def get_out(out_state): arr = [] for i in range(NUM_NEURONS): arr.append(int(round(rkf.func_to_calc_sigmoid(out_state[i][2])))) return arr
def get_out(out_state): arr = [] for i in range(NUM_NEURONS): arr.append(int(round(rkf.func_to_calc_sigmoid(out_state[i][2])))) return arr
def calc_S(step, neuron): sum_S = 0 # print("exp func : " + str(intern_state[step][j][2])) for j in range(NUM_NEURONS): sum_S += W[neuron][j] * rkf.func_to_calc_sigmoid(intern_state[step][j][2]) # print(sum_S) return sum_S
def calc_S(step, neuron): sum_S = 0 # print("exp func : " + str(intern_state[step][j][2])) for j in range(NUM_NEURONS): sum_S += W[neuron][j] * rkf.func_to_calc_sigmoid( intern_state[step][j][2]) # print(sum_S) return sum_S
def print_out(out_state): st_outr = '' idx = 0 for i in range(NUM_NEURONS): st_outr += str(int(round(rkf.func_to_calc_sigmoid(out_state[i][2])))) idx += 1 if idx == LINE_AMOUNT: print(st_outr) st_outr = '' idx = 0 print(st_outr)
def print_out(out_state): st_outr = '' idx = 0 for i in range(NUM_NEURONS): st_outr += str(int(round(rkf.func_to_calc_sigmoid(out_state[i][2])))) idx += 1 if idx == LINE_AMOUNT: print(st_outr) st_outr='' idx = 0 print(st_outr)