pyvista_validation.check.check_shape

pyvista_validation.check.check_shape(array: _ArrayLikeOrScalar[NumberType], /, shape: _ShapeLike | list[_ShapeLike], *, name: str = 'Array') → None

Check if an array has the specified shape.

Parameters:

arrayfloat | ArrayLike[float]

Number or array to check.

shapeShapeLike | list[ShapeLike]

A single shape or a list of any allowable shapes. If an integer, i, the shape is interpreted as (i,). Use a value of -1 for any dimension where its size is allowed to vary, e.g. (-1,3) if any Nx3 array is allowed. Use () for the shape of scalar values (that is, 0-dimensional). If a list, the array must have at least one of the specified shapes.

namestr, default: “Array”

Variable name to use in the error messages if any are raised.

Raises:

ValueError

If the array does not have any of the specified shapes.

See also

check_length

check_ndim

Examples

Check if an array is one-dimensional.

>>> import numpy as np
>>> from pyvista_validation import check_shape
>>> check_shape([1, 2, 3], shape=(-1))

Check if an array is one-dimensional or a scalar.

>>> check_shape(1, shape=[(), (-1)])

Check if an array is 3x3 or 4x4.

>>> check_shape(np.eye(3), shape=[(3, 3), (4, 4)])