/**
* Intialize lrthresh data
*
* @param dims_decom - dimensions with levels at LEVEL_DIMS
* @param randshift - randshift boolean
* @param mflags - selects which dimensions gets reshaped as the first dimension in matrix
* @param blkdims - contains block dimensions for all levels
*
*/
static struct lrthresh_data_s* lrthresh_create_data(const long dims_decom[DIMS], bool randshift, unsigned long mflags, const long blkdims[MAX_LEV][DIMS], float lambda, bool noise, int remove_mean)
{
PTR_ALLOC(struct lrthresh_data_s, data);
SET_TYPEID(lrthresh_data_s, data);
data->randshift = randshift;
data->mflags = mflags;
data->lambda = lambda;
data->noise = noise;
data->remove_mean = remove_mean;
// level dimensions
md_copy_dims(DIMS, data->dims_decom, dims_decom);
md_calc_strides(DIMS, data->strs_lev, dims_decom, CFL_SIZE);
// image dimensions
data->levels = dims_decom[LEVEL_DIM];
md_select_dims(DIMS, ~LEVEL_FLAG, data->dims, dims_decom);
md_calc_strides(DIMS, data->strs, data->dims, CFL_SIZE);
// blkdims
for(long l = 0; l < data->levels; l++) {
for (long i = 0; i < DIMS; i++)
data->blkdims[l][i] = blkdims[l][i];
}
return PTR_PASS(data);
}
static struct maps_data* maps_create_data(const long max_dims[DIMS],
unsigned int sens_flags, const complex float* sens, bool gpu)
{
struct maps_data* data = xmalloc(sizeof(struct maps_data));
// maximal dimensions
md_copy_dims(DIMS, data->max_dims, max_dims);
// sensitivity dimensions
md_select_dims(DIMS, sens_flags, data->mps_dims, max_dims);
md_calc_strides(DIMS, data->strs_mps, data->mps_dims, CFL_SIZE);
md_select_dims(DIMS, ~MAPS_FLAG, data->ksp_dims, max_dims);
md_calc_strides(DIMS, data->strs_ksp, data->ksp_dims, CFL_SIZE);
md_select_dims(DIMS, ~COIL_FLAG, data->img_dims, max_dims);
md_calc_strides(DIMS, data->strs_img, data->img_dims, CFL_SIZE);
#ifdef USE_CUDA
complex float* nsens = (gpu ? md_alloc_gpu : md_alloc)(DIMS, data->mps_dims, CFL_SIZE);
#else
assert(!gpu);
complex float* nsens = md_alloc(DIMS, data->mps_dims, CFL_SIZE);
#endif
md_copy(DIMS, data->mps_dims, nsens, sens, CFL_SIZE);
data->sens = nsens;
data->norm = NULL;
return data;
}
const struct linop_s* linop_zfinitediff_create(unsigned int D, const long dims[D], long diffdim, bool circular)
{
PTR_ALLOC(struct zfinitediff_data, data);
SET_TYPEID(zfinitediff_data, data);
data->D = D;
data->dim_diff = diffdim;
data->do_circdiff = circular;
data->dims_in = *TYPE_ALLOC(long[D]);
data->dims_adj = *TYPE_ALLOC(long[D]);
data->strides_in = *TYPE_ALLOC(long[D]);
data->strides_adj = *TYPE_ALLOC(long[D]);
md_copy_dims(D, data->dims_in, dims);
md_copy_dims(D, data->dims_adj, dims);
md_calc_strides(D, data->strides_in, data->dims_in, CFL_SIZE);
if (!data->do_circdiff)
data->dims_adj[data->dim_diff] -= 1;
md_calc_strides(D, data->strides_adj, data->dims_adj, CFL_SIZE);
const long* dims_adj = data->dims_adj;
const long* dims_in = data->dims_in;
return linop_create(D, dims_adj, D, dims_in, CAST_UP(PTR_PASS(data)),
zfinitediff_apply, zfinitediff_adjoint,
zfinitediff_normal, NULL, zfinitediff_del);
}
static struct ufft_data* ufft_create_data(const long ksp_dims[DIMS], const long pat_dims[DIMS], const complex float* pat, unsigned int flags, bool use_gpu)
{
PTR_ALLOC(struct ufft_data, data);
SET_TYPEID(ufft_data, data);
data->flags = flags;
data->use_gpu = use_gpu;
md_copy_dims(DIMS, data->pat_dims, pat_dims);
md_copy_dims(DIMS, data->ksp_dims, ksp_dims);
md_calc_strides(DIMS, data->pat_strs, pat_dims, CFL_SIZE);
md_calc_strides(DIMS, data->ksp_strs, ksp_dims, CFL_SIZE);
#ifdef USE_CUDA
data->pat = (use_gpu ? md_alloc_gpu : md_alloc)(DIMS, data->pat_dims, CFL_SIZE);
#else
data->pat = md_alloc(DIMS, data->pat_dims, CFL_SIZE);
#endif
md_copy(DIMS, data->pat_dims, data->pat, pat, CFL_SIZE);
data->fft_op = linop_fftc_create(DIMS, ksp_dims, flags);
return PTR_PASS(data);
}
static struct linop_s* linop_gdiag_create(unsigned int N, const long dims[N], unsigned int flags, const complex float* diag, bool rdiag)
{
PTR_ALLOC(struct cdiag_s, data);
SET_TYPEID(cdiag_s, data);
data->rmul = rdiag;
data->N = N;
PTR_ALLOC(long[N], dims2);
PTR_ALLOC(long[N], dstrs);
PTR_ALLOC(long[N], strs);
long ddims[N];
md_select_dims(N, flags, ddims, dims);
md_copy_dims(N, *dims2, dims);
md_calc_strides(N, *strs, dims, CFL_SIZE);
md_calc_strides(N, *dstrs, ddims, CFL_SIZE);
data->dims = *PTR_PASS(dims2);
data->strs = *PTR_PASS(strs);
data->dstrs = *PTR_PASS(dstrs);
data->diag = diag; // make a copy?
