sparse_voxels_validation

k3d.helpers.sparse_voxels_validation()

Check sparse voxels for array shape and values.

Returns

Sparse voxels validator function.

Return type

function

Raises

• TraitError – Expected an array of shape (N, 4) and got _.

• TraitError – Voxel coordinates and values must be non-negative.

Note

This validation function is used along with traitlets and traittypes packages, which are used to ensure the utilization of the right format and type within classes attributes.

See traittypes documentation for more informations.

Examples

Valid sparse voxels

from k3d.helpers import sparse_voxels_validation
import numpy as np
from traitlets import HasTraits, TraitError
from traittypes import Array

class Foo(HasTraits):
    bar = Array(type=np.uint32).valid(sparse_voxels_validation())

foo = Foo()

foo.bar = np.array([[1, 2, 4, 5],
                    [6, 7, 8, 9]])

"""
"""

Unvalid sparse voxels - wrong shape

from k3d.helpers import sparse_voxels_validation
import numpy as np
from traitlets import HasTraits, TraitError
from traittypes import Array

class Foo(HasTraits):
    bar = Array(type=np.uint32).valid(sparse_voxels_validation())

foo = Foo()

foo.bar = np.array([[1, 2, 3],
                    [4, 5, 6]])

"""
TraitError: Expected an array of shape (N, 4) and got (2, 3)
"""

Unvalid sparse voxels - negative coordinates

from k3d.helpers import sparse_voxels_validation
import numpy as np
from traitlets import HasTraits, TraitError
from traittypes import Array

class Foo(HasTraits):
    bar = Array(type=np.uint32).valid(sparse_voxels_validation())

foo = Foo()

foo.bar = np.array([[0, 0, 0, 0],
                    [1, 1, 1, 1],
                    [-2, -2, -2, -2]])

"""
TraitError: Voxel coordinates and values must be non-negative
"""