Merge branch 'master' of https://github.com/abster12/deepchem

script:

- nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem

  -v deepchem --nologcapture

- find ./deepchem | grep .py$ |xargs python -m doctest -v

- if [ $TRAVIS_PYTHON_VERSION == '3.5']; then

      find ./deepchem | grep .py$ |xargs python -m doctest -v;

  fi

- bash devtools/travis-ci/test_format_code.sh

after_success:

- echo $TRAVIS_SECURE_ENV_VARS

### Using a conda environment

You can install deepchem in a new conda environment using the conda commands in scripts/install_deepchem_conda.sh

Installing via this script will ensure that you are **installing from the source**.

```bash

git clone https://github.com/deepchem/deepchem.git      # Clone deepchem source code from GitHub

via this installation procedure.

### Easy Install via Conda

```bash

conda install -c deepchem -c rdkit -c conda-forge -c omnia deepchem=1.3.1

```

**Note:** `Easy Install` installs the latest stable version of `deepchem` and _does not install from source_. If you need to install from source make sure you follow the steps [here](#using-a-conda-environment).

### Using a Docker Image

Using a docker image requires an NVIDIA GPU.  If you do not have a GPU please follow the directions for [using a conda environment](#using-a-conda-environment)

import random

import numpy as np

from sklearn.metrics import roc_auc_score

import scipy

def symmetric_normalize_adj(adj):

    adj = adj[:n_atoms, :n_atoms]

    degree = np.sum(adj, axis=1)

    D = np.diag(degree)

    D_sqrt = scipy.linalg.sqrtm(D)

    D_sqrt_inv = scipy.linalg.inv(D_sqrt)

    D_sqrt = np.sqrt(D)

    D_sqrt_inv = np.linalg.inv(D_sqrt)

    sym_norm = D_sqrt_inv.dot(adj)

    sym_norm = sym_norm.dot(D_sqrt_inv)

    new_adj = np.zeros(orig_shape)

"""

Imports all submodules

"""

from __future__ import print_function

from __future__ import division

from __future__ import unicode_literals

"""

Process an input dataset into a format suitable for machine learning.

"""

from __future__ import print_function

from __future__ import division

from __future__ import unicode_literals

import os