#ifdef USE_CUDA
data->gpu_diag = NULL;
#endif
return linop_create(N, dims, N, dims, CAST_UP(PTR_PASS(data)), cdiag_apply, cdiag_adjoint, cdiag_normal, NULL, cdiag_free);
}
const struct operator_s* nufft_precond_create(const struct linop_s* nufft_op)
{
const auto data = CAST_DOWN(nufft_data, linop_get_data(nufft_op));
PTR_ALLOC(struct nufft_precond_data, pdata);
SET_TYPEID(nufft_precond_data, pdata);
assert(data->conf.toeplitz);
int N = data->N;
int ND = N + 1;
pdata->N = N;
pdata->cim_dims = *TYPE_ALLOC(long[ND]);
pdata->pre_dims = *TYPE_ALLOC(long[ND]);
pdata->cim_strs = *TYPE_ALLOC(long[ND]);
pdata->pre_strs = *TYPE_ALLOC(long[ND]);
md_copy_dims(ND, pdata->cim_dims, data->cim_dims);
md_select_dims(ND, data->flags, pdata->pre_dims, pdata->cim_dims);
md_calc_strides(ND, pdata->cim_strs, pdata->cim_dims, CFL_SIZE);
md_calc_strides(ND, pdata->pre_strs, pdata->pre_dims, CFL_SIZE);
pdata->pre = compute_precond(pdata->N, pdata->pre_dims, pdata->pre_strs, data->psf_dims, data->psf_strs, data->psf, data->linphase);
pdata->fft_op = linop_fft_create(pdata->N, pdata->cim_dims, data->flags);
const long* cim_dims = pdata->cim_dims; // need to dereference pdata before PTR_PASS
return operator_create(N, cim_dims, N, cim_dims, CAST_UP(PTR_PASS(pdata)), nufft_precond_apply, nufft_precond_del);
}
int main_repmat(int argc, char* argv[])
{
mini_cmdline(argc, argv, 4, usage_str, help_str);
long in_dims[DIMS];
long out_dims[DIMS];
complex float* in_data = load_cfl(argv[3], DIMS, in_dims);
int dim = atoi(argv[1]);
int rep = atoi(argv[2]);
assert(dim < DIMS);
assert(rep >= 0);
assert(1 == in_dims[dim]);
md_copy_dims(DIMS, out_dims, in_dims);
out_dims[dim] = rep;
complex float* out_data = create_cfl(argv[4], DIMS, out_dims);
long in_strs[DIMS];
long out_strs[DIMS];
md_calc_strides(DIMS, in_strs, in_dims, CFL_SIZE);
md_calc_strides(DIMS, out_strs, out_dims, CFL_SIZE);
md_copy2(DIMS, out_dims, out_strs, out_data, in_strs, in_data, CFL_SIZE);
unmap_cfl(DIMS, out_dims, out_data);
unmap_cfl(DIMS, in_dims, in_data);
exit(0);
}
/**
* Create a linear operator (without strides)
*
* @param N number of dimensions
* @param odims dimensions of output (codomain)
* @param idims dimensions of input (domain)
* @param data data for applying the operator
* @param forward function for applying the forward operation, A
* @param adjoint function for applying the adjoint operation, A^H
* @param normal function for applying the normal equations operation, A^H A
* @param norm_inv function for applying the pseudo-inverse operation, (A^H A + mu I)^-1
* @param del function for freeing the data
*/
struct linop_s* linop_create(unsigned int ON, const long odims[ON], unsigned int IN, const long idims[IN], void* data,
lop_fun_t forward, lop_fun_t adjoint, lop_fun_t normal, lop_p_fun_t norm_inv, del_fun_t del)
{
long ostrs[ON];
long istrs[IN];
md_calc_strides(ON, ostrs, odims, CFL_SIZE);
md_calc_strides(IN, istrs, idims, CFL_SIZE);
return linop_create2(ON, odims, ostrs, IN, idims, istrs, data, forward, adjoint, normal, norm_inv, del);
}
void fwtN(unsigned int N, unsigned int flags, const long shifts[N], const long dims[N], const long ostr[2 * N], complex float* out, const long istr[N], const complex float* in, const long flen, const float filter[2][2][flen])
{
long odims[2 * N];
wavelet_dims(N, flags, odims, dims, flen);
assert(md_calc_size(2 * N, odims) >= md_calc_size(N, dims));
// FIXME one of these is unnecessary if we use the output
complex float* tmpA = md_alloc_sameplace(2 * N, odims, CFL_SIZE, out);
complex float* tmpB = md_alloc_sameplace(2 * N, odims, CFL_SIZE, out);
long tidims[2 * N];
md_copy_dims(N, tidims, dims);
md_singleton_dims(N, tidims + N);
long tistrs[2 * N];
md_calc_strides(2 * N, tistrs, tidims, CFL_SIZE);
