/* nag_wav_dim3_coeff_ins (c09fzc) Example Program.
*
* Copyright 2024 Numerical Algorithms Group.
*
* Mark 30.1, 2024.
*/
#include <math.h>
#include <nag.h>
#include <stdio.h>
#define A(I, J, K) a[(K - 1) * lda * sda + (J - 1) * lda + I - 1]
#define AN(I, J, K) an[(K - 1) * lda * sda + (J - 1) * lda + I - 1]
#define B(I, J, K) b[(K - 1) * ldb * sdb + (J - 1) * ldb + I - 1]
#define D(I, J, K) d[(K - 1) * ldd * sdd + (J - 1) * ldd + I - 1]
int main(void) {
/* Scalars */
Integer exit_status = 0;
Integer lstate = 1, lseed = 1;
Integer i, j, k, lda, ldb, ldd, lenc, m, n, fr, mnfr, nf;
Integer nwcn, nwct, nwcfr;
Integer nwl, subid, denoised, cindex, ilev, sda, sdb, sdd, kk;
Nag_BaseRNG genid;
double mse, thresh, var, xmu;
/* Arrays */
char mode[25], wavnam[25];
double *a = 0, *an = 0, *b = 0, *c = 0, *d = 0, *x = 0;
Integer *dwtlvm = 0, *dwtlvn = 0, *dwtlvfr = 0, *state = 0;
Integer icomm[260], seed[1];
/* Nag Types */
Nag_Wavelet wavnamenum;
Nag_WaveletMode modenum;
Nag_MatrixType matrix = Nag_GeneralMatrix;
Nag_OrderType order = Nag_ColMajor;
Nag_DiagType diag = Nag_NonUnitDiag;
NagError fail;
INIT_FAIL(fail);
printf("nag_wav_dim3_coeff_ins (c09fzc) Example Program Results\n\n");
/* Skip heading in data file and read problem parameters. */
scanf("%*[^\n] %" NAG_IFMT "%" NAG_IFMT "%" NAG_IFMT "%*[^\n] ", &m, &n, &fr);
scanf("%24s%24s%*[^\n] ", wavnam, mode);
printf("MLDWT :: Wavelet : %s\n", wavnam);
printf(" End mode : %s\n", mode);
printf(" m : %4" NAG_IFMT "\n", m);
printf(" n : %4" NAG_IFMT "\n", n);
printf(" fr : %4" NAG_IFMT "\n\n", fr);
/* Allocate arrays to hold the original data, A, original data plus noise,
* AN, reconstruction using denoised coefficients, B, and randomly generated
* noise, X.
*/
lda = m;
ldb = m;
sda = n;
sdb = n;
if (!(a = NAG_ALLOC((sda) * (lda) * (fr), double)) ||
!(an = NAG_ALLOC((sda) * (lda) * (fr), double)) ||
!(b = NAG_ALLOC((sdb) * (ldb) * (fr), double)) ||
!(x = NAG_ALLOC((m * n * fr), double))) {
printf("Allocation failure\n");
exit_status = 1;
goto END;
}
/* nag_enum_name_to_value (x04nac).
* Converts NAG enum member name to value.
*/
wavnamenum = (Nag_Wavelet)nag_enum_name_to_value(wavnam);
modenum = (Nag_WaveletMode)nag_enum_name_to_value(mode);
/* Read in the original data. */
for (k = 1; k <= fr; k++) {
for (i = 1; i <= m; i++) {
for (j = 1; j <= n; j++)
scanf("%lf", &A(i, j, k));
scanf("%*[^\n]");
}
scanf("%*[^\n]");
}
/* Output the original data. */
printf("Input data :\n");
fflush(stdout);
for (k = 1; k <= fr; k++) {
nag_file_print_matrix_real_gen_comp(order, matrix, diag, m, n, &A(1, 1, k),
lda, "%11.4e", " ", Nag_NoLabels, 0,
Nag_NoLabels, 0, 80, 0, 0, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen_comp (x04cbc).\n%s\n",
fail.message);
exit_status = 2;
goto END;
}
printf("\n");
fflush(stdout);
}
/* Set up call to nag_rand_dist_normal (g05skc) in order to create some random
* noise from a normal distribution to add to the original data.
* Initial call to RNG initializer to get size of STATE array.
