Files
dpks-lab4/graph.py
T
2026-10-31 23:39:24 +02:00

72 lines
1.8 KiB
Python

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")