int main_estdelay(int argc, char* argv[])
{
bool ring = false;
int pad_factor = 100;
unsigned int no_intersec_sp = 1;
float size = 1.5;
const struct opt_s opts[] = {
OPT_SET('R', &ring, "RING method"),
OPT_INT('p', &pad_factor, "p", "[RING] Padding"),
OPT_UINT('n', &no_intersec_sp, "n", "[RING] Number of intersecting spokes"),
OPT_FLOAT('r', &size, "r", "[RING] Central region size"),
};
cmdline(&argc, argv, 2, 2, usage_str, help_str, ARRAY_SIZE(opts), opts);
num_init();
if (pad_factor % 2 != 0)
error("Pad_factor -p should be even\n");
long tdims[DIMS];
const complex float* traj = load_cfl(argv[1], DIMS, tdims);
long tdims1[DIMS];
md_select_dims(DIMS, ~MD_BIT(1), tdims1, tdims);
complex float* traj1 = md_alloc(DIMS, tdims1, CFL_SIZE);
md_slice(DIMS, MD_BIT(1), (long[DIMS]){ 0 }, tdims, traj1, traj, CFL_SIZE);
int main_bpsense(int argc, char* argv[])
{
// -----------------------------------------------------------
// set up conf and option parser
struct bpsense_conf conf = bpsense_defaults;
struct iter_admm_conf iconf = iter_admm_defaults;
conf.iconf = &iconf;
conf.iconf->rho = 10; // more sensibile default
bool usegpu = false;
const char* psf = NULL;
const char* image_truth_fname = NULL;
bool im_truth = false;
bool use_tvnorm = false;
double start_time = timestamp();
const struct opt_s opts[] = {
OPT_FLOAT('e', &conf.eps, "eps", "data consistency error"),
OPT_FLOAT('r', &conf.lambda, "lambda", "l2 regularization parameter"),
OPT_FLOAT('u', &conf.iconf->rho, "rho", "ADMM penalty parameter"),
OPT_SET('c', &conf.rvc, "real-value constraint"),
OPT_SET('t', &use_tvnorm, "use TV norm"),
OPT_STRING('T', &image_truth_fname, "file", "compare to truth image"),
OPT_UINT('i', &conf.iconf->maxiter, "iter", "max. iterations"),
OPT_SET('g', &usegpu, "(use gpu)"),
OPT_STRING('p', &psf, "file", "point-spread function"),
};
cmdline(&argc, argv, 3, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
if (NULL != image_truth_fname)
im_truth = true;
// -----------------------------------------------------------
// load data and print some info about the recon
int N = DIMS;
long dims[N];
long dims1[N];
long img_dims[N];
long ksp_dims[N];
complex float* kspace_data = load_cfl(argv[1], N, ksp_dims);
complex float* sens_maps = load_cfl(argv[2], N, dims);
for (int i = 0; i < 4; i++) // sizes2[4] may be > 1
if (ksp_dims[i] != dims[i])
error("Dimensions of kspace and sensitivities do not match!\n");
assert(1 == ksp_dims[MAPS_DIM]);
(usegpu ? num_init_gpu : num_init)();
if (dims[MAPS_DIM] > 1)
debug_printf(DP_INFO, "%ld maps.\nESPIRiT reconstruction.\n", dims[4]);
if (conf.lambda > 0.)
debug_printf(DP_INFO, "l2 regularization: %f\n", conf.lambda);
if (use_tvnorm)
debug_printf(DP_INFO, "use Total Variation\n");
else
debug_printf(DP_INFO, "use Wavelets\n");
if (im_truth)
debug_printf(DP_INFO, "Compare to truth\n");
md_select_dims(N, ~(COIL_FLAG | MAPS_FLAG), dims1, dims);
md_select_dims(N, ~COIL_FLAG, img_dims, dims);
// -----------------------------------------------------------
// initialize sampling pattern
complex float* pattern = NULL;
long pat_dims[N];
if (NULL != psf) {
pattern = load_cfl(psf, N, pat_dims);
// FIXME: check compatibility
} else {
pattern = md_alloc(N, dims1, CFL_SIZE);
estimate_pattern(N, ksp_dims, COIL_DIM, pattern, kspace_data);
}
// -----------------------------------------------------------
// print some statistics
size_t T = md_calc_size(N, dims1);
long samples = (long)pow(md_znorm(N, dims1, pattern), 2.);
debug_printf(DP_INFO, "Size: %ld Samples: %ld Acc: %.2f\n", T, samples, (float)T/(float)samples);
// -----------------------------------------------------------
// fftmod to un-center data
fftmod(N, ksp_dims, FFT_FLAGS, kspace_data, kspace_data);
fftmod(N, dims, FFT_FLAGS, sens_maps, sens_maps);
// -----------------------------------------------------------
// apply scaling
float scaling = estimate_scaling(ksp_dims, NULL, kspace_data);
debug_printf(DP_INFO, "Scaling: %f\n", scaling);
if (scaling != 0.)