long todims[2 * N];
md_copy_dims(2 * N, todims, tidims);
long tostrs[2 * N];
// maybe we should push the randshift into lower levels
//md_copy2(N, dims, tistrs, tmpA, istr, in, CFL_SIZE);
md_circ_shift2(N, dims, shifts, tistrs, tmpA, istr, in, CFL_SIZE);
for (unsigned int i = 0; i < N; i++) {
if (MD_IS_SET(flags, i)) {
todims[0 + i] = odims[0 + i];
todims[N + i] = odims[N + i];
md_calc_strides(2 * N, tostrs, todims, CFL_SIZE);
fwt1(2 * N, i, tidims, tostrs, tmpB, (void*)tmpB + tostrs[N + i], tistrs, tmpA, flen, filter);
md_copy_dims(2 * N, tidims, todims);
md_copy_dims(2 * N, tistrs, tostrs);
complex float* swap = tmpA;
tmpA = tmpB;
tmpB = swap;
}
}
md_copy2(2 * N, todims, ostr, out, tostrs, tmpA, CFL_SIZE);
md_free(tmpA);
md_free(tmpB);
}
struct linop_s* sampling_create(const long dims[DIMS], const long pat_dims[DIMS], const complex float* pattern)
{
struct sampling_data_s* data = xmalloc(sizeof(struct sampling_data_s));
md_select_dims(DIMS, ~MAPS_FLAG, data->dims, dims); // dimensions of kspace
md_calc_strides(DIMS, data->strs, data->dims, CFL_SIZE);
md_calc_strides(DIMS, data->pat_strs, pat_dims, CFL_SIZE);
data->pattern = pattern;
return linop_create(DIMS, data->dims, DIMS, data->dims, data, sampling_apply, sampling_apply, sampling_apply, NULL, sampling_free);
}
void iwtN(unsigned int N, unsigned int flags, const long shifts[N], const long dims[N], const long ostr[N], complex float* out, const long istr[2 * N], const complex float* in, const long flen, const float filter[2][2][flen])
{
long idims[2 * N];
wavelet_dims(N, flags, idims, dims, flen);
assert(md_calc_size(2 * N, idims) >= md_calc_size(N, dims));
complex float* tmpA = md_alloc_sameplace(2 * N, idims, CFL_SIZE, out);
complex float* tmpB = md_alloc_sameplace(2 * N, idims, CFL_SIZE, out);
long tidims[2 * N];
md_copy_dims(2 * N, tidims, idims);
long tistrs[2 * N];
md_calc_strides(2 * N, tistrs, tidims, CFL_SIZE);
long todims[2 * N];
md_copy_dims(2 * N, todims, tidims);
long tostrs[2 * N];
long ishifts[N];
for (unsigned int i = 0; i < N; i++)
ishifts[i] = -shifts[i];
md_copy2(2 * N, tidims, tistrs, tmpA, istr, in, CFL_SIZE);
for (int i = N - 1; i >= 0; i--) { // run backwards to maintain contigous blocks
if (MD_IS_SET(flags, i)) {
todims[0 + i] = dims[0 + i];
todims[N + i] = 1;
md_calc_strides(2 * N, tostrs, todims, CFL_SIZE);
iwt1(2 * N, i, todims, tostrs, tmpB, tistrs, tmpA, (void*)tmpA + tistrs[N + i], flen, filter);
md_copy_dims(2 * N, tidims, todims);
md_copy_dims(2 * N, tistrs, tostrs);
complex float* swap = tmpA;
tmpA = tmpB;
tmpB = swap;
}
}
//md_copy2(N, dims, ostr, out, tostrs, tmpA, CFL_SIZE);
md_circ_shift2(N, dims, ishifts, ostr, out, tostrs, tmpA, CFL_SIZE);
md_free(tmpA);
md_free(tmpB);
}
static complex float* compute_psf2(unsigned int N, const long psf_dims[N + 3], const long trj_dims[N + 3], const complex float* traj, const complex float* weights)
{
unsigned int ND = N + 3;
long img_dims[ND];
long img_strs[ND];
md_select_dims(ND, ~MD_BIT(N + 0), img_dims, psf_dims);
md_calc_strides(ND, img_strs, img_dims, CFL_SIZE);
// PSF 2x size
long img2_dims[ND];
long img2_strs[ND];
md_copy_dims(ND, img2_dims, img_dims);
for (int i = 0; i < 3; i++)
img2_dims[i] = (1 == img_dims[i]) ? 1 : (2 * img_dims[i]);
md_calc_strides(ND, img2_strs, img2_dims, CFL_SIZE);
complex float* traj2 = md_alloc(ND, trj_dims, CFL_SIZE);
md_zsmul(ND, trj_dims, traj2, traj, 2.);
complex float* psft = compute_psf(ND, img2_dims, trj_dims, traj2, weights);
md_free(traj2);
fftuc(ND, img2_dims, FFT_FLAGS, psft, psft);
// reformat
long sub2_strs[ND];
md_copy_strides(ND, sub2_strs, img2_strs);
for(int i = 0; i < 3; i++)
sub2_strs[i] *= 2;;
complex float* psf = md_alloc(ND, psf_dims, CFL_SIZE);
