Merge remote-tracking branch 'origin/master' into new_bm_design

# DeepChem

## Contributing to DeepChem

We actively encourage community contributions to DeepChem. The first place to start getting involved is by running our examples locally. Afterwards, we encourage contributors to give a shot to improving our documentation. While we take effort to provide good docs, there's plenty of room for improvement. All docs are hosted on Github, either in `README.md` file, or in the `docs/` directory.

Once you've got a sense of how the package works, we encourage the use of Github issues to discuss more complex changes,  raise requests for new features or propose changes to the global architecture of DeepChem. Once consensus is reached on the issue, please submit a PR with proposed modifications. All contributed code to DeepChem will be reviewed by a member of the DeepChem team, so please make sure your code style and documentation style match our guidelines!

## Contributor License Agreement

In order to get a pull request accepted you must fill out our [License Agreement](https://www.clahub.com/agreements/lilleswing/deepchem).  The purpose of this agreement is to enable DeepChem to distribute your code and its derivatives.

### The Agreement

Contributor offers to license certain software (a “Contribution” or multiple “Contributions”) to DeepChem, and DeepChem agrees to accept said Contributions, under the terms of the open source license [The MIT License](https://opensource.org/licenses/MIT)

The Contributor understands and agrees that DeepChem shall have the irrevocable and perpetual right to make and distribute copies of any Contribution, as well as to create and distribute collective works and derivative works of any Contribution, under [The MIT License](https://opensource.org/licenses/MIT).

DeepChem understands and agrees that Contributor retains copyright in its Contributions. Nothing in this Contributor Agreement shall be interpreted to prohibit Contributor from licensing its Contributions under different terms from the [The MIT License](https://opensource.org/licenses/MIT) or this Contributor Agreement.

### Code Style Guidelines

DeepChem uses [yapf](https://github.com/google/yapf) to autoformat code.

``` bash

pip install yapf==0.16.0

cd <git_root>

yapf -i <python_files changed>

```

Our integration tests will fail if code is not formatted correctly

### Documentation Style Guidelines

DeepChem uses [NumPy style documentation](https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt). Please follow these conventions when documenting code, since we use [Sphinx+Napoleon](http://www.sphinx-doc.org/en/stable/ext/napoleon.html) to automatically generate docs on [deepchem.io](deepchem.io).

FROM nvidia/cuda

# Install some utilities

RUN apt-get update && \

    apt-get install -y -q wget git libxrender1 && \

    apt-get clean

# Install miniconda

RUN MINICONDA="Miniconda2-latest-Linux-x86_64.sh" && \

    wget --quiet https://repo.continuum.io/miniconda/$MINICONDA && \

    bash $MINICONDA -b -p /miniconda && \

    rm -f $MINICONDA

ENV PATH /miniconda/bin:$PATH

# Install deepchem conda package from omnia

# TODO: Uncomment this when there is a stable release of deepchem.

#RUN conda config --add channels omnia

#RUN conda install --yes deepchem

# Install deepchem with GPU support from github using Tue 14 Mar 2017 git head

# TODO: Get rid of this when there is a stable release of deepchem.

RUN git clone https://github.com/deepchem/deepchem.git && \

    cd deepchem && \

    git checkout 415aebadff54175b7ba108964723c8f69438af94 && \

    bash scripts/install_deepchem_conda.sh root && \

    pip install tensorflow-gpu==0.12.1 && \

    python setup.py develop

# Clean up

RUN cd deepchem && \

    git clean -fX

# Run tests

#RUN pip install nose && \

#    nosetests -v deepchem --nologcapture

* [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)

* [boost](http://www.boost.org/)

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.

### Full Anaconda distribution

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

   Follow the [installation instructions](http://docs.continuum.io/anaconda/install#linux-install)

### Using a conda environment

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

2. `openbabel`

```bash

   conda install -c omnia openbabel=2.4.0

bash scripts/install_deepchem_conda.sh deepchem

pip install tensorflow-gpu==0.12.1                      # If you want GPU support

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

cd deepchem

python setup.py install                                 # Manual install

nosetests -v deepchem --nologcapture                    # Run tests

```

This creates a new conda environment `deepchem` and installs in it the dependencies that

are needed. To access it, use the `source activate deepchem` command.

