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]))
