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);
}
/**
*
* NUFFT operator initialization
*
* @param N - number of dimensions
* @param ksp_dims - kspace dimension
* @param cim_dims - coil images dimension
* @param traj - trajectory
* @param conf - configuration options
* @param use_gpu - use gpu boolean
*
*/
struct linop_s* nufft_create(unsigned int N, const long ksp_dims[N], const long cim_dims[N], const long traj_dims[N], const complex float* traj, const complex float* weights, struct nufft_conf_s conf, bool use_gpu)
{
struct nufft_data* data = (struct nufft_data*)xmalloc(sizeof(struct nufft_data));
data->N = N;
data->use_gpu = use_gpu;
data->traj = traj;
data->conf = conf;
data->width = 3.;
data->beta = calc_beta(2., data->width);
// get dims
assert(md_check_compat(N - 3, 0, ksp_dims + 3, cim_dims + 3));
unsigned int ND = N + 3;
data->ksp_dims = xmalloc(ND * sizeof(long));
data->cim_dims = xmalloc(ND * sizeof(long));
data->cml_dims = xmalloc(ND * sizeof(long));
data->img_dims = xmalloc(ND * sizeof(long));
data->trj_dims = xmalloc(ND * sizeof(long));
data->lph_dims = xmalloc(ND * sizeof(long));
data->psf_dims = xmalloc(ND * sizeof(long));
data->wgh_dims = xmalloc(ND * sizeof(long));
data->ksp_strs = xmalloc(ND * sizeof(long));
data->cim_strs = xmalloc(ND * sizeof(long));
data->cml_strs = xmalloc(ND * sizeof(long));
data->img_strs = xmalloc(ND * sizeof(long));
data->trj_strs = xmalloc(ND * sizeof(long));
data->lph_strs = xmalloc(ND * sizeof(long));
data->psf_strs = xmalloc(ND * sizeof(long));
data->wgh_strs = xmalloc(ND * sizeof(long));
md_singleton_dims(ND, data->cim_dims);
md_singleton_dims(ND, data->ksp_dims);
md_copy_dims(N, data->cim_dims, cim_dims);
md_copy_dims(N, data->ksp_dims, ksp_dims);
md_select_dims(ND, FFT_FLAGS, data->img_dims, data->cim_dims);
assert(3 == traj_dims[0]);
assert(traj_dims[1] == ksp_dims[1]);
assert(traj_dims[2] == ksp_dims[2]);
assert(md_check_compat(N - 3, ~0, traj_dims + 3, ksp_dims + 3));
assert(md_check_bounds(N - 3, ~0, traj_dims + 3, ksp_dims + 3));
md_singleton_dims(ND, data->trj_dims);
md_copy_dims(N, data->trj_dims, traj_dims);
// get strides
md_calc_strides(ND, data->cim_strs, data->cim_dims, CFL_SIZE);
md_calc_strides(ND, data->img_strs, data->img_dims, CFL_SIZE);
md_calc_strides(ND, data->trj_strs, data->trj_dims, CFL_SIZE);
md_calc_strides(ND, data->ksp_strs, data->ksp_dims, CFL_SIZE);
data->weights = NULL;
if (NULL != weights) {
md_singleton_dims(ND, data->wgh_dims);
md_select_dims(N, ~MD_BIT(0), data->wgh_dims, data->trj_dims);
md_calc_strides(ND, data->wgh_strs, data->wgh_dims, CFL_SIZE);
complex float* tmp = md_alloc(ND, data->wgh_dims, CFL_SIZE);
md_copy(ND, data->wgh_dims, tmp, weights, CFL_SIZE);
data->weights = tmp;
}
complex float* roll = md_alloc(ND, data->img_dims, CFL_SIZE);
rolloff_correction(2., data->width, data->beta, data->img_dims, roll);
data->roll = roll;
complex float* linphase = compute_linphases(N, data->lph_dims, data->img_dims);
md_calc_strides(ND, data->lph_strs, data->lph_dims, CFL_SIZE);
if (!conf.toeplitz)
md_zmul2(ND, data->lph_dims, data->lph_strs, linphase, data->lph_strs, linphase, data->img_strs, data->roll);
fftmod(ND, data->lph_dims, FFT_FLAGS, linphase, linphase);
fftscale(ND, data->lph_dims, FFT_FLAGS, linphase, linphase);
// md_zsmul(ND, data->lph_dims, linphase, linphase, 1. / (float)(data->trj_dims[1] * data->trj_dims[2]));
complex float* fftm = md_alloc(ND, data->img_dims, CFL_SIZE);
md_zfill(ND, data->img_dims, fftm, 1.);
fftmod(ND, data->img_dims, FFT_FLAGS, fftm, fftm);
data->fftmod = fftm;
data->linphase = linphase;
data->psf = NULL;
if (conf.toeplitz) {
#if 0
md_copy_dims(ND, data->psf_dims, data->lph_dims);
#else
md_copy_dims(3, data->psf_dims, data->lph_dims);
md_copy_dims(ND - 3, data->psf_dims + 3, data->trj_dims + 3);
data->psf_dims[N] = data->lph_dims[N];
#endif
md_calc_strides(ND, data->psf_strs, data->psf_dims, CFL_SIZE);
data->psf = compute_psf2(N, data->psf_dims, data->trj_dims, data->traj, data->weights);
}
md_copy_dims(ND, data->cml_dims, data->cim_dims);
data->cml_dims[N + 0] = data->lph_dims[N + 0];
md_calc_strides(ND, data->cml_strs, data->cml_dims, CFL_SIZE);
data->cm2_dims = xmalloc(ND * sizeof(long));
// !
