pyvista.core._validation.validate.validate_arrayNx3#
- validate_arrayNx3(arr, /, *, reshape=True, **kwargs)[source]#
Validate an array is numeric and has shape Nx3.
The array is checked to ensure its input values:
have shape
(N, 3)
or can be reshaped to(N, 3)
are numeric
The returned array is formatted so that its values:
have shape
(N, 3)
.
- Parameters:
- arrarray_like
Array to validate.
- reshapebool, default:
True
If
True
, 1D arrays with 3 elements are considered valid input and are reshaped to(1, 3)
to ensure the output is two-dimensional.- **kwargs
dict
,optional
Additional keyword arguments passed to
validate_array()
.
- Returns:
np.ndarray
Validated array with shape
(N, 3)
.
See also
validate_arrayN
Similar function for one-dimensional arrays.
validate_array
Generic array validation function.
Examples
Validate an Nx3 array.
>>> from pyvista import _validation >>> _validation.validate_arrayNx3(((1, 2, 3), (4, 5, 6))) array([[1, 2, 3], [4, 5, 6]])
One-dimensional 3-element arrays are automatically reshaped to 2D.
>>> _validation.validate_arrayNx3([1, 2, 3]) array([[1, 2, 3]])
Add additional constraints.
>>> _validation.validate_arrayNx3( ... ((1, 2, 3), (4, 5, 6)), must_be_in_range=[0, 10] ... ) array([[1, 2, 3], [4, 5, 6]])