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structure.txt
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structure.txt
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Parameter estimation of seeding and contamination rates in a subcritical percolation model on a triangular lattice using the method of simulated moments (MSM). Code implementation in Matlab (The MathWorks, Inc.).
Reference:
Felix Beck, Bence Mélykúti.
Parameter estimation in a subcritical percolation model with colouring
arXiv:1604.08908
https://arxiv.org/abs/1604.08908
Dependencies:
An additional MATLAB file must be downloaded!
fminsearchbnd: fminsearchbnd behaves similarly to fminsearch, except you can add bound constraints.
source and description: http://de.mathworks.com/matlabcentral/fileexchange/8277-fminsearchbnd--fminsearchcon/content/FMINSEARCHBND/fminsearchbnd.m
author: John D'Errico
Authors:
Felix Beck, Bence Melykuti (University of Freiburg, Germany)
2015-2017
Code structure:
msm
createsynthdata_determ
createsynthdata_random_m2 (needed for method 2 only)
simcalcs
fminsearchbnd
optim
simulation_m1/simulation_m2
contamination
simcalcs
createsynthdata
createsynthdata_determ
createsynthdata_random_m2 (needed for method 2 only)
simulation_m1/simulation_m2
plot_figure
plot_preprocessing
plot_panel
plot_wells
plot_colorshift
plot_edges
latex_table
latex_table_header
latex_table_footer
latex_finddataset
plot_preprocessing
createsynthdata_determ
latex_block
latex_finddataset
latex_findestimate
latex_table5
latex_table_header
latex_table_footer
latex_block
latex_blockrow
latex_finddataset
latex_findestimate
plot_preprocessing
createsynthdata_determ
simcalcs
createsynthdata_random_m2
optim
simulation_m1/simulation_m2
contamination
simcalcs
latex_table6
latex_table_header
latex_table_footer
latex_row
latex_finddataset
plot_preprocessing
createsynthdata_determ
simcalcs
createsynthdata_random_m2
optim_norma
simulation_m1/simulation_m2
contamination
simcalcs
(latex_table.m, latex_table5.m, latex_table6.m contain some of their functions as well, such as latex_table_header, latex_table_footer, latex_block, latex_blockrow, latex_row. Those are not separate files.)
---
msm.m
Inputs: simstep_max, loops, mu_max, method
Outputs: [solutions, result, experiment_matrix]
Variables saved (optionally): 'estimators', 'time', 'errors', 'input_values', 'optimizations'
Displays: optimizations, absd, result{2}
---
createsynthdata.m
Inputs:
nrows, ncols, simstep_max, shape, lambda, mu, method
Outputs:
ncolors, wells_before_contamination, wells_after_contamination, open_edges, experiment_edgelist, max_vertices, max_edges, originalrows, shiftedrows, true_values, totalvertices, totaledgelocations
Variables saved (optionally):
'nrows', 'ncols', 'ncolors', 'simstep_max', 'shape',...
'wells_before_contamination', 'wells_after_contamination',...
'open_edges', 'experiment_edgelist', 'max_vertices', 'max_edges',...
'originalrows', 'shiftedrows', 'lambda', 'mu', 'method',...
'true_values', 'totalvertices', 'totaledgelocations');
Felix Beck's synthetic data files contain:
wells_before_contamination, wells_after_contamination, open_edges, max_edges, shape, true_values
---
Goals with plotting:
Figure 1: process explained on 4 panels:
1 seeding
2 edges with the lattice
3 seeding overlaid on top of edges
4 observation without edges, with mixed colours
Figure 3: comparison of two experimental images
a few seeds, little-to-no contamination
b more seeds, more contamination
Input: wells before contamination, wells after contamination, edges, originalrows, shiftedrows
needs a function (plotwells.m) to be called to draw one panel
further functions to be called in arbitrary order for drawing
a all edges
b all wells
use cases for wells:
0 lattice vertices: tiny thin white outlines with black interior for vertices
1 non-empty wells: balls of colour with identical outline
2 thin white outlines with black interior for empty wells and balls of color with identical outline for non-empty wells
use cases:
Fig 1, 1&4: wells of type 2, (no edges)
Fig 1, 2: wells of type 0 on top of edges
Fig 1, 3: wells of type 2 on top of edges
Fig 3: wells of type 1, (no edges)