204 lines
6.4 KiB
Mathematica
204 lines
6.4 KiB
Mathematica
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function [partition,data,popnames_return,pvalue] = ...
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viewPartition3(data, popnames, npops, admixnpops, ...
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inliers, partition, pvalue, filename)
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% Kuin viewParition.m, mutta toimii itsen<EFBFBD>isesti. Ei siis tarvitse
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% globaalia COUNTS-muuttujaa.
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%global COUNTS;
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%npops = size(COUNTS, 3);
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% Determine the order of individuals by calculating the distances.
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nind = size(data,1);
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% inliers = unique(partition);
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% inliers = find(any(data));
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dist = zeros(1,nind*(nind-1)/2);
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k = 1;
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% m = 1;
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disp('---------------------------------------------------');
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fprintf('Permutating the individuals according to their relateness.\n');
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fprintf('This may take several minutes. Please wait...');
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for i=1:nind-1
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for j=i+1:nind
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dist(k) = distance(data(i,:)',data(j,:)');
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k = k +1;
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end
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end
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Z = linkage(dist);
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[T,perm] = dendrogram_alpha(Z,0);
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% [H,T,perm] = dendrogram_beta(Z,popnames(:,1)); % This function gives dendrograms.
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data = data(perm,:);
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popnames = popnames(perm,:);
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popnames_return = popnames; % this is the popnames to be saved
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partition = partition(perm,:);
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pvalue = pvalue(perm,:);
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% npairs = nchoosek(nind,2);
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% pairwisesimilarity = zeros(npairs,1);
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% clusters = cell(1,ncluster);
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% for i = 1:ncluster
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% clusters{i} = find(data(:,i)>0);
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% end
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% % 'adjacency matrix'
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% adj_mat = cell(ncluster,ncluster);
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% k = 2;
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% for i = 1:ncluster
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% for j = k:ncluster
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% adj_mat{i,j} = intersect(clusters{i},clusters{j});
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% end
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% k = k + 1;
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% end
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%
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% adj_mat = zeros(ncluster,ncluster);
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% k = 2;
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% for i = 1:ncluster
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% for j = k:ncluster
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% adj_mat(i,j) = length(intersect(clusters{i},clusters{j}));
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% end
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% k = k + 1;
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% end
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% adj_mat = adj_mat+adj_mat';
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% admix_count = sum(adj_mat,1);
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% order = zeros(1,ncluster);
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% middle_cluster = find(recomb_count==max(admix_count));
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% reference_cluster = middle_cluster;
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% middle_point = floor(ncluster/2);
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% order(middle_point) = middle_cluster(1);
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% for i = middle_point+1:ncluster
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% order(i) = find(adj_mat(:,reference_cluster)==max(adj_mat(:,reference_cluster)));
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% adj_mat(referecen_cluster,order(i)) = 0;
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% adj_mat(order(i),reference_cluster) = 0;
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% reference_cluster = order(i);
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% end
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% [ordered_cluster,ix] = sort(size_cluster,'descend');
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% disp(['Number of populations: ' num2str(npops)]);
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% if npops>30
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% disp(' ');
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% disp('Figure can be drawn only if the number of populations');
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% disp('is less or equal to 30.');
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% disp(' ');
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% return;
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% end
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varit = giveColors(npops);
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korkeinviiva = 1.05;
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pieninarvo = -korkeinviiva;
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h0 = figure;
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set(h0, 'NumberTitle', 'off'); %image_figure; %Muutettu
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set(h0,'Tag','admixture_result');
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set(h0,'Name',['Admixture Result After Permutation - ' filename]);
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if size(popnames,1) > 150 % display only groups
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for i=1:nind
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popnames{i,1} = cell({'|'}); % CELL in the CELL
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end
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end
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for i = inliers
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pool = find(partition==i);
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if isempty(pool)
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continue
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end
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chosen_ix = 1 + floor(length(pool)/2);
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% if ~find(pool==chosen_one) % gap, find the other way
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% chosen_one = pool(end) - floor(length(pool)/2);
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% if ~find(pool==chosen_one) % then the algorithm really sucks
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% chosen_one = pool(1);
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% end
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% end
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chosen_one = pool(chosen_ix);
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popnames{chosen_one,1} = {[popnames{chosen_one,1}{1} sprintf('Cluster%d',i)]};
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end
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tiedot.popnames = popnames;
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tiedot.info = data;
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set(h0,'UserData',tiedot);
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set(gca,'Xlim', [-.5 ,nind+.5], 'YLim', [pieninarvo ,korkeinviiva], ...
