Пример #1
0
#     29.,17.,4.4,
#     29.,17.4,4.5,
#     29.,19.,4.7,
# ]
# y_s=[
#     1.4, 0.8,0.2,
#     2,   0.8,0.18,
#     1.75,0.8,0.18,
#     1.74,0.8,0.18,
# ]

plt.figure(figsize=(7.4861, 7.4861))
for j in range(len(records_list)):
    ax = plt.subplot(4, 4, j + 1, aspect='equal')
    xx, linear_list, xymin, xymax = compute_multi_linear_fit(
        records=records_list[j],
        predictions=predictions_list[j],
    )
    ax.yaxis.set_major_formatter(FormatStrFormatter('%.0f'))
    if j in range(8, 12):
        plt.xlabel('Predictions(' + r'$10^8m^3$' + ')', )
    if j in [0, 4, 8]:
        plt.ylabel('Records(' + r'$10^8m^3$' + ')', )
    models = models_labels[j]
    markers = [
        'o',
        'v',
    ]
    zorders = [1, 0]
    # plt.text(x_s[j],y_s[j],fig_idx[j],fontweight='normal',fontsize=7)
    for i in range(len(predictions_list[j])):
        # plt.plot(predictions_list[i], records_list[i],marker=markers[i], markerfacecolor='w',markeredgecolor='blue',markersize=6.5)
Пример #2
0
    'h_d_7' : h_d_7['test_pred'][0:120].values,
    'h_e_7' : h_e_7['test_pred'][0:120].values,
    'h_s_7' : h_s_7['test_pred'][0:120].values,
    'h_v_7' : h_v_7['test_pred'][0:120].values,
    'x_m_7' : x_m_7['test_pred'][0:120].values,
    'x_d_7' : x_d_7['test_pred'][0:120].values,
    'x_e_7' : x_e_7['test_pred'][0:120].values,
    'x_s_7' : x_s_7['test_pred'][0:120].values,
    'x_v_7' : x_v_7['test_pred'][0:120].values,
    'z_m_7' : z_m_7['test_pred'][0:120].values,
    'z_d_7' : z_d_7['test_pred'][0:120].values,
    'z_e_7' : z_e_7['test_pred'][0:120].values,
    'z_s_7' : z_s_7['test_pred'][0:120].values,
    'z_v_7' : z_v_7['test_pred'][0:120].values,
}
xx,linear_list,xymin,xymax = compute_multi_linear_fit(records,preds)
h_records={
    'h_arma': h_arma['test_y'],
    'h_svr_1' : h_svr_1['test_y'][0:120].values,
    'h_dnn_1' : h_dnn_1['test_y'][0:120].values,
    'h_lstm_1' : h_lstm_1['test_y'][0:120].values,
    'h_m_1' : h_m_1['test_y'][0:120].values,
    'h_d_1' : h_d_1['test_y'][0:120].values,
    'h_e_1' : h_e_1['test_y'][0:120].values,
    'h_s_1' : h_s_1['test_y'][0:120].values,
    'h_v_1' : h_v_1['test_y'][0:120].values,
    'h_svr_3' : h_svr_3['test_y'][0:120].values,
    'h_dnn_3' : h_dnn_3['test_y'][0:120].values,
    'h_lstm_3' : h_lstm_3['test_y'][0:120].values,
    'h_m_3' : h_m_3['test_y'][0:120].values,
    'h_d_3' : h_d_3['test_y'][0:120].values,