import numpy as np
import pandas as pd
import matplotlib.pyplot as plt


path = "forecasts.csv"

df = pd.read_csv(path, encoding = "utf8")

gens = {
    "Солнце 50%": (3, [5, 10, 10]),
    "Ветер 50%": (1, [10])
}
cons = {
    "Больницы 50%": (2, [7, 5]),
    "Заводы 50%": (2, [8, 7]),
    "Дома 50%": (6, [8, 7, 8, 5, 8, 8])
}

total_gen = 0
total_con = 0


array_gen = []
array_con = []

array_gen_cost = []
array_con_cost = []


for i in range(len(df)):
    total_gen = 0
    total_con = 0

    gen_cost = 0
    con_cost = 0
    for j in gens:
        total_gen += gens[j][0]*df[j][i]
        for k in range(len(gens[j][1])):
            gen_cost += gens[j][1][k]
        if i in list(range(0,20)) or i in list(range(40, 66)):
            total_gen += 10
            gen_cost += 40
    for j in cons:
        total_con += cons[j][0]*df[j][i]
        for k in range(len(cons[j][1])):
            con_cost += cons[j][1][k]
    array_gen.append(total_gen)
    array_con.append(total_con)

    array_gen_cost.append(gen_cost)
    array_con_cost.append(con_cost)


fig, ax = plt.subplots()

ax.plot(array_con, '-b', label="Consumed")
ax.plot(array_gen, '-g', label="Generated")
ax.legend()

plt.show()


fig, ax = plt.subplots()

ax.plot(array_con_cost, '-b', label="Consumed")
ax.plot(array_gen_cost, '-g', label="Generated")
ax.legend()

plt.show()