md_zsmul(N, ksp_dims, kspace_data, kspace_data, 1. / scaling);
// -----------------------------------------------------------
// create l1 prox operator and transform
long minsize[DIMS] = { [0 ... DIMS - 1] = 1 };
minsize[0] = MIN(img_dims[0], 16);
minsize[1] = MIN(img_dims[1], 16);
minsize[2] = MIN(img_dims[2], 16);
const struct linop_s* l1op = NULL;
const struct operator_p_s* l1prox = NULL;
if (use_tvnorm) {
l1op = grad_init(DIMS, img_dims, FFT_FLAGS);
l1prox = prox_thresh_create(DIMS + 1, linop_codomain(l1op)->dims, 1., 0u, usegpu);
conf.l1op_obj = l1op;
} else {
bool randshift = true;
l1op = linop_identity_create(DIMS, img_dims);
conf.l1op_obj = wavelet_create(DIMS, img_dims, FFT_FLAGS, minsize, false, usegpu);
l1prox = prox_wavethresh_create(DIMS, img_dims, FFT_FLAGS, minsize, 1., randshift, usegpu);
}
// -----------------------------------------------------------
// create image and load truth image
complex float* image = create_cfl(argv[3], N, img_dims);
md_clear(N, img_dims, image, CFL_SIZE);
long img_truth_dims[DIMS];
complex float* image_truth = NULL;
if (im_truth)
image_truth = load_cfl(image_truth_fname, DIMS, img_truth_dims);
// -----------------------------------------------------------
// call recon
if (usegpu)
#ifdef USE_CUDA
bpsense_recon_gpu(&conf, dims, image, sens_maps, dims1, pattern, l1op, l1prox, ksp_dims, kspace_data, image_truth);
#else
assert(0);
#endif
else
int main_poisson(int argc, char* argv[])
{
int yy = 128;
int zz = 128;
bool cutcorners = false;
float vardensity = 0.;
bool vd_def = false;
int T = 1;
int rnd = 0;
bool msk = true;
int points = -1;
float mindist = 1. / 1.275;
float yscale = 1.;
float zscale = 1.;
unsigned int calreg = 0;
const struct opt_s opts[] = {
OPT_INT('Y', &yy, "size", "size dimension 1"),
OPT_INT('Z', &zz, "size", "size dimension 2"),
OPT_FLOAT('y', &yscale, "acc", "acceleration dim 1"),
OPT_FLOAT('z', &zscale, "acc", "acceleration dim 2"),
OPT_UINT('C', &calreg, "size", "size of calibration region"),
OPT_SET('v', &vd_def, "variable density"),
OPT_FLOAT('V', &vardensity, "", "(variable density)"),
OPT_SET('e', &cutcorners, "elliptical scanning"),
OPT_FLOAT('D', &mindist, "", "()"),
OPT_INT('T', &T, "", "()"),
OPT_CLEAR('m', &msk, "()"),
OPT_INT('R', &points, "", "()"),
};
cmdline(&argc, argv, 1, 1, usage_str, help_str, ARRAY_SIZE(opts), opts);
if (vd_def && (0. == vardensity))
vardensity = 20.;
if (-1 != points)
rnd = 1;
assert((yscale >= 1.) && (zscale >= 1.));
// compute mindest and scaling
float kspext = MAX(yy, zz);
int Pest = T * (int)(1.2 * powf(kspext, 2.) / (yscale * zscale));
mindist /= kspext;
yscale *= (float)kspext / (float)yy;
zscale *= (float)kspext / (float)zz;
if (vardensity != 0.) {
// TODO
}
long dims[5] = { 1, yy, zz, T, 1 };
complex float* mask = NULL;
if (msk) {
mask = create_cfl(argv[1], 5, dims);
md_clear(5, dims, mask, sizeof(complex float));
}
int M = rnd ? (points + 1) : Pest;
int P;
while (true) {
float (*points)[2] = xmalloc(M * sizeof(float[3]));
int* kind = xmalloc(M * sizeof(int));
kind[0] = 0;
if (!rnd) {
points[0][0] = 0.5;
points[0][1] = 0.5;
if (1 == T) {
P = poissondisc(2, M, 1, vardensity, mindist, points);
} else {
float (*delta)[T] = xmalloc(T * T * sizeof(complex float));
float dd[T];
for (int i = 0; i < T; i++)
dd[i] = mindist;
mc_poisson_rmatrix(2, T, delta, dd);
P = poissondisc_mc(2, T, M, 1, vardensity, (const float (*)[T])delta, points, kind);
