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218 lines
9.0 KiB
Matlab
218 lines
9.0 KiB
Matlab
%% TEMPLATE FOR AUTOMATIC TOMOGRAPHY CODE TESTS
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% test uses synthetic data to run all templates under well controlled
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% conditions, use setting if you want to add noise or other difficulties to
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% be tested during alignment
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cd(fullfile( fileparts(mfilename('fullpath')), '..'))
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addpath('tests')
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addpath('utils')
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addpath('./')
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addpath(find_base_package)
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%%%%%%%%%%%%%%%%%%%%%%%%%
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%%% Edit this section %%%
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%%%%%%%%%%%%%%%%%%%%%%%%%
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tested_templates = 1:3; % IDs of the tested templates
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templates_list ={ 'template_tomo_recons', ...
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'template_tomo_recons_lamino', ...
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'template_tomo_nonrigid', ...
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'template_tomo_recons_deprecated'...
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};
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verbose_level = -1; % -1 = keep very quiet the reconstructions
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% artificial data settings
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Npix_vol = [200,200,200] ;
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undersampling = 1; % level of undersampling compared to Crowther criterion
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noise_level = 0; % relative noise level with respect to the maximal phase value in the projections
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N_subtomos = 4;
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add_residual_layer = false; % add a thin metal-like layer to test behaviour with residua
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Nangles = ceil(pi/2*Npix_vol(1)) / undersampling;
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Nangles = ceil(Nangles/N_subtomos)*N_subtomos; % make splitable for 4 subtomos
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asize = ceil(Npix_vol(1:2) / 10); % size of the simulated probe
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if ~exist('GPU_id', 'var'); GPU_id = [1]; end
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if ~exist('base_path', 'var'); base_path = '../'; end
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%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%
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assert(all(GPU_id <= gpuDeviceCount), 'Select valid GPU id in GPU_id')
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utils.verbose(verbose_level)
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setenv('TMP',[base_path,'/tmp']) % TEMP for matlab scripts
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%% MAKE A PHANTOM
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utils.verbose(-1,'Creating phantom')
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rng default
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volData = randn(Npix_vol - asize(1), 'single');
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volData = (0.5+0.5*(utils.imgaussfilt3_fft(volData, 3) > 0)) .* ...
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(utils.imgaussfilt3_fft(volData, 10) > 0);
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volData = utils.imgaussfilt3_conv(volData, 0.6); % prevent too sharp edges
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if add_residual_layer
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% add kind of metalic layer to test robustness of the codes
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[X,Y,Z] = meshgrid(-Npix_vol(1)/2:Npix_vol(1)/2-1,-Npix_vol(2)/2:Npix_vol(2)/2-1,-Npix_vol(3)/2:Npix_vol(3)/2-1);
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layer = abs(0.1*X + 0.5*Y+0.2*Z + 50*utils.imgaussfilt3_fft(randn(Npix_vol, 'single'),10) )<0.5;
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volData = volData + 10*utils.crop_pad_3D(layer, size(volData));
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end
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volData = utils.apply_3D_apodization(volData, 0, Npix_vol(1)/5, 1);
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volData = utils.crop_pad_3D(volData, Npix_vol);
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for tested_template = templates_list(tested_templates)
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utils.verbose(struct('prefix', 'init'))
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%% test stage 0: load basic configuration parameters
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utils.verbose(-1,'Loading template "%s"', tested_template{1})
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if strcmpi(tested_template{1}, 'template_tomo_nonrigid')
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%nonrigid tomo has data generation already included in the template
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debug(1)
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run(tested_template{1})
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else
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par = struct();
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par.lamino_angle = 90; % default setting
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% set debugging info level and marks
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debug(1)
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warning('off', 'MATLAB:mpath:nameNonexistentOrNotADirectory')
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warning('off', 'MATLAB:dispatcher:pathWarning')
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run(tested_template{1})
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utils.verbose(-1,'Creating data')
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% create "data"
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if ~par.is_laminography
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theta = pi+linspace(0, 180*(1-1/Nangles), Nangles);
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else
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Nangles = Nangles * 2;
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theta = pi+linspace(0, 360*(1-1/Nangles), Nangles);
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end
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% create "N_subtomos" subtomos