*/
seed[0] = 642521;
genid = Nag_MersenneTwister;
subid = 0;
if (!(state = NAG_ALLOC((lstate), Integer))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* nag_rand_init_repeat (g05kfc).
* Query the size of state.
*/
lstate = 0;
nag_rand_init_repeat(genid, subid, seed, lseed, state, &lstate, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_rand_init_repeat (g05kfc).\n%s\n", fail.message);
exit_status = 3;
goto END;
}
/* Reallocate STATE. */
NAG_FREE(state);
if (!(state = NAG_ALLOC((lstate), Integer))) {
printf("Allocation failure\n");
exit_status = 4;
goto END;
}
/* nag_rand_init_repeat (g05kfc).
* Initialize the generator to a repeatable sequence.
*/
nag_rand_init_repeat(genid, subid, seed, lseed, state, &lstate, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_rand_init_repeat (g05kfc).\n%s\n", fail.message);
exit_status = 5;
goto END;
}
/* Set the distribution parameters for the random noise. */
xmu = 0.0;
var = 0.1E-3;
/* Generate the noise variates. */
/* nag_rand_dist_normal (g05skc).
* Generates a vector of pseudorandom numbers from a Normal distribution.
*/
mnfr = n * m * fr;
nag_rand_dist_normal(mnfr, xmu, var, state, x, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_rand_dist_normal (g05skc).\n%s\n", fail.message);
exit_status = 6;
goto END;
}
/* Add the noise to the original input and save in AN */
kk = 0;
for (k = 1; k <= n; k++) {
for (j = 1; j <= n; j++) {
for (i = 1; i <= m; i++) {
AN(i, j, k) = A(i, j, k) + x[kk];
kk = kk + 1;
}
}
}
/* Output the noisy data */
printf("Input data plus noise :\n");
fflush(stdout);
for (k = 1; k <= fr; k++) {
nag_file_print_matrix_real_gen_comp(order, matrix, diag, m, n, &AN(1, 1, k),
lda, "%11.4e", " ", Nag_NoLabels, 0,
Nag_NoLabels, 0, 80, 0, 0, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen_comp (x04cbc).\n%s\n",
fail.message);
exit_status = 7;
goto END;
}
printf("\n");
fflush(stdout);
}
/* nag_wav_dim3_init (c09acc).
* Three-dimensional wavelet filter initialization.
*/
nag_wav_dim3_init(wavnamenum, Nag_MultiLevel, modenum, m, n, fr, &nwl, &nf,
&nwct, &nwcn, &nwcfr, icomm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_init (c09acc).\n%s\n", fail.message);
exit_status = 8;
goto END;
}
/* Allocate arrays to hold the coefficients, c, and the dimensions
* of the coefficients at each level, dwtlvm, dwtlvn.
*/
lenc = nwct;
if (!(c = NAG_ALLOC((lenc), double)) ||
!(dwtlvm = NAG_ALLOC((nwl), Integer)) ||
!(dwtlvn = NAG_ALLOC((nwl), Integer)) ||
!(dwtlvfr = NAG_ALLOC((nwl), Integer))) {
printf("Allocation failure\n");
exit_status = 9;
goto END;
}
/* Perform a forwards multi-level transform on the noisy data. */
/* nag_wav_dim3_multi_fwd (c09fcc).
* Two-dimensional multi-level discrete wavelet transform.
*/
nag_wav_dim3_multi_fwd(m, n, fr, an, lda, sda, lenc, c, nwl, dwtlvm, dwtlvn,
dwtlvfr, icomm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_multi_fwd (c09fcc).\n%s\n", fail.message);
exit_status = 10;
goto END;
}
/* Reconstruct without thresholding of detail coefficients. */
/* nag_wav_dim3_mxolap_multi_inv (c09fdc).
* Two-dimensional inverse multi-level discrete wavelet transform.
