diff options
| author | mutantturkey <mutantturke@gmail.com> | 2013-03-08 14:28:04 -0500 | 
|---|---|---|
| committer | mutantturkey <mutantturke@gmail.com> | 2013-03-08 14:28:04 -0500 | 
| commit | d86ae7aecd3d4ea677db6133198a3cb2381a873c (patch) | |
| tree | 2f2175eca01f29a1bbb8a15c6c49e755945f1dd5 | |
| parent | d1c402420cfe75a04a7c181d5b3e45cdde7bcf72 (diff) | |
convert into a module, rename out functions so all quikr functions are withing quikr.function name
| -rwxr-xr-x | quikr.py | 12 | 
1 files changed, 5 insertions, 7 deletions
| @@ -4,7 +4,6 @@ import sys  import scipy.optimize.nnls  import scipy.sparse  import numpy as np -import quikr_util as qu  from subprocess import *  import argparse  import platform @@ -29,7 +28,7 @@ def isCompressed(filename):      return False -def quikr_train(input_file_location, kmer): +def train_matrix(input_file_location, kmer):    """    Takes a input fasta file, and kmer, returns a custom trained matrix    """ @@ -57,21 +56,20 @@ def quikr_train(input_file_location, kmer):    return matrix -def quikr_load_trained_matrix_from_file(input_fasta_location, trained_matrix_location, kmer, default_lambda): +def load_trained_matrix_from_file(trained_matrix_location):    """ This is a helper function to load our trained matrix and run quikr """ -  if qu.isCompressed(trained_matrix_location): +  if isCompressed(trained_matrix_location):      trained_matrix_file = gzip.open(trained_matrix_location, "rb")    else:      trained_matrix_file = open(trained_matrix_location, "rb")    trained_matrix = np.load(trained_matrix_file) -  xstar = quikr(input_fasta_location, trained_matrix, kmer, default_lambda) -  return xstar +  return trained_matrix -def quikr(input_fasta_location, trained_matrix, kmer, default_lambda): +def calculate_estimated_frequencies(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 | 
