function [result_viewer, result, post_result] = gtReconstructTestCase(test_data, det_index, use_ODF) if (~exist('det_index', 'var') || isempty(det_index)) det_index = 1; end if (~exist('use_ODF', 'var') || isempty(use_ODF)) use_ODF = 'none'; end rec_opts = gtReconstruct6DGetParamenters(test_data.parameters); if (~isfield(test_data, 'gv')) test_data.gv.dm = gtDefDmvol2Gvdm(test_data.dmvol); end gvdm = test_data.gv.dm(:, test_data.gv.used_ind); if (~isfield(test_data, 'intvol')) size_int_vol = [ ... size(test_data.dmvol, 1), ... size(test_data.dmvol, 2), ... size(test_data.dmvol, 3) ]; test_data.intvol = ones(size_int_vol, 'like', test_data.dmvol); end gvpow = test_data.intvol(test_data.gv.used_ind); gtGetMaxDisorientation(gvdm, [], 'diameter_average'); gtGetMaxDisorientation(gvdm, [], 'diameter_zero'); % f = figure(); % ax = axes('parent', f); % hold(ax, 'on') % scatter3(ax, gvdm(1, 1:10:end)', gvdm(2, 1:10:end)', gvdm(3, 1:10:end)', 20); sampler = GtOrientationSampling(test_data.parameters, test_data.grain,'detector_index', det_index); sampler.make_simple_grid_estim_ODF('cubic', rec_opts.grid_edge, false, 1); %rec_opts.ospace_oversize); % scatter3(ax, sampler.R_vectors{1}(:, 1), sampler.R_vectors{1}(:, 2), sampler.R_vectors{1}(:, 3), 20, 'r'); % drawnow(); ospace_bb = [min(gvdm, [], 2), max(gvdm, [], 2)]; sampler.make_res_even_simple_grid('cubic', rec_opts.grid_edge, ospace_bb, rec_opts.ospace_oversize); % scatter3(ax, sampler.R_vectors{1}(:, 1), sampler.R_vectors{1}(:, 2), sampler.R_vectors{1}(:, 3), 20, 'g'); % hold(ax, 'off') % drawnow(); if (rec_opts.ospace_super_sampling > 1) sampler.make_supersampling_simple_grid([1 2 3], rec_opts.ospace_super_sampling); end switch (use_ODF) case 'none' odf = []; case 'theo' % odf = gtGetODFFromGvdm(gvdm, sampler.lattice.gr, gvpow, 'nearest'); odf = gtGetODFFromGvdm(gvdm, sampler.lattice.gr, gvpow, 'linear'); end [algo, good_or] = gtReconstruct6DLaunchAlgorithm(sampler, rec_opts, ... test_data.parameters, 'det_index', det_index, 'ODF', odf); vols = algo.getCurrentSolution(); or_sizes = sampler.get_orientation_sampling_size(); [avg_R_vecs, avg_R_vecs_int, stddev_R_vecs] = sampler.getAverageOrientations(vols, good_or); avg_R_vec = sampler.getAverageOrientation(vols, good_or); s_g_odf = reshape(sampler.getODF(vols, good_or), or_sizes{1}); vol_size = size(avg_R_vecs_int); shift = gtFwdSimComputeVolumeShifts(test_data.grain.proj(det_index), test_data.parameters, vol_size); [kam, gam] = gtDefComputeKernelAverageMisorientation(avg_R_vecs, avg_R_vecs_int); [igm, gos] = gtDefComputeIntraGranularMisorientation(avg_R_vecs, avg_R_vecs_int, 'R_vector', test_data.grain.R_vector); % Restoring initial volume size (depending on the rounding) if (rec_opts.volume_downscaling > 1) fprintf('Expanding volumes..') c = tic(); avg_R_vecs_int = gtMathsUpsampleVolume(avg_R_vecs_int, rec_opts.volume_downscaling); avg_R_vecs = gtMathsUpsampleVolume(avg_R_vecs, rec_opts.volume_downscaling); stddev_R_vecs = gtMathsUpsampleVolume(stddev_R_vecs, rec_opts.volume_downscaling); kam = gtMathsUpsampleVolume(kam, rec_opts.volume_downscaling); igm = gtMathsUpsampleVolume(igm, rec_opts.volume_downscaling); vols = gtMathsUpsampleVolume(vols, rec_opts.volume_downscaling); fprintf('\b\b: Done (%f seconds).\n', toc(c)) end result = gt6DAssembleResult(test_data, sampler, vols); result.ODF6D = struct( ... 'voxels_avg_R_vectors', {avg_R_vecs}, ... 'intensity', {avg_R_vecs_int}, ... 'shift', {shift}, ... 'R_vectors', {sampler.get_R_vectors()}, ... 'voxels_stddev_R_vectors', {stddev_R_vecs}, ... 'single_grain_ODF', {s_g_odf}, ... 'single_grain_avg_R_vector', {avg_R_vec}, ... 'kernel_average_misorientation', {kam}, ... 'intra_granular_misorientation', {igm} ); post_result = gt6DPostProcessOrientationSpread(test_data, result, true); [proj_blobs, proj_spots] = algo.getProjectionOfCurrentSolution(); post_result.ODF6D = struct( ... 'orientation_volumes', {vols}, ... 'fwd_projected_blobs', {proj_blobs}, ... 'fwd_projected_spots', {proj_spots}, ... 'grain_average_misorientation', {gam}, ... 'grain_orientation_spread', {gos}, ... 'compute_statistics', {algo.get_statistics()} ); result_viewer = GtOrientationResultView(test_data, result, post_result, ... 'f_title', sprintf('Result Browser: algo "%s", det_id %d, ODF: "%s"', ... test_data.parameters.rec.grains.algorithm, det_index, use_ODF)); end