1234 lines
41 KiB
Matlab
1234 lines
41 KiB
Matlab
function [logml, npops, partitionSummary]=indMix(c,npops,dispText)
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% Greedy search algorithm with unknown number of classes for regular
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% clustering.
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% Input npops is not used if called by greedyMix or greedyPopMix.
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logml = 1;
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global PARTITION;
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global COUNTS;
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global SUMCOUNTS;
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global POP_LOGML;
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global LOGDIFF;
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clearGlobalVars;
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noalle = c.noalle; rows = c.rows; data = c.data;
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adjprior = c.adjprior; priorTerm = c.priorTerm; rowsFromInd = c.rowsFromInd;
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if isfield(c,'dist')
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dist = c.dist; Z = c.Z;
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end
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clear c;
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if nargin < 2
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dispText = 1;
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npopstext = [];
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ready = false;
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teksti = 'Input upper bound to the number of populations (possibly multiple values): ';
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while ready == false
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npopstextExtra = inputdlg(teksti ,...
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'Input maximum number of populations',1,{'20'});
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drawnow
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if isempty(npopstextExtra) % Painettu Cancel:ia
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return
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end
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npopstextExtra = npopstextExtra{1};
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if length(npopstextExtra)>=255
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npopstextExtra = npopstextExtra(1:255);
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npopstext = [npopstext ' ' npopstextExtra];
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teksti = 'The input field length limit (255 characters) was reached. Input more values: ';
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else
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npopstext = [npopstext ' ' npopstextExtra];
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ready = true;
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end
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end
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clear ready; clear teksti;
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if isempty(npopstext) | length(npopstext)==1
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return
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else
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npopsTaulu = str2num(npopstext);
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ykkoset = find(npopsTaulu==1);
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npopsTaulu(ykkoset) = []; % Mikäli ykkösiä annettu ylärajaksi, ne poistetaan.
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if isempty(npopsTaulu)
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logml = 1; partitionSummary=1; npops=1;
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return
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end
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clear ykkoset;
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end
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else
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npopsTaulu = npops;
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end
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nruns = length(npopsTaulu);
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initData = data;
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data = data(:,1:end-1);
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logmlBest = -1e50;
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partitionSummary = -1e50*ones(30,2); % Tiedot 30 parhaasta partitiosta (npops ja logml)
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partitionSummary(:,1) = zeros(30,1);
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worstLogml = -1e50; worstIndex = 1;
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for run = 1:nruns
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npops = npopsTaulu(run);
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if dispText
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dispLine;
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disp(['Run ' num2str(run) '/' num2str(nruns) ...
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', maximum number of populations ' num2str(npops) '.']);
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end
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ninds = size(rows,1);
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initialPartition = admixture_initialization(initData, npops, Z);
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[sumcounts, counts, logml] = ...
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initialCounts(initialPartition, data, npops, rows, noalle, adjprior);
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PARTITION = zeros(ninds, 1);
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for i=1:ninds
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apu = rows(i);
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PARTITION(i) = initialPartition(apu(1));
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end
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COUNTS = counts; SUMCOUNTS = sumcounts;
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POP_LOGML = computePopulationLogml(1:npops, adjprior, priorTerm);
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LOGDIFF = repmat(-Inf,ninds,npops);
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clear initialPartition; clear counts; clear sumcounts;
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% PARHAAN MIXTURE-PARTITION ETSIMINEN
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nRoundTypes = 7;
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kokeiltu = zeros(nRoundTypes, 1);
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roundTypes = [1 1]; %Ykkösvaiheen sykli kahteen kertaan.
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ready = 0; vaihe = 1;
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if dispText
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disp(' ');
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disp(['Mixture analysis started with initial ' num2str(npops) ' populations.']);
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end
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while ready ~= 1
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muutoksia = 0;
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if dispText
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disp(['Performing steps: ' num2str(roundTypes)]);
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end
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for n = 1:length(roundTypes)
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round = roundTypes(n);
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kivaluku=0;
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if kokeiltu(round) == 1 %Askelta kokeiltu viime muutoksen jälkeen
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elseif round==0 | round==1 %Yksilön siirtäminen toiseen populaatioon.
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inds = 1:ninds;
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aputaulu = [inds' rand(ninds,1)];
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aputaulu = sortrows(aputaulu,2);
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inds = aputaulu(:,1)';
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muutosNyt = 0;
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for ind = inds
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i1 = PARTITION(ind);
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[muutokset, diffInCounts] = laskeMuutokset(ind, rows, ...
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data, adjprior, priorTerm);
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if round==1, [maxMuutos, i2] = max(muutokset);
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end
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if (i1~=i2 & maxMuutos>1e-5)
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% Tapahtui muutos
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muutoksia = 1;
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if muutosNyt == 0
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muutosNyt = 1;
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if dispText
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disp('Action 1');
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end
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end
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kokeiltu = zeros(nRoundTypes,1);
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kivaluku = kivaluku+1;
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updateGlobalVariables(ind, i2, diffInCounts,...
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adjprior, priorTerm);
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logml = logml+maxMuutos;
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if logml>worstLogml
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[partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex);
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if (added==1) [worstLogml, worstIndex] = min(partitionSummary(:,2)); end
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end
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end
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end
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if muutosNyt == 0
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kokeiltu(round) = 1;
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end
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elseif round==2 %Populaation yhdistäminen toiseen.
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maxMuutos = 0;
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for pop = 1:npops
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[muutokset, diffInCounts] = laskeMuutokset2(pop, rows, ...
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data, adjprior, priorTerm);
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[isoin, indeksi] = max(muutokset);
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if isoin>maxMuutos
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maxMuutos = isoin;
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i1 = pop;
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i2 = indeksi;
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diffInCountsBest = diffInCounts;
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end
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end
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if maxMuutos>1e-5
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muutoksia = 1;
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kokeiltu = zeros(nRoundTypes,1);
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updateGlobalVariables2(i1,i2, diffInCountsBest, ...
