# When amending please keep colors and order same as energy graph

lang = "en"
#lang = "tr"

import numpy as np
import matplotlib.pyplot as plt
import sys
import seaborn as sns

# Data from https://enerji.gov.tr/eigm-raporlari Ulusal Enerji Denge Tabloları Sheet:BİN TEP yyyy Row 12:Enerji̇ Ürünleri̇ Arzi
year                  = ['2014','2015','2016','2017','2018','2019','2020','2021']

Taş_Kömürü            = [20199, 22428, 23597, 24707, 24679, 25120, 25449, 23444]
Linyit                = [12702, 11446, 13556, 13791, 15086, 15453, 13863, 16672]
Asfaltit              = [  372,   499,   778,   555,   697,  1022,   979,   707]
Kok                   = [  234,   299,   527,   504,   513,   420,   430,   744]
# Combine different types of coal
# Could not see how to add more than 2 arrays
Kömür                 = np.add(Taş_Kömürü,Linyit).tolist()
Kömür                 = np.add(Kömür,     Asfaltit).tolist()
Kömür                 = np.add(Kömür,     Kok).tolist()

Ham_Petrol            = [20802, 28015, 28709, 29491, 25099, 35448, 34393, 36241]
Petrol_Ürünleri       = [10823, 11194, 13495, 14786, 16814,  6006,  7797,  7742]
# Combine different types of oil
Petrol                = np.add(Ham_Petrol,Petrol_Ürünleri).tolist()

Doğalgaz              = [40201, 39651, 38338, 44319, 41171, 37128, 39806, 49231]
#Other (Diğer) is Bio and waste and may be wrong as not sure how to add up early years as categories changed for bio and waste
Diğer                 = [ 3495,  2938,  2843,  2531,  3014,  3157,  3396,  4099]
Hidrolik              = [ 3495,  5775,  5782,  5007,  5155,  7639,  6716,  4810]
Rüzgar                = [  733,  1002,  1334,  1540,  1716,  1869,  2135,  2704]
Jeotermal             = [ 3524,  4805,  6034,  7128,  8343,  9651, 10576, 11234]
Güneş                 = [  803,   828,   917,  1091,  1547,  1622,  1784,  2059]

# Convert to megatonnes as easier to read

coal          = np.divide(Kömür,                 1000).tolist()
oil           = np.divide(Petrol,                1000).tolist()
gas           = np.divide(Doğalgaz,              1000).tolist()
other         = np.divide(Diğer,                 1000).tolist()
hydro         = np.divide(Hidrolik,              1000).tolist()
wind          = np.divide(Rüzgar,                1000).tolist()
geothermal    = np.divide(Jeotermal,             1000).tolist()
solar         = np.divide(Güneş,                 1000).tolist()

if lang == "en":
 plt.title ("Primary energy supply in Turkey")
 plt.ylabel("Millions of tonnes of oil equivalent")
 plt.xlabel('Source: https://enerji.gov.tr/eigm-raporlari Ulusal Enerji Denge Tabloları Sheet:BİN TEP yyyy Row 12:Enerji̇ Ürünleri̇ Arzi', fontsize = 'x-small', color = 'grey')
 label_coal          = "coal"
 label_oil           = "oil"
 label_gas           = "gas"
 label_geothermal    = "geothermal"
 label_hydro         = "hydro"
 label_other         = "other"
 label_solar         = "solar"
 label_wind          = "wind"
elif lang == "tr":
 plt.title ("Türkiye'de birincil enerji arzı")
 plt.ylabel("Milyon TEP")
 labels = ["Kömür", "Petrol",  "Doğalgaz",  "Jeotermal", "Hidrolik", "Biyoenerji_ve_Atıklar", "Güneş", "Rüzgar"]
 plt.xlabel('Kaynak: https://enerji.gov.tr/eigm-raporlari Ulusal Enerji Denge Tabloları Tablo:BİN TEP yyyy Satır 12:Enerji̇ Ürünleri̇ Arzi', fontsize = 'x-small', color = 'grey')
 label_coal          = "kömür"
 label_oil           = "petrol"
 label_gas           = "gaz"
 label_geothermal    = "jeotermal"
 label_hydro         = "hidrolik"
 label_other         = "diğer"
 label_solar         = "güneş"
 label_wind          = "rüzgar"
else:
 print("Unknown language " + lang)
 sys.exit()

colors = ["brown","black","khaki","cornflowerblue","red","yellow","green","gray"]

plt.stackplot(year, coal, oil, gas, hydro, geothermal,  solar, wind, other, colors=colors)

#Position labels manually to make them quicker to read than a legend in a corner - might need slight adjustment as years added
plt.text(7.1,160,label_other,      fontsize = 'small')
plt.text(7.1,155,label_wind,       fontsize = 'small')
plt.text(7.1,150,label_solar,      fontsize = 'small')
plt.text(7.1,143,label_geothermal, fontsize = 'small')
plt.text(7.1,136,label_hydro,      fontsize = 'small')
plt.text(7.1,113,label_gas,        fontsize = 'large')
plt.text(7.1, 60,label_oil,        fontsize = 'large')
plt.text(7.1, 18,label_coal,       fontsize = 'large')

#Avoid chopping off labels
plt.tight_layout()


#Don't need the frame
sns.despine(bottom = True, left = True)

#Don't need the dash marks
plt.tick_params(left=False, bottom=False)

# Save graphic
if lang == "en":
 plt.savefig("primary_energy_Turkey.svg")
elif lang == "tr":
 plt.savefig("birincil_enerji_arzı_Türkiye.svg")
else:
 print("Unknown language " + lang)
 sys.exit()  

# Show graphic
plt.show()

# Resulting graph should be roughly similar to graph "Total primary energy supply (TPES) by source, Turkey"
# from https://www.iea.org/data-and-statistics but perhaps not exactly the same if Turkstat have revised their figures