trace#
- ivy.trace(x, /, *, offset=0, axis1=0, axis2=1, out=None)[source]#
Return the sum along the specified diagonals of a matrix (or a stack of matrices)
x
.Special cases
Let
N
equal the number of elements over which to compute the sum.If
N
is0
, the sum is0
(i.e., the empty sum).
For both real-valued and complex floating-point operands, special cases must be handled as if the operation is implemented by successive application of
ivy.add()
:- Parameters:
x (
Union
[Array
,NativeArray
]) – input array having shape(..., M, N)
and whose innermost two dimensions formMxN
matrices. Should have a numeric data type.offset (
int
, default:0
) –offset specifying the off-diagonal relative to the main diagonal. -
offset = 0
: the main diagonal. -offset > 0
: off-diagonal above the main diagonal. -offset < 0
: off-diagonal below the main diagonal.Default:
0
.axis1 (
int
, default:0
) – axis to be used as the first axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to0.
.axis2 (
int
, default:1
) – axis to be used as the second axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to1.
.out (
Optional
[Array
], default:None
) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
- Returns:
ret – an array containing the traces and whose shape is determined by removing the last two dimensions and storing the traces in the last array dimension. For example, if
x
has rankk
and shape(I, J, K, ..., L, M, N)
, then an output array has rankk-2
and shape(I, J, K, ..., L)
whereout[i, j, k, ..., l] = trace(a[i, j, k, ..., l, :, :])
The returned array must have the same data type as
x
.
Examples
With
ivy.Array
inputs:>>> x = ivy.array([[2., 0., 3.], ... [3., 5., 6.]]) >>> y = ivy.trace(x, offset=0) >>> print(y) ivy.array(7.)
>>> x = ivy.array([[[1., 2.], ... [3., 4.]], ... [[5., 6.], ... [7., 8.]]]) >>> y = ivy.trace(x, offset=1) >>> print(y) ivy.array([3., 4.])
>>> x = ivy.array([[1., 2., 3.], ... [4., 5., 6.], ... [7., 8., 9.]]) >>> y = ivy.zeros(1) >>> ivy.trace(x, offset=1,out=y) >>> print(y) ivy.array(8.)
With
ivy.NativeArray
inputs:>>> x = ivy.native_array([[2., 0., 3.],[3., 5., 6.]]) >>> y = ivy.trace(x, offset=0) >>> print(y) ivy.array(7.)
>>> x = ivy.native_array([[0, 1, 2], ... [3, 4, 5], ... [6, 7, 8]]) >>> y = ivy.trace(x, offset=1) >>> print(y) ivy.array(6)
With
ivy.Container
inputs:>>> x = ivy.Container( ... a = ivy.array([[7, 1, 2], ... [1, 3, 5], ... [0, 7, 4]]), ... b = ivy.array([[4, 3, 2], ... [1, 9, 5], ... [7, 0, 6]]) ... ) >>> y = ivy.trace(x, offset=0) >>> print(y) { a: ivy.array(14), b: ivy.array(19) }
>>> x = ivy.Container( ... a = ivy.array([[7, 1, 2], ... [1, 3, 5], ... [0, 7, 4]]), ... b = ivy.array([[4, 3, 2], ... [1, 9, 5], ... [7, 0, 6]]) ... ) >>> y = ivy.trace(x, offset=1) >>> print(y) { a: ivy.array(6), b: ivy.array(8) }
With multiple ivy.Container inputs:
>>> x = ivy.Container( ... a = ivy.array([[7, 1, 3], ... [8, 6, 5], ... [9, 7, 2]]), ... b = ivy.array([[4, 3, 2], ... [1, 9, 5], ... [7, 0, 6]]) ... ) >>> offset = ivy.Container(a=1, b=0) >>> y = ivy.trace(x, offset=offset) >>> print(y) { a: ivy.array(6), b: ivy.array(19) }
With Array instance method example:
>>> x = ivy.array([[2., 0., 11.], ... [3., 5., 12.], ... [1., 6., 13.], ... [8., 9., 14.]]) >>> y = x.trace(offset=1) >>> print(y) ivy.array(12.)