}
} else { // random pattern
P = M - 1;
for (int i = 0; i < P; i++)
random_point(2, points[i]);
}
if (P < M) {
for (int i = 0; i < P; i++) {
points[i][0] = (points[i][0] - 0.5) * yscale + 0.5;
points[i][1] = (points[i][1] - 0.5) * zscale + 0.5;
}
// throw away points outside
float center[2] = { 0.5, 0.5 };
int j = 0;
for (int i = 0; i < P; i++) {
if ((cutcorners ? dist : maxn)(2, center, points[i]) <= 0.5) {
points[j][0] = points[i][0];
points[j][1] = points[i][1];
j++;
}
}
P = j;
if (msk) {
// rethink module here
for (int i = 0; i < P; i++) {
int yy = (int)floorf(points[i][0] * dims[1]);
int zz = (int)floorf(points[i][1] * dims[2]);
if ((yy < 0) || (yy >= dims[1]) || (zz < 0) || (zz >= dims[2]))
continue;
if (1 == T)
mask[zz * dims[1] + yy] = 1.;//cexpf(2.i * M_PI * (float)kind[i] / (float)T);
else
mask[(kind[i] * dims[2] + zz) * dims[1] + yy] = 1.;//cexpf(2.i * M_PI * (float)kind[i] / (float)T);
}
} else {
#if 1
long sdims[2] = { 3, P };
complex float* samples = create_cfl(argv[1], 2, sdims);
for (int i = 0; i < P; i++) {
samples[3 * i + 0] = 0.;
samples[3 * i + 1] = (points[i][0] - 0.5) * dims[1];
samples[3 * i + 2] = (points[i][1] - 0.5) * dims[2];
// printf("%f %f\n", creal(samples[3 * i + 0]), creal(samples[3 * i + 1]));
}
unmap_cfl(2, sdims, (void*)samples);
#endif
}
break;
}
// repeat with more points
M *= 2;
free(points);
free(kind);
}
// calibration region
assert((mask != NULL) || (0 == calreg));
assert((calreg <= dims[1]) && (calreg <= dims[2]));
for (unsigned int i = 0; i < calreg; i++) {
for (unsigned int j = 0; j < calreg; j++) {
int y = (dims[1] - calreg) / 2 + i;
int z = (dims[2] - calreg) / 2 + j;
for (int k = 0; k < T; k++) {
if (0. == mask[(k * dims[2] + z) * dims[1] + y]) {
mask[(k * dims[2] + z) * dims[1] + y] = 1.;
P++;
}
}
}
}
printf("points: %d", P);
if (1 != T)
printf(", classes: %d", T);
if (NULL != mask) {
float f = cutcorners ? (M_PI / 4.) : 1.;
printf(", grid size: %ldx%ld%s = %ld (R = %f)", dims[1], dims[2], cutcorners ? "x(pi/4)" : "",
(long)(f * dims[1] * dims[2]), f * T * dims[1] * dims[2] / (float)P);
unmap_cfl(5, dims, (void*)mask);
}
printf("\n");
exit(0);
}
int main_pics(int argc, char* argv[])
{
// Initialize default parameters
struct sense_conf conf = sense_defaults;
bool use_gpu = false;
bool randshift = true;
unsigned int maxiter = 30;
float step = -1.;
// Start time count
double start_time = timestamp();
// Read input options
struct nufft_conf_s nuconf = nufft_conf_defaults;
nuconf.toeplitz = false;
float restrict_fov = -1.;
const char* pat_file = NULL;
const char* traj_file = NULL;
bool scale_im = false;
bool eigen = false;
float scaling = 0.;
unsigned int llr_blk = 8;
const char* image_truth_file = NULL;
bool im_truth = false;
const char* image_start_file = NULL;
bool warm_start = false;
bool hogwild = false;
bool fast = false;
float admm_rho = iter_admm_defaults.rho;
unsigned int admm_maxitercg = iter_admm_defaults.maxitercg;
struct opt_reg_s ropts;
ropts.r = 0;
ropts.algo = CG;
ropts.lambda = -1.;
const struct opt_s opts[] = {
{ 'l', true, opt_reg, &ropts, "1/-l2\t\ttoggle l1-wavelet or l2 regularization." },
OPT_FLOAT('r', &ropts.lambda, "lambda", "regularization parameter"),
{ 'R', true, opt_reg, &ropts, " <T>:A:B:C\tgeneralized regularization options (-Rh for help)" },
OPT_SET('c', &conf.rvc, "real-value constraint"),
