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authorCalvin <calvin@EESI>2013-02-27 14:40:15 -0500
committerCalvin <calvin@EESI>2013-02-27 14:40:15 -0500
commitd5528274719639989634f296f37da270fe88dd5d (patch)
treecefc34f91d690fd9d3615318b265df3784ade6a6
parent0732d29b06f67ec8fb54958ff453699b4f0bdb4d (diff)
Write the comments in for the work to be done
Comment first, write code later! Also I fixed an erroneous space that really didn't need to be there. Laid down the import for biopyton. Created the basic iteration through our fasta files and added loading of fasta file titles through biopython
-rwxr-xr-xmultifasta_to_otu.py16
1 files changed, 15 insertions, 1 deletions
diff --git a/multifasta_to_otu.py b/multifasta_to_otu.py
index 3e14fcf..e313e4a 100755
--- a/multifasta_to_otu.py
+++ b/multifasta_to_otu.py
@@ -1,5 +1,6 @@
#!/usr/bin/python
from multiprocessing import Pool
+from Bio import SeqIO
import multiprocessing
import os
import quikr_train as qt
@@ -54,7 +55,7 @@ def main():
if not os.path.isfile(args.trained_matrix):
parser.error("custom trained matrix not found")
- # use alternative lambda
+ # use alternative lambda
if args.lamb is not None:
lamb = args.lamb
@@ -67,11 +68,24 @@ def main():
# Load trained matrix
trained_matrix = np.load(args.trained_matrix);
+ # Return a list of the input directory
fasta_list = os.listdir(args.input_directory)
+ # Queue up and run our quikr functions.
pool = Pool(processes=jobs)
results = pool.map(quikr_call, fasta_list)
+ # Create a dictionary and load up our keys
+
+
+ for fasta in fasta_list:
+ fasta_file = open(input_directory + fasta, "rU")
+
+ for record in SeqIO.parse(fasta_file, "fasta") :
+
+ # load the keys with values from each fasta result
+
+ # Write the otu table
return 0
def quikr_call(fasta_file):