def __init__(self, to_clone=None):
"""
Create a new Transformable object, optionally cloning the
transformations of the supplied Transformable object.
"""
if to_clone is not None:
self.orientation = ObservableArray.like(to_clone.orientation)
self.size = ObservableArray.like(to_clone.size)
self.position = ObservableArray.like(to_clone.position)
self.auto_transform = dict(to_clone.auto_transform)
else:
self.orientation = ObservableArray.like([0., 0., 0.])
self.size = ObservableArray.like([1., 1., 1.])
self.position = ObservableArray.like([0., 0., 0.])
self.auto_transform = {
'size': True,
'orientation': True,
'position': True
}
self.check_arrays()
self.callbacks.add(self.check_arrays)
def test_replace_size(self):
new_size = [1., 2., 3.]
self.obj.size = ObservableArray.like(new_size)
assert np.array_equal(new_size, self.obj.size)
