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https://github.com/c-sooyoung/fold_slice.git
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299 lines
12 KiB
Matlab
299 lines
12 KiB
Matlab
%DM Difference-Map algorithm
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%
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% [self, cache, psi_dash, fourier_error ] = DM(self,par,cache,psi_dash,fourier_error, iter)
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%
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%
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% ** self structure containing inputs: e.g. current reconstruction results, data, mask, positions, pixel size, ..
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% ** par structure containing parameters for the engines
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% ** psi_dash complex projection from previous iteration, or emppty in first iteration
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% ** cache structure with precalculated values to avoid unnecessary overhead
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% ** fourier_error array [Npos,1] containing evolution of reconstruction error
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% ** iter current iteration number
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%
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% returns:
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% ++ self self-like structure with final reconstruction
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% ++ cache structure with precalculated values to avoid unnecessary overhead
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% ++ psi_dash complex projection from previous iteration, or emppty in first iteration
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% ++ fourier_error array [Npos,1] containing evolution of reconstruction error
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%
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% Publications most relevant to the Difference-Map implementation
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% + P. Thibault, M. Dierolf, A. Menzel, O. Bunk, C. David, F. Pfeiffer,
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% "High-Resolution Scanning X-ray Diffraction Microscopy," Science 321, 379-382 (2008)
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% + P. Thibault, M. Dierolf, O. Bunk, A. Menzel, F. Pfeiffer,
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% "Probe retrieval in ptychographic coherent diffractive imaging,"
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% Ultramicroscopy 109, 338–343 (2009)
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function [self, cache, psi_dash, fourier_error ] = DM(self,par,cache,psi_dash,fourier_error, iter)
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import utils.*
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import math.*
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import engines.GPU_MS.shared.*
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import engines.GPU_MS.GPU_wrapper.*
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psi = cell(par.Nmodes, 1);
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Psi = cell(par.Nmodes, 1);
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%%%%%%%%%%%%%%%%%%%%%%%%% Difference maps algorithm %%%%%%%%%%%%%%%%%%%
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beta = 1;
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gamma = 1;
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relax_mask = 1; % smoothly change relaxation of the mask
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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probe_norm = norm2(self.probe{1});
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object_modes = length(self.object);
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probe_amp_corr = [0,0];
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for ll = 1:par.object_modes
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obj_proj{ll} = Gzeros([self.Np_p, 0], true);
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end
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for ll = 1:object_modes
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obj_illum{ll,1} = Gzeros(self.Np_o);
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obj_update{ll,1} = Gzeros(self.Np_o, true);
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end
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for ll = 1:par.probe_modes
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probe_illum{ll} = Gzeros(size(self.probe{ll}));
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probe_update{ll} = Gzeros(size(self.probe{ll}), true);
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end
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% use precalculated blocks to be solved in parallel
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indices = cache.preloaded_indices_simple{1}.indices;
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scan_ids = cache.preloaded_indices_simple{1}.scan_ids;
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Nind = length(indices);
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p_ind = cell(max(par.probe_modes, par.object_modes),1);
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for jj = 1:Nind
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g_ind = indices{jj};
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for ll = 1:max(par.probe_modes, par.object_modes)
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if par.share_probe || ll > 1 % share incoherent modes
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p_ind{ll} = 1;
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else
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if all(scan_ids{jj} == scan_ids{jj}(1))
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p_ind{ll} = scan_ids{jj}(1);
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else
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p_ind{ll} = scan_ids{jj};
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end
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end
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end
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% load on GPU if needed
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if ~par.keep_on_gpu
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for ll = 1:max(par.probe_modes, par.object_modes)
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try; psi_dash{ll,jj} = Garray(psi_dash{ll,jj}); end
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end
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end
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%% fourier propagation
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for ll = 1:par.object_modes
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obj_proj{ll} = get_views(self.object, obj_proj{ll},1,ll, g_ind, cache, scan_ids{jj},[]);
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end
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for ll = 1:max(par.probe_modes, par.object_modes)
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probe{ll} = self.probe{min(ll,end)}(:,:,p_ind{ll});
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psi{ll} = bsxfun(@times, obj_proj{min(ll, end)}, probe{ll});
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if isempty(psi_dash{ll,jj}); psi_dash{ll,jj} = psi{ll}; end % initial guess
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% P_M (P_0(psi))
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Psi{ll} = Gfun(@DM_update_psi, gamma,psi{ll}, psi_dash{ll,jj} );
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Psi{ll} = fwd_fourier_proj(Psi{ll}, self.modes{min(ll,end)} );
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end