long factors[N];
for (unsigned int i = 0; i < N; i++)
factors[i] = ((img_dims[i] > 1) && (i < 3)) ? 2 : 1;
md_decompose(N + 0, factors, psf_dims, psf, img2_dims, psft, CFL_SIZE);
md_free(psft);
return psf;
}
static double bench_generic_add(long dims[DIMS], unsigned int flags, bool forloop)
{
long dimsX[DIMS];
long dimsY[DIMS];
long dimsC[DIMS];
md_select_dims(DIMS, flags, dimsX, dims);
md_select_dims(DIMS, ~flags, dimsC, dims);
md_select_dims(DIMS, ~0u, dimsY, dims);
long strsX[DIMS];
long strsY[DIMS];
md_calc_strides(DIMS, strsX, dimsX, CFL_SIZE);
md_calc_strides(DIMS, strsY, dimsY, CFL_SIZE);
complex float* x = md_alloc(DIMS, dimsX, CFL_SIZE);
complex float* y = md_alloc(DIMS, dimsY, CFL_SIZE);
md_gaussian_rand(DIMS, dimsX, x);
md_gaussian_rand(DIMS, dimsY, y);
long L = md_calc_size(DIMS, dimsC);
long T = md_calc_size(DIMS, dimsX);
double tic = timestamp();
if (forloop) {
for (long i = 0; i < L; i++) {
for (long j = 0; j < T; j++)
y[i + j * L] += x[j];
}
} else {
md_zaxpy2(DIMS, dims, strsY, y, 1., strsX, x);
}
double toc = timestamp();
md_free(x);
md_free(y);
return toc - tic;
}
int main_mip(int argc, char* argv[argc])
{
bool mIP = false;
const struct opt_s opts[] = {
OPT_SET('m', &mIP, "minimum" ),
};
cmdline(&argc, argv, 3, 3, usage_str, help_str, ARRAY_SIZE(opts), opts);
unsigned int flags = atoi(argv[1]);
long idims[DIMS];
complex float* in = load_cfl(argv[2], DIMS, idims);
long odims[DIMS];
md_select_dims(DIMS, ~flags, odims, idims);
complex float* out = create_cfl(argv[3], DIMS, odims);
complex float* tmp = md_alloc(DIMS, idims, CFL_SIZE);
md_zabs(DIMS, idims, tmp, in);
long istr[DIMS];
long ostr[DIMS];
md_calc_strides(DIMS, istr, idims, CFL_SIZE);
md_calc_strides(DIMS, ostr, odims, CFL_SIZE);
md_clear(DIMS, odims, out, CFL_SIZE);
md_max2(DIMS, idims, ostr, (float*)out, ostr, (const float*)out, istr, (const float*)tmp);
if (mIP) {
// need result of max in output
md_min2(DIMS, idims, ostr, (float*)out, ostr, (const float*)out, istr, (const float*)tmp);
}
md_free(tmp);
unmap_cfl(DIMS, idims, in);
unmap_cfl(DIMS, odims, out);
exit(0);
}
struct prox_dfwavelet_data* prepare_prox_dfwavelet_data(const long im_dims[DIMS], const long min_size[3], const complex float res[3], unsigned int flow_dim, float lambda, bool use_gpu)
{
// get dimension
PTR_ALLOC(struct prox_dfwavelet_data, data);
md_copy_dims(DIMS, data->im_dims, im_dims);
md_select_dims(DIMS, FFT_FLAGS, data->tim_dims, im_dims);
md_calc_strides(DIMS, data->im_strs, im_dims, CFL_SIZE);
// initialize temp
#ifdef USE_CUDA
if (use_gpu) {
data->vx = md_alloc_gpu(DIMS, data->tim_dims, CFL_SIZE);
data->vy = md_alloc_gpu(DIMS, data->tim_dims, CFL_SIZE);
data->vz = md_alloc_gpu(DIMS, data->tim_dims, CFL_SIZE);
} else
#endif
{
data->vx = md_alloc(DIMS, data->tim_dims, CFL_SIZE);
data->vy = md_alloc(DIMS, data->tim_dims, CFL_SIZE);
data->vz = md_alloc(DIMS, data->tim_dims, CFL_SIZE);
}
data->flow_dim = flow_dim;
data->slice_flag = ~FFT_FLAGS;
data->lambda = lambda;
data->plan = prepare_dfwavelet_plan(3, data->tim_dims, (long*) min_size, (complex float*) res, use_gpu);
return data;
}
void fftscale(unsigned int N, const long dims[N], unsigned long flags, complex float* dst, const complex float* src)
{
long strs[N];
md_calc_strides(N, strs, dims, CFL_SIZE);
fftscale2(N, dims, flags, strs, dst, strs, src);
}
const struct operator_s* fft_create(unsigned int D, const long dimensions[D], unsigned long flags, complex float* dst, const complex float* src, bool backwards)
{
long strides[D];
md_calc_strides(D, strides, dimensions, CFL_SIZE);
return fft_create2(D, dimensions, flags, strides, dst, strides, src, backwards);
}
/**
* Thresholding operator for l0-norm: f(x) = || x ||_0 <= k, as used in NIHT algorithm.