OPT_FLOAT('s', &step, "step", "iteration stepsize"),
OPT_UINT('i', &maxiter, "iter", "max. number of iterations"),
OPT_STRING('t', &traj_file, "file", "k-space trajectory"),
OPT_CLEAR('n', &randshift, "disable random wavelet cycle spinning"),
OPT_SET('g', &use_gpu, "use GPU"),
OPT_STRING('p', &pat_file, "file", "pattern or weights"),
OPT_SELECT('I', enum algo_t, &ropts.algo, IST, "(select IST)"),
OPT_UINT('b', &llr_blk, "blk", "Lowrank block size"),
OPT_SET('e', &eigen, "Scale stepsize based on max. eigenvalue"),
OPT_SET('H', &hogwild, "(hogwild)"),
OPT_SET('F', &fast, "(fast)"),
OPT_STRING('T', &image_truth_file, "file", "(truth file)"),
OPT_STRING('W', &image_start_file, "<img>", "Warm start with <img>"),
OPT_INT('d', &debug_level, "level", "Debug level"),
OPT_INT('O', &conf.rwiter, "rwiter", "(reweighting)"),
OPT_FLOAT('o', &conf.gamma, "gamma", "(reweighting)"),
OPT_FLOAT('u', &admm_rho, "rho", "ADMM rho"),
OPT_UINT('C', &admm_maxitercg, "iter", "ADMM max. CG iterations"),
OPT_FLOAT('q', &conf.cclambda, "cclambda", "(cclambda)"),
OPT_FLOAT('f', &restrict_fov, "rfov", "restrict FOV"),
OPT_SELECT('m', enum algo_t, &ropts.algo, ADMM, "Select ADMM"),
OPT_FLOAT('w', &scaling, "val", "scaling"),
OPT_SET('S', &scale_im, "Re-scale the image after reconstruction"),
};
cmdline(&argc, argv, 3, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
if (NULL != image_truth_file)
im_truth = true;
if (NULL != image_start_file)
warm_start = true;
long max_dims[DIMS];
long map_dims[DIMS];
long pat_dims[DIMS];
long img_dims[DIMS];
long coilim_dims[DIMS];
long ksp_dims[DIMS];
long traj_dims[DIMS];
// load kspace and maps and get dimensions
complex float* kspace = load_cfl(argv[1], DIMS, ksp_dims);
complex float* maps = load_cfl(argv[2], DIMS, map_dims);
complex float* traj = NULL;
if (NULL != traj_file)
traj = load_cfl(traj_file, DIMS, traj_dims);
md_copy_dims(DIMS, max_dims, ksp_dims);
md_copy_dims(5, max_dims, map_dims);
md_select_dims(DIMS, ~COIL_FLAG, img_dims, max_dims);
md_select_dims(DIMS, ~MAPS_FLAG, coilim_dims, max_dims);
if (!md_check_compat(DIMS, ~(MD_BIT(MAPS_DIM)|FFT_FLAGS), img_dims, map_dims))
error("Dimensions of image and sensitivities do not match!\n");
assert(1 == ksp_dims[MAPS_DIM]);
(use_gpu ? num_init_gpu : num_init)();
// print options
if (use_gpu)
debug_printf(DP_INFO, "GPU reconstruction\n");
if (map_dims[MAPS_DIM] > 1)
debug_printf(DP_INFO, "%ld maps.\nESPIRiT reconstruction.\n", map_dims[MAPS_DIM]);
if (hogwild)
debug_printf(DP_INFO, "Hogwild stepsize\n");
if (im_truth)
debug_printf(DP_INFO, "Compare to truth\n");
// initialize sampling pattern
complex float* pattern = NULL;
if (NULL != pat_file) {
pattern = load_cfl(pat_file, DIMS, pat_dims);
assert(md_check_compat(DIMS, COIL_FLAG, ksp_dims, pat_dims));
} else {
md_select_dims(DIMS, ~COIL_FLAG, pat_dims, ksp_dims);
pattern = md_alloc(DIMS, pat_dims, CFL_SIZE);
estimate_pattern(DIMS, ksp_dims, COIL_DIM, pattern, kspace);
}
if ((NULL != traj_file) && (NULL == pat_file)) {
md_free(pattern);
pattern = NULL;
nuconf.toeplitz = true;
} else {
// print some statistics
long T = md_calc_size(DIMS, pat_dims);
long samples = (long)pow(md_znorm(DIMS, pat_dims, pattern), 2.);
debug_printf(DP_INFO, "Size: %ld Samples: %ld Acc: %.2f\n", T, samples, (float)T / (float)samples);
}
if (NULL == traj_file) {
fftmod(DIMS, ksp_dims, FFT_FLAGS, kspace, kspace);