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%% load data to GPU (if not loaded yet)
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modF = get_modulus(self, cache, g_ind,true,jj);
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mask = get_mask(self, cache.mask_indices, g_ind);
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% get intensity (modulus) on detector including different corrections
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aPsi = get_reciprocal_model(self, Psi, modF, mask,iter, g_ind, par,cache);
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if iter > 0 && (par.get_error && (mod(iter,min(20, 2^(floor(2+iter/50)))) == 0 || iter < 20) || iter == par.number_iterations )
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[fourier_error(iter,g_ind)] = get_fourier_error(modF, aPsi, [],mask);
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end
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if ~isempty(mask)
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mask = single(1)-mask;
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mask = relax_mask + (min(relax_mask, par.pfft_relaxation) - relax_mask ) * mask;
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else
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mask = par.pfft_relaxation;
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end
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if iter == 0
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% in the first iteration only find optimal scale for the probe
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probe_amp_corr(1) = probe_amp_corr(1) + Ggather(sum(modF(:).^2));
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probe_amp_corr(2) = probe_amp_corr(2) + Ggather(sum(aPsi(:).^2));
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for ll = 1:size(psi_dash,2); psi_dash{ll,jj} = []; end
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continue
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end
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%% fourier (modulus) contraint
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Psi = modulus_constraint(modF,aPsi,Psi, mask, [], par, 0 );
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aPsi = []; modF = []; mask = [];
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for ll = 1:max(par.probe_modes, par.object_modes)
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Psi{ll} = back_fourier_proj(Psi{ll}, self.modes{min(end,ll)});
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psi_dash{ll,jj} = Gfun(@DM_update, psi_dash{ll,jj} ,beta, Psi{ll},psi{ll});
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end
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Psi = [];
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% get back from GPU if required
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if ~par.keep_on_gpu
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for ll = 1:max(par.probe_modes, par.object_modes)
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psi_dash{ll,jj} = Ggather(psi_dash{ll,jj});
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end
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end
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end
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if iter == 0
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% apply initial correction for the probe intensity and return
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probe_amp_corr = sqrt(probe_amp_corr(1) / probe_amp_corr(2)); %% calculate ratio between modF^2 and aPsi^2
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for ii = 1:par.probe_modes
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self.probe{ii} = self.probe{ii}*probe_amp_corr;
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end
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psi_dash = cell(size(psi_dash));
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verbose(2,'Probe amplitude corrected by %.3g',probe_amp_corr)
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return
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end
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%% iterative solver of the overlap constraint, important for initial convergence
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for kk = 1:10
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for ll = 1:object_modes
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obj_illum{ll}(:) = 0;
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obj_update{ll}(:) = 0i;
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end
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for ll = 1:par.probe_modes
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probe_illum{ll}(:) = 0;
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probe_update{ll}(:) = 0i;
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end
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probe_0 = self.probe;
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%% obj_update , obj_illum,probe_update,probe_illum is not reset to make it more stable
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for jj = 1:length(indices)
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for ll = 1:max(par.probe_modes, par.object_modes)
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if par.share_probe || ll > 1 % share incoherent modes
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p_ind{ll} = 1;
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else
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if all(scan_ids{jj} == scan_ids{jj}(1))
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p_ind{ll} = scan_ids{jj}(1);
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else
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p_ind{ll} = scan_ids{jj};
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end
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end
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end
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for ll = 1:par.probe_modes
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probe{ll} = self.probe{ll}(:,:,p_ind{ll});
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cprobe{ll} = conj(probe{ll});
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aprobe{ll} = real(probe{ll}.*cprobe{ll});
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end
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% move to GPU (if not there yet)
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for ll = 1:max(par.probe_modes, par.object_modes)
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psi_dash{ll,jj} = Garray(psi_dash{ll,jj});
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end
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g_ind = indices{jj};
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for ll = 1:par.object_modes
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obj_proj{ll} = get_views(self.object, obj_proj{ll},1,ll, g_ind, cache, scan_ids{jj},[]);
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end
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if iter >= par.probe_change_start
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for ll = 1:par.probe_modes
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%% update probe
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[probe_update{ll},probe_illum{ll}] = QQ_probe(psi_dash{ll,jj}, obj_proj{min(end,ll)}, probe_update{ll},probe_illum{ll}, p_ind{ll});
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end
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end
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if iter >= par.object_change_start
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%% update object