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adjprior, priorTerm);
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logml = logml + maxMuutos;
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if dispText
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disp('Action 2');
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end
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if logml>worstLogml
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[partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex);
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if (added==1) [worstLogml, worstIndex] = min(partitionSummary(:,2)); end
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end
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else
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kokeiltu(round) = 1;
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end
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elseif round==3 || round==4 %Populaation jakaminen osiin.
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maxMuutos = 0;
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ninds = size(rows,1);
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for pop = 1:npops
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inds2 = find(PARTITION==pop);
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ninds2 = length(inds2);
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if ninds2>2
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dist2 = laskeOsaDist(inds2, dist, ninds);
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Z2 = linkage(dist2');
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if round==3
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npops2 = max(min(20, floor(ninds2/5)),2);
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elseif round==4
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npops2 = 2; %Moneenko osaan jaetaan
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end
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T2 = cluster_own(Z2, npops2);
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muutokset = laskeMuutokset3(T2, inds2, rows, data, ...
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adjprior, priorTerm, pop);
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[isoin, indeksi] = max(muutokset(1:end));
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if isoin>maxMuutos
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maxMuutos = isoin;
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muuttuvaPop2 = rem(indeksi,npops2);
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if muuttuvaPop2==0, muuttuvaPop2 = npops2; end
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muuttuvat = inds2(find(T2==muuttuvaPop2));
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i2 = ceil(indeksi/npops2);
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end
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end
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end
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if maxMuutos>1e-5
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muutoksia = 1;
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kokeiltu = zeros(nRoundTypes,1);
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%rows = computeRows(rowsFromInd, muuttuvat, length(muuttuvat));
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rivit = [];
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for i = 1:length(muuttuvat)
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ind = muuttuvat(i);
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lisa = rows(ind,1):rows(ind,2);
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rivit = [rivit; lisa'];
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%rivit = [rivit; rows(ind)'];
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end
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diffInCounts = computeDiffInCounts(rivit', size(COUNTS,1), ...
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size(COUNTS,2), data);
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i1 = PARTITION(muuttuvat(1));
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updateGlobalVariables3(muuttuvat, diffInCounts, ...
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adjprior, priorTerm, i2);
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logml = logml + maxMuutos;
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if dispText
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if round==3
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disp('Action 3');
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else
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disp('Action 4');
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end
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end
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if logml>worstLogml
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[partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex);
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if (added==1) [worstLogml, worstIndex] = min(partitionSummary(:,2)); end
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end
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else
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kokeiltu(round)=1;
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end
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elseif round == 5 || round == 6
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j=0;
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muutettu = 0;
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poplogml = POP_LOGML;
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partition = PARTITION;
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counts = COUNTS;
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sumcounts = SUMCOUNTS;
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logdiff = LOGDIFF;
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pops = randperm(npops);
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while (j < npops & muutettu == 0)
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j = j+1;
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pop = pops(j);
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totalMuutos = 0;
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inds = find(PARTITION==pop);
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if round == 5
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aputaulu = [inds rand(length(inds),1)];
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aputaulu = sortrows(aputaulu,2);
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inds = aputaulu(:,1)';
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elseif round == 6
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inds = returnInOrder(inds, pop, ...
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rows, data, adjprior, priorTerm);
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end
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i = 0;
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while (length(inds) > 0 & i < length(inds))
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i = i+1;
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ind =inds(i);
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[muutokset, diffInCounts] = laskeMuutokset(ind, rows, ...
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data, adjprior, priorTerm);
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muutokset(pop) = -1e50; % Varmasti ei suurin!!!
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[maxMuutos, i2] = max(muutokset);
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updateGlobalVariables(ind, i2, diffInCounts,...
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adjprior, priorTerm);
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totalMuutos = totalMuutos+maxMuutos;
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logml = logml+maxMuutos;
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if round == 6
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% Lopetetaan heti kun muutos on positiivinen.
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if totalMuutos > 1e-5
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i=length(inds);
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end
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end
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end
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if totalMuutos>1e-5
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kokeiltu = zeros(nRoundTypes,1);
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muutettu=1;
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if muutoksia==0
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muutoksia = 1; % Ulompi kirjanpito.
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if dispText
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if round==5
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disp('Action 5');
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else
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disp('Action 6');
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end
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end
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end
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if logml>worstLogml
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[partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex);
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if (added==1) [worstLogml, worstIndex] = min(partitionSummary(:,2)); end
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end
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else
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% Missään vaiheessa tila ei parantunut.
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% Perutaan kaikki muutokset.
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PARTITION = partition;
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SUMCOUNTS = sumcounts;
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POP_LOGML = poplogml;
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COUNTS = counts;
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logml = logml - totalMuutos;
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LOGDIFF = logdiff;
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kokeiltu(round)=1;
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end
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end
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clear partition; clear sumcounts; clear counts; clear poplogml;
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elseif round == 7
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emptyPop = findEmptyPop(npops);
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j = 0;
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pops = randperm(npops);
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muutoksiaNyt = 0;
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if emptyPop == -1
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j = npops;
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end
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while (j < npops)
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j = j +1;
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pop = pops(j);
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inds2 = find(PARTITION == pop);
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ninds2 = length(inds2);
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if ninds2 > 5
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partition = PARTITION;
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sumcounts = SUMCOUNTS;
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counts = COUNTS;
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poplogml = POP_LOGML;
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logdiff = LOGDIFF;
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dist2 = laskeOsaDist(inds2, dist, ninds);
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Z2 = linkage(dist2');
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T2 = cluster_own(Z2, 2);
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muuttuvat = inds2(find(T2 == 1));
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muutokset = laskeMuutokset3(T2, inds2, rows, data, ...
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adjprior, priorTerm, pop);
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totalMuutos = muutokset(1, emptyPop);
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rivit = [];
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for i = 1:length(muuttuvat)
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ind = muuttuvat(i);
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lisa = rows(ind,1):rows(ind,2);
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rivit = [rivit lisa];
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end
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diffInCounts = computeDiffInCounts(rivit, size(COUNTS,1), ...
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size(COUNTS,2), data);
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updateGlobalVariables3(muuttuvat, diffInCounts, ...
