diff options
| -rw-r--r-- | src/matlab/quikrCustomTrained.m | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/src/matlab/quikrCustomTrained.m b/src/matlab/quikrCustomTrained.m index c7961c7..e594951 100644 --- a/src/matlab/quikrCustomTrained.m +++ b/src/matlab/quikrCustomTrained.m @@ -10,12 +10,12 @@ if nargin~=4 error('There must be exactly 4 input arguments: the training matrix, the /path/to/input/fastafile, the k-mer size, and lambda');
end
-[rws, clumns]=size(trainingmatrix); %get the size of the training matrix
-if rws~=4^k
+[rows, columns]=size(trainingmatrix); %get the size of the training matrix
+if rows~=4^k
error('Wrong k-mer size for input training matrix');
end
-[status, counts]=unix(['count-kmers -r 6 -1 -u ' inputfasta]); %count the 6-mers in the fasta file, in the forward direction, return the counts without labels
+[status, counts]=unix([sprintf('count-kmers -r %d -1 -u ',k) ' ' inputfasta]); %count the k-mers in the fasta file, in the forward direction, return the counts without labels.
if status ~= 0
error('count-kmers failed: ensure count-kmers is in your path.');
@@ -25,7 +25,7 @@ counts=counts/sum(counts); %normalize the counts into a probability vector yaux=[0;lambda*counts]; %form the sample vector
-Aaux=[ones(1,clumns);lambda*trainingmatrix]; %form the k-mer sensing matrix
+Aaux=[ones(1,columns);lambda*trainingmatrix]; %form the k-mer sensing matrix
warning off
xstar=lsqnonneg(Aaux,yaux); %perform the non-negative lease squares
warning on
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