Tensor

class Tensor(*args)

Tensor.

Available constructors:

Tensor(n_rows, n_columns, n_sheets)

Tensor(n_rows, n_columns, n_sheets, values)

Tensor(sequence)

Parameters:

n_rowsint,

Number of rows.

n_columnsint,

Number of columns.

n_sheetsint,

Number of sheets.

valuessequence of float with size , optional

Values. OpenTURNS uses column-major ordering (like Fortran) for reshaping the flat list of values. If not mentioned, a zero tensor is created.

sequencesequence of float

Values.

Methods

clean(threshold)	Set elements smaller than a threshold to zero.
getClassName()	Accessor to the object's name.
getId()	Accessor to the object's id.
getImplementation()	Accessor to the underlying implementation.
getName()	Accessor to the object's name.
getNbColumns()	Accessor to the number of columns.
getNbRows()	Accessor to the number of rows.
getNbSheets()	Accessor to the number of sheets.
getSheet(k)	Get a sheet of the tensor.
isEmpty()	Tell if the tensor is empty.
setName(name)	Accessor to the object's name.
setSheet(k, m)	Set a matrix as a sheet of the complex tensor.

Examples

>>> import openturns as ot
>>> print(ot.Tensor(2, 2, 2, [1]))
sheet #0
[[ 1 0 ]
 [ 0 0 ]]
sheet #1
[[ 0 0 ]
 [ 0 0 ]]
>>> T = ot.Tensor(2, 2, 3, range(2*2*3))
>>> print(T)
sheet #0
[[  0  2 ]
 [  1  3 ]]
sheet #1
[[  4  6 ]
 [  5  7 ]]
sheet #2
[[  8 10 ]
 [  9 11 ]]

Get or set terms:

>>> print(T[0, 0, 0])
0.0
>>> T[0, 0, 0] = 1.
>>> print(T[0, 0, 0])
1.0

Create an openturns tensor from a sequence:

>>> T = ot.Tensor([[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]])
>>> print(T)
sheet #0
[[  1  4 ]
 [  7 10 ]]
sheet #1
[[  2  5 ]
 [  8 11 ]]
sheet #2
[[  3  6 ]
 [  9 12 ]]

__init__(*args)

clean(threshold)

Set elements smaller than a threshold to zero.

Parameters:

thresholdfloat

Threshold for zeroing elements.

Returns:

cleaned_tensorTensor

Input tensor with elements smaller than the threshold set to zero.

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

The object class name (object.__class__.__name__).

getId()

Accessor to the object’s id.

Returns:

idint

Internal unique identifier.

getImplementation()

Accessor to the underlying implementation.

Returns:

implImplementation

A copy of the underlying implementation object.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getNbColumns()

Accessor to the number of columns.

Returns:

n_columnsint

getNbRows()

Accessor to the number of rows.

Returns:

n_rowsint

getNbSheets()

Accessor to the number of sheets.

Returns:

n_sheetsint

Examples

>>> import openturns as ot
>>> T = ot.Tensor(2, 2, 3, range(2*2*3))
>>> print(T.getNbSheets())
3

getSheet(k)

Get a sheet of the tensor.

Parameters:

sheetint

Index of sheet element.

Returns:

MMatrix

The sheet element.

Examples

>>> import openturns as ot
>>> T = ot.Tensor(2, 2, 3, range(2*2*3))
>>> print(T.getSheet(1))
[[ 4 6 ]
 [ 5 7 ]]

isEmpty()

Tell if the tensor is empty.

Returns:

is_emptybool

True if the tensor contains no element.

Examples

>>> import openturns as ot
>>> T = ot.Tensor()
>>> T.isEmpty()
True

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setSheet(k, m)

Set a matrix as a sheet of the complex tensor.

Parameters:

sheetint

Index of sheet element.

MMatrix

The matrix.

Examples

>>> import openturns as ot
>>> T = ot.Tensor(2, 2, 3, range(2*2*3))
>>> print(T)
sheet #0
[[  0  2 ]
 [  1  3 ]]
sheet #1
[[  4  6 ]
 [  5  7 ]]
sheet #2
[[  8 10 ]
 [  9 11 ]]
>>> M = ot.Matrix([[1, 2],[3, 4]])
>>> T.setSheet(0, M)
>>> print(T)
sheet #0
[[  1  2 ]
 [  3  4 ]]
sheet #1
[[  4  6 ]
 [  5  7 ]]
sheet #2
[[  8 10 ]
 [  9 11 ]]

Examples using the class

Create a quadratic function

Create a quadratic function