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[obj_update,obj_illum] = QQ_object(psi_dash{ll,jj}, obj_update,obj_illum, aprobe{min(ll,end)}, cprobe{min(ll,end)}, g_ind,min(ll, object_modes),scan_ids{jj},cache);
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end
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% get back from GPU if required
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if ~par.keep_on_gpu
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for ll = 1:max(par.probe_modes, par.object_modes)
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psi_dash{ll,jj} = Ggather(psi_dash{ll,jj});
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end
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end
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end
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for ll = 1:max([par.probe_modes, object_modes])
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if iter >= par.probe_change_start && ll <= par.probe_modes
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% add some inertia to prevent oscilations
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self.probe{ll} = update_probe(self, self.probe{ll} , probe_update{ll} , probe_illum{ll} , par, ll);
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end
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if iter >= par.object_change_start && ll <= object_modes
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self.object{ll} = Gfun(@update_object, self.object{ll}, obj_update{ll}, obj_illum{ll}, cache.MAX_ILLUM(ll)*1e-4, par.probe_inertia);
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end
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end
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if iter > par.probe_change_start
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% if both object and probe are recontructed, solve the
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% realspace constraint iterativelly
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min_iter = 1 + par.keep_on_gpu; % if par.keep_on_gpu==true, then the code is so slow that it is not worthy skip the norm calculation
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min_change = 0.01;
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if kk >= min_iter || verbose >= 2
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dprobe = max(norm2(self.probe{1} - probe_0{1}) ./ probe_norm);
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verbose(2,'Update probe difference: %3.2f%%', dprobe*100)
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end
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if kk >= min_iter && dprobe < min_change % change is below 1% and at least 2 iterations were done
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break
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end
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end
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end
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if verbose > 2
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for kk = 1:object_modes
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Nresid = sum2(utils.findresidues(self.object{kk}(cache.object_ROI{:})) > 0.1);
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if Nresid > 0
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verbose(1,'Number of residua in object %i: %i', kk, Nresid)
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end
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end
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end
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end
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function [probe_update,probe_illum] = QQ_probe(psi, obj_proj, probe_update,probe_illum, p_ind)
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import engines.GPU_MS.GPU_wrapper.*
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%% update probe
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[upd, illum] = Gfun(@QQ_probe_Gfun, psi,obj_proj);
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if size(probe_update,3)==1 % shared probe
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probe_update = probe_update+sum(upd,3);
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probe_illum = probe_illum+sum(illum,3);
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else
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probe_update(:,:,p_ind) = probe_update(:,:,p_ind)+sum(upd,3);
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probe_illum(:,:,p_ind) = probe_illum(:,:,p_ind)+sum(illum,3);
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end
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end
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function norm = get_probe_norm_aux(P0, P1)
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norm = abs(P0-P1).^2;
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end
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function [upd, illum] = QQ_probe_Gfun(psi,proj)
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upd = psi .* conj(proj) ;
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illum = abs(proj).^2;
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end
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function [obj_update,obj_illum] = QQ_object(psi,obj_update,obj_illum, aprobe, cprobe, g_ind,ll,scan_ids,cache)
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import engines.GPU_MS.shared.*
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%% update object
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psi = psi .* cprobe;
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[obj_update,obj_illum] = set_views_rc(obj_update,obj_illum,psi,aprobe,1,ll, g_ind, cache, scan_ids,[]);
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end
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function psi = DM_update_psi(gamma,psi, psi_dash )
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% real space update function for difference maps
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psi = (1+gamma)*psi - gamma*psi_dash;
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end
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function psi_dash = DM_update(psi_dash,beta, psi_tmp,psi )
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% update funciton for difference maps
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psi_dash = psi_dash + beta * ( psi_tmp - psi ) ;
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end
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function object = update_object(object, object_upd, object_illum, delta, inertia)
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% apply also some inertia in the object update
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object = object*inertia + (1-inertia)*object_upd./ (object_illum+delta);
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end
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function probe = update_probe(self, probe, probe_update, probe_illum, par, probe_id)
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import engines.GPU_MS.shared.*
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probe_new = probe_update ./ (probe_illum+1e-6);
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% apply probe support on the first probe mode
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if probe_id == 1
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probe_new = apply_probe_contraints(probe_new, self.modes{probe_id});
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end
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% add some inertia to prevent oscilations
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probe = par.probe_inertia*probe + (1-par.probe_inertia)*probe_new;
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end
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