md_copy_dims(ND, data->cm2_dims, data->cim_dims);
for (int i = 0; i < 3; i++)
data->cm2_dims[i] = (1 == cim_dims[i]) ? 1 : (2 * cim_dims[i]);
data->grid = md_alloc(ND, data->cml_dims, CFL_SIZE);
data->fft_op = linop_fft_create(ND, data->cml_dims, FFT_FLAGS, use_gpu);
return linop_create(N, ksp_dims, N, cim_dims,
data, nufft_apply, nufft_apply_adjoint, nufft_apply_normal, NULL, nufft_free_data);
}
/**
* Efficiently chain two matrix linops by multiplying the actual matrices together.
* Stores a copy of the new matrix.
* Returns: C = B A
*
* @param a first matrix (applied to input)
* @param b second matrix (applied to output of first matrix)
*/
struct linop_s* linop_matrix_chain(const struct linop_s* a, const struct linop_s* b)
{
const struct operator_matrix_s* a_data = CAST_DOWN(operator_matrix_s, linop_get_data(a));
const struct operator_matrix_s* b_data = CAST_DOWN(operator_matrix_s, linop_get_data(b));
// check compatibility
assert(linop_codomain(a)->N == linop_domain(b)->N);
assert(md_check_compat(linop_codomain(a)->N, 0u, linop_codomain(a)->dims, linop_domain(b)->dims));
unsigned int D = linop_domain(a)->N;
unsigned long outB_flags = md_nontriv_dims(D, linop_codomain(b)->dims);
unsigned long inB_flags = md_nontriv_dims(D, linop_domain(b)->dims);
unsigned long delB_flags = inB_flags & ~outB_flags;
unsigned int N = a_data->N;
assert(N == 2 * D);
long in_dims[N];
md_copy_dims(N, in_dims, a_data->in_dims);
long matA_dims[N];
md_copy_dims(N, matA_dims, a_data->mat_dims);
long matB_dims[N];
md_copy_dims(N, matB_dims, b_data->mat_dims);
long out_dims[N];
md_copy_dims(N, out_dims, b_data->out_dims);
for (unsigned int i = 0; i < D; i++) {
if (MD_IS_SET(delB_flags, i)) {
matA_dims[2 * i + 0] = a_data->mat_dims[2 * i + 1];
matA_dims[2 * i + 1] = a_data->mat_dims[2 * i + 0];
in_dims[2 * i + 0] = a_data->in_dims[2 * i + 1];
in_dims[2 * i + 1] = a_data->in_dims[2 * i + 0];
}
}
long matrix_dims[N];
md_singleton_dims(N, matrix_dims);
unsigned long iflags = md_nontriv_dims(N, in_dims);
unsigned long oflags = md_nontriv_dims(N, out_dims);
unsigned long flags = iflags | oflags;
// we combine a and b and sum over dims not in input or output
md_max_dims(N, flags, matrix_dims, matA_dims, matB_dims);
debug_printf(DP_DEBUG1, "tensor chain: %ld x %ld -> %ld\n",
md_calc_size(N, matA_dims), md_calc_size(N, matB_dims), md_calc_size(N, matrix_dims));
complex float* matrix = md_alloc(N, matrix_dims, CFL_SIZE);
debug_print_dims(DP_DEBUG2, N, matrix_dims);
debug_print_dims(DP_DEBUG2, N, in_dims);
debug_print_dims(DP_DEBUG2, N, matA_dims);
debug_print_dims(DP_DEBUG2, N, matB_dims);
debug_print_dims(DP_DEBUG2, N, out_dims);
md_ztenmul(N, matrix_dims, matrix, matA_dims, a_data->mat, matB_dims, b_data->mat);
// priv2 takes our doubled dimensions
struct operator_matrix_s* data = linop_matrix_priv2(N, out_dims, in_dims, matrix_dims, matrix);
/* although we internally use different dimensions we define the
* correct interface
*/
struct linop_s* c = linop_create(linop_codomain(b)->N, linop_codomain(b)->dims,
linop_domain(a)->N, linop_domain(a)->dims, CAST_UP(data),
linop_matrix_apply, linop_matrix_apply_adjoint,
linop_matrix_apply_normal, NULL, linop_matrix_del);
md_free(matrix);
return c;
}
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 {
void iwt2(unsigned int N, unsigned int flags, const long shifts[N], const long odims[N], const long ostr[N], complex float* out, const long idims[N], const long istr[N], const complex float* in, const long minsize[N], const long flen, const float filter[2][2][flen])
{
assert(wavelet_check_dims(N, flags, odims, minsize));
if (0 == flags) { // note: recursion does *not* end here
assert(md_check_compat(N, 0u, odims, idims));
md_copy2(N, idims, ostr, out, istr, in, CFL_SIZE);
return;
}
// check input dimensions
long idims2[N];
wavelet_coeffs2(N, flags, idims2, odims, minsize, flen);
assert(md_check_compat(N, 0u, idims2, idims));
long wdims2[2 * N];
wavelet_dims(N, flags, wdims2, odims, flen);
// only consider transform dims...
