Packages

class LOLTensorData extends TensorData

Each list is of the same length and stores a single dimension (similarly to parallel arrays).

There are as many dimensions as elements in columnTypes minus one. columnTypes describe the primitive type of the corresponding column (a dimension or a value).

Instances of this class are expected to be only constructed from existing lists (e.g., from Avro or Pegasus), so no corresponding builder class is provided.

Linear Supertypes
TensorData, AnyRef, Any
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  1. LOLTensorData
  2. TensorData
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Visibility
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Instance Constructors

  1. new LOLTensorData(columnTypes: Array[Representable], dimensions: List[List[_]], values: List[_])
  2. new LOLTensorData(columnTypes: Array[Representable], dimensions: List[List[_]], values: List[_], sort: Boolean)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def cardinality(): Int

    returns

    exact number of entries in the mapping from dimensions to values.

    Definition Classes
    LOLTensorData → TensorData
    Annotations
    @Override()
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def estimatedCardinality(): Int

    returns

    conservative estimate of number of entries in the mapping from dimensions to values. Can be cheaper to evaluate than the exact one.

    Definition Classes
    LOLTensorData → TensorData
    Annotations
    @Override()
  10. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. def getArity(): Int

    returns

    the arity, which is the total number of columns. As columns are dimensions plus a value, arity is by one greater than dimensionality.

    Definition Classes
    TensorData
  12. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. def getDimensions(): List[List[_]]
  14. def getShape(): Array[Long]

    returns

    the current shape of the data or the supplied shape of the data

    Definition Classes
    TensorData
  15. def getTypes(): Array[Representable]

    returns

    the types of all dimensions and the value as a single array.

    Definition Classes
    LOLTensorData → TensorData
    Annotations
    @Override()
  16. def getValues(): List[_]
  17. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  18. def isEmpty(): Boolean
    Definition Classes
    LOLTensorData → TensorData
    Annotations
    @Override()
  19. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  20. def iterator(): TensorIterator

    returns

    an iterator over entries in the mapping from dimensions to the value.

    Definition Classes
    LOLTensorData → TensorData
    Annotations
    @Override()
  21. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  25. def toString(): String
    Definition Classes
    AnyRef → Any
  26. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from TensorData

Inherited from AnyRef

Inherited from Any

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