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model.m
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function pattern = model(modelpar)
path(path,'Models/Reaction_Diffusion/');
path(path,'Models/Spiral_Wave/');
path(path,'Models/');
% Generate solution
switch modelpar.model
case 'Brusselator'
[U,~,X,Y] = Brusselator(modelpar.a,modelpar.b);
case 'SH'
[U,X,Y]= SH_2D(modelpar.a,modelpar.b, modelpar.init);
case 'SH_1D'
[U,X]= SH_1D(modelpar.a,modelpar.b);
case 'GS'
[U,V,X,Y]= Gray_Scott(modelpar.a,modelpar.b);
case 'Schnakenberg'
[U,X,Y]= Schnakenberg(modelpar.a,modelpar.b);
case 'Bullara'
[U,X,Y] = bullara_code(modelpar.a,modelpar.b,100, 5e7, 0, 0);
idx0 = U == 0;
idx1 = U == 1;
U(idx0) = 1;
U(idx1) = 0;
case 'Barkley'
anew = num2str(modelpar.a,'%1.6f');
bnew = num2str(modelpar.b,'%1.6f');
fid = fopen('Models/Spiral_Wave/Barkley/task.txt');
C=textscan(fid,'%s','delimiter','\n');
fclose(fid);
C{1}{1} = anew; C{1}{2} = bnew;
writecell(C{1},'Models/Spiral_Wave/Barkley/task.txt','QuoteStrings',0)
% if b > 0.05
% C{1}{11}(1:5) = num2str(100000);
% end
cd Models/Spiral_Wave/Barkley
system('rm tip.txt')
system('touch tip.txt')
system('./ezspiral')
cd ../../..
tip_pts = readtable('Models/Spiral_Wave/Barkley/tip.txt');
tip_pts = table2array(tip_pts);
U = readtable('Models/Spiral_Wave/Barkley/fc.txt');
U = U.Var2;
U = reshape(U(5:end),501,501);
X = linspace(0,100,501); Y = X;
[X,Y] = meshgrid(X,Y);
if size(tip_pts,1) > 1000 || size(tip_pts,1)==1
tip_pts = tip_pts(1000:end,:);
end
idx = find( (tip_pts(:,2)>98)+(tip_pts(:,2)<2) +...
+ (tip_pts(:,3)>98) + (tip_pts(:,3)<2) );
idx
if length(idx) > 0
idx = [1; idx;size(tip_pts,1) ];
d = diff(idx);
max_diff = [idx( find(d == max(d))):idx( find(d == max(d))+1) ] ;
tip_pts = tip_pts(max_diff,:);
% if ~isempty(idx)
% tip_pts = tip_pts(1:idx(1),:);
end
%U
case 'Bar-Eiswirth'
if modelpar.a < 0
modelpar.a = 1E-14;
end
anew = num2str(1/(modelpar.a),'%1.6f');
bnew = num2str(modelpar.b,'%1.6f');
length(anew)
length(bnew)
fid = fopen('Models/Spiral_Wave/Bar-Eiswirth/task.txt');
C=textscan(fid,'%s','delimiter','\n');
fclose(fid);
C{1}{2} = bnew; C{1}{3} = anew;
writecell(C{1},'Models/Spiral_Wave/Bar-Eiswirth/task.txt','QuoteStrings',0)
cd Models/Spiral_Wave/Bar-Eiswirth
system('rm tip.txt')
system('touch tip.txt')
system('./ezspiral')
cd ../../../
tip_pts = readtable('Models/Spiral_Wave/Bar-Eiswirth/tip.txt');
tip_pts = table2array(tip_pts);
U = readtable('Models/Spiral_Wave/Bar-Eiswirth/fc.txt');
U = U.Var2;
U = reshape(U(5:end),501,501);
% if strcmp(featpar.feature,'turbulence') == 0
if size(tip_pts,1) > 2000 || size(tip_pts,1)==1
tip_pts = tip_pts(2000:end,:);
end
idx = find( (tip_pts(:,2)>49)+(tip_pts(:,2)<1) +...