fftmod(DIMS, map_dims, FFT_FLAGS, maps, maps);
}
// apply fov mask to sensitivities
if (-1. != restrict_fov) {
float restrict_dims[DIMS] = { [0 ... DIMS - 1] = 1. };
restrict_dims[0] = restrict_fov;
restrict_dims[1] = restrict_fov;
restrict_dims[2] = restrict_fov;
apply_mask(DIMS, map_dims, maps, restrict_dims);
}
int main_ecalib(int argc, char* argv[])
{
long calsize[3] = { 24, 24, 24 };
int maps = 2;
bool one = false;
bool calcen = false;
bool print_svals = false;
struct ecalib_conf conf = ecalib_defaults;
const struct opt_s opts[] = {
OPT_FLOAT('t', &conf.threshold, "threshold", "This determined the size of the null-space."),
OPT_FLOAT('c', &conf.crop, "crop_value", "Crop the sensitivities if the eigenvalue is smaller than {crop_value}."),
OPT_VEC3('k', &conf.kdims, "ksize", "kernel size"),
OPT_VEC3('K', &conf.kdims, "", "()"),
OPT_VEC3('r', &calsize, "cal_size", "Limits the size of the calibration region."),
OPT_VEC3('R', &calsize, "", "()"),
OPT_INT('m', &maps, "maps", "Number of maps to compute."),
OPT_SET('S', &conf.softcrop, "create maps with smooth transitions (Soft-SENSE)."),
OPT_SET('W', &conf.weighting, "soft-weighting of the singular vectors."),
OPT_SET('I', &conf.intensity, "intensity correction"),
OPT_SET('1', &one, "perform only first part of the calibration"),
OPT_CLEAR('P', &conf.rotphase, "Do not rotate the phase with respect to the first principal component"),
OPT_CLEAR('O', &conf.orthiter, "()"),
OPT_FLOAT('b', &conf.perturb, "", "()"),
OPT_SET('V', &print_svals, "()"),
OPT_SET('C', &calcen, "()"),
OPT_SET('g', &conf.usegpu, "()"),
OPT_FLOAT('p', &conf.percentsv, "", "()"),
OPT_INT('n', &conf.numsv, "", "()"),
OPT_FLOAT('v', &conf.var, "variance", "Variance of noise in data."),
OPT_SET('a', &conf.automate, "Automatically pick thresholds."),
OPT_INT('d', &debug_level, "level", "Debug level"),
};
cmdline(&argc, argv, 2, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
if (-1. != conf.percentsv)
conf.threshold = -1.;
if (-1 != conf.numsv)
conf.threshold = -1.;
if (conf.automate) {
conf.crop = -1.;
conf.weighting = true;
}
if (conf.weighting) {
conf.numsv = -1.;
conf.threshold = 0;
conf.percentsv = -1.;
conf.orthiter = false;
}
int N = DIMS;
long ksp_dims[N];
complex float* in_data = load_cfl(argv[1], N, ksp_dims);
// assert((kdims[0] < calsize_ro) && (kdims[1] < calsize_ro) && (kdims[2] < calsize_ro));
// assert((ksp_dims[0] == 1) || (calsize_ro < ksp_dims[0]));
if (1 != ksp_dims[MAPS_DIM])
error("MAPS dimension is not of size one.\n");
long cal_dims[N];
complex float* cal_data = NULL;
if (!calcen) {
#ifdef USE_CC_EXTRACT_CALIB
cal_data = cc_extract_calib(cal_dims, calsize, ksp_dims, in_data);
#else
cal_data = extract_calib(cal_dims, calsize, ksp_dims, in_data, false);
#endif
} else {
for (int i = 0; i < 3; i++)
cal_dims[i] = (calsize[i] < ksp_dims[i]) ? calsize[i] : ksp_dims[i];
for (int i = 3; i < N; i++)
cal_dims[i] = ksp_dims[i];
cal_data = md_alloc(5, cal_dims, CFL_SIZE);
md_resize_center(5, cal_dims, cal_data, ksp_dims, in_data, CFL_SIZE);
}
for (int i = 0; i < 3; i++)
if (1 == ksp_dims[i])
conf.kdims[i] = 1;
long channels = cal_dims[3];
unsigned int K = conf.kdims[0] * conf.kdims[1] * conf.kdims[2] * channels;
float svals[K];
for (unsigned int i = 0; i < 3; i++)
if ((1 == cal_dims[i]) && (1 != ksp_dims[i]))
error("Calibration region not found!\n");
// To reproduce old results turn off rotation of phase.
