diff options
| author | Calvin <calvin@EESI> | 2013-02-27 12:07:51 -0500 | 
|---|---|---|
| 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; | 