+ (tip_pts(:,3)>49) + (tip_pts(:,3)<1) );
% else
% idx = [];
% end
if ~isempty(idx)
tip_pts = tip_pts(1:idx(1),:);
end
case 'Rossler'
cnew = num2str(modelpar.a,'%1.6f');
anew = num2str(modelpar.b,'%1.6f');
fid = fopen('Models/Spiral_Wave/Rossler/task.txt');
C=textscan(fid,'%s','delimiter','\n');
fclose(fid);
C{1}{3} = cnew; C{1}{1} = anew;
writecell(C{1},'Models/Spiral_Wave/Rossler/task.txt','QuoteStrings',0)
cd Models/Spiral_Wave/Rossler
system('./ezspiral')
cd ../../..
U = readtable('Models/Spiral_Wave/Rossler/fc.txt');
U = U.Var2;
U = reshape(U(5:end),526,526);
X = linspace(0,250,526); Y = X;
[X,Y] = meshgrid(X,Y);
% cd ../
tip_pts = [];
end
% Select set
switch modelpar.sets
case 'pos'
if max(U(:)) - min(U(:)) < 1E-5
X = []; Y = [];
else
X = X(U > min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% quantile(U(:), 0.7) );
if modelpar.xdim == 2
Y = Y(U > min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% quantile(U(:), 0.7));
end
end
case 'neg'
if max(U(:)) - min(U(:)) < 1E-5
X = []; Y = [];
else
X = X(U < min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% < quantile(U(:), 0.3));
if modelpar.xdim == 2
Y = Y(U < min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% < quantile(U(:), 0.3));
end
end
% case 'tip_points'
% if ~isempty(tip_pts)
% X = tip_pts(:,2);
% Y = tip_pts(:,3);
% else
% X = [];
% Y = [];
% end
case 'pos-filter'
% This is for fish
if max(U(:)) - min(U(:)) < 1E-5
X = []; Y = [];
else
X = X(U > min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% quantile(U(:), 0.7) );
if modelpar.xdim == 2
Y = Y(U > min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% quantile(U(:), 0.7));
end
end
pattern = [X,Y];
Dists = sqrt( (X-X').^2 + (Y - Y').^2 );
Dists_nn = zeros(1, size(X,1));
for i = 1:length(Dists_nn)
Dists(i,:) = sort( Dists(i,:) );
Dists_nn(i) = sum(Dists(i,2:11).^2/10);
end
idx = Dists_nn < quantile(Dists_nn,0.9);
X = X(idx);
Y = Y(idx);
case 'neg-filter'
if max(U(:)) - min(U(:)) < 1E-5
X = []; Y = [];
else
X = X(U < min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% < quantile(U(:), 0.3));
if modelpar.xdim == 2
Y = Y(U < min(U(:)) + modelpar.threshold*( max(U(:))-min(U(:))) );% < quantile(U(:), 0.3));
end
end
pattern = [X,Y];
Dists = sqrt( (X-X').^2 + (Y - Y').^2 );
Dists_nn = zeros(1, size(X,1));
for i = 1:length(Dists_nn)
Dists(i,:) = sort( Dists(i,:) );
Dists_nn(i) = sum(Dists(i,2:11).^2/10);
end
idx = Dists_nn < quantile(Dists_nn,0.9);
X = X(idx);
Y = Y(idx);
end
if strcmp( modelpar.sets, 'tip_points')
pattern = tip_pts;
elseif strcmp( modelpar.sets, 'homogeneous')
pattern = max(U(:))-min(U(:)) <= 1E-10
else
if modelpar.xdim == 2
pattern = [X,Y];
else
pattern = X;
end
end
% if size(pattern,1) > 1
% if strcmp( modelpar.sets, 'tip_points')
% figure(29);plot(pattern(:,2),pattern(:,3))
% else
% figure(29);scatter(pattern(:,1),pattern(:,2))
% end
% end