// conf.rotphase = false;
// FIXME: we should scale the data
(conf.usegpu ? num_init_gpu : num_init)();
if ((conf.var < 0) && (conf.weighting || (conf.crop < 0)))
conf.var = estvar_calreg(conf.kdims, cal_dims, cal_data);
if (one) {
#if 0
long maps = out_dims[4];
assert(caldims[3] == out_dims[3]);
assert(maps <= channels);
#endif
long cov_dims[4];
calone_dims(&conf, cov_dims, channels);
complex float* imgcov = md_alloc(4, cov_dims, CFL_SIZE);
calone(&conf, cov_dims, imgcov, K, svals, cal_dims, cal_data);
complex float* out = create_cfl(argv[2], 4, cov_dims);
md_copy(4, cov_dims, out, imgcov, CFL_SIZE);
unmap_cfl(4, cov_dims, out);
// caltwo(crthr, out_dims, out_data, emaps, cov_dims, imgcov, NULL, NULL);
md_free(imgcov);
} else {
long out_dims[N];
long map_dims[N];
for (int i = 0; i < N; i++) {
out_dims[i] = 1;
map_dims[i] = 1;
if ((i < 3) && (1 < conf.kdims[i])) {
out_dims[i] = ksp_dims[i];
map_dims[i] = ksp_dims[i];
}
}
assert(maps <= ksp_dims[COIL_DIM]);
out_dims[COIL_DIM] = ksp_dims[COIL_DIM];
out_dims[MAPS_DIM] = maps;
map_dims[COIL_DIM] = 1;
map_dims[MAPS_DIM] = maps;
const char* emaps_file = NULL;
if (4 == argc)
emaps_file = argv[3];
complex float* out_data = create_cfl(argv[2], N, out_dims);
complex float* emaps = (emaps_file ? create_cfl : anon_cfl)(emaps_file, N, map_dims);
calib(&conf, out_dims, out_data, emaps, K, svals, cal_dims, cal_data);
unmap_cfl(N, out_dims, out_data);
unmap_cfl(N, map_dims, emaps);
}
if (print_svals) {
for (unsigned int i = 0; i < K; i++)
printf("SVALS %d %f\n", i, svals[i]);
}
printf("Done.\n");
unmap_cfl(N, ksp_dims, in_data);
md_free(cal_data);
return 0;
}
int main_nlinv(int argc, char* argv[])
{
int iter = 8;
float l1 = -1.;
bool waterfat = false;
bool rvc = false;
bool normalize = true;
float restrict_fov = -1.;
float csh[3] = { 0., 0., 0. };
bool usegpu = false;
const char* psf = NULL;
const struct opt_s opts[] = {
OPT_FLOAT('l', &l1, "lambda", ""),
OPT_INT('i', &iter, "iter", ""),
OPT_SET('c', &rvc, ""),
OPT_CLEAR('N', &normalize, ""),
OPT_FLOAT('f', &restrict_fov, "FOV", ""),
OPT_STRING('p', &psf, "PSF", ""),
OPT_SET('g', &usegpu, "use gpu"),
};
cmdline(&argc, argv, 2, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
num_init();
assert(iter > 0);
long ksp_dims[DIMS];
complex float* kspace_data = load_cfl(argv[1], DIMS, ksp_dims);
long dims[DIMS];
md_copy_dims(DIMS, dims, ksp_dims);
if (waterfat)
dims[CSHIFT_DIM] = 2;
long img_dims[DIMS];
md_select_dims(DIMS, FFT_FLAGS|CSHIFT_FLAG, img_dims, dims);
long img_strs[DIMS];
md_calc_strides(DIMS, img_strs, img_dims, CFL_SIZE);
complex float* image = create_cfl(argv[2], DIMS, img_dims);
long msk_dims[DIMS];
md_select_dims(DIMS, FFT_FLAGS, msk_dims, dims);
long msk_strs[DIMS];
md_calc_strides(DIMS, msk_strs, msk_dims, CFL_SIZE);
complex float* mask;
complex float* norm = md_alloc(DIMS, msk_dims, CFL_SIZE);
complex float* sens = ((4 == argc) ? create_cfl : anon_cfl)((4 == argc) ? argv[3] : "", DIMS, ksp_dims);
complex float* pattern = NULL;
long pat_dims[DIMS];
if (NULL != psf) {
pattern = load_cfl(psf, DIMS, pat_dims);
// FIXME: check compatibility
} else {
md_copy_dims(DIMS, pat_dims, img_dims);
pattern = anon_cfl("", DIMS, pat_dims);
estimate_pattern(DIMS, ksp_dims, COIL_DIM, pattern, kspace_data);
}
if (waterfat) {
size_t size = md_calc_size(DIMS, msk_dims);
md_copy(DIMS, msk_dims, pattern + size, pattern, CFL_SIZE);
long shift_dims[DIMS];
md_select_dims(DIMS, FFT_FLAGS, shift_dims, msk_dims);
long shift_strs[DIMS];
md_calc_strides(DIMS, shift_strs, shift_dims, CFL_SIZE);
complex float* shift = md_alloc(DIMS, shift_dims, CFL_SIZE);
