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.,
.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
, where 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