def data(self, data):
self.geometry = Geometry.from_data(data['geometry'])
self.origin = Origin.from_data(
data['origin']) if data['origin'] else None
self.name = data['name']
self.attr = _attr_from_data(data['attr'])
self.init_transformation = Transformation.from_data(
data['init_transformation']
) if data['init_transformation'] else None
self.current_transformation = Transformation.from_data(
data['current_transformation']
) if data['current_transformation'] else None
def data(self, data):
self.attributes.update(data['attributes'] or {})
self.key = data['key']
self.frame.data = data['frame']
self.shape.data = data['shape']
self.features = [(Shape.from_data(shape), operation) for shape, operation in data['features']]
self.transformations = deque([Transformation.from_data(T) for T in data['transformations']])
def _publish_tf_static_xform(xform=None):
"""Start a docker service advertising a TF2 static transformation.
Parameters
----------
xform : :obj:`list` of :obj:`list` of :obj:`float`, optional
Transformation matrix. Defaults to a zero-matrix.
"""
if xform:
xform = Transformation.from_data(xform)
log.debug("Loading matrix from run_data.")
else:
xform = Transformation()
log.debug("Publishing zero matrix")
publish_static_transform(xform, scale_factor=1000) # mm to m scale factor
