diff options
author | Calvin <calvin@EESI> | 2013-02-27 12:07:51 -0500 |
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committer | Calvin <calvin@EESI> | 2013-02-27 12:07:51 -0500 |
commit | e7473956c15a9881174d63a99cac735e9482038e (patch) | |
tree | c38752e2a0b75f59e04a6cf4e57ea73a4dee9248 | |
parent | 6da40aa924e2720f358c64fd5aaa54ec2c726f0a (diff) |
* add helper quikr_load_trained_from_file to load file
* change quikr to load a numpy matrix, not file
-rwxr-xr-x | quikr.py | 10 |
1 files changed, 8 insertions, 2 deletions
@@ -47,7 +47,13 @@ def main(): np.savetxt(args.output, xstar, delimiter=",", fmt="%f") return 0 -def quikr(input_fasta_location, trained_matrix_location, kmer, default_lambda): +def quikr_load_trained_matrix_from_file(input_fasta_location, trained_matrix_location, kmer, default_lambda): + + trained_matrix = np.load(trained_matrix_location) + xstar = quikr(input_fasta_location, trained_matrix, kmer, default_lambda) + return xstar + +def quikr(input_fasta_location, trained_matrix, kmer, default_lambda): """ input_fasta is the input fasta file to find the estimated frequencies of trained_matrix is the trained matrix we are using to estimate the species @@ -80,7 +86,7 @@ def quikr(input_fasta_location, trained_matrix_location, kmer, default_lambda): counts = np.concatenate([np.zeros(1), counts]) # load our trained matrix - trained_matrix = np.load(trained_matrix_location) + #form the k-mer sensing matrix trained_matrix = trained_matrix * default_lambda; |