Documentation update
This commit is contained in:
Waldir Leoncio
parent
e885081f1d
commit
854c120916
2 changed files with 1 additions and 123 deletions
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@ -17,6 +17,7 @@ export(inputdlg)
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export(isfield)
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export(laskeMuutokset4)
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export(learn_simple_partition)
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export(linkage)
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export(logml2String)
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export(lueGenePopData)
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export(lueNimi)
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123
R/greedyMix.R
123
R/greedyMix.R
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@ -832,75 +832,6 @@ greedyMix <- function(
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# k = children(~t) - m;
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# end
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# %---------------------------------------------------------------------------------------
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# function [Z, dist] = newGetDistances(data, rowsFromInd)
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# ninds = max(data(:,end));
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# nloci = size(data,2)-1;
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# riviLkm = nchoosek(ninds,2);
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# empties = find(data<0);
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# data(empties)=0;
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# data = uint8(data); % max(noalle) oltava <256
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# pariTaulu = zeros(riviLkm,2);
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# aPointer=1;
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# for a=1:ninds-1
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# pariTaulu(aPointer:aPointer+ninds-1-a,1) = ones(ninds-a,1)*a;
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# pariTaulu(aPointer:aPointer+ninds-1-a,2) = (a+1:ninds)';
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# aPointer = aPointer+ninds-a;
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# end
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# eka = pariTaulu(:,ones(1,rowsFromInd));
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# eka = eka * rowsFromInd;
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# miinus = repmat(rowsFromInd-1 : -1 : 0, [riviLkm 1]);
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# eka = eka - miinus;
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# toka = pariTaulu(:,ones(1,rowsFromInd)*2);
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# toka = toka * rowsFromInd;
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# toka = toka - miinus;
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# %eka = uint16(eka);
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# %toka = uint16(toka);
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# summa = zeros(riviLkm,1);
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# vertailuja = zeros(riviLkm,1);
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# clear pariTaulu; clear miinus;
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# x = zeros(size(eka)); x = uint8(x);
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# y = zeros(size(toka)); y = uint8(y);
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# for j=1:nloci;
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# for k=1:rowsFromInd
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# x(:,k) = data(eka(:,k),j);
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# y(:,k) = data(toka(:,k),j);
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# end
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# for a=1:rowsFromInd
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# for b=1:rowsFromInd
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# vertailutNyt = double(x(:,a)>0 & y(:,b)>0);
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# vertailuja = vertailuja + vertailutNyt;
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# lisays = (x(:,a)~=y(:,b) & vertailutNyt);
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# summa = summa+double(lisays);
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# end
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# end
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# end
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# clear x; clear y; clear vertailutNyt;
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# nollat = find(vertailuja==0);
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# dist = zeros(length(vertailuja),1);
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# dist(nollat) = 1;
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# muut = find(vertailuja>0);
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# dist(muut) = summa(muut)./vertailuja(muut);
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# clear summa; clear vertailuja;
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# Z = linkage(dist');
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# %----------------------------------------------------------------------------------------
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@ -946,60 +877,6 @@ greedyMix <- function(
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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;
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# n = m; % since m is changing, we need to save m in n.
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# R = 1:n;
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# for s = 1:(n-1)
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# X = Y;
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# [v, k] = min(X);
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# i = floor(m+1/2-sqrt(m^2-m+1/4-2*(k-1)));
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# j = k - (i-1)*(m-i/2)+i;
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# Z(s,:) = [R(i) R(j) v]; % update one more row to the output matrix A
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# I1 = 1:(i-1); I2 = (i+1):(j-1); I3 = (j+1):m; % these are temp variables.
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# U = [I1 I2 I3];
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# I = [I1.*(m-(I1+1)/2)-m+i i*(m-(i+1)/2)-m+I2 i*(m-(i+1)/2)-m+I3];
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# J = [I1.*(m-(I1+1)/2)-m+j I2.*(m-(I2+1)/2)-m+j j*(m-(j+1)/2)-m+I3];
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# switch method
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# case 'si' %single linkage
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# Y(I) = min(Y(I),Y(J));
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# case 'av' % average linkage
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# Y(I) = Y(I) + Y(J);
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# case 'co' %complete linkage
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# Y(I) = max(Y(I),Y(J));
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# case 'ce' % centroid linkage
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# K = N(R(i))+N(R(j));
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# Y(I) = (N(R(i)).*Y(I)+N(R(j)).*Y(J)-(N(R(i)).*N(R(j))*v^2)./K)./K;
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# case 'wa'
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# Y(I) = ((N(R(U))+N(R(i))).*Y(I) + (N(R(U))+N(R(j))).*Y(J) - ...
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# N(R(U))*v)./(N(R(i))+N(R(j))+N(R(U)));
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# end
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# J = [J i*(m-(i+1)/2)-m+j];
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# Y(J) = []; % no need for the cluster information about j.
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# % update m, N, R
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# m = m-1;
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# N(n+s) = N(R(i)) + N(R(j));
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# R(i) = n+s;
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# R(j:(n-1))=R((j+1):n);
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# end
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# %-----------------------------------------------------------------------------------
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# function logml = ...
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# initialCounts(partition, data, npops, rows, noalle, adjprior)
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