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adjprior, priorTerm, emptyPop);
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muutettu = 1;
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while (muutettu == 1)
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muutettu = 0;
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% Siirretään yksilöitä populaatioiden välillä
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muutokset = laskeMuutokset5(inds2, rows, data, ...
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adjprior, priorTerm, pop, emptyPop);
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[maxMuutos, indeksi] = max(muutokset);
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muuttuva = inds2(indeksi);
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if (PARTITION(muuttuva) == pop)
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i2 = emptyPop;
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else
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i2 = pop;
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end
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if maxMuutos > 1e-5
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rivit = rows(muuttuva,1):rows(muuttuva,2);
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diffInCounts = computeDiffInCounts(rivit, size(COUNTS,1), ...
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size(COUNTS,2), data);
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updateGlobalVariables3(muuttuva,diffInCounts, ...
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adjprior, priorTerm, i2);
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muutettu = 1;
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totalMuutos = totalMuutos + maxMuutos;
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end
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end
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if totalMuutos > 1e-5
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muutoksia = 1;
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logml = logml + totalMuutos;
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if logml>worstLogml
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[partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex);
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if (added==1) [worstLogml, worstIndex] = min(partitionSummary(:,2)); end
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end
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if muutoksiaNyt == 0
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if dispText
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disp('Action 7');
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end
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muutoksiaNyt = 1;
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end
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kokeiltu = zeros(nRoundTypes,1);
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j = npops;
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else
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%palutetaan vanhat arvot
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PARTITION = partition;
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SUMCOUNTS = sumcounts;
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COUNTS = counts;
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POP_LOGML = poplogml;
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LOGDIFF = logdiff;
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end
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end
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end
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if muutoksiaNyt == 0
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kokeiltu(round)=1;
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end
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end
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end
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if muutoksia == 0
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if vaihe==1
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vaihe = 2;
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elseif vaihe==2
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vaihe = 3;
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elseif vaihe==3
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vaihe = 4;
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elseif vaihe==4;
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vaihe = 5;
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elseif vaihe==5
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ready = 1;
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end
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else
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muutoksia = 0;
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end
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if ready==0
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if vaihe==1
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roundTypes=[1];
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elseif vaihe==2
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roundTypes = [2 1];
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elseif vaihe==3
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roundTypes=[5 5 7];
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elseif vaihe==4
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roundTypes=[4 3 1];
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elseif vaihe==5
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roundTypes=[6 7 2 3 4 1];
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end
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end
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end
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% TALLENNETAAN
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npops = poistaTyhjatPopulaatiot(npops);
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POP_LOGML = computePopulationLogml(1:npops, adjprior, priorTerm);
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if dispText
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disp(['Found partition with ' num2str(npops) ' populations.']);
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disp(['Log(ml) = ' num2str(logml)]);
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disp(' ');
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end
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if logml>logmlBest
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% Päivitetään parasta löydettyä partitiota.
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logmlBest = logml;
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npopsBest = npops;
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partitionBest = PARTITION;
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countsBest = COUNTS;
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sumCountsBest = SUMCOUNTS;
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pop_logmlBest = POP_LOGML;
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logdiffbest = LOGDIFF;
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end
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end
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logml = logmlBest;
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npops = npopsBest;
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PARTITION = partitionBest;
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COUNTS = countsBest;
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SUMCOUNTS = sumCountsBest;
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POP_LOGML = pop_logmlBest;
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LOGDIFF = logdiffbest;
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%--------------------------------------------------------------------------
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function clearGlobalVars
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global COUNTS; COUNTS = [];
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global SUMCOUNTS; SUMCOUNTS = [];
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global PARTITION; PARTITION = [];
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global POP_LOGML; POP_LOGML = [];
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global LOGDIFF; LOGDIFF = [];
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%--------------------------------------------------------------------------
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function Z = linkage(Y, method)
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[k, n] = size(Y);
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m = (1+sqrt(1+8*n))/2;
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if k ~= 1 | m ~= fix(m)
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error('The first input has to match the output of the PDIST function in size.');
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end
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if nargin == 1 % set default switch to be 'co'
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method = 'co';
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end
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method = lower(method(1:2)); % simplify the switch string.
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monotonic = 1;
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Z = zeros(m-1,3); % allocate the output matrix.
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N = zeros(1,2*m-1);
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N(1:m) = 1;
|
|
n = m; % since m is changing, we need to save m in n.
|
|
R = 1:n;
|
|
for s = 1:(n-1)
|
|
X = Y;
|
|
[v, k] = min(X);
|
|
i = floor(m+1/2-sqrt(m^2-m+1/4-2*(k-1)));
|
|
j = k - (i-1)*(m-i/2)+i;
|
|
Z(s,:) = [R(i) R(j) v]; % update one more row to the output matrix A
|
|
I1 = 1:(i-1); I2 = (i+1):(j-1); I3 = (j+1):m; % these are temp variables.
|
|
U = [I1 I2 I3];
|
|
I = [I1.*(m-(I1+1)/2)-m+i i*(m-(i+1)/2)-m+I2 i*(m-(i+1)/2)-m+I3];
|
|
J = [I1.*(m-(I1+1)/2)-m+j I2.*(m-(I2+1)/2)-m+j j*(m-(j+1)/2)-m+I3];
|
|
|
|
switch method
|
|
case 'si' %single linkage
|
|
Y(I) = min(Y(I),Y(J));
|
|
case 'av' % average linkage
|
|
Y(I) = Y(I) + Y(J);
|
|
case 'co' %complete linkage
|
|
Y(I) = max(Y(I),Y(J));
|
|
case 'ce' % centroid linkage
|
|
K = N(R(i))+N(R(j));
|
|
Y(I) = (N(R(i)).*Y(I)+N(R(j)).*Y(J)-(N(R(i)).*N(R(j))*v^2)./K)./K;
|
|
case 'wa'
|
|
Y(I) = ((N(R(U))+N(R(i))).*Y(I) + (N(R(U))+N(R(j))).*Y(J) - ...