unsigned int X = shift_dims[READ_DIM];
unsigned int Y = shift_dims[PHS1_DIM];
unsigned int Z = shift_dims[PHS2_DIM];
for (unsigned int x = 0; x < X; x++)
for (unsigned int y = 0; y < Y; y++)
for (unsigned int z = 0; z < Z; z++)
shift[(z * Z + y) * Y + x] = cexp(2.i * M_PI * ((csh[0] * x) / X + (csh[1] * y) / Y + (csh[2] * z) / Z));
md_zmul2(DIMS, msk_dims, msk_strs, pattern + size, msk_strs, pattern + size, shift_strs, shift);
md_free(shift);
}
#if 0
float scaling = 1. / estimate_scaling(ksp_dims, NULL, kspace_data);
#else
float scaling = 100. / md_znorm(DIMS, ksp_dims, kspace_data);
#endif
debug_printf(DP_INFO, "Scaling: %f\n", scaling);
md_zsmul(DIMS, ksp_dims, kspace_data, kspace_data, scaling);
if (-1. == restrict_fov) {
mask = md_alloc(DIMS, msk_dims, CFL_SIZE);
md_zfill(DIMS, msk_dims, mask, 1.);
} else {
float restrict_dims[DIMS] = { [0 ... DIMS - 1] = 1. };
restrict_dims[0] = restrict_fov;
restrict_dims[1] = restrict_fov;
restrict_dims[2] = restrict_fov;
mask = compute_mask(DIMS, msk_dims, restrict_dims);
}
#ifdef USE_CUDA
if (usegpu) {
complex float* kspace_gpu = md_alloc_gpu(DIMS, ksp_dims, CFL_SIZE);
md_copy(DIMS, ksp_dims, kspace_gpu, kspace_data, CFL_SIZE);
noir_recon(dims, iter, l1, image, NULL, pattern, mask, kspace_gpu, rvc, usegpu);
md_free(kspace_gpu);
md_zfill(DIMS, ksp_dims, sens, 1.);
} else
#endif
noir_recon(dims, iter, l1, image, sens, pattern, mask, kspace_data, rvc, usegpu);
if (normalize) {
md_zrss(DIMS, ksp_dims, COIL_FLAG, norm, sens);
md_zmul2(DIMS, img_dims, img_strs, image, img_strs, image, msk_strs, norm);
}
if (4 == argc) {
long strs[DIMS];
md_calc_strides(DIMS, strs, ksp_dims, CFL_SIZE);
if (norm)
md_zdiv2(DIMS, ksp_dims, strs, sens, strs, sens, img_strs, norm);
fftmod(DIMS, ksp_dims, FFT_FLAGS, sens, sens);
}
md_free(norm);
md_free(mask);
unmap_cfl(DIMS, ksp_dims, sens);
unmap_cfl(DIMS, pat_dims, pattern);
unmap_cfl(DIMS, img_dims, image);
unmap_cfl(DIMS, ksp_dims, kspace_data);
exit(0);
}
int main_ecaltwo(int argc, char* argv[])
{
long maps = 2; // channels;
struct ecalib_conf conf = ecalib_defaults;
const struct opt_s opts[] = {
OPT_FLOAT('c', &conf.crop, "crop_value", "Crop the sensitivities if the eigenvalue is smaller than {crop_value}."),
OPT_LONG('m', &maps, "maps", "Number of maps to compute."),
OPT_SET('S', &conf.softcrop, "()"),
OPT_CLEAR('O', &conf.orthiter, "()"),
OPT_SET('g', &conf.usegpu, "()"),
};
cmdline(&argc, argv, 5, 6, usage_str, help_str, ARRAY_SIZE(opts), opts);
long in_dims[DIMS];
complex float* in_data = load_cfl(argv[4], DIMS, in_dims);
int channels = 0;
while (in_dims[3] != (channels * (channels + 1) / 2))
channels++;
debug_printf(DP_INFO, "Channels: %d\n", channels);
assert(maps <= channels);
long out_dims[DIMS] = { [0 ... DIMS - 1] = 1 };
long map_dims[DIMS] = { [0 ... DIMS - 1] = 1 };
out_dims[0] = atoi(argv[1]);
out_dims[1] = atoi(argv[2]);
out_dims[2] = atoi(argv[3]);
out_dims[3] = channels;
out_dims[4] = maps;
assert((out_dims[0] >= in_dims[0]));
assert((out_dims[1] >= in_dims[1]));
assert((out_dims[2] >= in_dims[2]));
for (int i = 0; i < 3; i++)
map_dims[i] = out_dims[i];
map_dims[3] = 1;
map_dims[4] = maps;
complex float* out_data = create_cfl(argv[5], DIMS, out_dims);
complex float* emaps;
if (7 == argc)
emaps = create_cfl(argv[6], DIMS, map_dims);
else
emaps = md_alloc(DIMS, map_dims, CFL_SIZE);
caltwo(&conf, out_dims, out_data, emaps, in_dims, in_data, NULL, NULL);
if (conf.intensity) {
debug_printf(DP_DEBUG1, "Normalize...\n");
normalizel1(DIMS, COIL_FLAG, out_dims, out_data);
}
