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
|
function [V] = test_train()
clear;
more off;
rand('state', 123456);
n = 10;
m = 3;
K = 4;
X = rand(n, m);
Z = [ones(n, 1), X];
set_matrix(Z, "data->Z", "data->m+1");
y = [2 1 3 2 3 2 4 1 3 4];
set_matrix(y, "data->y", "1");
p = 1.2143;
kappa = 0.90298;
lambda = 0.00219038;
epsilon = 1e-15;
rho = ones(n, 1);
seedV = rand(m+1, K-1);
set_matrix(seedV, "seed->V", "data->K-1");
[W, t] = msvmmaj(X, y, rho, p, kappa, lambda, epsilon, 'show', 0, seedV);
V = [t'; W];
fprintf('\n');
assert_matrix(V, "model->V", "model->K-1");
end
function set_matrix(A, name, cols)
for ii=1:size(A, 1)
for jj=1:size(A, 2)
fprintf("matrix_set(%s, %s, %i, %i, %.16f);\n", name, cols, ii-1, jj-1, A(ii, jj));
end
end
fprintf("\n");
end
function assert_matrix(A, name, cols)
for ii=1:size(A, 1)
for jj=1:size(A, 2)
fprintf(["mu_assert(fabs(matrix_get(%s, %s, %i, %i) -\n%.16f) <", ...
" eps,\n\"Incorrect %s at %i, %i\");\n"], name, cols, ...
ii-1, jj-1, A(ii, jj), name, ii-1, jj-1);
end
end
fprintf("\n");
end
|
