Added changes to process scripts.

import openpyxl as px

import numpy as np

import argparse

import csv

from rdkit import Chem

import subprocess

from vs_utils.utils import SmilesGenerator

def parse_args(input_args=None):

  """Parse command-line arguments."""

  parser = argparse.ArgumentParser()

  parser.add_argument('--data', required=1,

  parser.add_argument('--input-file', required=1,

                      help='Input file with data.')

  parser.add_argument("--columns", required=1, nargs="+",

                      help = "Names of columns.")

  parser.add_argument('--column-types', required=1, nargs="+",

                      choices=['string', 'float', 'list', 'float-array'],

                      help='Name of dataset to process.')

  parser.add_argument("--name", required=1,

                      help="Name of the dataset.")

  parser.add_argument("--out", required=1,

  column_types = ["string", "string", "float", "float", "float", "float",

      "float", "float", "float", "float"]

def generate_targets(xlsx_file, columns, column_types, out_pkl, out_sdf):

  """Process input data file."""

  rows, mols = [], []

def gen_xlsx_rows(xlxs_file):

  W = px.load_workbook(xlsx_file, use_iterators=True)

  p = W.get_sheet_by_name(name="Sheet1")

  return p.iter_rows()

def get_xlsx_row_data(row):

  return [cell.internal_value for cell in row]

def gen_csv_rows(csv_file):

  # This is a memory leak...

  f = open(csv_file, "rb")

  return csv.reader(f, delimiter="\t")

def generate_targets(input_file, columns, column_types, out_pkl, out_sdf, type="csv"):

  """Process input data file."""

  rows, mols = [], []

  smiles = SmilesGenerator()

  for row_index, row in enumerate(p.iter_rows()):

  if type == "xlsx":

    row_gen = gen_xlsx_rows(input_file)

  elif type == "csv":

    row_gen = gen_csv_rows(input_file)

  for row_index, raw_row in enumerate(row_gen):

    print row_index

    # Skip row labels.

    if row_index == 0:

      continue

    row_data = [cell.internal_value for cell in row]

    if type == "xlsx":

      row_data = get_xlsx_row_data(raw_row)

    elif type == "csv":

      row_data = raw_row 

    row = {}

    for ind, (column, column_type) in enumerate(zip(columns, column_types)):

      if column_type == "string":

        row[column] = row_data[ind]

      elif column_type == "float":

        row[column] = parse_float_input(row_data[ind])

      elif column_type == "float-array" and ind = len(columns) - 1:

        row[column] = np.array(row_data[ind:])

      elif column_type == "list":

        row[column] = row_data[ind].split(",")

      elif column_type == "float-array":

        row[column] = np.array(row_data[ind].split(","))

    mol = Chem.MolFromSmiles(row["smiles"])

    row["smiles"] = smiles.get_smiles(mol)

def main():

  args = parse_args()

  out_pkl, out_sdf = generate_directories(args.name, args.out)

  generate_targets(args.data, out_pkl, out_sdf)

  generate_targets(args.input_file, args.columns, args.column_types, out_pkl, out_sdf)

  generate_fingerprints(args.name, args.out)