|
|
N(R(U))*v)./(N(R(i))+N(R(j))+N(R(U)));
|
|
end
|
|
J = [J i*(m-(i+1)/2)-m+j];
|
|
Y(J) = []; % no need for the cluster information about j.
|
|
|
|
% update m, N, R
|
|
m = m-1;
|
|
N(n+s) = N(R(i)) + N(R(j));
|
|
R(i) = n+s;
|
|
R(j:(n-1))=R((j+1):n);
|
|
end
|
|
|
|
|
|
%-----------------------------------------------------------------------
|
|
|
|
|
|
function [sumcounts, counts, logml] = ...
|
|
initialPopCounts(data, npops, rows, noalle, adjprior)
|
|
|
|
nloci=size(data,2);
|
|
counts = zeros(max(noalle),nloci,npops);
|
|
sumcounts = zeros(npops,nloci);
|
|
|
|
for i=1:npops
|
|
for j=1:nloci
|
|
i_rivit = rows(i,1):rows(i,2);
|
|
havainnotLokuksessa = find(data(i_rivit,j)>=0);
|
|
sumcounts(i,j) = length(havainnotLokuksessa);
|
|
for k=1:noalle(j)
|
|
alleleCode = k;
|
|
N_ijk = length(find(data(i_rivit,j)==alleleCode));
|
|
counts(k,j,i) = N_ijk;
|
|
end
|
|
end
|
|
end
|
|
|
|
logml = laskeLoggis(counts, sumcounts, adjprior);
|
|
|
|
%-----------------------------------------------------------------------
|
|
|
|
|
|
function loggis = laskeLoggis(counts, sumcounts, adjprior)
|
|
npops = size(counts,3);
|
|
|
|
logml2 = sum(sum(sum(gammaln(counts+repmat(adjprior,[1 1 npops]))))) ...
|
|
- npops*sum(sum(gammaln(adjprior))) - ...
|
|
sum(sum(gammaln(1+sumcounts)));
|
|
loggis = logml2;
|
|
|
|
|
|
%------------------------------------------------------------------------------------
|
|
|
|
|
|
function popLogml = computePopulationLogml(pops, adjprior, priorTerm)
|
|
% Palauttaa length(pops)*1 taulukon, jossa on laskettu korikohtaiset
|
|
% logml:t koreille, jotka on määritelty pops-muuttujalla.
|
|
|
|
global COUNTS;
|
|
global SUMCOUNTS;
|
|
x = size(COUNTS,1);
|
|
y = size(COUNTS,2);
|
|
z = length(pops);
|
|
|
|
popLogml = ...
|
|
squeeze(sum(sum(reshape(...
|
|
gammaln(repmat(adjprior,[1 1 length(pops)]) + COUNTS(:,:,pops)) ...
|
|
,[x y z]),1),2)) - sum(gammaln(1+SUMCOUNTS(pops,:)),2) - priorTerm;
|
|
%--------------------------------------------------------------------------
|
|
|
|
|
|
function [muutokset, diffInCounts] = ...
|
|
laskeMuutokset(ind, globalRows, data, adjprior, priorTerm)
|
|
% Palauttaa npops*1 taulun, jossa i:s alkio kertoo, mikä olisi
|
|
% muutos logml:ssä, mikäli yksilö ind siirretään koriin i.
|
|
% diffInCounts on poistettava COUNTS:in siivusta i1 ja lisättävä
|
|
% COUNTS:in siivuun i2, mikäli muutos toteutetaan.
|
|
%
|
|
% Lisäys 25.9.2007:
|
|
% Otettu käyttöön globaali muuttuja LOGDIFF, johon on tallennettu muutokset
|
|
% logml:ssä siirrettäessä yksilöitä toisiin populaatioihin.
|
|
|
|
global COUNTS; global SUMCOUNTS;
|
|
global PARTITION; global POP_LOGML;
|
|
global LOGDIFF;
|
|
|
|
npops = size(COUNTS,3);
|
|
muutokset = LOGDIFF(ind,:);
|
|
|
|
i1 = PARTITION(ind);
|
|
i1_logml = POP_LOGML(i1);
|
|
muutokset(i1) = 0;
|
|
|
|
rows = globalRows(ind,1):globalRows(ind,2);
|
|
diffInCounts = computeDiffInCounts(rows, size(COUNTS,1), size(COUNTS,2), data);
|
|
diffInSumCounts = sum(diffInCounts);
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)-diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)-diffInSumCounts;
|
|
new_i1_logml = computePopulationLogml(i1, adjprior, priorTerm);
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)+diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)+diffInSumCounts;
|
|
|
|
i2 = find(muutokset==-Inf); % Etsitään populaatiot jotka muuttuneet viime kerran jälkeen.
|
|
i2 = setdiff(i2,i1);
|
|
i2_logml = POP_LOGML(i2);
|
|
|
|
ni2 = length(i2);
|
|
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)+repmat(diffInCounts, [1 1 ni2]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)+repmat(diffInSumCounts,[ni2 1]);
|
|
new_i2_logml = computePopulationLogml(i2, adjprior, priorTerm);
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)-repmat(diffInCounts, [1 1 ni2]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)-repmat(diffInSumCounts,[ni2 1]);
|
|
|
|
muutokset(i2) = new_i1_logml - i1_logml ...
|
|
+ new_i2_logml - i2_logml;
|
|
LOGDIFF(ind,:) = muutokset;
|
|
|
|
|
|
%----------------------------------------------------------------------
|
|
|
|
|
|
function diffInCounts = computeDiffInCounts(rows, max_noalle, nloci, data)
|
|
% Muodostaa max_noalle*nloci taulukon, jossa on niiden alleelien
|
|
% lukumäärät (vastaavasti kuin COUNTS:issa), jotka ovat data:n
|
|
% riveillä rows. rows pitää olla vaakavektori.
|
|
|
|
diffInCounts = zeros(max_noalle, nloci);
|
|
for i=rows
|
|
row = data(i,:);
|
|
notEmpty = find(row>=0);
|
|
|
|
if length(notEmpty)>0
|
|
diffInCounts(row(notEmpty) + (notEmpty-1)*max_noalle) = ...
