-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathlab3.py
More file actions
125 lines (92 loc) · 4.4 KB
/
Copy pathlab3.py
File metadata and controls
125 lines (92 loc) · 4.4 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
import random
import numpy as np
import copy
x1min = 10
x1max = 50
x2min = -20
x2max = 60
x3min = -20
x3max = 20
xAvmax = x1max+x2max+x3max/3
xAvmin = x1min+x2min+x3min/3
ymax = int(200+xAvmax)
ymin = int(200+xAvmin)
print("{:^31}{:^41}".format('Кодованє значення X', 'Матриця для m=3'))
print("{:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5}"
.format("№", "X1", "X2", "X3", "#", "№", "X1", "X2", "X3", "Y1", "Y2", "Y3"))
Xi = [[1, 1, 1, 1], [-1, -1, +1, +1], [-1, +1, -1, +1], [-1, +1, +1, -1]]
X = [[x1min, x1min, x1max, x1max],
[x2min, x2max, x2min, x2max],
[x3min, x3max, x3max, x3min]]
Y = [[random.randrange(138, 247, 1) for _ in range(4)] for __ in range(3)]
for i in range(4):
print("{:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5} {:>5}"
.format(i+1, Xi[1][i], Xi[2][i], Xi[3][i], "#", i+1, X[0][i], X[1][i], X[2][i], Y[0][i], Y[1][i], Y[2][i]))
print("\n_________Критерій Кохрена________")
print("Середнє значення відгуку функції: ")
yav = [(Y[0][i]+Y[1][i]+Y[2][i])/3 for i in range(4)]
my = sum(yav)/4
mx = [sum(X[i]) for i in range(3)]
a = [(X[i][0]*yav[0] + X[i][1]*yav[1] + X[i][2]*yav[2] + X[i][3]*yav[3])/4 for i in range(3)]
a11 = (X[0][0]**2 + X[0][1]**2 + X[0][2]**2 + X[0][3]**2)/4
a22 = (X[1][0]**2 + X[1][1]**2 + X[1][2]**2 + X[1][3]**2)/4
a33 = (X[2][0]**2 + X[2][1]**2 + X[2][2]**2 + X[2][3]**2)/4
a12 = a21 = (X[0][0]*X[1][0] + X[0][1]*X[1][1] + X[0][2]*X[1][2] + X[0][3]*X[1][3])/4
a13 = a31 = (X[0][0]*X[2][0] + X[0][1]*X[2][1] + X[0][2]*X[2][2] + X[0][3]*X[2][3])/4
a23 = a32 = (X[1][0]*X[2][0] + X[1][1]*X[2][1] + X[1][2]*X[2][2] + X[1][3]*X[2][3])/4
b = []
b01 = np.array([[my, mx[0], mx[1], mx[2]], [a[0], a11, a12, a13], [a[1], a12, a22, a32], [a[2], a13, a23, a33]])
b02 = np.array([[1, mx[0], mx[1], mx[2]], [mx[0], a11, a12, a13], [mx[1], a12, a22, a32], [mx[2], a13, a23, a33]])
b.append(np.linalg.det(b01)/np.linalg.det(b02))
b11 = np.array([[1, my, mx[1], mx[2]], [mx[0], a[0], a12, a13], [mx[1], a[1], a22, a32], [mx[2], a[2], a23, a33]])
b12 = copy.deepcopy(b02)
b.append(np.linalg.det(b11)/np.linalg.det(b12))
b21 = np.array([[1, mx[0], my, mx[2]], [mx[0], a11, a[0], a13], [mx[1], a12, a[1], a32], [mx[2], a13, a[2], a33]])
b22 = copy.deepcopy(b02)
b.append(np.linalg.det(b21)/np.linalg.det(b22))
b31 = np.array([[1, mx[0], mx[1], my], [mx[0], a11, a12, a[0]], [mx[1], a12, a22, a[1]], [mx[2], a13, a23, a[2]]])
b32 = copy.deepcopy(b02)
b.append(np.linalg.det(b31)/np.linalg.det(b32))
for i in range(4):
print("y{} середнє = {:.2f} = {:.2f}".format(i+1, b[0] + b[1]*X[0][i] + b[2]*X[1][i] + b[3]*X[2][i], yav[i]))
print("Рівняння регресії: ŷ = {:.3f} + {:.3f} * X1 + {:.3f} * X2 + {:.3f} * X3".format(b[0], b[1], b[2], b[3]))
print("\nДисперсія по рядкам")
d = [((Y[0][i] - yav[0])**2 + (Y[1][i] - yav[1])**2 + (Y[2][i] - yav[2])**2)/3 for i in range(4)]
print("d1 = {:.2f} d2 = {:.2f} d3 = {:.2f} d4 = {:.2f}".format(*d))
m = 3
Gp = max(d)/sum(d)
f1 = m-1
f2 = N = 4
Gt = 0.7679
print(f"Gp = {Gp}\nGt = {Gt}")
if Gp < Gt:
print("Gp < Gt\nОтже -Дисперсія однорідна-")
else:
print("Дисперсія неоднорідна(збільшемо кількість дослідів)")
m += 1
print("\n____________Критерій Стьюдента__________")
sb = sum(d)/N
ssbs = sb / N * m
sbs = ssbs**0.5
beta = [(yav[0] * Xi[i][0] + yav[1] * Xi[i][1] + yav[2] * Xi[i][2] + yav[3]*Xi[i][3])/4 for i in range(4)]
t = [abs(beta[i])/sbs for i in range(4)]
print("t0 = {:.2f} t1 = {:.2f} t2 = {:.2f} t3 = {:.2f}".format(*t))
f3 = f1*f2
ttabl = 2.306
for i in range(4):
if t[i] < ttabl:
print(f"t{i} < ttabl, b{i} не значимий")
b[i] = 0
yy = [b[0] + b[1]*X[0][i] + b[2]*X[1][i] + b[3]*X[2][i] for i in range(4)]
print("\n___________________________Критерій Фішера__________________________")
d_ = 2
sad = ((yy[0] - yav[0])**2 + (yy[1] - yav[1])**2 + (yy[2] - yav[2])**2 + (yy[3] - yav[3])**2)*(m/(N-d_))
Fp = sad / sb
print("d1 = {:.2f} d2 = {:.2f} d3 = {:.2f} d4 = {:.2f} d5 = {:.2f}".format(*d, sb))
print(f"Fpratk = {Fp:.2f}")
print('Ftabl = 4.5')
Ft = 4.5
if Fp > Ft:
print("Fprakt > Ftabl", "\nРівняння неадекватно оригіналу")
else:
print("Fprakt < Ftabl", "\nРівняння адекватно оригіналу")