class Tensor3D extends Error with Serializable
The Tensor3D
class is a simple implementation for 3-dimensional tensors.
The names of the dimensions corresponds to MATLAB (row, column, sheet).
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Instance Constructors
-
new
Tensor3D(u: Array[Array[Array[Double]]])
Construct a tensor from three dimensional array.
Construct a tensor from three dimensional array.
- u
the three dimensional array
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new
Tensor3D(dim1: Int)
Construct a 'dim1' by 'dim1' by 'dim1' cubic tensor.
Construct a 'dim1' by 'dim1' by 'dim1' cubic tensor.
- dim1
the row and column dimension
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new
Tensor3D(dim1: Int, dim2: Int, dim3: Int, v: Array[Array[Array[Double]]] = null)
- dim1
size of the 1st level/dimension (row) of the tensor (height)
- dim2
size of the 2nd level/dimension (column) of the tensor (width)
- dim3
size of the 3rd level/dimension (sheet) of the tensor (depth)
Value Members
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final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
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-
def
*(b: MatrixD, c: MatrixD, d: MatrixD): Tensor3D
Multiply (multilinear product) 'this' tensor by three matrices 'b', 'c' and 'd'.
Multiply (multilinear product) 'this' tensor by three matrices 'b', 'c' and 'd'.
this * (a, b, c)
- b
the first matrix to multiply by (requires 'leDimensions')
- c
the second matrix to multiply by (requires 'leDimensions')
- d
the thrid matrix to multiply by (requires 'leDimensions')
- See also
www.stat.uchicago.edu/~lekheng/work/icm1.pdf - equation 15.1
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def
*(s: Double): Tensor3D
Multiply 'this' tensor by scalar 's'.
Multiply 'this' tensor by scalar 's'.
- s
the scalar to multiply by
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def
**(b: Tensor3D): Tensor3D
Multiply elementwise (Hadamard product) 'this' tensor by tensor 'b'.
Multiply elementwise (Hadamard product) 'this' tensor by tensor 'b'.
- b
the tensor to add (requires 'leDimensions')
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def
+(s: Double): Tensor3D
Add 'this' tensor and scalar 's'.
Add 'this' tensor and scalar 's'.
- s
the scalar to add
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def
+(b: Tensor3D): Tensor3D
Add 'this' tensor and tensor 'b'.
Add 'this' tensor and tensor 'b'.
- b
the tensor to add (requires 'leDimensions')
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def
-(s: Double): Tensor3D
From 'this' tensor subtract scalar 's'.
From 'this' tensor subtract scalar 's'.
- s
the scalar to add
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def
-(b: Tensor3D): Tensor3D
From 'this' tensor subtract tensor 'b'.
From 'this' tensor subtract tensor 'b'.
- b
the tensor to add (requires 'leDimensions')
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final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
apply(is: Ints, js: Ints, ks: Ints): Tensor3D
Retrieve the 'is, js, ks' row-column-sheet selections from the tensor.
Retrieve the 'is, js, ks' row-column-sheet selections from the tensor.
- is
1st dimension (row) indices of the tensor (null => all)
- js
2nd dimension (column) indices of the tensor (null => all)
- ks
3rd dimension (sheet) indices of the tensor
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def
apply(is: Ints, js: Ints): Tensor3D
Retrieve the 'is, js' row-column selections from the tensor.
Retrieve the 'is, js' row-column selections from the tensor.
- is
1st dimension (row) indices of the tensor (null => all)
- js
2nd dimension (column) indices of the tensor
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def
apply(is: Ints): Tensor3D
Retrieve the 'is' row selections from the tensor.
Retrieve the 'is' row selections from the tensor.
- is
1st dimension (row) indices of the tensor
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def
apply(ii: Int2, jj: Int2, kk: Int2): Tensor3D
Retrieve the 'ii._1' to 'ii._2', 'jj._1' to 'jj._2', 'kk._1' to 'kk._2' row-column-sheet slice of the tensor.
Retrieve the 'ii._1' to 'ii._2', 'jj._1' to 'jj._2', 'kk._1' to 'kk._2' row-column-sheet slice of the tensor.
- ii
1st dimension (row) indices of the tensor (null => all)
- jj
2nd dimension (column) indices of the tensor (null => all)
- kk
3rd dimension (sheet) indices of the tensor
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def
apply(ii: Int2, jj: Int2): Tensor3D
Retrieve the 'ii._1' to 'ii._2', 'jj._1' to 'jj._2' row-column slice of the tensor.