* y = HT(x, k) (hard thresholding, ie keeping the k largest elements).
*
* @param D number of dimensions
* @param dim dimensions of x
* @param k threshold parameter (non-zero elements to keep)
* @param flags bitmask for joint thresholding
*/
const struct operator_p_s* prox_niht_thresh_create(unsigned int D, const long dim[D], const unsigned int k, const unsigned long flags)
{
PTR_ALLOC(struct thresh_s, data);
SET_TYPEID(thresh_s, data);
data->lambda = 0.;
data->k = k;
data->D = D;
data->flags = flags;
data->unitary_op = NULL;
PTR_ALLOC(long[D], ndim);
md_copy_dims(D, *ndim, dim);
data->dim = *PTR_PASS(ndim);
// norm dimensions are the flagged input dimensions
PTR_ALLOC(long[D], norm_dim);
md_select_dims(D, ~flags, *norm_dim, data->dim);
data->norm_dim = *PTR_PASS(norm_dim);
PTR_ALLOC(long[D], nstr);
md_calc_strides(D, *nstr, data->dim, CFL_SIZE);
data->str = *PTR_PASS(nstr);
return operator_p_create(D, dim, D, dim, CAST_UP(PTR_PASS(data)), hardthresh_apply, thresh_del);
}
/**
* Proximal operator for l1-norm with unitary transform: f(x) = lambda || T x ||_1
*
* @param D number of dimensions
* @param dim dimensions of x
* @param lambda threshold parameter
* @param unitary_op unitary linear operator
* @param flags bitmask for joint soft-thresholding
*/
extern const struct operator_p_s* prox_unithresh_create(unsigned int D, const struct linop_s* unitary_op, const float lambda, const unsigned long flags)
{
PTR_ALLOC(struct thresh_s, data);
SET_TYPEID(thresh_s, data);
data->lambda = lambda;
data->D = D;
data->flags = flags;
data->unitary_op = unitary_op;
const long* dims = linop_domain(unitary_op)->dims;
PTR_ALLOC(long[D], ndim);
md_copy_dims(D, *ndim, dims);
data->dim = *PTR_PASS(ndim);
PTR_ALLOC(long[D], nstr);
md_calc_strides(D, *nstr, data->dim, CFL_SIZE);
data->str = *PTR_PASS(nstr);
// norm dimensions are the flagged transform dimensions
// FIXME should use linop_codomain(unitary_op)->N
PTR_ALLOC(long[D], norm_dim);
md_select_dims(D, ~flags, *norm_dim, linop_codomain(unitary_op)->dims);
data->norm_dim = *PTR_PASS(norm_dim);
return operator_p_create(D, dims, D, dims, CAST_UP(PTR_PASS(data)), unisoftthresh_apply, thresh_del);
}
void fwt(unsigned int N, unsigned int flags, const long shifts[N], const long dims[N], complex float* out, const long istr[N], const complex float* in, const long minsize[N], long flen, const float filter[2][2][flen])
{
if (0 == flags) {
if (out != in)
md_copy2(N, dims, istr, out, istr, in, CFL_SIZE);
return;
}
unsigned long coeffs = wavelet_coeffs(N, flags, dims, minsize, flen);
long wdims[2 * N];
wavelet_dims(N, flags, wdims, dims, flen);
long ostr[2 * N];
md_calc_strides(2 * N, ostr, wdims, CFL_SIZE);
long offset = coeffs - md_calc_size(2 * N, wdims);
debug_printf(DP_DEBUG4, "%d %ld %ld\n", flags, coeffs, offset);
long shifts0[N];
for (unsigned int i = 0; i < N; i++)
shifts0[i] = 0;
fwtN(N, flags, shifts, dims, ostr, out + offset, istr, in, flen, filter);
fwt(N, wavelet_filter_flags(N, flags, wdims, minsize), shifts0, wdims, out, ostr, out + offset, minsize, flen, filter);
}
int main_reshape(int argc, char* argv[])
{
cmdline(&argc, argv, 3, 100, usage_str, help_str, 0, NULL);
num_init();
unsigned int flags = atoi(argv[1]);
unsigned int n = bitcount(flags);
assert((int)n + 3 == argc - 1);
long in_dims[DIMS];
long in_strs[DIMS];
long out_dims[DIMS];
long out_strs[DIMS];
complex float* in_data = load_cfl(argv[n + 2], DIMS, in_dims);
