def configure(self, time_series): """ Do any configuration needed before launching and create an instance of the algorithm. """ shape = time_series.read_data_shape() LOG.debug("time_series shape is %s" % (str(shape))) ##-------------------- Fill Algorithm for Analysis -------------------## self.algorithm = NodeComplexCoherence() self.algorithm.time_series = time_series self.memory_factor = 1
def configure(self, time_series): """ Do any configuration needed before launching and create an instance of the algorithm. """ self.input_time_series_index = time_series self.input_shape = (self.input_time_series_index.data_length_1d, self.input_time_series_index.data_length_2d, self.input_time_series_index.data_length_3d, self.input_time_series_index.data_length_4d) LOG.debug("Time series shape is %s" % (str(self.input_shape))) # -------------------- Fill Algorithm for Analysis -------------------## self.algorithm = NodeComplexCoherence() self.memory_factor = 1
def configure(self, view_model): # type: (NodeComplexCoherenceModel) -> None """ Do any configuration needed before launching and create an instance of the algorithm. """ self.input_time_series_index = self.load_entity_by_gid(view_model.time_series.hex) self.input_shape = (self.input_time_series_index.data_length_1d, self.input_time_series_index.data_length_2d, self.input_time_series_index.data_length_3d, self.input_time_series_index.data_length_4d) self.log.debug("Time series shape is %s" % (str(self.input_shape))) # -------------------- Fill Algorithm for Analysis -------------------## self.algorithm = NodeComplexCoherence() self.memory_factor = 1
def get_input_tree(self): """ Return a list of lists describing the interface to the analyzer. This is used by the GUI to generate the menus and fields necessary for defining a simulation. """ algorithm = NodeComplexCoherence() algorithm.trait.bound = self.INTERFACE_ATTRIBUTES_ONLY tree = algorithm.interface[self.INTERFACE_ATTRIBUTES] for node in tree: if node['name'] == 'time_series': node['conditions'] = FilterChain( fields=[FilterChain.datatype + '._nr_dimensions'], operations=["=="], values=[4]) return tree
def get_traited_datatype(self): return NodeComplexCoherence()