cc.factorie.la

SingletonIndexedTensor

trait SingletonIndexedTensor extends SparseIndexedTensor with SingletonTensor

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Inherited
  1. SingletonIndexedTensor
  2. SingletonTensor
  3. ReadOnlyTensor
  4. SparseIndexedTensor
  5. SparseTensor
  6. Tensor
  7. Serializable
  8. Serializable
  9. MutableDoubleSeq
  10. IncrementableDoubleSeq
  11. SparseDoubleSeq
  12. DoubleSeq
  13. AnyRef
  14. Any
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Abstract Value Members

  1. abstract def activeDomain: IntSeq

    Definition Classes
    Tensor
  2. abstract def activeDomains: Array[IntSeq]

    Definition Classes
    Tensor
  3. abstract def blankCopy: Tensor

    Definition Classes
    Tensor
  4. abstract def copy: Tensor

    Definition Classes
    Tensor
  5. abstract def dimensions: Array[Int]

    Definition Classes
    Tensor
  6. abstract def length: Int

    Definition Classes
    DoubleSeq
  7. abstract def numDimensions: Int

    Definition Classes
    Tensor
  8. abstract def singleIndex: Int

    Definition Classes
    SingletonTensor
  9. abstract def singleValue: Double

    Definition Classes
    SingletonTensor

Concrete Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. def *(v: Double): Tensor

    Definition Classes
    Tensor
  5. def *=(ds: DoubleSeq): Unit

    Definition Classes
    MutableDoubleSeq
  6. def *=(d: Double): Unit

    Definition Classes
    MutableDoubleSeq
  7. def *=(i: Int, incr: Double): Unit

    Definition Classes
    MutableDoubleSeq
  8. def +(that: Tensor): Tensor

    Definition Classes
    Tensor
  9. def ++=(tensors: Iterable[Tensor]): SingletonIndexedTensor.this.type

    Definition Classes
    Tensor
  10. def +=(i: Int, incr: Double): Unit

  11. def +=(ds: DoubleSeq, factor: DoubleSeq): Unit

    Increment by the element-wise product of ds and factor.

    Increment by the element-wise product of ds and factor.

    Definition Classes
    IncrementableDoubleSeq
  12. def +=(a: Array[Double], factor: Double): Unit

    Definition Classes
    IncrementableDoubleSeq
  13. def +=(ds: DoubleSeq, factor: Double): Unit

    Definition Classes
    IncrementableDoubleSeq
  14. def +=(a: Array[Double]): Unit

    Definition Classes
    IncrementableDoubleSeq
  15. final def +=(ds: DoubleSeq): Unit

    Definition Classes
    IncrementableDoubleSeq
  16. def +=(d: Double): Unit

    Definition Classes
    IncrementableDoubleSeq
  17. def -(that: Tensor): Tensor

    Definition Classes
    Tensor
  18. def -=(ds: DoubleSeq): Unit

    Definition Classes
    IncrementableDoubleSeq
  19. final def -=(d: Double): Unit

    Definition Classes
    IncrementableDoubleSeq
  20. def -=(i: Int, incr: Double): Unit

    Definition Classes
    IncrementableDoubleSeq
  21. def /(v: Double): Tensor

    Definition Classes
    Tensor
  22. def /=(ds: DoubleSeq): Unit

    Definition Classes
    MutableDoubleSeq
  23. final def /=(d: Double): Unit

    Definition Classes
    MutableDoubleSeq
  24. final def /=(i: Int, incr: Double): Unit

    Definition Classes
    MutableDoubleSeq
  25. def :=(a: Array[Double], offset: Int): Unit

    Definition Classes
    MutableDoubleSeq
  26. def :=(a: Array[Double]): Unit

    Definition Classes
    MutableDoubleSeq
  27. def :=(ds: DoubleSeq): Unit

    Definition Classes
    MutableDoubleSeq
  28. def :=(d: Double): Unit

    Definition Classes
    MutableDoubleSeq
  29. def =+(a: Array[Double], offset: Int, f: Double): Unit

    Increment given array (starting at offset index) with contents of this DoubleSeq, multiplied by factor f.

    Increment given array (starting at offset index) with contents of this DoubleSeq, multiplied by factor f.

