pyvista.core._validation.check.check_shape

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pyvista.core._validation.check.check_shape#

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

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 (i.e. 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 shape(s).

See also

check_length
check_ndim

Examples

Check if an array is one-dimensional.

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

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

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

Check if an array is 3x3 or 4x4.

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