def test_equation_unconstrained_hebbian_learning_ca3_out(self): hpc = HPC([49, 240, 1600, 480, 49], 0.67, 0.25, 0.04, # connection rates: (in_ec, ec_dg, dg_ca3) 0.10, 0.01, 0.04, # firing rates: (ec, dg, ca3) 0.7, 1, 0.1, 0.5, # gamma, epsilon, nu, turnover rate 0.10, 0.95, 0.8, 2.0) # k_m, k_r, a_i, alpha empty_activation_values_l1 = np.zeros_like(hpc.ca3_values.get_value()).astype(np.float32) empty_activation_values_l1.put([0, 0], 1) hpc.set_ca3_values(empty_activation_values_l1) empty_activation_values_l2 = np.zeros_like(hpc.output_values.get_value()).astype(np.float32) empty_activation_values_l2.put([0, 0], 1) hpc.set_output(empty_activation_values_l2) current_weight_element = hpc.ca3_out_weights.get_value()[0][0] next_weight_element = hpc._gamma * current_weight_element + 1 hpc.wire_ca3_out(hpc.ca3_values.get_value(return_internal_type=True), hpc.output_values.get_value(return_internal_type=True), hpc.ca3_out_weights.get_value(return_internal_type=True)) self.assertAlmostEqual(hpc.ca3_out_weights.get_value()[0][0], next_weight_element, places=6, msg="Weight update did not correspond to the predicted update value of the equation: " "next_weight_el != w_el : "+str(next_weight_element)+" != " + str(hpc.ca3_out_weights.get_value()[0][0]))