Module org.tensorflow.ndarray
Package org.tensorflow.ndarray.impl.sparse.slice

Class ObjectSparseSlice<T,​U extends NdArray<T>>

    • Constructor Detail

      • ObjectSparseSlice

        public ObjectSparseSlice​(SparseNdArray<T,​U> source,
                         long sourcePosition,
                         DimensionalSpace dimensions)
        Creates a BooleanSparseSlice
        Parameters:
        source - the source Sparse Array that this object slices.
        sourcePosition - the relative source position into the source
        dimensions - the dimensional space for the window

    • Method Detail

      • toDense

        public U toDense()
        Converts the sparse window to a dense NdArray
        Specified by:
        toDense in class SparseSlice<T,​U extends NdArray<T>>
        Returns:
        the NdArray

      • setObject

        public U setObject​(T value,
                   long... coordinates)
        Description copied from class: AbstractSparseNdArray
        Assigns the value of the scalar found at the given coordinates.

        To access the scalar element, the number of coordinates provided must be equal to the number of dimensions of this array (i.e. its rank). For example: 

        
  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
  matrix.setObject(10.0f, 0, 1);  // succeeds
  matrix.setObject(10.0f, 0);  // throws IllegalRankException

  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
  scalar.setObject(10.0f);  // succeeds
        Note: if this array stores values of a primitive type, prefer the usage of the specialized method in the subclass for that type. For example, floatArray.setFloat(10.0f, 0);
        Specified by:
        setObject in interface NdArray<T>
        Overrides:
        setObject in class AbstractSparseNdArray<T,​U extends NdArray<T>>
        Parameters:
        value - the value to assign
        coordinates - coordinates of the scalar to assign
        Returns:
        this array

      • set

        public U set​(NdArray<T> src,
             long... coordinates)
        Description copied from class: AbstractSparseNdArray
        Assigns the value of the N-dimensional element found at the given coordinates.

        The number of coordinates provided can be anywhere between 0 and rank - 1. For example: 

        
  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
  matrix.set(vector(10.0f, 20.0f), 0);  // success
  matrix.set(scalar(10.0f), 1, 0); // success
        Specified by:
        set in interface NdArray<T>
        Overrides:
        set in class AbstractSparseNdArray<T,​U extends NdArray<T>>
        Parameters:
        src - an array of the values to assign
        coordinates - coordinates of the element to assign
        Returns:
        this array

      • read

        public U read​(DataBuffer<T> dst)
        Read the content of this N-dimensional array into the destination buffer.

        The size of the buffer must be equal or greater to the Shaped.size() of this array, or an exception is thrown. After the copy, content of the buffer and of the array can be altered independently, without affecting each other.

        Specified by:
        read in interface NdArray<T>
        Parameters:
        dst - the destination buffer
        Returns:
        this array
        See Also:
        DataBuffer.size()

      • slice

        public U slice​(Index... indices)
        Description copied from class: SparseSlice
        Creates a multi-dimensional view (or slice) of this array by mapping one or more dimensions to the given index selectors.

        Slices allow to traverse an N-dimensional array in any of its axis and/or to filter only elements of interest. For example, for a given matrix on the [x, y] axes, it is possible to iterate elements at y=0 for all x.

        Any changes applied to the returned slice affect the data of this array as well, as there is no copy involved.

        Example of usage: 

        
    FloatNdArray matrix3d = NdArrays.ofFloats(shape(3, 2, 4));  // with [x, y, z] axes

    // Iterates elements on the x axis by preserving only the 3rd value on the z axis,
    // (i.e. [x, y, 2])
    matrix3d.slice(all(), all(), at(2)).elements(0).forEach(m -> {
      assertEquals(shape(2), m); // y=2, z=0 (scalar)
    });

    // Creates a slice that contains only the last element of the y axis and elements with an
    // odd `z` coordinate.
    FloatNdArray slice = matrix3d.slice(all(), at(1), odd());
    assertEquals(shape(3, 2), slice.shape());  // x=3, y=0 (scalar), z=2 (odd coordinates)

    // Iterates backward the elements on the x axis
    matrix3d.slice(flip()).elements(0).forEach(m -> {
      assertEquals(shape(2, 4), m);  // y=2, z=4
    });
        Specified by:
        slice in interface NdArray<T>
        Overrides:
        slice in class SparseSlice<T,​U extends NdArray<T>>
        Parameters:
        indices - index selectors per dimensions, starting from dimension 0 of this array.
        Returns:
        the element resulting of the index selection

      • slice

        public U slice​(long position,
               DimensionalSpace sliceDimensions)
        Specified by:
        slice in class org.tensorflow.ndarray.impl.AbstractNdArray<T,​U extends NdArray<T>>

      • getType

        public Class<T> getType()