mirror of
https://github.com/MillironX/beefblup.git
synced 2024-11-13 03:03:08 +00:00
Fixed additive relationship matrix creation
This commit is contained in:
parent
0ba6bae677
commit
f54fd46fda
2 changed files with 44 additions and 57 deletions
|
@ -61,13 +61,29 @@ data = sortrows(data,2);
|
|||
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
|
||||
animal2row = @(id) find(strcmp(data(:,1), id));
|
||||
row2animal = @(rownum) [data{rownum,1}];
|
||||
ids = [data{:,1}];
|
||||
% Define fields to hold id values for animals and their parents
|
||||
ids = char(data{:,1});
|
||||
damids = char(data{:,3});
|
||||
sireids = char(data{:,4});
|
||||
numanimals = length(data(:,1));
|
||||
|
||||
% Define fields to hold the index values for animals and their parents
|
||||
dam = zeros(numanimals,1);
|
||||
sire = zeros(numanimals,1);
|
||||
|
||||
% Find all row numbers where an animal was a parent
|
||||
for i=1:numanimals
|
||||
% Find all animals that this animal birthed
|
||||
dammatch = ismember(damids, ids(i,:), 'rows');
|
||||
damindexes = find(dammatch == 1);
|
||||
dam(damindexes) = i;
|
||||
|
||||
% Find all animals that this animal sired
|
||||
sirematch = ismember(sireids, ids(i,:), 'rows');
|
||||
sireindexes = find(sirematch == 1);
|
||||
sire(sireindexes) = i;
|
||||
end
|
||||
|
||||
% Store column numbers that need to be deleted
|
||||
% Column 6 contains an intermediate Excel calculation and always needs to
|
||||
% be deleted
|
||||
|
@ -181,53 +197,34 @@ disp('Creating the additive relationship matrix...')
|
|||
% Create an empty matrix for the additive relationship matrix
|
||||
A = zeros(numanimals, numanimals);
|
||||
|
||||
% Create lambdas to find sire and dam of each animal
|
||||
id2dam = @(id) [data{animal2row(num2str(id)), 3}];
|
||||
id2sire = @(id) [data{animal2row(num2str(id)), 4}];
|
||||
row2dam = @(rownum) [data{rownum, 3}];
|
||||
row2sire = @(rownum) [data{rownum, 4}];
|
||||
rowofdam = @(id) animal2row(id2dam(id));
|
||||
rowofsire = @(id) animal2row(id2sire(id));
|
||||
row2rowofdam = @(rownum) rowofdam(row2animal(rownum));
|
||||
row2rowofsire = @(rownum) rowofsire(row2animal(rownum));
|
||||
|
||||
% Create the additive relationship matrix by the FORTRAN method presented
|
||||
% by Henderson
|
||||
for i = 1:numanimals
|
||||
id = row2animal(i);
|
||||
if isempty(row2rowofsire(i)) && isempty(row2rowofdam(i))
|
||||
if dam(i) ~= 0 && sire(i) ~= 0
|
||||
for j = 1:(i-1)
|
||||
A(j,i) = 0;
|
||||
A(j,i) = 0.5*(A(j,sire(i))+A(j,dam(i)));
|
||||
A(i,j) = A(j,i);
|
||||
end
|
||||
A(i,i) = 1;
|
||||
continue
|
||||
end
|
||||
|
||||
if isempty(row2rowofsire(i)) && not(isempty(row2dam(i)))
|
||||
for j = 1:(i-1)
|
||||
A(j,i) = A(j,row2rowofdam(i));
|
||||
A(i,j) = A(j,row2rowofdam(i));
|
||||
end
|
||||
A(i,i) = 1;
|
||||
continue
|
||||
end
|
||||
|
||||
if isempty(row2rowofdam(i)) && not(isempty(row2rowofsire(i)))
|
||||
for j=1:(i-1)
|
||||
A(j,i) = A(j,row2rowofsire(i));
|
||||
A(i,j) = A(j,row2rowofsire(i));
|
||||
end
|
||||
A(i,i) = 1;
|
||||
continue
|
||||
end
|
||||
|
||||
for j=1:(i-1)
|
||||
A(j,i) = 0.5.*(A(j,row2rowofsire(i)) + A(j,row2rowofdam(i)));
|
||||
A(i,j) = 0.5.*(A(j,row2rowofsire(i)) + A(j,row2rowofdam(i)));
|
||||
end
|
||||
A(i,i) = 1 + 0.5.*A(row2rowofsire(i), row2rowofdam(i));
|
||||
continue
|
||||
|
||||
A(i,i) = 1 + 0.5*A(sire(i),dam(i));
|
||||
elseif dam(i) ~= 0 && sire(i) == 0
|
||||
for j = 1:(i-1)
|
||||
A(j,i) = 0.5*A(j,dam(i));
|
||||
A(i,j) = A(j,i);
|
||||
end
|
||||
A(i,i) = 1;
|
||||
elseif dam(i) == 0 && sire(i) ~=0
|
||||
for j = 1:(i-1)
|
||||
A(j,i) = 0.5*A(j,sire(i));
|
||||
A(i,j) = A(j,i);
|
||||
end
|
||||
A(i,i) = 1;
|
||||
else
|
||||
for j = 1:(i-1)
|
||||
A(j,i) = 0;
|
||||
A(i,j) = 0;
|
||||
end
|
||||
A(i,i) = 1;
|
||||
end
|
||||
end
|
||||
|
||||
disp('Creating the additive relationship matrix... Done!')
|
||||
|
|
|
@ -1,10 +0,0 @@
|
|||
% uniquenan
|
||||
% Serves the same purpose as UNIQUE, but ensures any NaN fields are not
|
||||
% counted
|
||||
function y = uniquenan(x)
|
||||
y = unique(x);
|
||||
if any(isnan(y))
|
||||
y(isnan(y)) = [];
|
||||
y(end + 1) = NaN;
|
||||
end
|
||||
end
|
Loading…
Reference in a new issue