1
0
Fork 0
mirror of https://github.com/MillironX/beefblup.git synced 2024-11-13 03:03:08 +00:00

Construct additive relationship matrix

This commit is contained in:
Thomas A. Christensen II 2018-09-21 16:42:23 -06:00
parent 0da8dc6e7a
commit f2615b1048

View file

@ -26,11 +26,15 @@ data(:,2) = num2cell(datenum(data(:,2)));
% Sort the array by date
data = sortrows(data,2);
% Coerce all id fields to string format
strings = [1 3 4];
data(:,strings) = cellfun(@num2str, data(:,strings), 'UniformOutput', false);
% Create a lookup lambda function to find the animal represented by a
% certain id
animalrow = @(id) find(strcmp(data(:,1), id));
ids = [data{:,1}];
numanimals = length(ids);
numanimals = length(data(:,1));
% Store column numbers that need to be deleted
% Column 6 contains an intermediate Excel calculation and always needs to
@ -117,4 +121,46 @@ for i = 1:length(normal)
end
% Create an empty matrix for the additive relationship matrix
A = sparse(numanimals, numanimals);
A = sparse(numanimals, numanimals);
% Create lambdas to find sire and dam of each animal
dam = @(id) [data{animalrow(num2str(id)), 3}];
sire = @(id) [data{animalrow(num2str(id)), 4}];
% Create the additive relationship matrix by the FORTRAN method presented
% by Henderson
for i = 1:numanimals
if strcmp(sire(i), 'NaN') && strcmp(dam(i), 'NaN')
for j = 1:(i-1)
A(j,i) = 0;
end
A(i,i) = 1;
continue
end
if strcmp(sire(i), 'NaN') && not(strcmp(dam(i), 'NaN'))
for j = 1:(i-1)
A(j,i) = A(j,str2double(dam(i)));
A(i,j) = A(j,str2double(dam(i)));
end
A(i,i) = 1;
continue
end
if strcmp(dam(i), 'NaN') && not(strcmp(sire(i), 'NaN'))
for j=1:(i-1)
A(j,i) = A(j,str2double(sire(i)));
A(i,j) = A(j,str2double(sire(i)));
end
A(i,i) = 1;
continue
end
for j=1:(i-1)
A(j,i) = 0.5.*(A(j,str2double(sire(i))) + A(j,str2double(dam(i))));
A(i,j) = 0.5.*(A(j,str2double(sire(i))) + A(j,str2double(dam(i))));
end
A(i,i) = 1 + 0.5.*A(str2double(sire(i)), str2double(dam(i)));
continue
end