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authorCalvin <calvin@EESI>2013-02-18 09:01:52 -0500
committerCalvin <calvin@EESI>2013-02-18 09:01:52 -0500
commitc69b7e13895e8692afedb742bfdcc110bd982974 (patch)
tree10ea4f946411b0fea8c24f94bb5697d8f8808796
parentb8f5709b8bebb1ebe53505505b1360cc21e1691b (diff)
set the input matrix properly
-rwxr-xr-xquikr.py7
1 files changed, 4 insertions, 3 deletions
diff --git a/quikr.py b/quikr.py
index 1feb82d..4b29cec 100755
--- a/quikr.py
+++ b/quikr.py
@@ -33,6 +33,7 @@ def main():
# If we are using a custom trained matrix, we need to do some basic checks
if args.trained_matrix is not None:
+ trained_matrix_location = args.trained_matrix
if not os.path.isfile(args.trained_matrix):
parser.error("custom trained matrix not be found")
@@ -50,8 +51,8 @@ def main():
trained_matrix_location = "output.npy"
input_lambda = 10000
kmer = 6
- xstar = quikr(args.fasta, trained_matrix_location, kmer, input_lambda)
-
+ xstar = quikr(args.fasta, trained_matrix_location, kmer, input_lambda)
+ print xstar
return 0
def quikr(input_fasta_location, trained_matrix_location, kmer, default_lambda):
@@ -90,7 +91,7 @@ def quikr(input_fasta_location, trained_matrix_location, kmer, default_lambda):
# perform the non-negative least squares
# import pdb; pdb.set_trace()
- counts = np.rot90(counts)
+ trained_matrix = np.rot90(trained_matrix)
xstar = scipy.optimize.nnls(trained_matrix, counts)
xstar = xstar / sum(xstar)