# HG changeset patch
# User davidvanzessen
# Date 1394543772 14400
# Node ID 9cf5050738ca14620fd09f9126146ed98b101a46
# Parent  3cce6e04b1e828315937208a1a70021f45e8c77d
Uploaded

diff -r 3cce6e04b1e8 -r 9cf5050738ca RScript.r
--- a/RScript.r	Thu Jan 23 08:35:31 2014 -0500
+++ b/RScript.r	Tue Mar 11 09:16:12 2014 -0400
@@ -26,8 +26,7 @@
 library(data.table)
 
 
-t
-read.table(inFile, sep="\t", header=TRUE, fill=T, comment.char="")
+test = read.table(inFile, sep="\t", header=TRUE, fill=T, comment.char="")
 
 test = test[test$Sample != "",]
 
diff -r 3cce6e04b1e8 -r 9cf5050738ca imgtconvert.py
--- a/imgtconvert.py	Thu Jan 23 08:35:31 2014 -0500
+++ b/imgtconvert.py	Tue Mar 11 09:16:12 2014 -0400
@@ -1,4 +1,5 @@
 import pandas as pd
+pd.options.mode.chained_assignment = None  # default='warn'
 import re
 import argparse
 import os
@@ -135,4 +136,4 @@
 outFrame["CDR3 Length DNA"] = outFrame["CDR3 Seq DNA"].map(str).map(len)
 safeLength = lambda x: len(x) if type(x) == str else 0
 outFrame = outFrame[(outFrame["CDR3 Seq DNA"].map(safeLength) > 0) & (outFrame["Top V Gene"] != "NA") & (outFrame["Top D Gene"] != "NA") & (outFrame["Top J Gene"] != "NA")] #filter out weird rows?
-outFrame.to_csv(outFile, sep="\t", index=False, index_label="index")
\ No newline at end of file
+outFrame.to_csv(outFile, sep="\t", index=False, index_label="index")