pyvista.core._validation.validate.validate_axes#

validate_axes( *axes, normalize=True, must_be_orthogonal=True, must_have_orientation='right', name='Axes', )[source]#

Validate 3D axes vectors.

By default, the axes are normalized and checked to ensure they are orthogonal and have a right-handed orientation.

Parameters:

*axesarray_like: Axes to be validated. Axes may be specified as a single argument of a 3x3 array of row vectors or as separate arguments for each 3-element axis vector. If only two vectors are given and must_have_orientation is not None, the third vector is automatically calculated as the cross-product of the two vectors such that the axes have the correct orientation.
normalizebool, default: True: If True, the axes vectors are individually normalized to each have a norm of 1.
must_be_orthogonalbool, default: True: Check if the axes are orthogonal. If True, the cross product between any two axes vectors must be parallel to the third.
must_have_orientationstr, default: ‘right’: Check if the axes have a specific orientation. If right, the cross-product of the first axis vector with the second must have a positive direction. If left, the direction must be negative. If None, the orientation is not checked.
namestr, default: “Axes”: Variable name to use in the error messages if any of the validation checks fail.

Returns:

np.ndarray: Validated 3x3 axes array of row vectors.

Examples

Validate an axes array.

>>> import numpy as np
>>> from pyvista import _validation
>>> _validation.validate_axes(np.eye(3))
array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])

Validate individual axes vectors as a 3x3 array.

>>> _validation.validate_axes([1, 0, 0], [0, 1, 0], [0, 0, 1])
array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])

Create a validated left-handed axes array from two vectors.

>>> _validation.validate_axes(
...     [1, 0, 0], [0, 1, 0], must_have_orientation='left'
... )
array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0., -1.]])