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