/**
* ICA function. Computes the W matrix from the
* preprocessed data.
*/
static mat ICA_compute(mat X, int rows, int cols)
{
mat TXp, GWX, W, Wd, W1, D, TU, TMP;
vect d, lim;
int i, it;
// matrix creation
TXp = mat_create(cols, rows);
GWX = mat_create(rows, cols);
W = mat_create(rows, rows);
Wd = mat_create(rows, rows);
D = mat_create(rows, rows);
TMP = mat_create(rows, rows);
TU = mat_create(rows, rows);
W1 = mat_create(rows, rows);
d = vect_create(rows);
// W rand init
mat_apply_fx(W, rows, rows, fx_rand, 0);
// sW <- La.svd(W)
mat_copy(W, rows, rows, Wd);
svdcmp(Wd, rows, rows, d, D);
// W <- sW$u %*% diag(1/sW$d) %*% t(sW$u) %*% W
mat_transpose(Wd, rows, rows, TU);
vect_apply_fx(d, rows, fx_inv, 0);
mat_diag(d, rows, D);
mat_mult(Wd, rows, rows, D, rows, rows, TMP);
mat_mult(TMP, rows, rows, TU, rows, rows, D);
mat_mult(D, rows, rows, W, rows, rows, Wd); // W = Wd
// W1 <- W
mat_copy(Wd, rows, rows, W1);
// lim <- rep(1000, maxit); it = 1
lim = vect_create(MAX_ITERATIONS);
for (i=0; i<MAX_ITERATIONS; i++)
lim[i] = 1000;
it = 0;
// t(X)/p
mat_transpose(X, rows, cols, TXp);
mat_apply_fx(TXp, cols, rows, fx_div_c, cols);
while (lim[it] > TOLERANCE && it < MAX_ITERATIONS) {
// wx <- W %*% X
mat_mult(Wd, rows, rows, X, rows, cols, GWX);
// gwx <- tanh(alpha * wx)
mat_apply_fx(GWX, rows, cols, fx_tanh, 0);
// v1 <- gwx %*% t(X)/p
mat_mult(GWX, rows, cols, TXp, cols, rows, TMP); // V1 = TMP
// g.wx <- alpha * (1 - (gwx)^2)
mat_apply_fx(GWX, rows, cols, fx_1sub_sqr, 0);
// v2 <- diag(apply(g.wx, 1, FUN = mean)) %*% W
mat_mean_rows(GWX, rows, cols, d);
mat_diag(d, rows, D);
mat_mult(D, rows, rows, Wd, rows, rows, TU); // V2 = TU
// W1 <- v1 - v2
mat_sub(TMP, TU, rows, rows, W1);
// sW1 <- La.svd(W1)
mat_copy(W1, rows, rows, W);
svdcmp(W, rows, rows, d, D);
// W1 <- sW1$u %*% diag(1/sW1$d) %*% t(sW1$u) %*% W1
mat_transpose(W, rows, rows, TU);
vect_apply_fx(d, rows, fx_inv, 0);
mat_diag(d, rows, D);
mat_mult(W, rows, rows, D, rows, rows, TMP);
mat_mult(TMP, rows, rows, TU, rows, rows, D);
mat_mult(D, rows, rows, W1, rows, rows, W); // W1 = W
// lim[it + 1] <- max(Mod(Mod(diag(W1 %*% t(W))) - 1))
mat_transpose(Wd, rows, rows, TU);
mat_mult(W, rows, rows, TU, rows, rows, TMP);
lim[it+1] = fabs(mat_max_diag(TMP, rows, rows) - 1);
// W <- W1
mat_copy(W, rows, rows, Wd);
it++;
}
// clean up
mat_delete(TXp, cols, rows);
mat_delete(GWX, rows, cols);
mat_delete(W, rows, rows);
mat_delete(D, rows, rows);
mat_delete(TMP, rows, rows);
mat_delete(TU, rows, rows);
mat_delete(W1, rows, rows);
vect_delete(d);
return Wd;
}
/**
* ICA function. Computes the W matrix from the
* preprocessed data.
