Merge pull request #84 from BinPro/develop

New version: 0.3.1

.travis.yml

@@ -15,7 +15,7 @@ before_install:
    - export PATH=/home/travis/miniconda/bin:$PATH
    - conda update --yes conda
    - sudo apt-get update -qq
-   - sudo apt-get install -qq build-essential libgsl0-dev
+   - sudo apt-get install -qq build-essential libgsl0-dev bedtools
 install:
   - conda install --yes python=$TRAVIS_PYTHON_VERSION cython numpy scipy biopython pandas pip scikit-learn
   - pip install bcbio-gff

MANIFEST.in

@@ -1 +1,3 @@
 recursive-include c-concoct *.h
+include LICENSE.txt
+include README.md

README.md

@@ -1,4 +1,4 @@
-#CONCOCT 0.3.0 [![Build Status](https://travis-ci.org/BinPro/CONCOCT.png?branch=master)](https://travis-ci.org/BinPro/CONCOCT)#
+#CONCOCT 0.3.1 [![Build Status](https://travis-ci.org/BinPro/CONCOCT.png?branch=master)](https://travis-ci.org/BinPro/CONCOCT)#
 
 A program for unsupervised binning of metagenomic contigs by using nucleotide composition, 
 coverage data in multiple samples and linkage data from paired end reads.
@@ -87,15 +87,15 @@ You need to [get Docker installed](https://www.docker.io/gettingstarted/) and sp
 
 We provide a Docker image:
 
-<b>binnisb/concoct_0.3.0</b> contains CONCOCT and all its dependencies for the [complete worklfow](doc/complete_example.md). Currently it does not do SCG evaluation.
+<b>binnisb/concoct_0.3.1</b> contains CONCOCT and all its dependencies for the [complete worklfow](doc/complete_example.md). Currently it does not do SCG evaluation.
 
 The following command will then download the image from the Docker image index, map the Data folder to the image and log you into the docker image.
 ```
-sudo docker run -v /home/USER/Data:/opt/Data -i -t binnisb/concoct_0.3.0 bash
+sudo docker run -v /home/USER/Data:/opt/Data -i -t binnisb/concoct_0.3.1 bash
 ```
 To test concoct you can then do:
 ```
-$ cd /opt/CONCOCT-0.3.0
+$ cd /opt/CONCOCT-0.3.1
 $ nosetests
 ```
 Which should execute all tests without errors.

bin/concoct

@@ -23,12 +23,9 @@ def main(args):
     if len(threshold_filter[threshold_filter==True]) < 2:
         logging.error('Not enough contigs pass the threshold filter. Exiting!')
         sys.exit(-1)
-
+    
     if cov is not None:
-        joined = composition.join(
-            cov.ix[:,cov_range[0]:cov_range[1]],
-            how="inner"
-            )
+        joined = composition.join(cov.ix[:,cov_range[0]:cov_range[1]],how="inner")
     else:
         joined = composition