vector_norm

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vector_norm#

class saiunit.linalg.vector_norm(x, *, axis=None, keepdims=False, ord=2, **kwargs)#

Compute the vector norm of a vector or batch of vectors.

SaiUnit implementation of numpy.linalg.vector_norm().

Parameters:

  • x (Array | ndarray | bool | number | bool | int | float | complex | saiunit.Quantity) – N-dimensional input.

  • axis (int | tuple[int, ...] | None) – Axis (or axes) along which to compute the norm. If None (default), x is flattened first.

  • keepdims (bool) – If True, reduced axes are kept as size-1 dimensions (default: False).

  • ord (int | str) – Type of norm (default: 2). See numpy.linalg.norm() for available options.

Returns:

out – Vector norm of x. Carries the same unit as x.

Return type:

Array | saiunit.Quantity

Examples

>>> import saiunit as u
>>> import jax.numpy as jnp

Norm of a single vector:

>>> x = jnp.array([1., 2., 3.]) * u.meter
>>> u.linalg.vector_norm(x)
3.7416575 * meter

Batch of vectors along axis 1:

>>> x = jnp.array([[1., 2., 3.],
...                [4., 5., 7.]]) * u.meter
>>> u.linalg.vector_norm(x, axis=1)
ArrayImpl([3.7416575, 9.48683262], dtype=float32) * meter
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