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theta = reshape(reshape(theta, N_subtomos,[])',1,[]);
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par.subtomos = reshape(ones(Nangles/N_subtomos,N_subtomos).*[1:N_subtomos],1,[]);
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% Add noise and offsets to the measured positions to make the
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% alignment more difficult
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position_errors = (0.1*randn(Nangles,2) + 0.1*sind(3*theta')) * Npix_vol(3);
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asize = asize + ceil(max(asize, max(abs(position_errors)))/32)*32; % avoid the sample going out of FOV
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par.asize = asize;
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if par.lamino_angle == 90
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Npix_proj = [Npix_vol(3), ceil(sqrt(2)*Npix_vol(1))]+asize;
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max_sample_height = inf;
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else
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Npix_proj = ceil(sqrt(2)*Npix_vol([3,1]) .* [cosd(par.lamino_angle), 1] )+asize;
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max_sample_height = 5e-6 ;
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end
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% provide other parameters required by the template
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par.factor = 1;
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par.factor_edensity = 1;
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par.pixel_size = 50e-9;
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par.scans_string = '';
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par.output_folder = '???'; % some nonexistent folder, in default the template should not write any data during debug mode
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obj_interf_pos_x = 0;
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obj_interf_pos_y = 0;
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delta_stack_prealign = [] ;
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par.tilt_angle = 0;
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par.skewness_angle = 0;
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par.lambda = 0.2e-9;
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par.scanstomo = 1:Nangles;
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par.air_gap = [5,5];
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par.GPU_list = GPU_id;
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par.nresidua_per_frame = 0;
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% generate geometry
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Npix_vol(3) = min(Npix_vol(3),ceil(max_sample_height / par.pixel_size)-1);
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CoR = Npix_proj/2 + position_errors;
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[cfg, vectors] = astra.ASTRA_initialize(Npix_vol, Npix_proj, theta, par.lamino_angle, 'rotation_center', CoR);
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% find optimal split, for small volumes below 600^3 no split is needed
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split = astra.ASTRA_find_optimal_split(cfg);
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par.illum_sum = ones(Npix_proj);
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% generate complex projections
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stack_object = tomo.Ax_sup_partial(utils.crop_pad_3D(volData, Npix_vol), cfg, vectors, split);
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stack_object = stack_object / math.sp_quantile(stack_object, 0.99, 10);
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if noise_level>0; stack_object = stack_object + noise_level * randn(size(stack_object)); end
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stack_object = exp(-0.1*stack_object - 4i*stack_object);
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object = stack_object(:,:,1);
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if strcmpi(tested_template, 'template_tomo_recons_lamino')
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% create errors in global geometry -> test automatic refinement
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par.tilt_angle = -0.5;
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par.skewness_angle = 0.5;
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else
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par.tilt_angle = 0;
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par.skewness_angle = 0;
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end
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%% test stage 1: load test data and continue with the remplate
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utils.verbose(-1,'Loading template "%s"', tested_template{1})
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debug(2)
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utils.verbose(struct('prefix', 'template'))
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run(tested_template{1})
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% check results of the geometry refinement provided by tests
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if strcmpi(tested_template, 'template_tomo_recons_lamino')
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assert(abs(par.tilt_angle) < 0.1 && abs(par.skewness_angle) < 0.1, 'Geometry refinement in laminography did not work well')
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end
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end
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clearvars -except par tested_templates Nangles volData Npix_vol asize N_subtomos GPU_id noise_level test_astra test_mex_function test_simulated_data test_real_data base_path
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end
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2017 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
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%
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% If this code, or subfunctions or parts of it, is used for research in a
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% publication or if it is fully or partially rewritten for another
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% computing language the authors and institution should be acknowledged
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% in written form in the publication: “Data processing was carried out
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% using the “cSAXS matlab package” developed by the CXS group,
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
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% proper use and the correctness of the results.
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