|
|
diffInCounts(row(notEmpty) + (notEmpty-1)*max_noalle) + 1;
|
|
end
|
|
end
|
|
|
|
%------------------------------------------------------------------------
|
|
|
|
|
|
%-------------------------------------------------------------------------------------
|
|
|
|
|
|
function updateGlobalVariables(ind, i2, diffInCounts, ...
|
|
adjprior, priorTerm)
|
|
% Suorittaa globaalien muuttujien muutokset, kun yksilö ind
|
|
% on siirretään koriin i2.
|
|
|
|
global PARTITION;
|
|
global COUNTS;
|
|
global SUMCOUNTS;
|
|
global POP_LOGML;
|
|
global LOGDIFF;
|
|
|
|
i1 = PARTITION(ind);
|
|
PARTITION(ind)=i2;
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1) - diffInCounts;
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2) + diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:) - sum(diffInCounts);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:) + sum(diffInCounts);
|
|
|
|
POP_LOGML([i1 i2]) = computePopulationLogml([i1 i2], adjprior, priorTerm);
|
|
|
|
LOGDIFF(:,[i1 i2]) = -Inf;
|
|
inx = [find(PARTITION==i1); find(PARTITION==i2)];
|
|
LOGDIFF(inx,:) = -Inf;
|
|
|
|
|
|
%--------------------------------------------------------------------------
|
|
%--
|
|
|
|
%------------------------------------------------------------------------------------
|
|
|
|
|
|
function [muutokset, diffInCounts] = laskeMuutokset2( ...
|
|
i1, globalRows, data, adjprior, priorTerm);
|
|
% Palauttaa npops*1 taulun, jossa i:s alkio kertoo, mikä olisi
|
|
% muutos logml:ssä, mikäli korin i1 kaikki yksilöt siirretään
|
|
% koriin i.
|
|
|
|
global COUNTS; global SUMCOUNTS;
|
|
global PARTITION; global POP_LOGML;
|
|
npops = size(COUNTS,3);
|
|
muutokset = zeros(npops,1);
|
|
|
|
i1_logml = POP_LOGML(i1);
|
|
|
|
inds = find(PARTITION==i1);
|
|
ninds = length(inds);
|
|
|
|
if ninds==0
|
|
diffInCounts = zeros(size(COUNTS,1), size(COUNTS,2));
|
|
return;
|
|
end
|
|
|
|
rows = [];
|
|
for i = 1:ninds
|
|
ind = inds(i);
|
|
lisa = globalRows(ind,1):globalRows(ind,2);
|
|
rows = [rows; lisa'];
|
|
%rows = [rows; globalRows{ind}'];
|
|
end
|
|
|
|
diffInCounts = computeDiffInCounts(rows', size(COUNTS,1), size(COUNTS,2), data);
|
|
diffInSumCounts = sum(diffInCounts);
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)-diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)-diffInSumCounts;
|
|
new_i1_logml = computePopulationLogml(i1, adjprior, priorTerm);
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)+diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)+diffInSumCounts;
|
|
|
|
i2 = [1:i1-1 , i1+1:npops];
|
|
i2_logml = POP_LOGML(i2);
|
|
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)+repmat(diffInCounts, [1 1 npops-1]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)+repmat(diffInSumCounts,[npops-1 1]);
|
|
new_i2_logml = computePopulationLogml(i2, adjprior, priorTerm);
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)-repmat(diffInCounts, [1 1 npops-1]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)-repmat(diffInSumCounts,[npops-1 1]);
|
|
|
|
muutokset(i2) = new_i1_logml - i1_logml ...
|
|
+ new_i2_logml - i2_logml;
|
|
|
|
|
|
%---------------------------------------------------------------------------------
|
|
|
|
|
|
function updateGlobalVariables2( ...
|
|
i1, i2, diffInCounts, adjprior, priorTerm);
|
|
% Suorittaa globaalien muuttujien muutokset, kun kaikki
|
|
% korissa i1 olevat yksilöt siirretään koriin i2.
|
|
|
|
global PARTITION;
|
|
global COUNTS;
|
|
global SUMCOUNTS;
|
|
global POP_LOGML;
|
|
global LOGDIFF;
|
|
|
|
inds = find(PARTITION==i1);
|
|
PARTITION(inds) = i2;
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1) - diffInCounts;
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2) + diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:) - sum(diffInCounts);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:) + sum(diffInCounts);
|
|
|
|
POP_LOGML(i1) = 0;
|
|
POP_LOGML(i2) = computePopulationLogml(i2, adjprior, priorTerm);
|
|
|
|
LOGDIFF(:,[i1 i2]) = -Inf;
|
|
inx = [find(PARTITION==i1); find(PARTITION==i2)];
|
|
LOGDIFF(inx,:) = -Inf;
|
|
|
|
|
|
%--------------------------------------------------------------------------
|
|
%----
|
|
|
|
function muutokset = laskeMuutokset3(T2, inds2, globalRows, ...
|
|
data, adjprior, priorTerm, i1)
|
|
% Palauttaa length(unique(T2))*npops taulun, jossa (i,j):s alkio
|
|
% kertoo, mikä olisi muutos logml:ssä, jos populaation i1 osapopulaatio
|
|
% inds2(find(T2==i)) siirretään koriin j.