md_calc_strides(DIMS, in_strs, in_dims, CFL_SIZE);
md_copy_dims(DIMS, out_dims, in_dims);
unsigned int j = 0;
for (unsigned int i = 0; i < DIMS; i++)
if (MD_IS_SET(flags, i))
out_dims[i] = atoi(argv[j++ + 2]);
assert(j == n);
assert(md_calc_size(DIMS, in_dims) == md_calc_size(DIMS, out_dims));
md_calc_strides(DIMS, out_strs, out_dims, CFL_SIZE);
for (unsigned int i = 0; i < DIMS; i++)
if (!(MD_IS_SET(flags, i) || (in_strs[i] == out_strs[i])))
error("Dimensions are not consistent at index %d.\n");
complex float* out_data = create_cfl(argv[n + 3], DIMS, out_dims);
md_copy(DIMS, in_dims, out_data, in_data, CFL_SIZE);
unmap_cfl(DIMS, in_dims, in_data);
unmap_cfl(DIMS, out_dims, out_data);
exit(0);
}
static struct linop_s* linop_fft_create_priv(int N, const long dims[N], unsigned int flags, bool forward, bool center)
{
const struct operator_s* plan = fft_measure_create(N, dims, flags, true, false);
const struct operator_s* iplan = fft_measure_create(N, dims, flags, true, true);
PTR_ALLOC(struct fft_linop_s, data);
SET_TYPEID(fft_linop_s, data);
data->frw = plan;
data->adj = iplan;
data->N = N;
data->center = center;
data->dims = *TYPE_ALLOC(long[N]);
md_copy_dims(N, data->dims, dims);
data->strs = *TYPE_ALLOC(long[N]);
md_calc_strides(N, data->strs, data->dims, CFL_SIZE);
long fft_dims[N];
md_select_dims(N, flags, fft_dims, dims);
data->nscale = (float)md_calc_size(N, fft_dims);
lop_fun_t apply = forward ? fft_linop_apply : fft_linop_adjoint;
lop_fun_t adjoint = forward ? fft_linop_adjoint : fft_linop_apply;
struct linop_s* lop = linop_create(N, dims, N, dims, CAST_UP(PTR_PASS(data)), apply, adjoint, fft_linop_normal, NULL, fft_linop_free);
if (center) {
// FIXME: should only allocate flagged dims
complex float* fftmod_mat = md_alloc(N, dims, CFL_SIZE);
complex float* fftmodk_mat = md_alloc(N, dims, CFL_SIZE);
// we need fftmodk only because we want to apply scaling only once
complex float one[1] = { 1. };
md_fill(N, dims, fftmod_mat, one, CFL_SIZE);
fftmod(N, dims, flags, fftmodk_mat, fftmod_mat);
fftscale(N, dims, flags, fftmod_mat, fftmodk_mat);
struct linop_s* mod = linop_cdiag_create(N, dims, ~0u, fftmod_mat);
struct linop_s* modk = linop_cdiag_create(N, dims, ~0u, fftmodk_mat);
struct linop_s* tmp = linop_chain(mod, lop);
tmp = linop_chain(tmp, modk);
linop_free(lop);
linop_free(mod);
linop_free(modk);
lop = tmp;
}
return lop;
}
void overlapandsave(int N, const long dims[N], const long blk[N], complex float* dst, complex float* src1, const long dim2[N], complex float* src2)
{
// [------++++
// [------
long ndims[2 * N];
long L[2 * N];
long ndim2[2 * N];
long ndim3[2 * N];
for (int i = 0; i < N; i++) {
assert(0 == dims[i] % blk[i]);
assert(dim2[i] <= blk[i]);
ndims[i * 2 + 1] = dims[i] / blk[i];
ndims[i * 2 + 0] = blk[i];
L[i * 2 + 1] = dims[i] / blk[i];
L[i * 2 + 0] = blk[i] + dim2[i] - 1;
ndim2[i * 2 + 1] = 1;
ndim2[i * 2 + 0] = dim2[i];
ndim3[i * 2 + 1] = dims[i] / blk[i] - 0;
ndim3[i * 2 + 0] = blk[i];
}
long T = md_calc_size(2 * N, L);
complex float* tmp = xmalloc(T * 8);
long str1[2 * N];
long str2[2 * N];
long str3[2 * N];
md_calc_strides(2 * N, str1, ndims, 8);
md_calc_strides(2 * N, str2, L, 8);
md_calc_strides(2 * N, str3, ndim3, 8);
md_clear(2 * N, L, tmp, 8);
md_copy2(2 * N, ndim3, str2, tmp, str1, src1, 8);
conv(2 * N, ~0, CONV_VALID, CONV_CAUSAL, ndims, dst, L, tmp, ndim2, src2);
free(tmp);
}
