#import numpy as np
from matplotlib import pyplot as plt

for i in range(1, 4):
    exec(f"data{i} = list(zip(*[x for x in [[float(j) for j in k.strip().split(',')] for k in open(\"data{i}.csv\").read().split(\"\\n\")[1:] if k] if x[1] <= 1200]))")

for i in range(5):
    title = "S,D,D_avg,T,C".split(',')[i]
    plt.cla()
    plt.figure(figsize = (17/1.3, 11.2/1.3))
    plt.title(title)
    plt.plot(data1[1], data1[i+3])
    plt.plot(data2[1], data2[i+3])
    plt.plot(data3[1], data3[i+3])
    plt.legend(labels = ["Кільце", "Дерево", "Решітка"])
    plt.xlim(0, 1100)
    plt.tight_layout()
    #plt.show()
    plt.savefig(f"diagram-{title}.svg", format = 'svg')

splits = 0, 55, 240, 1100


vsss = []
smas = []
for i in range(3):
    def get_avgs(d):
        s = tuple(zip(*[j for j in zip(*d) if j[1] >= splits[i] and j[1] < splits[i+1]]))
        vs = []
        for v in range(5):
            vs.append(sum(s[v+3]) / len(s[v+3]))
            print(round(vs[-1], 7), end = " ")

        print()

        return vs

    vss = []
    print(f"Range {splits[i]}-{splits[i+1]}")
    for x in range(3):
        exec(f"vss.append(get_avgs(data{x+1}))")

    vals = list(zip(*vss))
    print("Normed:")
    t = []
    for v in vals:
        m = min(v)
        t.append([x / m for x in v])
        print([round(x, 5) for x in t[-1]])


    t = zip(*t)
    print("Sigmas:")
    smas.append([])
    for v in t:
        smas[-1].append(sum(v))
        print(round(smas[-1][-1], 5), end = " ")

    print()
    print()

    vsss.append(vss)

dsas = {i:v for i, v in zip([f"Діапазон {i+1}" for i in range(3)], smas)}
print(dsas)
plt.cla()
plt.figure(figsize = (17/1.4, 17/1.4))
plt.grouped_bar(dsas, bar_spacing = 0.25, tick_labels = ["Кільце", "Дерево", "Решітка"])
plt.legend()
plt.tight_layout()
#plt.show()
plt.savefig("histogram.svg", format = "svg")