clear all
close all
load('Conns_n150.mat')
%% parameters
n=150;
tinterp=10;
parameters=getParam(n,CeRem,CeLoc,CeLocI);
%% prescan
%prescan===============================
tend=1.5;
T=0:parameters.h*tinterp:tend;%for plotting
nIt=(tend)/parameters.h+1;
tic
%using all 0 initial condition for Py
initCond=zeros(2*n^2,1);
parameters.NValue=getNoise(nIt,n);
Y=runSheet(initCond,parameters);
bgInitc=Y(end,:);
toc
%% real run
parameters=getParam(n,CeRem,CeLoc,CeLocI);
tend=10;
T=0:parameters.h*tinterp:tend;%for plotting
nIt=(tend)/parameters.h+1;
%!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
ClusterNum=20; %change this number to change the number of subclusters
% !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
PercentHetP=0.08;
P=parameters.PyInput(1);
%percentM=20/n^2;
%[CellLocM,CellLocMV] = makeCellCluster(0.01,percentM,n);
CellLocVAll=[];
CellLocAll=zeros(n,n);
for cn=1:ClusterNum
[CellLoc,CellLocV] = makeCellCluster(1,PercentHetP/ClusterNum,n);%to scan: clustering coeff and percent of bad cells
CellLocVAll=[CellLocVAll, CellLocV];
CellLocAll=CellLocAll+CellLoc;
end
CellLocVAll=unique(CellLocVAll);
%Ramp=[P*ones(1,250), P:abs((P-1))/500:1, 1*ones(1,1750)];
Ramp=[P*ones(1,500), P:abs((P-1))/1000:1, 1*ones(1,2*1750)];
parameters.PyInput=P*(ones(n^2,nIt));
parameters.PyInput(CellLocVAll,:)=repmat(Ramp,length(CellLocVAll),1);
%real runs===============================
%using initial condition all 1
tic
initCond=bgInitc;
parameters.NValue=getNoise(nIt,n);
Y=runSheetPRamp(initCond,parameters);
Py=Y(1:tinterp:end,1:n^2);
mPy=mean(Py,2);sPy=std(Py,0,2);
toc
%% plot
load('MayColourMap')
figure(1)
imagesc(CellLocAll>=1)
colormap(mycmap)
TPts=[51 111 151 201 251 301 501];
figure(11)
for k=1:length(TPts)
subplot(1,length(TPts),k)
imagesc(reshape(Py(TPts(k),:),n,n) )
colormap(mycmap)
caxis([0 0.5])
title(sprintf('T=%g',T(TPts(k))))
end