long dims1[N];
md_select_dims(N, flags, dims1, odims);
long wdims[2 * N];
wavelet_dims(N, flags, wdims, dims1, flen);
long level_coeffs = md_calc_size(2 * N, wdims);
// ... which get embedded in dimension b
unsigned int b = ffs(flags) - 1;
long istr2[2 * N];
md_calc_strides(2 * N, istr2, wdims, istr[b]);
// merge with original strides
for (unsigned int i = 0; i < N; i++)
if (!MD_IS_SET(flags, i))
istr2[i] = istr[i];
assert(idims[b] >= level_coeffs);
long offset = (idims[b] - level_coeffs) * (istr[b] / CFL_SIZE);
long bands = md_calc_size(N, wdims + N);
long coeffs = md_calc_size(N, wdims + 0);
// subtract coefficients in high band
idims2[b] -= (bands - 1) * coeffs;
assert(idims2[b] > 0);
debug_printf(DP_DEBUG4, "ifwt2: flags:%d lcoeffs:%ld coeffs:%ld (space:%ld) bands:%ld str:%ld off:%ld\n", flags, level_coeffs, coeffs, idims2[b], bands, istr[b], offset / ostr[b]);
// fix me we need temp storage
complex float* tmp = md_alloc_sameplace(2 * N, wdims2, CFL_SIZE, out);
long tstr[2 * N];
md_calc_strides(2 * N, tstr, wdims2, CFL_SIZE);
md_copy2(2 * N, wdims2, tstr, tmp, istr2, in + offset, CFL_SIZE);
long shifts0[N];
for (unsigned int i = 0; i < N; i++)
shifts0[i] = 0;
unsigned int flags2 = wavelet_filter_flags(N, flags, wdims, minsize);
assert((0 == offset) == (0u == flags2));
if (0u != flags2) {
long idims3[N];
wavelet_coeffs2(N, flags2, idims3, wdims2, minsize, flen);
long istr3[N];
embed(N, flags, istr3, idims3, istr);
iwt2(N, flags2, shifts0, wdims2, tstr, tmp, idims3, istr3, in, minsize, flen, filter);
}
iwtN(N, flags, shifts, odims, ostr, out, tstr, tmp, flen, filter);
md_free(tmp);
}
int main_nufft(int argc, char* argv[])
{
int c;
bool adjoint = false;
bool inverse = false;
bool use_gpu = false;
bool sizeinit = false;
struct nufft_conf_s conf = nufft_conf_defaults;
struct iter_conjgrad_conf cgconf = iter_conjgrad_defaults;
long coilim_dims[DIMS];
md_singleton_dims(DIMS, coilim_dims);
float lambda = 0.;
while (-1 != (c = getopt(argc, argv, "d:m:l:aiht"))) {
switch (c) {
case 'i':
inverse = true;
break;
case 'a':
adjoint = true;
break;
case 'd':
sscanf(optarg, "%ld:%ld:%ld", &coilim_dims[0], &coilim_dims[1], &coilim_dims[2]);
sizeinit = true;
break;
case 'm':
cgconf.maxiter = atoi(optarg);
break;
case 'l':
lambda = atof(optarg);
break;
case 't':
conf.toeplitz = true;
break;
case 'h':
usage(argv[0], stdout);
help();
exit(0);
default:
usage(argv[0], stderr);
exit(1);
}
}
if (argc - optind != 3) {
usage(argv[0], stderr);
exit(1);
}
// Read trajectory
long traj_dims[DIMS];
complex float* traj = load_cfl(argv[optind + 0], DIMS, traj_dims);
assert(3 == traj_dims[0]);
num_init();
if (inverse || adjoint) {
long ksp_dims[DIMS];
const complex float* ksp = load_cfl(argv[optind + 1], 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 (!sizeinit) {
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[optind + 2], DIMS, coilim_dims);
md_clear(DIMS, coilim_dims, img, CFL_SIZE);
const struct linop_s* nufft_op = nufft_create(DIMS, ksp_dims, coilim_dims, traj_dims, traj, NULL, conf, use_gpu);