debug_printf(DP_DEBUG1, "Crop maps... (%.2f)\n", conf.crop);
crop_sens(out_dims, out_data, conf.softcrop, conf.crop, emaps);
debug_printf(DP_DEBUG1, "Fix phase...\n");
fixphase(DIMS, out_dims, COIL_DIM, out_data, out_data);
debug_printf(DP_INFO, "Done.\n");
unmap_cfl(DIMS, in_dims, in_data);
unmap_cfl(DIMS, out_dims, out_data);
if (7 == argc)
unmap_cfl(DIMS, map_dims, emaps);
else
md_free(emaps);
exit(0);
}
int main_nufft(int argc, char* argv[])
{
bool adjoint = false;
bool inverse = false;
bool use_gpu = false;
bool precond = false;
bool dft = false;
struct nufft_conf_s conf = nufft_conf_defaults;
struct iter_conjgrad_conf cgconf = iter_conjgrad_defaults;
long coilim_vec[3] = { 0 };
float lambda = 0.;
const struct opt_s opts[] = {
OPT_SET('a', &adjoint, "adjoint"),
OPT_SET('i', &inverse, "inverse"),
OPT_VEC3('d', &coilim_vec, "x:y:z", "dimensions"),
OPT_VEC3('D', &coilim_vec, "", "()"),
OPT_SET('t', &conf.toeplitz, "Toeplitz embedding for inverse NUFFT"),
OPT_SET('c', &precond, "Preconditioning for inverse NUFFT"),
OPT_FLOAT('l', &lambda, "lambda", "l2 regularization"),
OPT_UINT('m', &cgconf.maxiter, "", "()"),
OPT_SET('s', &dft, "DFT"),
};
cmdline(&argc, argv, 3, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
long coilim_dims[DIMS] = { 0 };
md_copy_dims(3, coilim_dims, coilim_vec);
// Read trajectory
long traj_dims[DIMS];
complex float* traj = load_cfl(argv[1], DIMS, traj_dims);
assert(3 == traj_dims[0]);
num_init();
if (inverse || adjoint) {
long ksp_dims[DIMS];
const complex float* ksp = load_cfl(argv[2], DIMS, ksp_dims);
assert(1 == ksp_dims[0]);
assert(md_check_compat(DIMS, ~(PHS1_FLAG|PHS2_FLAG), ksp_dims, traj_dims));
md_copy_dims(DIMS - 3, coilim_dims + 3, ksp_dims + 3);
if (0 == md_calc_size(DIMS, coilim_dims)) {
estimate_im_dims(DIMS, coilim_dims, traj_dims, traj);
debug_printf(DP_INFO, "Est. image size: %ld %ld %ld\n", coilim_dims[0], coilim_dims[1], coilim_dims[2]);
}
complex float* img = create_cfl(argv[3], DIMS, coilim_dims);
md_clear(DIMS, coilim_dims, img, CFL_SIZE);
const struct linop_s* nufft_op;
if (!dft)
nufft_op = nufft_create(DIMS, ksp_dims, coilim_dims, traj_dims, traj, NULL, conf, use_gpu);
else
nufft_op = nudft_create(DIMS, FFT_FLAGS, ksp_dims, coilim_dims, traj_dims, traj);
if (inverse) {
const struct operator_s* precond_op = NULL;
if (conf.toeplitz && precond)
precond_op = nufft_precond_create(nufft_op);
lsqr(DIMS, &(struct lsqr_conf){ lambda }, iter_conjgrad, CAST_UP(&cgconf),
nufft_op, NULL, coilim_dims, img, ksp_dims, ksp, precond_op);
if (conf.toeplitz && precond)
operator_free(precond_op);
} else {
radio_param_t *radio_param;
} radio_priv_t;
typedef struct radio_driver_s {
char* name;
char* info;
int (*init_frac)(radio_priv_t* priv);
void (*set_volume)(radio_priv_t* priv,int volume);
int (*get_volume)(radio_priv_t* priv,int* volume);
int (*set_frequency)(radio_priv_t* priv,float frequency);
int (*get_frequency)(radio_priv_t* priv,float* frequency);
} radio_driver_t;
#define OPT_BASE_STRUCT radio_param_t
static const m_option_t stream_opts_fields[] = {
OPT_FLOAT("title", freq_channel, 0),
OPT_STRING("capture", capture, 0),
{0}
};
static void close_s(struct stream *stream);
#ifdef CONFIG_RADIO_CAPTURE
static int clear_buffer(radio_priv_t* priv);
#endif
/*****************************************************************
* \brief parse channels parameter and store result into list
* \param freq_channel if channels!=NULL this mean channel number, otherwise - frequency
* \param pfreq selected frequency (from selected channel or from URL)
* \result STREAM_OK if success, STREAM_ERROR otherwise