void overlapandadd(int N, const long dims[N], const long blk[N], complex float* dst, complex float* src1, const long dim2[N], complex float* src2)
{
long ndims[2 * N];
long L[2 * N];
long ndim2[2 * N];
long ndim3[2 * N];
for (int i = 0; i < N; i++) {
assert(0 == dims[i] % blk[i]);
assert(dim2[i] <= blk[i]);
ndims[i * 2 + 1] = dims[i] / blk[i];
ndims[i * 2 + 0] = blk[i];
L[i * 2 + 1] = dims[i] / blk[i];
L[i * 2 + 0] = blk[i] + dim2[i] - 1;
ndim2[i * 2 + 1] = 1;
ndim2[i * 2 + 0] = dim2[i];
ndim3[i * 2 + 1] = dims[i] / blk[i] + 1;
ndim3[i * 2 + 0] = blk[i];
}
long T = md_calc_size(2 * N, L);
complex float* tmp = xmalloc(T * 8);
// conv_causal_extend(2 * N, L, tmp, ndims, src1, ndim2, src2);
conv(2 * N, ~0, CONV_EXTENDED, CONV_CAUSAL, L, tmp, ndims, src1, ndim2, src2);
// [------++++||||||||
//long str1[2 * N];
long str2[2 * N];
long str3[2 * N];
//md_calc_strides(2 * N, str1, ndims, 8);
md_calc_strides(2 * N, str2, L, 8);
md_calc_strides(2 * N, str3, ndim3, 8);
md_clear(2 * N, ndim3, dst, CFL_SIZE);
md_zadd2(2 * N, L, str3, dst, str3, dst, str2, tmp);
free(tmp);
}
struct linop_s* linop_sampling_create(const long dims[DIMS], const long pat_dims[DIMS], const complex float* pattern)
{
PTR_ALLOC(struct sampling_data_s, data);
SET_TYPEID(sampling_data_s, data);
md_copy_dims(DIMS, data->pat_dims, pat_dims);
md_select_dims(DIMS, ~MAPS_FLAG, data->dims, dims); // dimensions of kspace
md_calc_strides(DIMS, data->strs, data->dims, CFL_SIZE);
md_calc_strides(DIMS, data->pat_strs, data->pat_dims, CFL_SIZE);
data->pattern = (complex float*)pattern;
#ifdef USE_CUDA
data->gpu_pattern = NULL;
#endif
const long* dims2 = data->dims;
return linop_create(DIMS, dims2, DIMS, dims2, CAST_UP(PTR_PASS(data)), sampling_apply, sampling_apply, sampling_apply, NULL, sampling_free);
}
/*
* Nuclear norm calculation for arbitrary block sizes
*/
float lrnucnorm(const struct operator_p_s* op, const complex float* src)
{
struct lrthresh_data_s* data = (struct lrthresh_data_s*)operator_p_get_data(op);
long strs1[DIMS];
md_calc_strides(DIMS, strs1, data->dims_decom, 1);
float nnorm = 0.;
for (int l = 0; l < data->levels; l++) {
const complex float* srcl = src + l * strs1[LEVEL_DIM];
// Initialize
long blkdims[DIMS];
long blksize = 1;
for (unsigned int i = 0; i < DIMS; i++) {
blkdims[i] = data->blkdims[l][i];
blksize *= blkdims[i];
}
// Special case if blocksize is 1
if (blksize == 1) {
for (long j = 0; j < md_calc_size(DIMS, data->dims); j++)
nnorm += 2 * cabsf(srcl[j]);
continue;
}
// Initialize data
struct svthresh_blockproc_data* svdata = svthresh_blockproc_create(data->mflags, 0., 0);
// Initialize tmp
complex float* tmp;
#ifdef USE_CUDA
tmp = (data->use_gpu ? md_alloc_gpu : md_alloc)(DIMS, data->dims, CFL_SIZE);
#else
tmp = md_alloc(DIMS, data->dims, CFL_SIZE);
#endif
// Copy to tmp
//debug_print_dims(DP_DEBUG1, DIMS, data->dims);
md_copy(DIMS, data->dims, tmp, srcl, CFL_SIZE);
// Block SVD Threshold
nnorm = blockproc(DIMS, data->dims, blkdims, (void*)svdata, nucnorm_blockproc, tmp, tmp);
// Free tmp
free(svdata);
md_free(tmp);
}
return nnorm;
}
const struct linop_s* linop_fmac_create(unsigned int N, const long dims[N],
unsigned int oflags, unsigned int iflags, unsigned int tflags, const complex float* tensor)
{
PTR_ALLOC(struct fmac_data, data);
SET_TYPEID(fmac_data, data);
data->N = N;
data->dims = *TYPE_ALLOC(long[N]);
md_copy_dims(N, data->dims, dims);
data->idims = *TYPE_ALLOC(long[N]);
