inseti: example
Example of input parameters to run start not with default parameters.
Contents
Description
If you want to run start not with the default parameters you can set the fields in struct seti in this or another file in the folder inseti and refer to this file by Parameter inseti.
Attention in usage of the framework
- start calls setInput, in which pre-defined variables (except closed test and inseti) are deleted.
- Therefore you must define the struct seti in such a file (and not in terminal).
- The name of a new file in inseti must differ from existing functions (because the file in inseti is called by eval).
Syntax and Example
inseti = 'example';
start
Input Parameters of struct seti
Note that this are some, but not all input parameters.
% -- dirname: suffix seti.dirSuffix = '_test'; % Suffix of the folder created in folder |output| to store the results % -- setGrid seti.dim = 2; % dimension of scattering problem (2 or 3) % Make sure to choose a suitable contrast in seti.contrast. seti.rCD = 0.2; % size of computational domain |[-rCD,rCD]^dim| seti.nCD = 256; % number of discretization points in each dimension % -- setKernel seti.k = 250; % wave number seti.model = 'helmholtz'; % input helmholtz will choose automatically % helmholtz2D or helmholtz3D dependent on the dim % -- setContrast seti.contrast = 'cornerBallSparse2D'; % Set the name of contrast function as string (files in folder |incontrasts|). % Make sure to choose the correct dimension of the problem in |seti.dim|. % A list of available contrasts is in setContrast. % -- expSetup (set experimental set-up) seti.incPntsType = 'circle'; % Geometry: type of transmitters seti.measPntsType = 'circle'; % Geometry: type of receivers seti.incNb = 35; % Geometry: number of transmitters seti.measNb = 35; % Geometry: number of receivers seti.radSrc = 5; % Geometry: radius of sphere containing transmitters seti.radMeas = 5; % Geometry: radius of sphere containing receivers % Fore more details of geometry type circle and further geometries like square and borehole, see |pntsGeometry|. seti.incType = 'pointSource'; % Type of incident fields: 'pointSource' or 'planeWave' seti.measType = 'nearField'; % Type of measurements: 'nearField' or 'farField' % -- reconstruction seti.invNo = 6; % Do not change in published code (no other option). seti.delta = 0.01; % Relative noise level (for noisy simulated data and assumed in reconstruction process to stop by discrepancy principle) seti.physBounds = [-1,3,0,3]; % Bounds for real/imaginary part of contrast: [reMin, reMax, imMin, imMax] seti.alpha = 500; % Regularization parameter of sparse penalty term seti.beta = 1E-5; % Regularization parameter of total variation penalty term seti.useDis = 1; % 1, then discrepancy principle is used to stop reconstruction process (outer iteration) seti.tau = 2.5; % Discrepancy principle stops at parameter \tau \delta seti.nOut = 30; % Maximal number of reconstruction steps (outer iteration) % -- reconstruction with PDA seti.pdaN = 50; % number of inner iteration steps (PDA) seti.pdaStepsize = 'fix'; % how primal and dual stepsizes in pda are choosen % 'fix' (tau = sigma = 1/L). % In our experience you should not change it. % -- figures and files seti.plotFreq = 1; % Frequency to plot outer iteration (0: no plot) seti.plotPublish = 1; % 1: plot design for publication (e.g. without title) % see plot2DstylePublish.m and plot3DstylePublish.m seti.usecbarlim = 1; % 1: set limits of colorbar manually (0: automatically) seti.cbarlim = [-0.2, 1.4]; % limits vor colorbars [cbarmin, cbarmax] seti.savepng = 1; % 0 or 1, save figures as *.png (default: 1) seti.saveepsc = 0; % 0 or 1, save figures as colored *.eps (default: 0) seti.savefig = 0; % 0 or 1, save figures as *.fig (default: 0) seti.savedata = 1; % 0 or 1, saves relative discrepancy, error % and difference of computed contrast to its predecessor % as save_dis.mat, save_err.mat and % save_dif.mat in folder output.
More About
- rCD: In comparison to a similar Parameter
in the Manuscript, see [1], we have the relation:
= rCD/2 = 0.1.
References
[1] Florian Bürgel, Kamil S. Kazimierski, and Armin Lechleiter. A sparsity regularization and total variation based computational framework for the inverse medium problem in scattering. Journal of Computational Physics, 339:1-30, 2017. URL: https://doi.org/10.1016/j.jcp.2017.03.011.