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']
