Bug fix

Dockerfile

@@ -1,10 +1,7 @@
 FROM continuumio/miniconda3
 LABEL maintainer="anruadhawick@gmail.com"
 
-RUN conda install -y pytorch cudatoolkit=11.3 -c pytorch
-RUN conda install -c conda-forge biopython
-RUN conda install -y tqdm tabulate
-RUN conda install -y -c anaconda scikit-learn
+RUN conda install -y numpy scipy seaborn h5py hdbscan gcc openmp tqdm biopython fraggenescan hmmer tabulate pytorch pytorch-cuda=11.7 -c pytorch -c nvidia -c bioconda c conda-forge biopython
 RUN apt-get update && \
     apt-get -y install g++ bzip2 lzma-dev zlib1g-dev libbz2-dev && \
     apt-get -y install libcurl4-openssl-dev libpthread-stubs0-dev liblzma-dev libomp-dev
@@ -17,7 +14,7 @@ RUN ["bash", "docker_build.sh"]
 
 ENV PATH="/usr/LRBinner/:${PATH}"
 
-ENTRYPOINT ["LRBinner"]
+ENTRYPOINT ["lrbinner.py"]
 CMD ["--help"]
 
 # docker build -t anuradhawick/lrbinner .

README.md

@@ -7,17 +7,17 @@
 ![GitHub](https://img.shields.io/github/license/anuradhawick/LRBinner)
 ![GitHub code size in bytes](https://img.shields.io/github/languages/code-size/anuradhawick/LRBinner)
 
-## Use Docker!
+## Docker pathway
 
 `Dockerfile` is now available. (If you're familiar deploying a docker file, No Image pushed yet)
 
 ## Dependencies
 LRBinner is coded purely using C++ (v9+) and Python 3.10. To run LRBinner, you will need to install the following python and C++ modules.
 
-A possible conda environment to work (credits [Calum Walsh](https://github.com/cazzlewazzle89))
+A possible conda/mamba environment to work (credits [Calum Walsh](https://github.com/cazzlewazzle89))
 
 ```sh
-conda create -n lrbinner -y python=3.10 numpy scipy seaborn h5py hdbscan gcc openmp tqdm biopython fraggenescan hmmer tabulate pytorch pytorch-cuda=11.7 -c pytorch -c nvidia
+conda create -n lrbinner -y python=3.10 numpy scipy seaborn h5py hdbscan gcc openmp tqdm biopython fraggenescan hmmer tabulate pytorch pytorch-cuda=11.7 -c pytorch -c nvidia -c bioconda
 ```
 
 ### Python dependencies
@@ -232,7 +232,7 @@ optional arguments:
 
 ## Citation
 
-If you use LRBinner please cite using the the following bibtex files
+If you use LRBinner please cite using the following bibtex entries.
 
 ```bibtex
 @InProceedings{wickramarachchi_et_al:LIPIcs.WABI.2021.11,
@@ -273,6 +273,4 @@ If you use LRBinner please cite using the the following bibtex files
 
 ```
 
-> More updates to come!
-
-> Get in touch [anuradhawick.com](https://anuradhawick.com)
+Get in touch and connect at [anuradhawick.com](https://anuradhawick.com) or email [info@anuradhawick.com](mailto:info@anuradhawick.com)

lrbinner.py

@@ -4,6 +4,7 @@
 import sys
 import time
 import logging
+import shutil
 
 from mbcclr_utils import pipelines
 
@@ -110,6 +111,8 @@ def main():
 
     # running mode
     mode = args.mode
+    # is resuming
+    resume = args.resume
 
     reads_path = args.reads_path
     threads = args.threads
@@ -120,6 +123,9 @@ def main():
     logger = logging.getLogger('LRBinner')
     logger.setLevel(logging.DEBUG)
 
+    if not resume and os.path.isdir(f"{output}"):
+        shutil.rmtree(output)
+
     formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
     consoleHeader = logging.StreamHandler()
     consoleHeader.setFormatter(formatter)

mbcclr_utils/pipelines.py

@@ -1,12 +1,8 @@
 import pickle
-import os
 import logging
-import sys
-from collections import defaultdict
 from Bio import SeqIO
 import numpy as np
 import random
-import shutil
 
 from mbcclr_utils.runners_utils import *
 from mbcclr_utils import ae_utils
@@ -34,8 +30,6 @@ def run_contig_binning(args):
     checkpoints_path = f"{output}/checkpoints"
 
     if not resume:
-        if os.path.isdir(f"{output}"):
-            shutil.rmtree(f"{output}")
         checkpoint = Checkpointer(checkpoints_path)
     else:
         logger.info("Resuming the program from previous checkpoints")
@@ -265,8 +259,6 @@ def run_reads_binning(args):
     checkpoints_path = f"{output}/checkpoints"
 
     if not resume:
-        if os.path.isdir(f"{output}"):
-            shutil.rmtree(f"{output}")
         checkpoint = Checkpointer(checkpoints_path)
     else:
         logger.info("Resuming the program from previous checkpoints")