From 854c120916bc08ac631bd1cd9180b3be70760240 Mon Sep 17 00:00:00 2001
From: Waldir Leoncio <waldir.leoncio@gmail.com>
Date: Tue, 14 Jul 2020 14:35:48 +0200
Subject: [PATCH] Documentation update

---
 NAMESPACE     |   1 +
 R/greedyMix.R | 123 --------------------------------------------------
 2 files changed, 1 insertion(+), 123 deletions(-)

diff --git a/NAMESPACE b/NAMESPACE
index 70e107a..b7d74df 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -17,6 +17,7 @@ export(inputdlg)
 export(isfield)
 export(laskeMuutokset4)
 export(learn_simple_partition)
+export(linkage)
 export(logml2String)
 export(lueGenePopData)
 export(lueNimi)
diff --git a/R/greedyMix.R b/R/greedyMix.R
index 1939e69..51e4e3d 100644
--- a/R/greedyMix.R
+++ b/R/greedyMix.R
@@ -832,75 +832,6 @@ greedyMix <- function(
 # 	   k = children(~t) - m;
 # 	end
 
-
-# 	%---------------------------------------------------------------------------------------
-
-# 	function [Z, dist] = newGetDistances(data, rowsFromInd)
-
-# 	ninds = max(data(:,end));
-# 	nloci = size(data,2)-1;
-# 	riviLkm = nchoosek(ninds,2);
-
-# 	empties = find(data<0);
-# 	data(empties)=0;
-# 	data = uint8(data);   % max(noalle) oltava <256
-
-# 	pariTaulu = zeros(riviLkm,2);
-# 	aPointer=1;
-# 	for a=1:ninds-1
-# 		pariTaulu(aPointer:aPointer+ninds-1-a,1) = ones(ninds-a,1)*a;
-# 		pariTaulu(aPointer:aPointer+ninds-1-a,2) = (a+1:ninds)';
-# 		aPointer = aPointer+ninds-a;
-# 	end
-
-# 	eka = pariTaulu(:,ones(1,rowsFromInd));
-# 	eka = eka * rowsFromInd;
-# 	miinus = repmat(rowsFromInd-1 : -1 : 0, [riviLkm 1]);
-# 	eka = eka - miinus;
-
-# 	toka = pariTaulu(:,ones(1,rowsFromInd)*2);
-# 	toka = toka * rowsFromInd;
-# 	toka = toka - miinus;
-
-# 	%eka = uint16(eka);
-# 	%toka = uint16(toka);
-
-# 	summa = zeros(riviLkm,1);
-# 	vertailuja = zeros(riviLkm,1);
-
-# 	clear pariTaulu; clear miinus;
-
-# 	x = zeros(size(eka));    x = uint8(x);
-# 	y = zeros(size(toka));   y = uint8(y);
-
-# 	for j=1:nloci;
-
-# 		for k=1:rowsFromInd
-# 			x(:,k) = data(eka(:,k),j);
-# 			y(:,k) = data(toka(:,k),j);
-# 		end
-
-# 		for a=1:rowsFromInd
-# 			for b=1:rowsFromInd
-# 				vertailutNyt = double(x(:,a)>0 & y(:,b)>0);
-# 				vertailuja = vertailuja + vertailutNyt;
-# 				lisays = (x(:,a)~=y(:,b) & vertailutNyt);
-# 				summa = summa+double(lisays);
-# 			end
-# 		end
-# 	end
-
-# 	clear x;    clear y;   clear vertailutNyt;
-# 	nollat = find(vertailuja==0);
-# 	dist = zeros(length(vertailuja),1);
-# 	dist(nollat) = 1;
-# 	muut = find(vertailuja>0);
-# 	dist(muut) = summa(muut)./vertailuja(muut);
-# 	clear summa; clear vertailuja;
-
-# 	Z = linkage(dist');
-
-
 # 	%----------------------------------------------------------------------------------------
 
 
@@ -946,60 +877,6 @@ greedyMix <- function(
 # 	%----------------------------------------------------------------------------------------
 
 
-# 	function Z = linkage(Y, method)
-# 	[k, n] = size(Y);
-# 	m = (1+sqrt(1+8*n))/2;
-# 	if k ~= 1 | m ~= fix(m)
-# 	  error('The first input has to match the output of the PDIST function in size.');
-# 	end
-# 	if nargin == 1 % set default switch to be 'co'
-# 	   method = 'co';
-# 	end
-# 	method = lower(method(1:2)); % simplify the switch string.
-# 	monotonic = 1;
-# 	Z = zeros(m-1,3); % allocate the output matrix.
-# 	N = zeros(1,2*m-1);
-# 	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 logml = ...
 # 		initialCounts(partition, data, npops, rows, noalle, adjprior)