mindspore.ops.vander

mindspore.ops.vander(x, N=None)[source]

Generates a Vandermonde matrix. The columns of the output matrix are powers of the input vector. The i-th output column is the input vector raised element-wise to the power of $N - i - 1$ .

Parameters

x (Tensor) – 1-D input array.
N (int, optional) – Number of columns in the output. Default: None, N will be assigned as $l e n (x)$ .

Returns

Tensor, the columns are $x^{0}, x^{1}, . . ., x^{(N - 1)}$ .

Raises

TypeError – If input x is not Tensor.
ValueError – If x is not 1-D.
TypeError – If input N is not int.
ValueError – If N <= 0.

Supported Platforms:: Ascend GPU CPU

Examples

>>> from mindspore import Tensor, ops
>>> a = Tensor([1., 2., 3., 5.])
>>> print(ops.vander(a, N=3))
[[1.   1.   1.]
 [4.   2.   1.]
 [9.   3.   1.]
 [25.  5.   1.]]
>>> a = Tensor([1., 2., 3., 5.])
>>> print(ops.vander(a))
[[1.    1.   1.   1.]
 [8.    4.   2.   1.]
 [27.   9.   3.   1.]
 [125.  25.  5.   1.]]