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

sudo: required

dist: trusty

install:

- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then

    wget https://repo.continuum.io/archive/Anaconda2-4.2.0-Linux-x86_64.sh -O anaconda.sh;

  else

    wget https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh -O anaconda.sh;

  fi

- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then wget https://repo.continuum.io/archive/Anaconda2-4.2.0-Linux-x86_64.sh

  -O anaconda.sh; else wget https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh

  -O anaconda.sh; fi

- bash anaconda.sh -b -p $HOME/anaconda

- export PATH="$HOME/anaconda/bin:$PATH"

- hash -r

script:

- nosetests -v deepchem --nologcapture

after_success:

- echo $TRAVIS_SECURE_ENV_VARS

- source devtools/travis-ci/after_sucess.sh

# AWS access_key and secret key secured through travis secure var api.

env:

  global:

  - secure: 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

  - secure: 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

deepchem

=============

Deep Learning Toolchain for Drug Discovery and Quantum Chemistry

Requirements

------------

# DeepChem

DeepChem aims to provide a high quality open-source toolchain that

democratizes the use of deep-learning in drug discovery, materials science, and quantum

chemistry. DeepChem is a package developed by the [Pande group](https://pande.stanford.edu/) at

Stanford and originally created by [Bharath Ramsundar](http://rbharath.github.io/). 

### Table of contents:

* [Requirements](#requirements)

* [Installation from Source](#installation)

* [FAQ](#faq)

* [Getting Started](#getting-started)

    * [Input Formats](#input-formats)

    * [Data Featurization](#data-featurization)

* [DeepChem Publications](#deepchem-publications)

* [Examples](/examples)

* [About Us](#about-us)

## Requirements

* [openbabel](http://openbabel.org/wiki/Main_Page)

* [pandas](http://pandas.pydata.org/)

* [rdkit](http://www.rdkit.org/docs/Install.html)

* [mdtraj](http://mdtraj.org/)

* [tensorflow](https://www.tensorflow.org/)

Linux (64-bit) Installation from Source

---------------------------------------

## Installation

```deepchem``` currently supports both Python 2.7 and Python 3.5, but is not supported on any OS'es except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below.

Installation from source is the only currently supported format. ```deepchem``` currently supports both Python 2.7 and Python 3.5, but is not supported on any OS'es except 64 bit linux. Please make sure you follow the directions below precisely. While you may already have system versions of some of these packages, there is no guarantee that `deepchem` will work with alternate versions than those specified below.

1. Download the **64-bit** Python 2.7 or Python 3.5 versions of Anaconda for linux [here](https://www.continuum.io/downloads#_unix). 

    Note that the full test-suite uses up a fair amount of memory. 

    Try running tests for one submodule at a time if memory proves an issue.

Frequently Asked Questions

--------------------------

## FAQ

1. Question: I'm seeing some failures in my test suite having to do with MKL

   ```Intel MKL FATAL ERROR: Cannot load libmkl_avx.so or libmkl_def.so.```

   If you see a core-dump, then it's a sign there's an issue with your `openbabel` install. Try reinstalling `openbabel` from source for your machine.

Getting Started

---------------

## Getting Started

The first step to getting started is looking at the examples in the `examples/` directory. Try running some of these examples on your system and verify that the models train successfully. Afterwards, to apply `deepchem` to a new problem, try starting from one of the existing examples and modifying it step by step to work with your new use-case.

### Input Formats

Accepted input formats for deepchem include csv, pkl.gz, and sdf files. For

example, with a csv input, in order to build models, we expect the

following columns to have entries for each row in the csv file.

1. A column containing SMILES strings [1].

2. A column containing an experimental measurement.

3. (Optional) A column containing a unique compound identifier.

Here's an example of a potential input file. 

|Compound ID    | measured log solubility in mols per litre | smiles         | 

|---------------|-------------------------------------------|----------------| 

| benzothiazole | -1.5                                      | c2ccc1scnc1c2  | 

Here the "smiles" column contains the SMILES string, the "measured log

solubility in mols per litre" contains the experimental measurement and

"Compound ID" contains the unique compound identifier.

[2] Anderson, Eric, Gilman D. Veith, and David Weininger. "SMILES, a line

notation and computerized interpreter for chemical structures." US

Environmental Protection Agency, Environmental Research Laboratory, 1987.

### Data Featurization

Most machine learning algorithms require that input data form vectors.

However, input data for drug-discovery datasets routinely come in the

format of lists of molecules and associated experimental readouts. To

transform lists of molecules into vectors, we need to use the ``deechem``

featurization class ``DataFeaturizer``. Instances of this class must be

passed a ``Featurizer`` object. ``deepchem`` provides a number of

different subclasses of ``Featurizer`` for convenience:

## DeepChem Publications

1. [Computational Modeling of β-secretase 1 (BACE-1) Inhibitors using

Ligand Based

Approaches](http://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00290)

## About Us

DeepChem is a package by the [Pande group](https://pande.stanford.edu/) at Stanford. DeepChem was originally created by [Bharath Ramsundar](http://rbharath.github.io/), and has grown through the contributions of a number of undergraduate, graduate, and postdoctoral researchers working with the Pande lab.

# Create the docs and push them to S3

# -----------------------------------

echo "About to install numpydoc, s3cmd"

pip install numpydoc s3cmd

pip install numpydoc s3cmd msmb_theme sphinx_rtd_theme

conda list -e

mkdir -p docs/_build

echo "About to build docs"

sphinx-build -b html docs docs/_build

sphinx-apidoc -f -o docs/source deepchem

sphinx-build -b html docs/source docs/_build

echo "About to push docs to s3"

python devtools/travis-ci/push-docs-to-s3.py

BUCKET_NAME = 'deepchem.io'

if not any(d.project_name == 's3cmd' for d in pip.get_installed_distributions()):

  raise ImportError('The s3cmd pacakge is required. try $ pip install s3cmd')

  raise ImportError('The s3cmd package is required. try $ pip install s3cmd')

print("os.environ.keys()")

print(os.environ.keys())

# The secret key is available as a secure environment variable

# on travis-ci to push the build documentation to Amazon S3.

deepchem.featurizers.basic

==========================

.. automodule:: deepchem.featurizers.basic

   .. rubric:: Classes

   .. autosummary::

      Featurizer

      MolecularWeight

      RDKitDescriptors

 No newline at end of file