mindspore.numpy.var¶

mindspore.numpy.var(x, axis=None, ddof=0, keepdims=False)[source]

Computes the variance along the specified axis. The variance is the average of the squared deviations from the mean, i.e., $$var = mean(abs(x - x.mean())**2)$$.

Returns the variance, which is computed for the flattened array by default, otherwise over the specified axis.

Note

Numpy arguments dtype and out are not supported.

Parameters
• x (Tensor) – A Tensor to be calculated.

• axis (Union[None, int, tuple(int)]) – Axis or axes along which the variance is computed. The default is to compute the variance of the flattened array. Default: None.

• ddof (int) – Means Delta Degrees of Freedom. Default: 0. The divisor used in calculations is $$N - ddof$$, where $$N$$ represents the number of elements.

• keepdims (bool) – Default: False.

Supported Platforms:

Ascend GPU CPU

Returns

Standard deviation tensor.

Examples

>>> import mindspore.numpy as np
>>> input_x = np.array([1., 2., 3., 4.])
>>> output = np.var(input_x)
>>> print(output)
1.25