def __init__(self, width, height, n_rows, n_columns):
HasTraits.__init__(self)
n_scenes = n_rows * n_columns
if n_scenes < 1:
raise ValueError("n_rows=%r, n_columns=%r" % (n_rows, n_columns))
self.scenes = tuple(MlabSceneModel() for _ in xrange(n_scenes))
for i, scene in enumerate(self.scenes):
self.add_trait(SCENE_NAME % i, scene)
if n_rows == n_columns == 1:
self.view = View(Item(SCENE_NAME % 0,
editor=SceneEditor(scene_class=Scene),
resizable=True,
show_label=False),
width=width,
height=height,
resizable=True)
else:
rows = []
for row in xrange(n_rows):
columns = []
for column in xrange(n_columns):
i = row * n_columns + column
item = Item(SCENE_NAME % i,
editor=SceneEditor(scene_class=Scene),
resizable=True,
show_label=False)
columns.append(item)
rows.append(HGroup(*columns))
self.view = View(VGroup(*rows))
self.figures = [scene.mayavi_scene for scene in self.scenes]
def setUp(self):
EnamlTestAssistant.setUp(self)
enaml_source = """
from enaml.widgets.api import MainWindow
from traits_enaml.widgets.mayavi_canvas import MayaviCanvas
enamldef MainView(MainWindow):
attr scene
MayaviCanvas:
scene << parent.scene
"""
self.scene = MlabSceneModel()
self.view, _ = self.parse_and_create(enaml_source, scene=self.scene)
self.canvas = self.find_enaml_widget(self.view, 'MayaviCanvas')
def _scene_default(self):
return MlabSceneModel()
def _scene2_default(self):
self.engine2.start()
return MlabSceneModel(engine=self.engine2)
def __init__(self, *args, **kwargs):
super(HasTraits, self).__init__(*args, **kwargs)
self.FiberEngine.start()
self.FiberScene = MlabSceneModel(engine=self.FiberEngine)
self.draw()
def _scene2_default(self):
" The default initializer for 'scene2' "
self.engine2.start()
scene2 = MlabSceneModel(engine=self.engine2)
return scene2
def _scene1_default(self):
" The default initializer for 'scene1' "
self.engine1.start()
scene1 = MlabSceneModel(engine=self.engine1)
return scene1
def __init__(self, ds, engine=None, **kwargs):
super(DVMayavi, self).__init__(ds, **kwargs)
if engine is not None:
self.scene = MlabSceneModel(engine=engine)
else:
self.scene = MlabSceneModel()
def test_updating_the_scene(self):
canvas = self.canvas
with self.assertTraitChanges(canvas.model, 'scene', count=1):
canvas.scene = MlabSceneModel()
self.assertEqual(canvas.model.scene, canvas.scene)