*/
nag_wav_dim3_mxolap_multi_inv(nwl, lenc, c, m, n, fr, b, ldb, sdb, icomm,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_mxolap_multi_inv (c09fdc).\n%s\n",
fail.message);
exit_status = 11;
goto END;
}
/* Calculate the Mean Square Error of the noisy reconstruction. */
mse = 0.0;
for (k = 1; k <= fr; k++)
for (j = 1; j <= n; j++)
for (i = 1; i <= m; i++)
mse = mse + pow((A(i, j, k) - B(i, j, k)), 2);
mse = mse / (double)(m * n * fr);
printf("Without denoising Mean Square Error is %11.4e\n\n", mse);
/* Now perform the denoising by extracting each of the detail
* coefficients at each level and applying hard thresholding
* Allocate a 2D array to hold the detail coefficients
*/
ldd = dwtlvm[nwl - 1];
sdd = dwtlvn[nwl - 1];
if (!(d = NAG_ALLOC((ldd) * (sdd) * (dwtlvfr[nwl - 1]), double))) {
printf("Allocation failure\n");
exit_status = 12;
goto END;
}
/* Calculate the threshold based on VisuShrink denoising. */
thresh = sqrt(var) * sqrt(2. * log((double)(m * n * fr)));
denoised = 0;
/* For each level */
for (ilev = nwl; ilev >= 1; ilev -= 1) {
/* Select detail coefficients */
for (cindex = 1; cindex <= 7; cindex++) {
/* Extract coefficients into the 2D array d */
/* nag_wav_dim3_coeff_ext (c09fyc).
* Three-dimensional discrete wavelet transform coefficient extraction.
*/
nag_wav_dim3_coeff_ext(ilev, cindex, lenc, c, d, ldd, sdd, icomm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_coeff_ext (c09fyc).\n%s\n",
fail.message);
exit_status = 13;
goto END;
}
/* Perform the hard thresholding operation */
for (k = 1; k <= dwtlvfr[nwl - ilev]; k++)
for (j = 1; j <= dwtlvn[nwl - ilev]; j++)
for (i = 1; i <= dwtlvm[nwl - ilev]; i++)
if (fabs(D(i, j, k)) < thresh) {
D(i, j, k) = 0.0;
denoised = denoised + 1;
}
/* Insert the denoised coefficients back into c. */
/* nag_wav_dim3_coeff_ins (c09fzc).
* Three-dimensional discrete wavelet transform coefficient insertion.
*/
nag_wav_dim3_coeff_ins(ilev, cindex, lenc, c, d, ldd, sdd, icomm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_coeff_ins (c09fzc).\n%s\n",
fail.message);
exit_status = 14;
goto END;
}
}
}
/* Output the number of coefficients that were set to zero */
printf("Number of coefficients denoised is %4" NAG_IFMT " out of %4" NAG_IFMT
"\n\n",
denoised, nwct - dwtlvm[0] * dwtlvn[0] * dwtlvfr[0]);
fflush(stdout);
/* Reconstruct original data following thresholding of detail coefficients */
/* nag_wav_dim3_mxolap_multi_inv (c09fdc).
* Three-dimensional inverse multi-level discrete wavelet transform.
*/
nag_wav_dim3_mxolap_multi_inv(nwl, lenc, c, m, n, fr, b, ldb, sdb, icomm,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_wav_dim3_mxolap_multi_inv (c09fdc).\n%s\n",
fail.message);
exit_status = 15;
goto END;
}
/* Calculate the Mean Square Error of the denoised reconstruction. */
mse = 0.0;
for (k = 1; k <= n; k++)
for (j = 1; j <= n; j++)
for (i = 1; i <= m; i++)
mse = mse + pow((A(i, j, k) - B(i, j, k)), 2);
mse = mse / (double)(m * n * fr);
printf("With denoising Mean Square Error is %11.4e \n\n", mse);
/* Output the denoised reconstruction. */
printf("Reconstruction of denoised input :\n");
fflush(stdout);
for (k = 1; k <= fr; k++) {
nag_file_print_matrix_real_gen_comp(order, matrix, diag, m, n, &B(1, 1, k),
ldb, "%11.4e", " ", Nag_NoLabels, 0,
Nag_NoLabels, 0, 80, 0, 0, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen_comp (x04cbc).\n%s\n",
fail.message);
exit_status = 16;
goto END;
}
if (k < fr)
printf("\n");
fflush(stdout);
}
END:
NAG_FREE(a);
NAG_FREE(an);
NAG_FREE(b);
NAG_FREE(c);
NAG_FREE(d);
NAG_FREE(x);
NAG_FREE(dwtlvm);
NAG_FREE(dwtlvn);
NAG_FREE(dwtlvfr);
NAG_FREE(state);
return exit_status;
}