import numpy as np
import matplotlib.pyplot as plt

# %% Data:

t_array = np.arange(2010, 2019+1)
kpi_obs_array = np.array(
    [92.1, 93.3, 93.9, 95.9, 97.9, 
     100.0, 103.6, 105.5,108.4, 110.8])

# %% Prediction:

a = 1.412
b = -2747

kpi_pred_array = a*t_array + b

# %% Plotting:

plt.close('all')
plt.figure(num=1, figsize=(12, 9))

plt.plot(t_array, kpi_obs_array,'bo-',
         label='kpi_virkelig')
plt.plot(t_array, kpi_pred_array,'ro-',
         label='kpi_predikert')
plt.legend()
plt.title('Konsumprisindeks (KPI)-virkelig og predikert')
plt.xlabel('t [year]')
plt.grid()

# plt.savefig('prog_plot_kpi_2010_2019_pred_and_real.pdf')
plt.show()