Exemple #1
0
struct nlop_s* nlop_chain(const struct nlop_s* a, const struct nlop_s* b)
{
	assert(1 == nlop_get_nr_in_args(a));
	assert(1 == nlop_get_nr_out_args(a));
	assert(1 == nlop_get_nr_in_args(b));
	assert(1 == nlop_get_nr_out_args(b));

	const struct linop_s* la = linop_from_nlop(a);
	const struct linop_s* lb = linop_from_nlop(b);

	if ((NULL != la) && (NULL != lb))
		return nlop_from_linop(linop_chain(la, lb));

	PTR_ALLOC(struct nlop_s, n);

	const struct linop_s* (*der)[1][1] = TYPE_ALLOC(const struct linop_s*[1][1]);
	n->derivative = &(*der)[0][0];

	if (NULL == la)
		la = a->derivative[0];

	if (NULL == lb)
		lb = b->derivative[0];

	n->op = operator_chain(a->op, b->op);
	n->derivative[0] = linop_chain(la, lb);

	return PTR_PASS(n);
}
Exemple #2
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;
}
Exemple #3
0
const struct operator_s* sense_recon_create(const struct sense_conf* conf, const long dims[DIMS],
		  const struct linop_s* sense_op,
		  const long pat_dims[DIMS], const complex float* pattern,
		  italgo_fun2_t italgo, iter_conf* iconf,
		  unsigned int num_funs,
		  const struct operator_p_s* thresh_op[num_funs],
		  const struct linop_s* thresh_funs[num_funs],
		  const long ksp_dims[DIMS],
		  const struct operator_s* precond_op)
{
	struct lsqr_conf lsqr_conf = { conf->cclambda };

	const struct operator_s* op = NULL;


	long img_dims[DIMS];
	md_select_dims(DIMS, ~COIL_FLAG, img_dims, dims);


	if (conf->rvc) {

		struct linop_s* rvc = rvc_create(DIMS, img_dims);
		struct linop_s* tmp_op = linop_chain(rvc, sense_op);

		linop_free(rvc);
		linop_free(sense_op);
		sense_op = tmp_op;
	}

	assert(1 == conf->rwiter);

	if (NULL == pattern) {

		op = lsqr2_create(&lsqr_conf, italgo, iconf, sense_op, precond_op,
					num_funs, thresh_op, thresh_funs);

	} else {

		complex float* weights = md_alloc(DIMS, pat_dims, CFL_SIZE);	// FIXME: GPU
#if 0
		// buggy
//		md_zsqrt(DIMS, pat_dims, weights, pattern);
#else
		long dimsR[DIMS + 1];
		real_from_complex_dims(DIMS, dimsR, pat_dims);
		md_sqrt(DIMS + 1, dimsR, (float*)weights, (const float*)pattern);
#endif
		struct linop_s* weights_op = linop_cdiag_create(DIMS, ksp_dims, FFT_FLAGS, weights);	// FIXME: check pat_dims

		op = wlsqr2_create(&lsqr_conf, italgo, iconf,
						sense_op, weights_op, precond_op,
						num_funs, thresh_op, thresh_funs);
	}

	return op;
}
Exemple #4
0
/**
 * Create sense operator, y = F S x,
 * where F is the Fourier transform and S is the sensitivity maps
 *
 * @param max_dims maximal dimensions across all data structures
 * @param sens_flags active map dimensions
 * @param sens sensitivities
 * @param gpu TRUE if using gpu
 */
struct linop_s* sense_init(const long max_dims[DIMS], 
			unsigned int sens_flags, const complex float* sens, bool gpu)
{
	long ksp_dims[DIMS];
	md_select_dims(DIMS, ~MAPS_FLAG, ksp_dims, max_dims);

	struct linop_s* fft = linop_fft_create(DIMS, ksp_dims, FFT_FLAGS, gpu);
	struct linop_s* maps = maps_create(max_dims, sens_flags, sens, gpu);

	struct linop_s* sense_op = linop_chain(maps, fft);

	linop_free(fft);
	linop_free(maps);

