Merge pull request #323 from rbharath/docs_debug

- conda install h5py

- pip install keras

- export KERAS_BACKEND=tensorflow

- conda install seaborn

- conda install six

- conda install dill

- conda install runipy

- conda install ipyparallel

- pip install runipy

- pip install nglview

- conda install -c omnia mdtraj

- python setup.py install

#- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0rc1-cp27-none-linux_x86_64.whl;

#  -O else export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0rc1-cp35-cp35m-linux_x86_64.whl;

#  -O fi 

#- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then pip install --ignore-installed --upgrade $TF_BINARY_URL;

#  -O else pip3 install --ignore-installed --upgrade $TF_BINARY_URL;

#  -O fi

- conda install -c https://conda.anaconda.org/jjhelmus tensorflow=0.10.0rc0

script:

- nosetests -v deepchem --nologcapture

import numpy as np

import csv

import numbers

import dill

import tempfile

from rdkit import Chem

import time

    2) Complex featurization

      -) PDB files for interacting molecules.

    3) User specified featurizations.

  """

  time1 = time.time()

  df[featurizer.feature_fields] = df[featurizer.feature_fields].apply(pd.to_numeric)

import os

import numpy as np

import pandas as pd

import multiprocessing as mp

import random

from functools import partial

from deepchem.utils.save import save_to_disk

    mols = list(mols)

    features = []

    for i, mol in enumerate(mols):

      if verbose and i % log_every_n == 0:

        log("Featurizing %d / %d" % (i, len(mols)))

      if mol is not None:

        features.append(self._featurize(mol))

      else:

import tempfile

import os

import shutil

import multiprocessing as mp

import time