    Definition Classes
    SingletonIndexedTensorSparseDoubleSeqDoubleSeq
  30. final def =+(a: Array[Double], f: Double): Unit

    Definition Classes
    DoubleSeq
  31. final def =+(a: Array[Double], offset: Int): Unit

    Definition Classes
    DoubleSeq
  32. final def =+(a: Array[Double]): Unit

    Definition Classes
    DoubleSeq
  33. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  34. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  35. def _indices: Array[Int]

    Definition Classes
    SingletonTensorSparseTensor
  36. def _makeReadable(): Unit

    Definition Classes
    SingletonTensorSparseTensor
  37. def _unsafeActiveDomainSize: Int

    Definition Classes
    SingletonTensorSparseTensor
  38. def _values: Array[Double]

  39. def _valuesSeq: ArrayDoubleSeq

    Definition Classes
    SparseIndexedTensorSparseTensor
  40. def abs(): Unit

    Definition Classes
    MutableDoubleSeq
  41. val activeDomainSize: Int

    Definition Classes
    SingletonTensorTensorSparseDoubleSeq
  42. def activeElements: Iterator[(Int, Double)]

    Definition Classes
    SingletonIndexedTensorTensor
  43. def addString(b: StringBuilder, start: String, sep: String, end: String): StringBuilder

    Append a string representation of this DoubleSeq to the StringBuilder.

    Append a string representation of this DoubleSeq to the StringBuilder.

    Definition Classes
    DoubleSeq
  44. def apply(i: Int): Double

    Definition Classes
    SingletonIndexedTensorDoubleSeq
  45. def asArray: Array[Double]

    Return the values as an Array[Double].

    Return the values as an Array[Double]. Not guaranteed to be a copy; in fact if it is possible to return a pointer to an internal array, it will simply return this.

    Definition Classes
    DoubleSeq
  46. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  47. def asSeq: Seq[Double]

    With uncopied contents

    With uncopied contents

    Definition Classes
    DoubleSeq
  48. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  49. def contains(d: Double): Boolean

    Definition Classes
    SparseDoubleSeqDoubleSeq
  50. def containsNaN: Boolean

  51. def copyInto(t: SparseIndexedTensor): Unit

  52. def cosineSimilarity(t: DoubleSeq): Double

    Definition Classes
    Tensor
  53. def defaultValue: Double

    The default value at indices not covered by activeDomain.

    The default value at indices not covered by activeDomain. Subclasses may override this

    Definition Classes
    Tensor
  54. def different(t: DoubleSeq, threshold: Double): Boolean

    Definition Classes
    SparseDoubleSeqDoubleSeq
  55. def dimensionsMatch(t: Tensor): Boolean

    Definition Classes
    Tensor
  56. def dot(t: DoubleSeq): Double

    Definition Classes
    SingletonIndexedTensorTensor
  57. def ensureDimensionsMatch(t: Tensor): Unit

    Definition Classes
    Tensor
  58. def entropy: Double

    Assumes that the values are already normalized to sum to 1.

    Assumes that the values are already normalized to sum to 1.

    Definition Classes
    SparseDoubleSeqDoubleSeq
  59. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  60. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  61. def exists(f: (Double) ⇒ Boolean): Boolean

    Definition Classes
    Tensor
  62. def expNormalize(logZ: Double): Unit

    Exponential the elements of the array such that they are normalized to sum to one, but do so efficiently by providing logZ.

    Exponential the elements of the array such that they are normalized to sum to one, but do so efficiently by providing logZ. Note that to maximize efficiency, this method does not verify that the logZ value was the correct one to cause proper normalization.

    Definition Classes
    MutableDoubleSeq
  63. def expNormalize(): Double

    Exponentiate the elements of the array, and then normalize them to sum to one.

    Exponentiate the elements of the array, and then normalize them to sum to one.

    Definition Classes
    MutableDoubleSeq
  64. def expNormalized: Tensor

    Definition Classes
    Tensor
  65. def exponentiate(): Unit

    Definition Classes
    MutableDoubleSeq
  66. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  67. def foldActiveElements(seed: Double, f: (Int, Double, Double) ⇒ Double): Double

    Definition Classes
    Tensor
  68. def foldLeft[B](z: B)(f: (B, Double) ⇒ B): B

    Definition Classes
    DoubleSeq
  69. def forall(f: (Double) ⇒ Boolean): Boolean

    Definition Classes
    DoubleSeq
  70. def forallActiveElements(f: (Int, Double) ⇒ Boolean): Boolean

    Definition Classes
    SingletonIndexedTensorTensorSparseDoubleSeq
  71. def forallElements(f: (Int, Double) ⇒ Boolean): Boolean

    Definition Classes
    DoubleSeq
  72. def foreach(f: (Double) ⇒ Unit): Unit

    Definition Classes
    DoubleSeq
  73. def foreachActiveElement(f: (Int, Double) ⇒ Unit): Unit

    Definition Classes
    SingletonIndexedTensorDoubleSeq
  74. def foreachElement(f: (Int, Double) ⇒ Unit): Unit

    Definition Classes
    DoubleSeq
  75. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  76. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  77. def indexOf(d: Double): Int

    Definition Classes
    SparseDoubleSeqDoubleSeq
  78. def infinityNorm: Double

    Definition Classes
    SparseDoubleSeqDoubleSeq
  79. def isDense: Boolean

    Definition Classes
    SparseTensorTensor
  80. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  81. def isUniform: Boolean

    Definition Classes
    Tensor
  82. def jsDivergence(p: DoubleSeq): Double

    Assumes that the values are already normalized to sum to 1.