Check [this link](https://conda.io/docs/using/envs.html) for more information about

the benefits and usage of conda environments. **Warning**: Segmentation faults can [still happen](https://github.com/deepchem/deepchem/pull/379#issuecomment-277013514)

via this installation procedure.

### Installing Dependencies Manually

3. `rdkit`

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

   Follow the [installation instructions](http://docs.continuum.io/anaconda/install#linux-install)

2. `rdkit`

   ```bash

   conda install -c rdkit rdkit

   ```

4. `joblib`

3. `joblib`

   ```bash

   conda install joblib 

   ```

5. `six`

4. `six`

   ```bash

   pip install six

   ```

5. `networkx`

   ```bash

   conda install -c anaconda networkx=1.11

   ```

6. `mdtraj`

   ```bash

    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.

### Using a conda environment

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

### Using a Docker Image

For major releases we will create docker environments with everything pre-installed

``` bash

bash scripts/install_deepchem_conda.sh deepchem

pip install tensorflow-gpu==0.12.1                      # If you want GPU support

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

cd deepchem

python setup.py install                                 # Manual install

nosetests -v deepchem --nologcapture                    # Run tests

# This will the download the latest stable deepchem docker image into your images

docker pull deepchemio/deepchem

# This will create a container out of our latest image

docker run -i -t deepchemio/deepchem

# You are now in a docker container whose python has deepchem installed

# For example you can run our tox21 benchmark

cd deepchem/examples

python benchmark.py -d tox21

# Or you can start playing with it in the command line

pip install jupyter

ipython

import deepchem as dc

```

This creates a new conda environment `deepchem` and installs in it the dependencies that

are needed. To access it, use the `source activate deepchem` command.

Check [this link](https://conda.io/docs/using/envs.html) for more information about

the benefits and usage of conda environments. **Warning**: Segmentation faults can [still happen](https://github.com/deepchem/deepchem/pull/379#issuecomment-277013514)

via this installation procedure.

## FAQ

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

|kaggle          |MT-NN regression    |2200            |3200           |

## Contributing to DeepChem

We actively encourage community contributions to DeepChem. The first place to start getting involved is by running our examples locally. Afterwards, we encourage contributors to give a shot to improving our documentation. While we take effort to provide good docs, there's plenty of room for improvement. All docs are hosted on Github, either in this `README.md` file, or in the `docs/` directory.

Once you've got a sense of how the package works, we encourage the use of Github issues to discuss more complex changes,  raise requests for new features or propose changes to the global architecture of DeepChem. Once consensus is reached on the issue, please submit a PR with proposed modifications. All contributed code to DeepChem will be reviewed by a member of the DeepChem team, so please make sure your code style and documentation style match our guidelines!

### Code Style Guidelines

DeepChem uses [yapf](https://github.com/google/yapf) to autoformat code.  We created a git pre-commit hook to make this process easier.

``` bash

cp devtools/travis-ci/pre-commit .git/hooks

pip install yapf==0.16.0

```

### Documentation Style Guidelines

DeepChem uses [NumPy style documentation](https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt). Please follow these conventions when documenting code, since we use [Sphinx+Napoleon](http://www.sphinx-doc.org/en/stable/ext/napoleon.html) to automatically generate docs on [deepchem.io](deepchem.io).

### Gitter

Join us on gitter at [https://gitter.im/deepchem/Lobby](https://gitter.im/deepchem/Lobby). Probably the easiest place to ask simple questions or float requests for new features.

__author__ = "Bharath Ramsundar"

__copyright__ = "Copyright 2016, Stanford University"

__license__ = "GPL"

__license__ = "MIT"

def sparsify_features(X):