Retrieve the 'ii._1' to 'ii._2', 'jj._1' to 'jj._2' row-column slice of the tensor.
- ii
1st dimension (row) indices of the tensor (null => all)
- jj
2nd dimension (column) indices of the tensor
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def
apply(ii: Int2): Tensor3D
Retrieve the 'ii._1' to 'ii._2' row slice of the tensor.
Retrieve the 'ii._1' to 'ii._2' row slice of the tensor.
- ii
1st dimension (row) indices of the tensor
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def
apply(i: Int): MatriD
Retrieve the 'i' matrix from the tensor.
Retrieve the 'i' matrix from the tensor.
- i
1st dimension (row) index of the tensor
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def
apply(i: Int, j: Int): VectoD
Retrieve the 'i, j' vector from the tensor.
Retrieve the 'i, j' vector from the tensor.
- i
1st dimension (row) index of the tensor
- j
2nd dimension (column) index of the tensor
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def
apply(i: Int, j: Int, k: Int): Double
Retrieve the 'i, j, k' element from the tensor.
Retrieve the 'i, j, k' element from the tensor.
- i
1st dimension (row) index of the tensor
- j
2nd dimension (column) index of the tensor
- k
3rd dimension (sheet) index of the tensor
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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- val dim1: Int
- val dim2: Int
- val dim3: Int
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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var
fString: String
Format string used for printing vector values (change using 'setFormat')
Format string used for printing vector values (change using 'setFormat')
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final
def
flaw(method: String, message: String): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
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def
leDimensions(b: Tensor3D): Boolean
Check whether the dimensions of 'this' tensor are less than or equal to 'le' those of the other tensor 'b'.
Check whether the dimensions of 'this' tensor are less than or equal to 'le' those of the other tensor 'b'.
- b
the other matrix
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final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
not(is: Ints, js: Ints, ks: Ints): Tensor3D
Retrieve the complement of the 'is' row selections from the tensor.
Retrieve the complement of the 'is' row selections from the tensor.
- is
1st dimension (row) indices of the tensor
- js
2nd dimension (column) indices of the tensor
- ks
3rd dimension (sheet) indices of the tensor
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def
not(is: Ints, js: Ints): Tensor3D
Retrieve the complement of the 'is' row selections from the tensor.
Retrieve the complement of the 'is' row selections from the tensor.
- is
1st dimension (row) indices of the tensor
- js
2nd dimension (column) indices of the tensor
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def
not(is: Ints): Tensor3D
Retrieve the complement of the 'is' row selections from the tensor.
Retrieve the complement of the 'is' row selections from the tensor.
- is
1st dimension (row) indices of the tensor
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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- val range1: Range
- val range2: Range
- val range3: Range
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def
set(x: Double): Unit
Set all the tensor element values to 'x'.
Set all the tensor element values to 'x'.
- x
the value to set all elements to
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def
setFormat(newFormat: String): Unit
Set the format to the 'newFormat'.
Set the format to the 'newFormat'.
- newFormat
the new format string
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
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-
def
toString(): String
Convert 'this' tensor to a string with a double line break after each sheet and a single line break after each row.
Convert 'this' tensor to a string with a double line break after each sheet and a single line break after each row.
- Definition Classes
- Tensor3D → AnyRef → Any
-
def
toString2: String
Convert 'this' tensor to a string with a line break after each sheet.
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def
update(i: Int, x: MatrixD): Unit
Update a single matrix of the tensor to the given matrix.
Update a single matrix of the tensor to the given matrix.
- i
1st dimension (row) index of the tensor
- x
the matrix to be updated at the above position in the tensor
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def
update(i: Int, j: Int, x: VectorD): Unit
Update a single vector of the tensor to the given vector.
Update a single vector of the tensor to the given vector.
- i
1st dimension (row) index of the tensor
- j
2nd dimension (column) index of the tensor
- x
the vector to be updated at the above position in the tensor
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def
update(i: Int, j: Int, k: Int, x: Double): Unit
Update a single element of the tensor to the given value.
Update a single element of the tensor to the given value.
- i
1st dimension (row) index of the tensor
- j
2nd dimension (column) index of the tensor
- k
3rd dimension (sheet) index of the tensor
- x
the value to be updated at the above position in the tensor
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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final
def
wait(): Unit
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def
finalize(): Unit
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