dataset_angle[cal_index] = pd.DataFrame(dataset_angle[cal_index], columns=['Angle'])
# filter angles out of range
valid_angle = (cfg.min_angle <= dataset_angle[cal_index]['Angle']) & \
(cfg.max_angle >= dataset_angle[cal_index]['Angle'])
test_data[cal_index] = test_data[cal_index].loc[valid_angle]
dataset_angle[cal_index] = dataset_angle[cal_index].loc[valid_angle]
dataset_angle[cal_index] = np.array(dataset_angle[cal_index]).ravel()
"""
create trainset
"""
ant_pat = fn_exp.find_pattern(test_data[cal_index], dataset_angle[cal_index])
train = np.repeat(ant_pat, cfg_exp.cal_rep, axis=0)
noise = np.random.normal(0, cfg_exp.cal_noise, train.shape)
train += noise
train_max = np.max(train[:, :-1], axis=1).reshape((train.shape[0], 1))
train -= train_max
# train angles
ant_angles = [cfg.min_angle]
while ant_angles[-1] < cfg.max_angle:
ant_angles.append(ant_angles[-1] + 2.5)
ant_angles = np.array(ant_angles)
ant_angles = np.repeat(ant_angles, cfg_exp.cal_rep)
rfc[cal_index].fit(arranged_data[cal_index], dataset_angle[cal_index])
# # plot test prediction(angle) - for checking
# x = range(dataset_angle[cal_index].shape[0])
#
# # creating predicted test set angles
# test_prediction = rfc[cal_index].predict(arranged_data[cal_index]).tolist()
# plt.plot(x, dataset_angle[cal_index], 'ro', x, test_prediction, 'go')
# plt.show()
"""
Plot antennas' graph
"""
# Find parameters SD (from not arranged data)
sd_ant = fn_exp.cal_sd(dataseta_for_sd, dataset_angle[cal_index])
ant_pat = fn_exp.find_pattern(arranged_data[cal_index], dataset_angle[cal_index])
ant_angles = [cfg.min_angle]
while ant_angles[-1] < cfg.max_angle:
ant_angles.append(ant_angles[-1] + 2.5)
ant_angles = np.array(ant_angles)
# # plotting
# plt.figure(1)
# plt.subplot(211)
# plt.plot(ant_angles, ant_pat[:, 0], 'r', ant_angles, ant_pat[:, 0] + sd_ant[:, 0], 'r--',
# ant_angles, ant_pat[:, 0] - sd_ant[:, 0], 'r--',
# ant_angles, ant_pat[:, 1], 'g', ant_angles, ant_pat[:, 1] + sd_ant[:, 1], 'g--',
# ant_angles, ant_pat[:, 1] - sd_ant[:, 1], 'g--',
# ant_angles, ant_pat[:, 2], 'b', ant_angles, ant_pat[:, 2] + sd_ant[:, 2], 'b--',
# ant_angles, ant_pat[:, 2] - sd_ant[:, 2], 'b--',
