def main(): distance_list = [] expected_of_R_2_sum_list = [] expected_of_R_4_sum_list = [] steps_list = [] M = 350000 for steps in range(10, 35, 5): distance_list = [] for walker_number in range(0, M): a = RandomChain(0, 0, 0) x, y, z = a.add_X_spheres(steps) distance_squared = math.sqrt(x ** 2 + y ** 2 + z ** 2) distance_list.append(distance_squared) expected_of_R_2_sum = 0 expected_of_R_4_sum = 0 for distance_square in distance_list: expected_of_R_2_sum = expected_of_R_2_sum + distance_square expected_of_R_4_sum = expected_of_R_4_sum + distance_square ** 2 expected_of_R_2_sum = expected_of_R_2_sum / M expected_of_R_4_sum = expected_of_R_4_sum / M expected_of_R_2_sum_list.append(expected_of_R_2_sum) expected_of_R_4_sum_list.append(expected_of_R_4_sum) steps_list.append(steps) delta = math.sqrt((expected_of_R_4_sum - expected_of_R_2_sum) / M) print "expected_of_R_2_sum: " + str(expected_of_R_2_sum) print "expected_of_R_4_sum: " + str(expected_of_R_4_sum) print "delta: " + str(delta) best_line(np.log(steps_list), np.log(expected_of_R_2_sum_list))
def main(): distance_list = [] expected_of_R_2_sum_list = [] expected_of_R_4_sum_list = [] steps_list = [] M = 350000 for steps in range(10, 40, 5): distance_list = [] for walker_number in range(0, M): walker = Randomwalker(0, 0) x, y = walker.walk_X_steps(steps) distance_squared = math.sqrt(x ** 2 + y ** 2) distance_list.append(distance_squared) expected_of_R_2_sum = 0 expected_of_R_4_sum = 0 for distance_square in distance_list: expected_of_R_2_sum = expected_of_R_2_sum + distance_square expected_of_R_4_sum = expected_of_R_4_sum + distance_square ** 2 expected_of_R_2_sum = expected_of_R_2_sum / M expected_of_R_4_sum = expected_of_R_4_sum / M expected_of_R_2_sum_list.append(expected_of_R_2_sum) expected_of_R_4_sum_list.append(expected_of_R_4_sum) steps_list.append(steps) delta = math.sqrt((expected_of_R_4_sum - expected_of_R_2_sum) / M) print "expected_of_R_2_sum: " + str(expected_of_R_2_sum) print "expected_of_R_4_sum: " + str(expected_of_R_4_sum) print "delta: " + str(delta) best_line(steps_list, expected_of_R_2_sum_list)