*/
static mat ICA_compute(mat X, int rows, int cols) {
mat TXp, GWX, W, Wd, W1, D, TU, TMP;
vect d, lim;
int i, it;
FILE *OutputFile;
clock_t clock1, clock2;
float time;
//char ascii_path[512];
//strcpy(ascii_path, "/storage/sdcard0/NickGun/EEG/Log.txt");
//FILE *Log;
// matrix creation
TXp = mat_create(cols, rows);
GWX = mat_create(rows, cols);
W = mat_create(rows, rows);
Wd = mat_create(rows, rows);
D = mat_create(rows, rows);
TMP = mat_create(rows, rows);
TU = mat_create(rows, rows);
W1 = mat_create(rows, rows);
d = vect_create(rows);
// W rand init
mat_apply_fx(W, rows, rows, fx_rand, 0);
// sW <- La.svd(W)
mat_copy(W, rows, rows, Wd);
svdcmp(Wd, rows, rows, d, D);
// W <- sW$u %*% diag(1/sW$d) %*% t(sW$u) %*% W
mat_transpose(Wd, rows, rows, TU);
vect_apply_fx(d, rows, fx_inv, 0);
mat_diag(d, rows, D);
mat_mult(Wd, rows, rows, D, rows, rows, TMP);
mat_mult(TMP, rows, rows, TU, rows, rows, D);
mat_mult(D, rows, rows, W, rows, rows, Wd); // W = Wd
// W1 <- W
mat_copy(Wd, rows, rows, W1);
// lim <- rep(1000, maxit); it = 1
lim = vect_create(MAX_ITERATIONS);
for (i = 0; i < MAX_ITERATIONS; i++)
lim[i] = 1000;
it = 0;
// t(X)/p
mat_transpose(X, rows, cols, TXp);
mat_apply_fx(TXp, cols, rows, fx_div_c, cols);
while (lim[it] > TOLERANCE && it < MAX_ITERATIONS) {
// wx <- W %*% X
mat_mult(Wd, rows, rows, X, rows, cols, GWX);
// gwx <- tanh(alpha * wx)
mat_apply_fx(GWX, rows, cols, fx_tanh, 0);
// v1 <- gwx %*% t(X)/p
mat_mult(GWX, rows, cols, TXp, cols, rows, TMP); // V1 = TMP
// g.wx <- alpha * (1 - (gwx)^2)
mat_apply_fx(GWX, rows, cols, fx_1sub_sqr, 0);
// v2 <- diag(apply(g.wx, 1, FUN = mean)) %*% W
mat_mean_rows(GWX, rows, cols, d);
mat_diag(d, rows, D);
mat_mult(D, rows, rows, Wd, rows, rows, TU); // V2 = TU
// W1 <- v1 - v2
mat_sub(TMP, TU, rows, rows, W1);
// sW1 <- La.svd(W1)
mat_copy(W1, rows, rows, W);
svdcmp(W, rows, rows, d, D);
// W1 <- sW1$u %*% diag(1/sW1$d) %*% t(sW1$u) %*% W1
mat_transpose(W, rows, rows, TU);
vect_apply_fx(d, rows, fx_inv, 0);
mat_diag(d, rows, D);
mat_mult(W, rows, rows, D, rows, rows, TMP);
mat_mult(TMP, rows, rows, TU, rows, rows, D);
mat_mult(D, rows, rows, W1, rows, rows, W); // W1 = W
// lim[it + 1] <- max(Mod(Mod(diag(W1 %*% t(W))) - 1))
mat_transpose(Wd, rows, rows, TU); //chuyen vi
mat_mult(W, rows, rows, TU, rows, rows, TMP); //TMP=WxTU
lim[it + 1] = fabs(mat_max_diag(TMP, rows, rows) - 1);
if(lim[it+1]<0.1)
break;
/*
OutputFile = fopen("/storage/sdcard0/Nickgun/EEG/data/lim",
"at");
fprintf(OutputFile, "%f \n", lim[it+1]);
fclose(OutputFile);
// W <- W1
*/
mat_copy(W, rows, rows, Wd);
it++;
}
// clean up
mat_delete(TXp, cols, rows);
mat_delete(GWX, rows, cols);
mat_delete(W, rows, rows);
mat_delete(D, rows, rows);
mat_delete(TMP, rows, rows);
mat_delete(TU, rows, rows);
mat_delete(W1, rows, rows);
vect_delete(d);
return Wd;
}