	return sense_op;
}
static
const struct linop_s* sense_nc_init(const long max_dims[DIMS], const long map_dims[DIMS], const complex float* maps, const long ksp_dims[DIMS], const long traj_dims[DIMS], const complex float* traj, struct nufft_conf_s conf, _Bool use_gpu)
{
	long coilim_dims[DIMS];
	long img_dims[DIMS];
	md_select_dims(DIMS, ~MAPS_FLAG, coilim_dims, max_dims);
	md_select_dims(DIMS, ~COIL_FLAG, img_dims, max_dims);

	const struct linop_s* fft_op = nufft_create(DIMS, ksp_dims, coilim_dims, traj_dims, traj, NULL, conf, use_gpu);
	const struct linop_s* maps_op = maps2_create(coilim_dims, map_dims, img_dims, maps, use_gpu);

	const struct linop_s* lop = linop_chain(maps_op, fft_op);

	linop_free(maps_op);
	linop_free(fft_op);

	return lop;
}
Exemple #6
0
static
const struct linop_s* sense_nc_init(const long max_dims[DIMS], const long map_dims[DIMS], const complex float* maps, const long ksp_dims[DIMS], const long traj_dims[DIMS], const complex float* traj, struct nufft_conf_s conf, struct operator_s** precond_op)
{
	long coilim_dims[DIMS];
	long img_dims[DIMS];
	md_select_dims(DIMS, ~MAPS_FLAG, coilim_dims, max_dims);
	md_select_dims(DIMS, ~COIL_FLAG, img_dims, max_dims);

	const struct linop_s* fft_op = nufft_create(DIMS, ksp_dims, coilim_dims, traj_dims, traj, NULL, conf);
	const struct linop_s* maps_op = maps2_create(coilim_dims, map_dims, img_dims, maps);

	//precond_op[0] = (struct operator_s*) nufft_precond_create( fft_op );
	precond_op[0] = NULL;

	const struct linop_s* lop = linop_chain(maps_op, fft_op);

	linop_free(maps_op);
	linop_free(fft_op);

	return lop;
}
Exemple #7
0
void opt_reg_configure(unsigned int N, const long img_dims[N], struct opt_reg_s* ropts, const struct operator_p_s* prox_ops[NUM_REGS], const struct linop_s* trafos[NUM_REGS], unsigned int llr_blk, bool randshift, bool use_gpu)
{
	float lambda = ropts->lambda;

	if (-1. == lambda)
		lambda = 0.;

	// if no penalities specified but regularization
	// parameter is given, add a l2 penalty

	struct reg_s* regs = ropts->regs;

	if ((0 == ropts->r) && (lambda > 0.)) {

		regs[0].xform = L2IMG;
		regs[0].xflags = 0u;
		regs[0].jflags = 0u;
		regs[0].lambda = lambda;
		ropts->r = 1;
	}



	int nr_penalties = ropts->r;
	long blkdims[MAX_LEV][DIMS];
	int levels;


	for (int nr = 0; nr < nr_penalties; nr++) {

		// fix up regularization parameter
		if (-1. == regs[nr].lambda)
			regs[nr].lambda = lambda;

		switch (regs[nr].xform) {

			case L1WAV:
				debug_printf(DP_INFO, "l1-wavelet regularization: %f\n", regs[nr].lambda);

				if (0 != regs[nr].jflags)
					debug_printf(DP_WARN, "joint l1-wavelet thresholding not currently supported.\n");

				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);


				unsigned int wflags = 0;
				for (unsigned int i = 0; i < DIMS; i++) {

					if ((1 < img_dims[i]) && MD_IS_SET(regs[nr].xflags, i)) {

						wflags = MD_SET(wflags, i);
						minsize[i] = MIN(img_dims[i], 16);
					}
				}

				trafos[nr] = linop_identity_create(DIMS, img_dims);
				prox_ops[nr] = prox_wavelet3_thresh_create(DIMS, img_dims, wflags, minsize, regs[nr].lambda, randshift);
				break;

			case TV:
				debug_printf(DP_INFO, "TV regularization: %f\n", regs[nr].lambda);

				trafos[nr] = linop_grad_create(DIMS, img_dims, regs[nr].xflags);
				prox_ops[nr] = prox_thresh_create(DIMS + 1,
						linop_codomain(trafos[nr])->dims,
						regs[nr].lambda, regs[nr].jflags | MD_BIT(DIMS), use_gpu);
				break;

			case LLR:
				debug_printf(DP_INFO, "lowrank regularization: %f\n", regs[nr].lambda);

