Commit a1d40a7b authored by Bharath Ramsundar's avatar Bharath Ramsundar
Browse files

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

parents 4555d413 c9be3663
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.style.yapf

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[style]
based_on_style = google
indent_width = 2
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@@ -15,19 +15,20 @@ install:
- conda update -q conda
- conda config --add channels http://conda.binstar.org/omnia
- conda install pandas
- conda install -c omnia rdkit
- conda install -c rdkit rdkit
- conda install -c omnia boost=1.59.0
- conda install -c omnia openbabel
- conda install joblib
- conda install h5py
- pip install six
#- pip install keras
- export KERAS_BACKEND=tensorflow
- conda install -c conda-forge protobuf=3.1.0
- conda install -c omnia mdtraj
- pip install tensorflow
- pip install tensorflow==0.12.1
- pip install yapf==0.16.0
- python setup.py install
script:
- nosetests -v deepchem --nologcapture
- bash devtools/travis-ci/test_format_code.sh
after_success:
- echo $TRAVIS_SECURE_ENV_VARS
- source devtools/travis-ci/after_sucess.sh
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@@ -51,7 +51,7 @@ Installation from source is the only currently supported format. ```deepchem```

3. `rdkit`
   ```bash
   conda install -c omnia rdkit
   conda install -c rdkit rdkit
   ```

4. `joblib`
@@ -74,7 +74,7 @@ Installation from source is the only currently supported format. ```deepchem```
    contact your local sysadmin to work out a custom installation. If your
    version of Linux is recent, then the following command will work:
    ```
    pip install tensorflow-gpu
    pip install tensorflow-gpu==0.12.1
    ```

8. `deepchem`: Clone the `deepchem` github repo:
@@ -221,8 +221,8 @@ Random splitting

|Dataset    |Model               |Train score/ROC-AUC|Valid score/ROC-AUC|
|-----------|--------------------|-------------------|-------------------|
|tox21      |logistic regression |0.903              |0.735              |
|           |Multitask network   |0.856              |0.783              |
|tox21      |logistic regression |0.902              |0.715              |
|           |Multitask network   |0.844              |0.795              |
|           |robust MT-NN        |0.855              |0.773              |
|           |graph convolution   |0.865              |0.827              |
|muv        |logistic regression |0.957              |0.719              |
@@ -383,11 +383,12 @@ We actively encourage community contributions to DeepChem. The first place to st
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 broadly follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html). In terms of practical changes, the biggest effect is that all code uses 2-space indents instead of 4-space indents. We encourage new contributors to make use of [pylint](https://www.pylint.org/) with the following command
```
pylint --disable=invalid-name --indent-string "  " --extension-pkg-whitelist=numpy [file.py]
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
```
Aim for a score of at least 8/10 on contributed files.

### 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).

deepchem/.gitignore

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core_grid.tar.gz
dock/autodock_vina_1_1_2_linux_x86/
random_full_DNN.tar.gz
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@@ -28,6 +28,18 @@ def load_solubility_data():
  
  return loader.featurize(input_file)

def load_butina_data():
  """Loads solubility dataset"""
  current_dir = os.path.dirname(os.path.abspath(__file__))
  featurizer = dc.feat.CircularFingerprint(size=1024)
  tasks = ["task"]
  # task_type = "regression"
  input_file = os.path.join(current_dir, "../../models/tests/butina_example.csv")
  loader = dc.data.CSVLoader(
      tasks=tasks, smiles_field="smiles", featurizer=featurizer)
  
  return loader.featurize(input_file)

def load_multitask_data():
  """Load example multitask data."""
  current_dir = os.path.dirname(os.path.abspath(__file__))
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