|
|
|
|
global COUNTS; global SUMCOUNTS;
|
|
global PARTITION; global POP_LOGML;
|
|
npops = size(COUNTS,3);
|
|
npops2 = length(unique(T2));
|
|
muutokset = zeros(npops2, npops);
|
|
|
|
i1_logml = POP_LOGML(i1);
|
|
for pop2 = 1:npops2
|
|
inds = inds2(find(T2==pop2));
|
|
ninds = length(inds);
|
|
if ninds>0
|
|
rows = [];
|
|
for i = 1:ninds
|
|
ind = inds(i);
|
|
lisa = globalRows(ind,1):globalRows(ind,2);
|
|
rows = [rows; lisa'];
|
|
%rows = [rows; globalRows{ind}'];
|
|
end
|
|
diffInCounts = computeDiffInCounts(rows', size(COUNTS,1), size(COUNTS,2), data);
|
|
diffInSumCounts = sum(diffInCounts);
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)-diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)-diffInSumCounts;
|
|
new_i1_logml = computePopulationLogml(i1, adjprior, priorTerm);
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1)+diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:)+diffInSumCounts;
|
|
|
|
i2 = [1:i1-1 , i1+1:npops];
|
|
i2_logml = POP_LOGML(i2)';
|
|
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)+repmat(diffInCounts, [1 1 npops-1]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)+repmat(diffInSumCounts,[npops-1 1]);
|
|
new_i2_logml = computePopulationLogml(i2, adjprior, priorTerm)';
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2)-repmat(diffInCounts, [1 1 npops-1]);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:)-repmat(diffInSumCounts,[npops-1 1]);
|
|
|
|
muutokset(pop2,i2) = new_i1_logml - i1_logml ...
|
|
+ new_i2_logml - i2_logml;
|
|
end
|
|
end
|
|
|
|
%------------------------------------------------------------------------------------
|
|
|
|
function muutokset = laskeMuutokset5(inds, globalRows, data, adjprior, ...
|
|
priorTerm, i1, i2)
|
|
|
|
% Palauttaa length(inds)*1 taulun, jossa i:s alkio kertoo, mikä olisi
|
|
% muutos logml:ssä, mikäli yksilö i vaihtaisi koria i1:n ja i2:n välillä.
|
|
|
|
global COUNTS; global SUMCOUNTS;
|
|
global PARTITION; global POP_LOGML;
|
|
|
|
ninds = length(inds);
|
|
muutokset = zeros(ninds,1);
|
|
|
|
i1_logml = POP_LOGML(i1);
|
|
i2_logml = POP_LOGML(i2);
|
|
|
|
for i = 1:ninds
|
|
ind = inds(i);
|
|
if PARTITION(ind)==i1
|
|
pop1 = i1; %mistä
|
|
pop2 = i2; %mihin
|
|
else
|
|
pop1 = i2;
|
|
pop2 = i1;
|
|
end
|
|
rows = globalRows(ind,1):globalRows(ind,2);
|
|
diffInCounts = computeDiffInCounts(rows, size(COUNTS,1), size(COUNTS,2), data);
|
|
diffInSumCounts = sum(diffInCounts);
|
|
|
|
COUNTS(:,:,pop1) = COUNTS(:,:,pop1)-diffInCounts;
|
|
SUMCOUNTS(pop1,:) = SUMCOUNTS(pop1,:)-diffInSumCounts;
|
|
COUNTS(:,:,pop2) = COUNTS(:,:,pop2)+diffInCounts;
|
|
SUMCOUNTS(pop2,:) = SUMCOUNTS(pop2,:)+diffInSumCounts;
|
|
|
|
new_logmls = computePopulationLogml([i1 i2], adjprior, priorTerm);
|
|
muutokset(i) = sum(new_logmls);
|
|
|
|
COUNTS(:,:,pop1) = COUNTS(:,:,pop1)+diffInCounts;
|
|
SUMCOUNTS(pop1,:) = SUMCOUNTS(pop1,:)+diffInSumCounts;
|
|
COUNTS(:,:,pop2) = COUNTS(:,:,pop2)-diffInCounts;
|
|
SUMCOUNTS(pop2,:) = SUMCOUNTS(pop2,:)-diffInSumCounts;
|
|
end
|
|
|
|
muutokset = muutokset - i1_logml - i2_logml;
|
|
|
|
%------------------------------------------------------------------------------------
|
|
|
|
|
|
function updateGlobalVariables3(muuttuvat, diffInCounts, ...
|
|
adjprior, priorTerm, i2);
|
|
% Suorittaa globaalien muuttujien päivitykset, kun yksilöt 'muuttuvat'
|
|
% siirretään koriin i2. Ennen siirtoa yksilöiden on kuuluttava samaan
|
|
% koriin.
|
|
|
|
global PARTITION;
|
|
global COUNTS;
|
|
global SUMCOUNTS;
|
|
global POP_LOGML;
|
|
global LOGDIFF;
|
|
|
|
i1 = PARTITION(muuttuvat(1));
|
|
PARTITION(muuttuvat) = i2;
|
|
|
|
COUNTS(:,:,i1) = COUNTS(:,:,i1) - diffInCounts;
|
|
COUNTS(:,:,i2) = COUNTS(:,:,i2) + diffInCounts;
|
|
SUMCOUNTS(i1,:) = SUMCOUNTS(i1,:) - sum(diffInCounts);
|
|
SUMCOUNTS(i2,:) = SUMCOUNTS(i2,:) + sum(diffInCounts);
|
|
|
|
POP_LOGML([i1 i2]) = computePopulationLogml([i1 i2], adjprior, priorTerm);
|
|
|
|
LOGDIFF(:,[i1 i2]) = -Inf;
|
|
inx = [find(PARTITION==i1); find(PARTITION==i2)];
|
|
LOGDIFF(inx,:) = -Inf;
|
|
|
|
|
|
%----------------------------------------------------------------------------
|
|
|
|
|
|
function dist2 = laskeOsaDist(inds2, dist, ninds)
|
|
% Muodostaa dist vektorista osavektorin, joka sisältää yksilöiden inds2
|
|
% väliset etäisyydet. ninds=kaikkien yksilöiden lukumäärä.
|
|
|
|
ninds2 = length(inds2);
|
|
apu = zeros(nchoosek(ninds2,2),2);
|
|
rivi = 1;
|
|
for i=1:ninds2-1
|
|
for j=i+1:ninds2
|
|
apu(rivi, 1) = inds2(i);
|
|
apu(rivi, 2) = inds2(j);
|
|
rivi = rivi+1;
|
|
end
|
|
end
|
|
apu = (apu(:,1)-1).*ninds - apu(:,1) ./ 2 .* (apu(:,1)-1) + (apu(:,2)-apu(:,1));
|
|
dist2 = dist(apu);
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|
|
|
|
|
%-----------------------------------------------------------------------------------
|
|
|
|
|
|
function npops = poistaTyhjatPopulaatiot(npops)
|
|
% Poistaa tyhjentyneet populaatiot COUNTS:ista ja
|
|
% SUMCOUNTS:ista. Päivittää npops:in ja PARTITION:in.