				// add locally lowrank penalty
				levels = llr_blkdims(blkdims, regs[nr].jflags, img_dims, llr_blk);

				assert(1 == levels);
				assert(levels == img_dims[LEVEL_DIM]);

				for(int l = 0; l < levels; l++)
#if 0
					blkdims[l][MAPS_DIM] = img_dims[MAPS_DIM];
#else
				blkdims[l][MAPS_DIM] = 1;
#endif

				int remove_mean = 0;

				trafos[nr] = linop_identity_create(DIMS, img_dims);
				prox_ops[nr] = lrthresh_create(img_dims, randshift, regs[nr].xflags, (const long (*)[DIMS])blkdims, regs[nr].lambda, false, remove_mean, use_gpu);
				break;

			case MLR:
#if 0
				// FIXME: multiscale low rank changes the output image dimensions 
				// and requires the forward linear operator. This should be decoupled...
				debug_printf(DP_INFO, "multi-scale lowrank regularization: %f\n", regs[nr].lambda);

				levels = multilr_blkdims(blkdims, regs[nr].jflags, img_dims, 8, 1);

				img_dims[LEVEL_DIM] = levels;
				max_dims[LEVEL_DIM] = levels;

				for(int l = 0; l < levels; l++)
					blkdims[l][MAPS_DIM] = 1;

				trafos[nr] = linop_identity_create(DIMS, img_dims);
				prox_ops[nr] = lrthresh_create(img_dims, randshift, regs[nr].xflags, (const long (*)[DIMS])blkdims, regs[nr].lambda, false, 0, use_gpu);

				const struct linop_s* decom_op = sum_create( img_dims, use_gpu );
				const struct linop_s* tmp_op = forward_op;
				forward_op = linop_chain(decom_op, forward_op);

				linop_free(decom_op);
				linop_free(tmp_op);
#else
				debug_printf(DP_WARN, "multi-scale lowrank regularization not yet supported: %f\n", regs[nr].lambda);
#endif

				break;

			case IMAGL1:
				debug_printf(DP_INFO, "l1 regularization of imaginary part: %f\n", regs[nr].lambda);

				trafos[nr] = linop_rdiag_create(DIMS, img_dims, 0, &(complex float){ 1.i });
				prox_ops[nr] = prox_thresh_create(DIMS, img_dims, regs[nr].lambda, regs[nr].jflags, use_gpu);
				break;

			case IMAGL2:
				debug_printf(DP_INFO, "l2 regularization of imaginary part: %f\n", regs[nr].lambda);

				trafos[nr] = linop_rdiag_create(DIMS, img_dims, 0, &(complex float){ 1.i });
				prox_ops[nr] = prox_leastsquares_create(DIMS, img_dims, regs[nr].lambda, NULL);
				break;

			case L1IMG:
				debug_printf(DP_INFO, "l1 regularization: %f\n", regs[nr].lambda);

				trafos[nr] = linop_identity_create(DIMS, img_dims);
				prox_ops[nr] = prox_thresh_create(DIMS, img_dims, regs[nr].lambda, regs[nr].jflags, use_gpu);
				break;

			case L2IMG:
				debug_printf(DP_INFO, "l2 regularization: %f\n", regs[nr].lambda);

				trafos[nr] = linop_identity_create(DIMS, img_dims);
				prox_ops[nr] = prox_leastsquares_create(DIMS, img_dims, regs[nr].lambda, NULL);
				break;

			case FTL1:
				debug_printf(DP_INFO, "l1 regularization of Fourier transform: %f\n", regs[nr].lambda);

				trafos[nr] = linop_fft_create(DIMS, img_dims, regs[nr].xflags);
				prox_ops[nr] = prox_thresh_create(DIMS, img_dims, regs[nr].lambda, regs[nr].jflags, use_gpu);
				break;
		}