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'XTick', [], 'XTickLabel', [], 'YTick', [], 'YTickLabel', []);
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% Display the color bars
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for i=1:nind
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if any(data(i,:)>0)
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cumOsuudet = cumsum(data(i,:));
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% Pylv<EFBFBD><EFBFBD>n piirt<EFBFBD>minen
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for j=1:admixnpops
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if j==1
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if cumOsuudet(1)>0
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h0 =patch([i-1, i, i, i-1], [0, 0, cumOsuudet(1), cumOsuudet(1)], varit(inliers(j),:));
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set(h0,'EdgeColor','none'); % Midevaa varten kommentoitava!
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end
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else
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if (cumOsuudet(j)>cumOsuudet(j-1))
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h0 = patch([i-1, i, i, i-1], [cumOsuudet(j-1), cumOsuudet(j-1), ...
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cumOsuudet(j), cumOsuudet(j)], varit(inliers(j),:));
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set(h0,'EdgeColor','none'); % Midevaa varten kommentoitava!
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end
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end
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end
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end
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end
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% Display the texts
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if ~isempty(popnames)
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npops = size(popnames,1); % NB! npops now stands for the number of individuals.
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for i=1:npops
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firstInd = popnames{i,2};
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if size(popnames,1)~=nind
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line([firstInd-1, firstInd-1], [0,1], 'Color', 'k'); %Populaatioiden rajat
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end
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% The determination of x_paikka is changed, since popnames could be
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% non-sequential. - Jing
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if i<npops
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% x_paikka = popnames{i,2}-1+(popnames{i+1,2}-popnames{i,2})/2;
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x_paikka = i-1;
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else
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% x_paikka = popnames{i,2}-1+(nind+1-popnames{i,2})/2;
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x_paikka = i-1+(nind+1-i)/2;
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end
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korkeuskerroin = pieninarvo / -0.2;
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suhdekerroin = npops/6;
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names = popnames{i,1}{1};
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max_length = length(names);
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for letter_num = 1: max_length % {1}
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letter = names(letter_num);%alter .004|
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color_ix = find(data(i,:)==max(data(i,:)));
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color_ix = color_ix(1);
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text(x_paikka+korjaus(letter)*suhdekerroin, ...
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0.0005*korkeuskerroin-0.02*letter_num*korkeuskerroin, ...
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letter, 'Interpreter','none','Color',varit(inliers(color_ix),:));
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% text(x_paikka+korjaus(letter)*suhdekerroin, ...
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% pieninarvo*letter_num/max_length, ...
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% letter, 'Interpreter','none','Color',varit(color_ix,:));
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end
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end
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line([nind,nind],[0,1],'Color','k');
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end
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fprintf('Finished.\n');
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%-------------------------------------------------------------------------------------
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function extra = korjaus(letter)
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if any(letter == 'ijlI')
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extra = 0.022;
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elseif any(letter == 'r')
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extra = 0.016;
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elseif any(letter == 'k')
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extra = 0.009;
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elseif any(letter == 'f')
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extra = 0.013;
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elseif any(letter == 't')
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extra = 0.014;
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elseif any(letter == 'w')
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extra = -0.003;
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else
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extra = 0;
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end;
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