removing old scripts

## Corporate Supporters

DeepChem is supported by a number of corporate partners who use DeepChem to solve interesting problems.

### Schrödinger

[![Schödinger](https://github.com/deepchem/deepchem/blob/master/docs/source/_static/schrodinger_logo.png)](https://www.schrodinger.com/)

> DeepChem has transformed how we think about building QSAR and QSPR models when very large data sets are available; and we are actively using DeepChem to investigate how to best combine the power of deep learning with next generation physics-based scoring methods.

### DeepCrystal

<img src="https://github.com/deepchem/deepchem/blob/master/docs/source/_static/deep_crystal_logo.png" alt="DeepCrystal Logo" height=150px/>

> DeepCrystal was an early adopter of DeepChem, which we now rely on to abstract away some of the hardest pieces of deep learning in drug discovery. By open sourcing these efficient implementations of chemically / biologically aware deep-learning systems, DeepChem puts the latest research into the hands of the scientists that need it, materially pushing forward the field of in-silico drug discovery in the process.

#!/bin/bash

#SBATCH --job-name=controller

#SBATCH --output=controller_%A_%a.out

#SBATCH --error=controller_%A_%a.err

#SBATCH --time=12:00:00

##SBATCH --partition=normal

#SBATCH --partition=bigmem

#SBATCH --qos=bigmem

#SBATCH -n 4

ipcontroller --ip='*' --log-to-file=False &

for i in {0..90}; do

    echo $i;

    sbatch engine.sh

done

sleep 48h

"""

Manipulate CSV data files.

"""

from __future__ import print_function

from __future__ import division

from __future__ import absolute_import

import pandas as pd

import csv

import argparse

def parse_args(input_args=None):

  parser = argparse.ArgumentParser()

  parser.add_argument(

    "--descriptor", required=1,

    help="Name of input descriptor CSV file.")

  parser.add_argument(

    "--activities", required=1,

    help="Name of input activities CSV file.")

  parser.add_argument(

    "--output", required=1,

    help="Name of output CSV file.")

  return parser.parse_args(input_args)

def remove_trailing_comma(infile, outfile):

  with open(infile, 'r') as infile, open(outfile, 'w') as outfile:

    csv_writer = csv.writer(outfile)

    for row in csv.reader(infile):

      csv_writer.writerow(row[:-1])  # removes the last comma in each row

# TODO (Bowen): make this function less memory intensive

def combine_descriptor_activities(descriptor_file, activities_file, outfile):

  # set 1st column as the column index of dataframe

  descriptor_df = pd.read_csv(descriptor_file,

                              index_col=0)

  activities_df = pd.read_csv(activities_file, index_col=0)

  # merge descriptor and activities dataframe into output dataframe based on

  # the molecule name, which is the index for both dataframes (but named

  # differently). Default merge is inner merge

  combined_df = pd.merge(descriptor_df, activities_df,

                         left_index=True, right_index=True)

  # need to manually set dataframe indexname after merge based on index

  combined_df.index.name = "Molecule"

  combined_df.to_csv(outfile)

def main():

  args = parse_args()

  descriptor_file = args.descriptor

  activities_file = args.activities

  outfile = args.output

  combine_descriptor_activities(descriptor_file, activities_file, outfile)

if __name__ == '__main__':

  main()

from tensorflow.python.client import device_lib

def get_available_gpus():

  local_device_protos = device_lib.list_local_devices()

  return [x.name for x in local_device_protos if x.device_type == 'GPU']

print(get_available_gpus())