std(x, axis=None, ddof=0, keepdims=False)¶
Computes the standard deviation along the specified axis. The standard deviation is the square root of the average of the squared deviations from the mean, i.e., \(std = sqrt(mean(abs(x - x.mean())**2))\).
Returns the standard deviation, which is computed for the flattened array by default, otherwise over the specified axis.
Numpy arguments dtype, out and where are not supported.
x (Tensor) – A Tensor to be calculated.
Axis or axes along which the standard deviation is computed. Default: None.
If None, compute the standard deviation of the flattened array.
ddof (int) – Means Delta Degrees of Freedom. The divisor used in calculations is \(N - ddof\), where \(N\) represents the number of elements. Default: 0.
keepdims – Default: False.
Standard deviation tensor.
- Supported Platforms:
>>> import mindspore.numpy as np >>> input_x = np.array([1., 2., 3., 4.]) >>> output = np.std(input_x) >>> print(output) 1.118034