def set_transformation(self, transformation, init=False):
if not transformation.__class__ == self.Transformation:
# create an object of the proper type and take only the attributes
# of interest.
if isinstance(transformation, Translation):
t = transformation.t
else:
t = None
if isinstance(transformation, Rotation):
r = transformation.r
else:
r = None
if self.Transformation == Translation:
if t is None:
transformation = Translation.identity()
else:
transformation = Translation(t)
elif self.Transformation == Rotation:
if r is None:
transformation = Rotation.identity()
else:
transformation = Rotation(r)
else: # self.Transformation == Complete:
if r is None:
r = numpy.identity(3, float)
if t is None:
t = numpy.zeros(3, float)
transformation = Complete(r, t)
self.transformation = transformation
if not init:
self.invalidate_transformation_list()
def do(self):
cache = context.application.cache
for node in cache.nodes:
translated_children = []
for child in node.children:
if isinstance(child, GLTransformationMixin) and isinstance(
child.transformation, Translation):
if child.get_fixed():
translated_children = []
break
translated_children.append(child)
if len(translated_children) == 0:
continue
mass, com = compute_center_of_mass(iter_particles(node))
if mass == 0.0:
continue
tensor = compute_inertia_tensor(iter_particles(node), com)
transformation = Complete(align_rotation_matrix(tensor), com)
CenterAlignBase.do(self, node, translated_children, transformation)
def update_gui(self):
if self.status is not None:
self.la_num_iter.set_text("%i" % self.status.step)
self.la_rms_error.set_text(
express_measure(
numpy.sqrt(self.status.value / self.num_springs),
"Length"))
self.progress_bar.set_text("%i%%" %
int(self.status.progress * 100))
self.progress_bar.set_fraction(self.status.progress)
for state_index, frame, variable in zip(
self.state_indices, self.involved_frames,
self.minimize.root_expression.state_variables):
if isinstance(variable, iterative.var.Frame):
r, t = variable.extract_state(state_index,
self.status.state)
frame.set_transformation(Complete(r, t))
elif isinstance(variable, iterative.var.Translation):
t = variable.extract_state(state_index, self.status.state)
new_transformation = frame.transformation.copy_with(t=t)
frame.set_transformation(new_transformation)
context.application.main.drawing_area.queue_draw()
def endElement(self, name):
if name == "zml_file": return
# now that we have gatherd all information of this tag, create an appropriate object
# first find the tags involved in this operation
current_tag = self.hierarchy[-1][-1]
child_tags = []
if not current_tag.being_processed:
current_tag = self.hierarchy[-2][-1]
child_tags = self.hierarchy[-1]
# do it
if name == "str": current_tag.value = str(current_tag.content)
elif name == "float": current_tag.value = float(current_tag.content)
elif name == "int": current_tag.value = int(current_tag.content)
elif name == "bool":
temp = current_tag.content.lower().strip()
if temp == 'true': current_tag.value = True
else: current_tag.value = False
elif name == "list": current_tag.value = [tag.value for tag in child_tags]
elif name == "dict": current_tag.value = dict((tag.label, tag.value) for tag in child_tags)
elif name == "tuple": current_tag.value = tuple(tag.value for tag in child_tags)
elif name == "shape":
current_tag.value = tuple(int(item) for item in current_tag.content.split())
elif name == "cells":
current_tag.value = numpy.array([eval(item) for item in current_tag.content.split()])
elif name == "array":
child_dict = dict((tag.name, tag.value) for tag in child_tags)
current_tag.value = numpy.reshape(child_dict["cells"], child_dict["shape"])
elif name == "grid":
current_tag.value = numpy.reshape(numpy.array([eval(item) for item in current_tag.content.split()]), (int(current_tag.attributes["rows"]), int(current_tag.attributes["cols"]), -1))
elif name == "binary":
current_tag.value = StringIO.StringIO()
current_tag.content.seek(0)
base64.decode(current_tag.content, current_tag.value)
elif name == "translation":
current_tag.value = Translation(child_tags[0].value)
elif name == "rotation":
current_tag.value = Rotation(child_tags[0].value)
elif name == "transformation":
child_dict = dict((tag.label, tag.value) for tag in child_tags)
current_tag.value = Complete(
child_dict["rotation_matrix"],
child_dict["translation_vector"],
)
elif name == "unit_cell":
child_dict = dict((tag.label, tag.value) for tag in child_tags)
current_tag.value = UnitCell(
child_dict["matrix"],
child_dict["active"],
)
elif name == "expression":
current_tag.value = Expression(current_tag.content)
elif name == "reference":
current_tag.value = None
referent_tag = self.hierarchy[-3][-1]
target_ids = self.target_ids.get(referent_tag)
if target_ids is None:
target_ids = []
self.target_ids[referent_tag] = target_ids
target_ids.append(int(current_tag.attributes["to"]))
elif name == "model_object":
Class = context.application.plugins.get_node(str(current_tag.attributes["class"]))
current_tag.state = dict((tag.label, tag.value) for tag in child_tags)
current_tag.value = Class()
self.model_object_tags[int(current_tag.attributes["id"])] = current_tag
else: pass
# close the door
current_tag.content = None
current_tag.close()
if len(child_tags) > 0: self.hierarchy.pop()
