def __init__(self, axis, **kwargs): HasTraits.__init__(self, **kwargs) # @UndefinedVariable
def __init__(self, couch_points): # Do not forget to call the parent's __init__ HasTraits.__init__(self) self.couch_points = couch_points self.setup_animation()
def __init__(self, *args, **kwargs): # noqa: D102 logger.debug( "Initializing Kit2fiff-GUI with %s backend", ETSConfig.toolkit) HasTraits.__init__(self, *args, **kwargs)
def __init__(self, **traits): HasTraits.__init__(self, **traits) self.engine_view = EngineView(engine=self.scene.engine)
def __init__(self): # Do not forget to call the parent's __init__ HasTraits.__init__(self) x, y, z, = tens_fld(1,1,1,self.beta, self.alpha) self.plot = self.scene.mlab.mesh(x, y, z, colormap='copper', representation='surface')
def __init__(self, visualisation_model, decision_threshold, start_day=3, num_of_shown_days="30 days", precompute_cache=False): ''' :param visualisation_model: an instance of EventDataModel :param decision_threshold: a float larger or equal to 0.0 that is used for deciding when an anomaly score is significantly anomalous :param start_day: an integer >= or an instance of datetime.date or an string, like "2014-10-11" or a tuple, like (2014, 10, 11) :param num_of_shown_days: an integer > 1 that specifies the number of days back in time from start_day that will be shown. :param precompute_cache: boolean that indates whether all anomaly scores should be computed at once or when asked for. :return: ''' assert isinstance(visualisation_model, EventDataModel) assert isinstance( start_day, int) or isinstance(start_day, str) or isinstance( start_day, datetime.date) or (isinstance(start_day, tuple) and len(start_day) == 3) HasTraits.__init__(self) self.used_cache_size = 0 # must be initialized self._data = visualisation_model._event_data_object self.num_of_shown_days = num_of_shown_days # Updates self.used_cache_size self._vis_model = visualisation_model self._anomaly_detector = visualisation_model._anomaly_detector self.anomaly_detection_threshold = decision_threshold dates = visualisation_model._event_data_object.dates_ self._data_times = array([datetools.to_datetime(d) for d in dates]) self.source_names = list( unique(visualisation_model._event_data_object.sources_)) self._data_sources = array([ self.source_names.index(source) for source in visualisation_model._event_data_object.sources_ ]) self._num_of_sources = len(unique( self.source_names)) # number of sources self.barcharts = [] self.barchart_actors = [] self.time_text3ds = [] self.source_text3ds = [] self.xy_positions = [] self._high_start_day_number = int( (self._data_times.max() - self._data_times.min()).days) self.scene.anti_aliasing_frames = 8 # add traits dynamically self.add_trait("Relative_Start_Day", Range(0, self._high_start_day_number)) self.add_trait("_selected_source_name", Enum(None, [None] + self.source_names)) self.configure_traits() # add the mouse pick handler self.picker = self.scene.mayavi_scene.on_mouse_pick( self.vis_picker, 'cell') self.picker.tolerance = 0.01 self.severity_color = [ (1, x / 100.0, x / 100.0) for x in range(70, 30, -40 / self._vis_model.num_of_severity_levels_) ] # This used for a fix to manage a bug in Mayavi library, an invisible default object self._obj = self.scene.mlab.points3d(0, 0, 0, opacity=0.0) # Cache all anomaly calculations for all data values if precompute_cache: self.used_cache_size = len(self._data) for data_index in xrange(len(self._data)): self._populate_cache(data_index) self.start_day = start_day self.update()
def test_new(self): # Should not raise DeprecationWarning. HasTraits(x=10)
def service_factory(**properties): """ A factory for foos. """ return HasTraits(**properties)
def __init__(self): HasTraits.__init__(self) x, y, z = curve(self.n_turns) self.plot = self.scene.mlab.plot3d(x, y, z)
def __init__(self): HasTraits.__init__(self) x, y, z = curve(n_turns=2) # Populating our plot self.plot = self.scene.mlab.plot3d(x, y, z)
def __init__(self, text="", **kwtraits): if 'text' not in kwtraits: kwtraits['text'] = text HasTraits.__init__(self, **kwtraits) self._bounding_box = [0, 0] return
def set(self, *args, **kw): print('nacsd', args, kw) return HasTraits.set(self, *args, **kw)
def __init__(self, kp): """Initializer of the UI class""" ################################################### # # Initialize the scene # ################################################### # super class initializer HasTraits.__init__(self) # Drawer instance self.drawer = Drawer(self.scene) ################################################### # # Retrieve Data # ################################################### # store the kp self.kp = kp if self.kp.owl_files: self.kp.load_owl() elif self.kp.n3_files: self.kp.load_n3() elif self.kp.blazehost: self.kp.get_everything_blaze() else: self.kp.get_everything() ################################################### # # Fill the side lists # ################################################### # get data properties dps = self.kp.get_data_properties() for dp in dps: self.dataproperties_list.append(TraitDataProperty(dp_name = str(dp[0]), dp_domain = str(dp[1]), dp_range = str(dp[2]))) # get object properties ops = self.kp.get_object_properties() for op in ops: self.objectproperties_list.append(TraitObjectProperty(op_name = str(op[0]), op_domain = str(op[1]), op_range = str(op[2]))) # get instances for res in self.kp.get_instances(): self.resources_list.append(TraitResource(resource_name = str(res[0]))) # get classes cs = self.kp.get_classes() for c in cs: self.classes_list.append(TraitClass(class_name = str(c))) ################################################### # # Draw # ################################################### # initialize data structures self.res_list = ResourceList() self.planes = [] self.active_labels = [] # get and analyze knowledge self.data_classifier() self.calculate_placement() self.draw()
def __init__(self, path=default_path): HasTraits.__init__(self) self.path = path self.exp_path = os.path.dirname(self.path)
def __init__(self, **kwargs): transforms.Transform.__init__(self) HasTraits.__init__(self, **kwargs) # @UndefinedVariable
#class TestClass(HasTraits): # b1 = Bool # b2 = Bool # b3 = Bool # _updated = Bool(False) # #for e in dir(view1): # print e #for attr in ['b1', "title", "handler", "buttons"]: # print attr, getattr(view1, attr, None) #tc = TestClass() #tc.add_trait( 'b4',Bool) t = HasTraits() nameL = [] for i in range(4): name = 'r%d' % i t.add_trait(name, Range(1, 10, i)) nameL.append(name) view1 = View(nameL, title="Alter Title", handler=TC_Handler(), buttons=['OK', 'Cancel']) t.configure_traits(view=view1)
def __init__(self, **traits): HasTraits.__init__(self, **traits) self.generate_data()
def __init__(self): # Do not forget to call the parent's __init__ HasTraits.__init__(self) data = sio.loadmat('img_max50') self.H = data['H1']