to determine the location of

    • isInUpperTail

      public boolean isInUpperTail(int dim, T value)
      Returns true if a given value for a given dimension is mapped to the upper tail of the distribution.
      Parameters:
      dim - The dimension number of the axis of interest
      value - The value to determine the location of

    • isInMiddle

      public boolean isInMiddle(List<T> values)
      Returns true if a given set of values are mapped to the middle of the distribution.
      Parameters:
      values - The set of values to determine the location of

    • isInMiddle

      public boolean isInMiddle(int dim, T value)
      Returns true if a given value for a given dimension is mapped to the middle of the distribution.
      Parameters:
      dim - The dimension number of the axis of interest
      value - The value to determine the location of

    • isOutside

      public boolean isOutside(List<T> values)
      Returns true if a given set of values are outside the distribution.
      Parameters:
      values - The set of values to determine the location of

    • isOutside

      public boolean isOutside(int dim, T value)
      Returns true if a given value for a given dimension is outside the distribution.
      Parameters:
      value - The value to determine the location of

    • dfd

      public DiscreteFrequencyDistribution dfd()
      Get the discrete frequency distribution associated with this histogram.

    • countData

      public void countData(Iterable<List<T>> data)
      Counts the data contained in the given data source using the underlying bin distribution.
      Parameters:
      data - The total data to count

    • countData

      public void countData(List<Iterable<T>> data)
      Counts the data contained in the given data source using the underlying bin distribution.
      Parameters:
      data - The total data to count

    • addData

      public void addData(Iterable<List<T>> data)
      Counts additional data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
      Parameters:
      data - The new data to count

    • addData

      public void addData(List<Iterable<T>> data)
      Counts additional data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
      Parameters:
      data - The new data to count

    • subtractData

      public void subtractData(Iterable<List<T>> data)
      Uncounts some original data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
      Parameters:
      data - The old data to uncount

    • subtractData

      public void subtractData(List<Iterable<T>> data)
      Uncounts some original data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
      Parameters:
      data - The old data to uncount

    • increment

      public void increment(long[] binPos)
      Directly increment a bin by position.
      Parameters:
      binPos - The 1-d index of the bin

    • decrement

      public void decrement(long[] binPos)
      Directly decrement a bin by position.
      Parameters:
      binPos - The 1-d index of the bin

    • increment

      public void increment(List<T> values)
      Directly increment a bin by value.
      Parameters:
      values - The values to map to a bin position

    • decrement

      public void decrement(List<T> values)
      Directly decrement a bin by value,
      Parameters:
      values - The values to map to a bin position

    • resetCounters

      public void resetCounters()
      Resets all data counts to 0.

    • numDimensions

      public int numDimensions()
      Return the number of dimensions of the frequency distribution of this histogram.
      Specified by:
      numDimensions in interface EuclideanSpace

    • dimension

      public long dimension(int d)
      Return the size of the given dimension of the frequency distribution of this histogram.
      Specified by:
      dimension in interface Dimensions
      Parameters:
      d -

    • dimensions

      public void dimensions(long[] dims)
      Fill the provided long[] with the sizes of all dimensions of the frequency distribution of this histogram.
      Specified by:
      dimensions in interface Dimensions
      Parameters:
      dims -

    • randomAccess

      public RandomAccess<LongType> randomAccess()
      Description copied from interface: RandomAccessible
      Create a random access sampler for integer coordinates.

      The returned random access covers as much of the domain as possible.

      Please note: RandomAccessibleIntervals have a finite domain (their Interval), so RandomAccessible.randomAccess() is only guaranteed to cover this finite domain. This may lead to unexpected results when using Views. In the following code 
       RandomAccessible<T> extended = Views.extendBorder( img )
 RandomAccessibleInterval<T> cropped = Views.interval( extended, img );
 RandomAccess<T> a1 = extended.randomAccess();
 RandomAccess<T> a2 = cropped.randomAccess();
      The access a1 on the extended image is valid everywhere. However, somewhat counter-intuitively, the access a2 on the extended and cropped image is only valid on the interval img to which the extended image was cropped. The access is only required to cover this interval, because it is the domain of the cropped image. Views attempts to provide the fastest possible access that meets this requirement, and will therefore strip the extension. To deal with this, if you know that you need to access pixels outside the domain of the RandomAccessibleInterval, and you know that the RandomAccessibleInterval is actually defined beyond its interval boundaries, then use the RandomAccessible.randomAccess(Interval) variant and specify which interval you actually want to access. In the above example, 
       RandomAccess<T> a2 = cropped.randomAccess( Intervals.expand( img, 10 ) );
      will provide the extended access as expected.
      Specified by:
      randomAccess in interface RandomAccessible<T>
      Returns:
      random access sampler

    • randomAccess

      public RandomAccess<LongType> randomAccess(Interval interval)
      Description copied from interface: RandomAccessible
      Create a random access sampler for integer coordinates.

      The returned random access is intended to be used in the specified interval only. Thus, the RandomAccessible may provide optimized versions. If the interval is completely contained in the domain, the random access is guaranteed to provide the same values as that obtained by RandomAccessible.randomAccess() within the interval.