data->istrs = *TYPE_ALLOC(long[N]);
md_select_dims(N, ~iflags, data->idims, dims);
md_calc_strides(N, data->istrs, data->idims, CFL_SIZE);
data->odims = *TYPE_ALLOC(long[N]);
data->ostrs = *TYPE_ALLOC(long[N]);
md_select_dims(N, ~oflags, data->odims, dims);
md_calc_strides(N, data->ostrs, data->odims, CFL_SIZE);
data->tstrs = *TYPE_ALLOC(long[N]);
data->tdims = *TYPE_ALLOC(long[N]);
md_select_dims(N, ~tflags, data->tdims, dims);
md_calc_strides(N, data->tstrs, data->tdims, CFL_SIZE);
data->tensor = tensor;
#ifdef USE_CUDA
data->gpu_tensor = NULL;
#endif
long odims[N];
md_copy_dims(N, odims, data->odims);
long idims[N];
md_copy_dims(N, idims, data->idims);
return linop_create(N, odims, N, idims,
CAST_UP(PTR_PASS(data)), fmac_apply, fmac_adjoint, NULL,
NULL, fmac_free_data);
}
void data_consistency(const long dims[DIMS], complex float* dst, const complex float* pattern, const complex float* kspace1, const complex float* kspace2)
{
assert(1 == dims[MAPS_DIM]);
long strs[DIMS];
long dims1[DIMS];
long strs1[DIMS];
md_select_dims(DIMS, ~COIL_FLAG, dims1, dims);
md_calc_strides(DIMS, strs1, dims1, CFL_SIZE);
md_calc_strides(DIMS, strs, dims, CFL_SIZE);
complex float* tmp = md_alloc_sameplace(DIMS, dims, CFL_SIZE, dst);
md_zmul2(DIMS, dims, strs, tmp, strs, kspace2, strs1, pattern);
md_zsub(DIMS, dims, tmp, kspace2, tmp);
md_zfmac2(DIMS, dims, strs, tmp, strs, kspace1, strs1, pattern);
md_copy(DIMS, dims, dst, tmp, CFL_SIZE);
md_free(tmp);
}
/**
* Singular Value Thresholding
*
* @param M - matrix column size
* @param N - matrix row size
* @param lambda - regularization parameter
* @param A - input/output matrix
*/
float svthresh(long M, long N, float lambda, complex float* dst, const complex float* src) //FIXME: destroys input
{
long minMN = MIN(M,N);
long dimsU[3] = {M,minMN,1};
long dimsVT[3] = {minMN,N,1};
long dimsS[3] = {minMN,1,1};
// long dimsAA[3] = {minMN, minMN,1};
long strsVT[3];
long strsS[3];
md_calc_strides(3, strsVT, dimsVT, CFL_SIZE);
md_calc_strides(3, strsS, dimsS, FL_SIZE);
complex float* U = md_alloc_sameplace(3, dimsU, CFL_SIZE, src);
complex float* VT = md_alloc_sameplace(3, dimsVT, CFL_SIZE, src );
float* S = md_alloc_sameplace(3, dimsS, FL_SIZE, src);
// complex float* AA = md_alloc_sameplace(3, dimsAA, CFL_SIZE, src );
// lapack_normal_multiply( M, N, (M > N), (complex float (*) [])AA, (const complex float (*) [])src );
// SVD
lapack_svd_econ(M, N, (complex float (*) []) U, (complex float (*) []) VT, S, (complex float (*) [N])src);
// Thresh S
md_softthresh(3, dimsS, lambda, 0, S, S);
// VT = S * VT
md_mul2( 3, dimsVT, strsVT, (float*) VT, strsVT, (float*) VT, strsS, S );
md_mul2( 3, dimsVT, strsVT, ((float*) VT)+1, strsVT, ((float*) VT)+1, strsS, S );
// dst = U * VT
blas_matrix_multiply( M, N, minMN, (complex float (*) [N])dst, (const complex float (*) [minMN])U, (const complex float (*) [N])VT );
md_free(U);
md_free(VT);
md_free(S);
return 0;
}
static struct sum_data* sum_create_data( const long imgd_dims[DIMS], bool use_gpu )
{
PTR_ALLOC(struct sum_data, data);
// decom dimensions
md_copy_dims(DIMS, data->imgd_dims, imgd_dims);
md_calc_strides(DIMS, data->imgd_strs, imgd_dims, CFL_SIZE);
// image dimensions
data->levels = imgd_dims[LEVEL_DIM];
md_select_dims(DIMS, ~LEVEL_FLAG, data->img_dims, imgd_dims);
md_calc_strides(DIMS, data->img_strs, data->img_dims, CFL_SIZE);
data->tmp = NULL;
data->use_gpu = use_gpu;
return data;
}