if (inverse) {
lsqr(DIMS, &(struct lsqr_conf){ lambda }, iter_conjgrad, &cgconf,
nufft_op, NULL, coilim_dims, img, ksp_dims, ksp);
} else {
int main_rsense(int argc, char* argv[])
{
bool usegpu = false;
int maps = 2;
int ctrsh = 0.;
bool sec = false;
bool scale_im = false;
const char* pat_file = NULL;
struct sense_conf sconf = sense_defaults;
struct grecon_conf conf = { NULL, &sconf, false, false, false, true, 30, 0.95, 0. };
int c;
while (-1 != (c = getopt(argc, argv, "l:r:s:i:p:Sgh"))) {
switch(c) {
case 'r':
conf.lambda = atof(optarg);
break;
case 's':
conf.step = atof(optarg);
break;
case 'i':
conf.maxiter = atoi(optarg);
break;
case 'l':
if (1 == atoi(optarg))
conf.l1wav = true;
else if (2 == atoi(optarg))
conf.l1wav = false;
else {
usage(argv[0], stderr);
exit(1);
}
break;
case 'S':
scale_im = true;
break;
case 'h':
usage(argv[0], stdout);
help();
exit(0);
case 'g':
usegpu = true;
break;
case 'p':
pat_file = strdup(optarg);
break;
default:
usage(argv[0], stderr);
exit(1);
}
}
if (argc - optind != 3) {
usage(argv[0], stderr);
exit(1);
}
int N = DIMS;
long dims[N];
long img_dims[N];
long ksp_dims[N];
long sens_dims[N];
complex float* kspace_data = load_cfl(argv[optind + 0], N, ksp_dims);
complex float* sens_maps = load_cfl(argv[optind + 1], N, sens_dims);
assert(1 == ksp_dims[MAPS_DIM]);
md_copy_dims(N, dims, ksp_dims);
if (!sec) {
dims[MAPS_DIM] = sens_dims[MAPS_DIM];
} else {
assert(maps <= ksp_dims[COIL_DIM]);
dims[MAPS_DIM] = maps;
}
for (int i = 0; i < 4; i++) { // sizes2[4] may be > 1
if (ksp_dims[i] != dims[i]) {
fprintf(stderr, "Dimensions of kspace and sensitivities do not match!\n");
exit(1);
}
}
complex float* pattern = NULL;
long pat_dims[DIMS];
if (NULL != pat_file) {
pattern = load_cfl(pat_file, DIMS, pat_dims);
assert(md_check_compat(DIMS, COIL_FLAG, ksp_dims, pat_dims));
}
debug_printf(DP_INFO, "%ld map(s)\n", dims[MAPS_DIM]);
if (conf.l1wav)
debug_printf(DP_INFO, "l1-wavelet regularization\n");
md_select_dims(N, ~COIL_FLAG, img_dims, dims);
(usegpu ? num_init_gpu : num_init)();
// float scaling = estimate_scaling(ksp_dims, sens_maps, kspace_data);
float scaling = estimate_scaling(ksp_dims, NULL, kspace_data);
debug_printf(DP_INFO, "Scaling: %f\n", scaling);
if (0. != scaling)
md_zsmul(N, ksp_dims, kspace_data, kspace_data, 1. / scaling);
debug_printf(DP_INFO, "Readout FFT..\n");
ifftuc(N, ksp_dims, READ_FLAG, kspace_data, kspace_data);
debug_printf(DP_INFO, "Done.\n");
complex float* image = create_cfl(argv[optind + 2], N, img_dims);
debug_printf(DP_INFO, "Reconstruction...\n");
struct ecalib_conf calib;
if (sec) {
calib = ecalib_defaults;
calib.crop = ctrsh;
conf.calib = &calib;
}
rgrecon(&conf, dims, image, sens_dims, sens_maps, pat_dims, pattern, kspace_data, usegpu);
if (scale_im)
md_zsmul(DIMS, img_dims, image, image, scaling);
debug_printf(DP_INFO, "Done.\n");
unmap_cfl(N, img_dims, image);
unmap_cfl(N, ksp_dims, kspace_data);
unmap_cfl(N, sens_dims, sens_maps);
exit(0);
}