|
|
|
|
global COUNTS;
|
|
global SUMCOUNTS;
|
|
global PARTITION;
|
|
global LOGDIFF;
|
|
|
|
notEmpty = find(any(SUMCOUNTS,2));
|
|
COUNTS = COUNTS(:,:,notEmpty);
|
|
SUMCOUNTS = SUMCOUNTS(notEmpty,:);
|
|
LOGDIFF = LOGDIFF(:,notEmpty);
|
|
|
|
for n=1:length(notEmpty)
|
|
apu = find(PARTITION==notEmpty(n));
|
|
PARTITION(apu)=n;
|
|
end
|
|
npops = length(notEmpty);
|
|
|
|
|
|
%---------------------------------------------------------------
|
|
|
|
|
|
function dispLine;
|
|
disp('---------------------------------------------------');
|
|
|
|
%--------------------------------------------------------------
|
|
|
|
function num2 = omaRound(num)
|
|
% Pyöristää luvun num 1 desimaalin tarkkuuteen
|
|
num = num*10;
|
|
num = round(num);
|
|
num2 = num/10;
|
|
|
|
%---------------------------------------------------------
|
|
function mjono = logml2String(logml)
|
|
% Palauttaa logml:n string-esityksen.
|
|
|
|
mjono = ' ';
|
|
if abs(logml)<10000
|
|
%Ei tarvita e-muotoa
|
|
mjono(7) = palautaYks(abs(logml),-1);
|
|
mjono(6) = '.';
|
|
mjono(5) = palautaYks(abs(logml),0);
|
|
mjono(4) = palautaYks(abs(logml),1);
|
|
mjono(3) = palautaYks(abs(logml),2);
|
|
mjono(2) = palautaYks(abs(logml),3);
|
|
pointer = 2;
|
|
while mjono(pointer)=='0' & pointer<7
|
|
mjono(pointer) = ' ';
|
|
pointer=pointer+1;
|
|
end
|
|
if logml<0
|
|
mjono(pointer-1) = '-';
|
|
end
|
|
else
|
|
suurinYks = 4;
|
|
while abs(logml)/(10^(suurinYks+1)) >= 1
|
|
suurinYks = suurinYks+1;
|
|
end
|
|
if suurinYks<10
|
|
mjono(7) = num2str(suurinYks);
|
|
mjono(6) = 'e';
|
|
mjono(5) = palautaYks(abs(logml),suurinYks-1);
|
|
mjono(4) = '.';
|
|
mjono(3) = palautaYks(abs(logml),suurinYks);
|
|
if logml<0
|
|
mjono(2) = '-';
|
|
end
|
|
elseif suurinYks>=10
|
|
mjono(6:7) = num2str(suurinYks);
|
|
mjono(5) = 'e';
|
|
mjono(4) = palautaYks(abs(logml),suurinYks-1);
|
|
mjono(3) = '.';
|
|
mjono(2) = palautaYks(abs(logml),suurinYks);
|
|
if logml<0
|
|
mjono(1) = '-';
|
|
end
|
|
end
|
|
end
|
|
|
|
function digit = palautaYks(num,yks)
|
|
% palauttaa luvun num 10^yks termin kertoimen
|
|
% string:inä
|
|
% yks täytyy olla kokonaisluku, joka on
|
|
% vähintään -1:n suuruinen. Pienemmillä
|
|
% luvuilla tapahtuu jokin pyöristysvirhe.
|
|
|
|
if yks>=0
|
|
digit = rem(num, 10^(yks+1));
|
|
digit = floor(digit/(10^yks));
|
|
else
|
|
digit = num*10;
|
|
digit = floor(rem(digit,10));
|
|
end
|
|
digit = num2str(digit);
|
|
|
|
|
|
function mjono = kldiv2str(div)
|
|
mjono = ' ';
|
|
if abs(div)<100
|
|
%Ei tarvita e-muotoa
|
|
mjono(6) = num2str(rem(floor(div*1000),10));
|
|
mjono(5) = num2str(rem(floor(div*100),10));
|
|
mjono(4) = num2str(rem(floor(div*10),10));
|
|
mjono(3) = '.';
|
|
mjono(2) = num2str(rem(floor(div),10));
|
|
arvo = rem(floor(div/10),10);
|
|
if arvo>0
|
|
mjono(1) = num2str(arvo);
|
|
end
|
|
|
|
else
|
|
suurinYks = floor(log10(div));
|
|
mjono(6) = num2str(suurinYks);
|
|
mjono(5) = 'e';
|
|
mjono(4) = palautaYks(abs(div),suurinYks-1);
|
|
mjono(3) = '.';
|
|
mjono(2) = palautaYks(abs(div),suurinYks);
|
|
end
|
|
|
|
|
|
%--------------------------------------------------------------------------
|
|
%Seuraavat kolme funktiota liittyvat alkupartition muodostamiseen.