      Specified by:
      randomAccess in interface RandomAccessible<T>
      Parameters:
      interval - in which interval you intend to use the random access.
      Returns:
      random access sampler

    • min

      public long min(int d)
      Description copied from interface: Interval
      Get the minimum in dimension d.
      Specified by:
      min in interface Interval
      Parameters:
      d - dimension
      Returns:
      minimum in dimension d.

    • min

      public void min(long[] min)
      Description copied from interface: Interval
      Write the minimum of each dimension into long[].
      Specified by:
      min in interface Interval
      Parameters:
      min -

    • min

      public void min(Positionable min)
      Description copied from interface: Interval
      Sets a Positionable to the minimum of this Interval
      Specified by:
      min in interface Interval
      Parameters:
      min -

    • max

      public long max(int d)
      Description copied from interface: Interval
      Get the maximum in dimension d.
      Specified by:
      max in interface Interval
      Parameters:
      d - dimension
      Returns:
      maximum in dimension d.

    • max

      public void max(long[] max)
      Description copied from interface: Interval
      Write the maximum of each dimension into long[].
      Specified by:
      max in interface Interval
      Parameters:
      max -

    • max

      public void max(Positionable max)
      Description copied from interface: Interval
      Sets a Positionable to the maximum of this Interval
      Specified by:
      max in interface Interval
      Parameters:
      max -

    • realMin

      public double realMin(int d)
      Description copied from interface: RealInterval
      Get the minimum in dimension d.
      Specified by:
      realMin in interface RealInterval
      Parameters:
      d - dimension
      Returns:
      minimum in dimension d.

    • realMin

      public void realMin(double[] min)
      Description copied from interface: RealInterval
      Write the minimum of each dimension into double[].
      Specified by:
      realMin in interface RealInterval
      Parameters:
      min -

    • realMin

      public void realMin(RealPositionable min)
      Description copied from interface: RealInterval
      Sets a RealPositionable to the minimum of this Interval
      Specified by:
      realMin in interface RealInterval
      Parameters:
      min -

    • realMax

      public double realMax(int d)
      Description copied from interface: RealInterval
      Get the maximum in dimension d.
      Specified by:
      realMax in interface RealInterval
      Parameters:
      d - dimension
      Returns:
      maximum in dimension d.

    • realMax

      public void realMax(double[] max)
      Description copied from interface: RealInterval
      Write the maximum of each dimension into double[].
      Specified by:
      realMax in interface RealInterval
      Parameters:
      max -

    • realMax

      public void realMax(RealPositionable max)
      Description copied from interface: RealInterval
      Sets a RealPositionable to the maximum of this Interval
      Specified by:
      realMax in interface RealInterval
      Parameters:
      max -

    • cursor

      public Cursor<LongType> cursor()
      Description copied from interface: IterableRealInterval

      Returns a RealCursor that iterates with optimal speed without calculating the location at each iteration step. Localization is performed on demand.

      Use this where localization is required rarely/ not for each iteration.

      Specified by:
      cursor in interface IterableInterval<T>
      Specified by:
      cursor in interface IterableRealInterval<T>
      Returns:
      fast iterating iterator

    • localizingCursor

      public Cursor<LongType> localizingCursor()
      Description copied from interface: IterableRealInterval

      Returns a RealLocalizable Iterator that calculates its location at each iteration step. That is, localization is performed with optimal speed.

      Use this where localization is required often/ for each iteration.

      Specified by:
      localizingCursor in interface IterableInterval<T>
      Specified by:
      localizingCursor in interface IterableRealInterval<T>
      Returns:
      fast localizing iterator

    • size

      public long size()
      Description copied from interface: IterableRealInterval

      Returns the number of elements in this Function.

      Specified by:
      size in interface IterableRealInterval<T>
      Returns:
      number of elements

    • firstElement

      public LongType firstElement()
      Description copied from interface: IterableRealInterval
      Get the first element of this IterableRealInterval. This is a shortcut for cursor().next(). This can be used to create a new variable of type T using firstElement().createVariable(), which is useful in generic methods to store temporary results, e.g., a running sum over pixels in the IterableRealInterval.
      Specified by:
      firstElement in interface IterableRealInterval<T>
      Returns:
      the first element in iteration order.

    • iterationOrder

      public Object iterationOrder()
      Description copied from interface: IterableRealInterval
      Returns the iteration order of this IterableRealInterval. If the returned object equals (Object.equals(Object)) the iteration order of another IterableRealInterval f then they can be copied by synchronous iteration. That is, having an Iterator on this and another Iterator on f, moving both in synchrony will point both of them to corresponding locations in their source domain. In other words, this and f have the same iteration order and means and the same number of elements.
      Specified by:
      iterationOrder in interface IterableRealInterval<T>
      Returns:
      the iteration order of this IterableRealInterval.
      See Also:

    • iterator

      public Iterator<LongType> iterator()
      Specified by:
      iterator in interface Iterable<T>

    • factory

      public ImgFactory<LongType> factory()
      Description copied from interface: Img
      Get a ImgFactory that creates Imgs of the same kind as this one. This is useful to create Imgs for temporary storage in generic methods where the specific Img type is unknown. Note, that the factory can be used even if all references to this Img have been invalidated.
      Specified by:
      factory in interface Img<T>
      Returns:
      a factory for Imgs of the same kind as this one.

    • copy

      public HistogramNd<T> copy()
      Specified by:
      copy in interface Img<T>
      Returns:
      - A copy of the current Img instance, all pixels are duplicated