With Container instance method example:
>>> x = ivy.Container( ... a=ivy.array([[2., 0., 11.], ... [3., 5., 12.]]), ... b=ivy.array([[1., 6., 13.], ... [8., 9., 14.]]) ... ) >>> y = x.trace(offset=0) >>> print(y) { a: ivy.array(7.), b: ivy.array(10.) }
- Array.trace(self, /, *, offset=0, axis1=0, axis2=1, out=None)[source]#
ivy.Array instance method variant of ivy.trace. This method Returns the sum along the specified diagonals of a matrix (or a stack of matrices).
- Parameters:
self (
Array
) – input array having shape(..., M, N)
and whose innermost two dimensions formMxN
matrices. Should have a floating-point data type.offset (
int
, default:0
) – Offset of the diagonal from the main diagonal. Can be both positive and negative. Defaults to 0.axis1 (
int
, default:0
) – axis to be used as the first axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to0.
.axis2 (
int
, default:1
) – axis to be used as the second axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to1.
.out (
Optional
[Array
], default:None
) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Array
- Returns:
ret – an array containing the traces and whose shape is determined by removing the last two dimensions and storing the traces in the last array dimension. For example, if
x
has rankk
and shape(I, J, K, ..., L, M, N)
, then an output array has rankk-2
and shape(I, J, K, ..., L)
whereout[i, j, k, …, l] = trace(a[i, j, k, …, l, :, :])
The returned array must have the same data type as
x
.
Examples
>>> x = ivy.array([[1., 2.], [3., 4.]]) >>> y = x.trace() >>> print(y) ivy.array(5.)
>>> x = ivy.array([[1., 2., 4.], [6., 5., 3.]]) >>> y = ivy.Array.trace(x) >>> print(y) ivy.array(6.)
- Container.trace(self, /, *, offset=0, axis1=0, axis2=1, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#
ivy.Container instance method variant of ivy.trace. This method Returns the sum along the specified diagonals of a matrix (or a stack of matrices).
- Parameters:
self (
Container
) – input container having shape(..., M, N)
and whose innermost two dimensions formMxN
matrices. Should have a floating-point data type.offset (
Union
[int
,Container
], default:0
) – Offset of the diagonal from the main diagonal. Can be both positive and negative. Defaults to 0.axis1 (
Union
[int
,Container
], default:0
) – axis to be used as the first axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to0.
.axis2 (
Union
[int
,Container
], default:1
) – axis to be used as the second axis of the 2-D sub-arrays from which the diagonals should be taken. Defaults to1.
.key_chains (
Optional
[Union
[List
[str
],Dict
[str
,str
],Container
]], default:None
) – The key-chains to apply or not apply the method to. Default isNone
.to_apply (
Union
[bool
,Container
], default:True
) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default isTrue
.prune_unapplied (
Union
[bool
,Container
], default:False
) – Whether to prune key_chains for which the function was not applied. Default isFalse
.map_sequences (
Union
[bool
,Container
], default:False
) – Whether to also map method to sequences (lists, tuples). Default isFalse
.out (
Optional
[Container
], default:None
) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.
- Return type:
Container
- Returns:
ret – a container containing the traces and whose shape is determined by removing the last two dimensions and storing the traces in the last array dimension. For example, if
x
has rankk
and shape(I, J, K, ..., L, M, N)
, then an output array has rankk-2
and shape(I, J, K, ..., L)
whereout[i, j, k, …, l] = trace(a[i, j, k, …, l, :, :])
The returned array must have the same data type as
x
.
Examples
With
ivy.Container
input: >>> x = ivy.Container( … a = ivy.array([[7, 1, 2], … [1, 3, 5], … [0, 7, 4]]), … b = ivy.array([[4, 3, 2], … [1, 9, 5], … [7, 0, 6]])) >>> y = x.trace() >>> print(y) {a: ivy.array(14), b: ivy.array(19)
}