    Assumes that the values are already normalized to sum to 1.

    Definition Classes
    SparseDoubleSeqDoubleSeq
  83. def klDivergence(p: DoubleSeq): Double

    Assumes that the values in both DoubleSeq are already normalized to sum to 1.

    Assumes that the values in both DoubleSeq are already normalized to sum to 1.

    Definition Classes
    SparseDoubleSeqDoubleSeq
  84. def l2Similarity(t: DoubleSeq): Double

    Definition Classes
    DoubleSeq
  85. def map(f: (Double) ⇒ Double): DoubleSeq

    Definition Classes
    DoubleSeq
  86. def max: Double

  87. def maxIndex: Int

  88. def maxIndex2: (Int, Int)

    Definition Classes
    SparseDoubleSeqDoubleSeq
  89. def maxNormalize(): Unit

    Definition Classes
    MutableDoubleSeq
  90. def min: Double

  91. def mkString: String

    Definition Classes
    DoubleSeq
  92. def mkString(sep: String): String

    Definition Classes
    DoubleSeq
  93. def mkString(start: String, sep: String, end: String): String

    Definition Classes
    DoubleSeq
  94. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  95. def normalize(): Double

    Definition Classes
    MutableDoubleSeq
  96. def normalizeLogProb(): Double

    expNormalize, then put back into log-space.

    expNormalize, then put back into log-space.

    Definition Classes
    MutableDoubleSeq
  97. def normalized: Tensor

    Definition Classes
    Tensor
  98. final def notify(): Unit

    Definition Classes
    AnyRef
  99. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  100. def oneNorm: Double

    Definition Classes
    SparseDoubleSeqDoubleSeq
  101. def oneNormalize(): Double

    Definition Classes
    MutableDoubleSeq
  102. def outer(t: Tensor): Tensor

    Definition Classes
    Tensor
  103. def printLength: Int

    Definition Classes
    Tensor
  104. def sampleIndex(normalizer: Double)(implicit r: Random): Int

    Definition Classes
    SparseDoubleSeqDoubleSeq
  105. def sampleIndex(implicit r: Random): Int

    Careful, for many subclasses this is inefficient because it calls the method "sum" to get the normalizer.

    Careful, for many subclasses this is inefficient because it calls the method "sum" to get the normalizer.

    Definition Classes
    DoubleSeq
  106. final def size: Int

    Definition Classes
    DoubleSeq
  107. def sizeHint(size: Int): Unit

    Definition Classes
    SingletonTensorSparseTensor
  108. def stringPrefix: String

    Definition Classes
    Tensor
  109. def substitute(oldValue: Double, newValue: Double): Unit

    Definition Classes
    MutableDoubleSeq
  110. def sum: Double

  111. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  112. def toArray: Array[Double]

    Return the values as an Array[Double].

    Return the values as an Array[Double]. Guaranteed to be a copy, not just a pointer to an internal array that would change with changes to the DoubleSeq

    Definition Classes
    SparseDoubleSeqDoubleSeq
  113. def toSeq: Seq[Double]

    With copied contents

    With copied contents

    Definition Classes
    DoubleSeq
  114. def toString(): String

    Definition Classes
    Tensor → AnyRef → Any
  115. def top(n: Int): TopN[String]

    Return records for the n elements with the largest values.

    Return records for the n elements with the largest values.

    Definition Classes
    DoubleSeq
  116. final def twoNorm: Double

    Definition Classes
    DoubleSeq
  117. def twoNormSquared: Double

    Definition Classes
    SparseDoubleSeqDoubleSeq
  118. def twoNormalize(): Double

    Definition Classes
    MutableDoubleSeq
  119. def twoSquaredNormalize(): Double

    Definition Classes
    MutableDoubleSeq
  120. def update(i: Int, v: Double): Unit

    Definition Classes
    ReadOnlyTensorTensorMutableDoubleSeq
  121. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  122. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  123. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  124. def zero(): Unit

Inherited from SingletonTensor

Inherited from ReadOnlyTensor

Inherited from SparseIndexedTensor

Inherited from SparseTensor

Inherited from Tensor

Inherited from Serializable

Inherited from Serializable

Inherited from MutableDoubleSeq

Inherited from IncrementableDoubleSeq

Inherited from SparseDoubleSeq

Inherited from DoubleSeq

Inherited from AnyRef

Inherited from Any

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