|
|
|
|
function initial_partition=admixture_initialization(data_matrix,nclusters, Z)
|
|
|
|
size_data=size(data_matrix);
|
|
nloci=size_data(2)-1;
|
|
n=max(data_matrix(:,end));
|
|
T=cluster_own(Z,nclusters);
|
|
initial_partition=zeros(size_data(1),1);
|
|
for i=1:n
|
|
kori=T(i);
|
|
here=find(data_matrix(:,end)==i);
|
|
for j=1:length(here)
|
|
initial_partition(here(j),1)=kori;
|
|
end
|
|
end
|
|
|
|
function T = cluster_own(Z,nclust)
|
|
true=logical(1);
|
|
false=logical(0);
|
|
maxclust = nclust;
|
|
% Start of algorithm
|
|
m = size(Z,1)+1;
|
|
T = zeros(m,1);
|
|
% maximum number of clusters based on inconsistency
|
|
if m <= maxclust
|
|
T = (1:m)';
|
|
elseif maxclust==1
|
|
T = ones(m,1);
|
|
else
|
|
clsnum = 1;
|
|
for k = (m-maxclust+1):(m-1)
|
|
i = Z(k,1); % left tree
|
|
if i <= m % original node, no leafs
|
|
T(i) = clsnum;
|
|
clsnum = clsnum + 1;
|
|
elseif i < (2*m-maxclust+1) % created before cutoff, search down the tree
|
|
T = clusternum(Z, T, i-m, clsnum);
|
|
clsnum = clsnum + 1;
|
|
end
|
|
i = Z(k,2); % right tree
|
|
if i <= m % original node, no leafs
|
|
T(i) = clsnum;
|
|
clsnum = clsnum + 1;
|
|
elseif i < (2*m-maxclust+1) % created before cutoff, search down the tree
|
|
T = clusternum(Z, T, i-m, clsnum);
|
|
clsnum = clsnum + 1;
|
|
end
|
|
end
|
|
end
|
|
|
|
function T = clusternum(X, T, k, c)
|
|
m = size(X,1)+1;
|
|
while(~isempty(k))
|
|
% Get the children of nodes at this level
|
|
children = X(k,1:2);
|
|
children = children(:);
|
|
|
|
% Assign this node number to leaf children
|
|
t = (children<=m);
|
|
T(children(t)) = c;
|
|
|
|
% Move to next level
|
|
k = children(~t) - m;
|
|
end
|
|
|
|
%--------------------------------------------------------------------------
|
|
|
|
function [sumcounts, counts, logml] = ...
|
|
initialCounts(partition, data, npops, rows, noalle, adjprior)
|
|
|
|
nloci=size(data,2);
|
|
ninds = size(rows, 1);
|
|
|
|
koot = rows(:,1) - rows(:,2) + 1;
|
|
maxSize = max(koot);
|
|
|
|
counts = zeros(max(noalle),nloci,npops);
|
|
sumcounts = zeros(npops,nloci);
|
|
for i=1:npops
|
|
for j=1:nloci
|
|
havainnotLokuksessa = find(partition==i & data(:,j)>=0);
|
|
sumcounts(i,j) = length(havainnotLokuksessa);
|
|
for k=1:noalle(j)
|
|
alleleCode = k;
|
|
N_ijk = length(find(data(havainnotLokuksessa,j)==alleleCode));
|
|
counts(k,j,i) = N_ijk;
|
|
end
|
|
end
|
|
end
|
|
|
|
%initializeGammaln(ninds, maxSize, max(noalle));
|
|
|
|
logml = laskeLoggis(counts, sumcounts, adjprior);
|
|
|
|
%--------------------------------------------------------------------------
|
|
|
|
|
|
function [partitionSummary, added] = addToSummary(logml, partitionSummary, worstIndex)
|
|
% Tiedetään, että annettu logml on isompi kuin huonoin arvo
|
|
% partitionSummary taulukossa. Jos partitionSummary:ssä ei vielä ole
|
|
% annettua logml arvoa, niin lisätään worstIndex:in kohtaan uusi logml ja
|
|
% nykyistä partitiota vastaava nclusters:in arvo. Muutoin ei tehdä mitään.
|
|
|
|
apu = find(abs(partitionSummary(:,2)-logml)<1e-5);
|
|
if isempty(apu)
|
|
% Nyt löydetty partitio ei ole vielä kirjattuna summaryyn.
|
|
global PARTITION;
|
|
npops = length(unique(PARTITION));
|
|
partitionSummary(worstIndex,1) = npops;
|
|
partitionSummary(worstIndex,2) = logml;
|
|
added = 1;
|
|
else
|
|
added = 0;
|
|
end
|
|
|
|
%--------------------------------------------------------------------------
|
|
|
|
function inds = returnInOrder(inds, pop, globalRows, data, ...
|
|
adjprior, priorTerm)
|
|
% Palauttaa yksilöt järjestyksessä siten, että ensimmäisenä on
|
|
% se, jonka poistaminen populaatiosta pop nostaisi logml:n
|
|
% arvoa eniten.
|
|
|
|
global COUNTS; global SUMCOUNTS;
|
|
ninds = length(inds);
|
|
apuTaulu = [inds, zeros(ninds,1)];
|
|
|
|
for i=1:ninds
|
|
ind =inds(i);
|
|
rows = globalRows(i,1):globalRows(i,2);
|
|
diffInCounts = computeDiffInCounts(rows, size(COUNTS,1), size(COUNTS,2), data);
|
|
diffInSumCounts = sum(diffInCounts);
|
|
|
|
COUNTS(:,:,pop) = COUNTS(:,:,pop)-diffInCounts;
|
|
SUMCOUNTS(pop,:) = SUMCOUNTS(pop,:)-diffInSumCounts;
|
|
apuTaulu(i, 2) = computePopulationLogml(pop, adjprior, priorTerm);
|
|
COUNTS(:,:,pop) = COUNTS(:,:,pop)+diffInCounts;
|
|
SUMCOUNTS(pop,:) = SUMCOUNTS(pop,:)+diffInSumCounts;
|
|
end
|
|
apuTaulu = sortrows(apuTaulu,2);
|
|
inds = apuTaulu(ninds:-1:1,1);
|
|
|
|
%--------------------------------------------------------------------------
|
|
|
|
function [emptyPop, pops] = findEmptyPop(npops)
|
|
% Palauttaa ensimmäisen tyhjän populaation indeksin. Jos tyhjiä
|
|
% populaatioita ei ole, palauttaa -1:n.
|
|
|
|
global PARTITION;
|
|
pops = unique(PARTITION)';
|
|
if (length(pops) ==npops)
|
|
emptyPop = -1;
|
|
else
|
|
popDiff = diff([0 pops npops+1]);
|
|
emptyPop = min(find(popDiff > 1));
|
|
end
|