def __init__(self,
params,
input_vectors,
dimensions,
plot_for_itr=0,
activity_classes=None,
output_loc=None):
self.parameters = params
self.inputs = np.asarray(input_vectors)
self.growth_handler = Growth_Handler.GrowthHandler()
self.dimensions = dimensions
self.learn_smooth_sample_size = self.parameters.get_learn_smooth_sample_size(
len(self.inputs))
self.gsom_nodemap = {}
self.plot_for_itr = plot_for_itr
self.display = Display_Utils.Display(None, None)
self.activity_classes = activity_classes
self.output_save_location = output_loc
# Parameters for recurrent gsom
self.globalContexts = np.zeros(
(self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.globalContexts_evaluation = np.zeros(
(self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.alphas = Utils.Utilities.get_decremental_alphas(
self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS)
self.previousBMU = np.zeros(
(1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.previousBMU_evaluation = np.zeros(
(1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
def __init__(self,
params,
dimensions,
plot_for_itr=0,
activity_classes=None,
output_loc=None):
threading.Thread.__init__(self)
self.parameters = params
self.growth_handler = Growth_Handler.GrowthHandler()
self.dimensions = dimensions
# self.learn_smooth_sample_size = self.parameters.get_learn_smooth_sample_size(len(inputs))
self.gsom_nodemap = {}
self.plot_for_itr = plot_for_itr
self.display = Display_Utils.Display(None, None)
self.activity_classes = activity_classes
self.output_save_location = output_loc
self.att = 0.5
self.att_learning_rate = 0.01
self.recurrent_weights_batch = []
self.emotion_features_batch = []
self.behaviour_features_batch = []
self.BATCH_SIZE = 10
# Parameters for recurrent gsom
self.globalContexts = np.zeros(
(self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.globalContexts_evaluation = np.zeros(
(self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.alphas = Utils.Utilities.get_decremental_alphas(
self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS)
self.previousBMU = np.zeros(
(1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
self.previousBMU_evaluation = np.zeros(
(1, self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS, self.dimensions))
def __init__(self, params):
threading.Thread.__init__(self)
self.parameters = params
self.growth_handler = Growth_Handler.GrowthHandler()
self.gsom_nodemap = {}
# Parameters for recurrent gsom
self.alphas = Utils.Utilities.get_decremental_alphas(
self.parameters.NUMBER_OF_TEMPORAL_CONTEXTS)
