Loading README.md +33 −56 Original line number Diff line number Diff line Loading @@ -46,48 +46,28 @@ Installation from source is the only currently supported format. ```deepchem``` conda install -c omnia openbabel=2.4.0 ``` 3. `pandas` ```bash conda install pandas ``` 4. `rdkit` 3. `rdkit` ```bash conda install -c omnia rdkit ``` 5. `boost` ```bash conda install -c omnia boost=1.59.0 ``` 6. `joblib` 4. `joblib` ```bash conda install joblib ``` 7. `keras` ```bash pip install keras --user ``` `deepchem` only supports the `tensorflow` backend for keras. To set the backend to `tensorflow`, add the following line to your `~/.bashrc` 5. `keras` ```bash export KERAS_BACKEND=tensorflow pip install keras ``` See [keras docs](https://keras.io/backend/) for more details and alternate methods of setting backend. `deepchem` only supports the `tensorflow` (default) backend for keras. 8. `mdtraj` 6. `mdtraj` ```bash conda install -c omnia mdtraj ``` 9. `scikit-learn` ```bash conda install scikit-learn ``` 10. `tensorflow`: Installing `tensorflow` on older versions of Linux (which 7. `tensorflow`: Installing `tensorflow` on older versions of Linux (which have glibc < 2.17) can be very challenging. For these older Linux versions, contact your local sysadmin to work out a custom installation. If your version of Linux is recent, then the following command will work: Loading @@ -95,12 +75,7 @@ Installation from source is the only currently supported format. ```deepchem``` conda install -c https://conda.anaconda.org/jjhelmus tensorflow ``` 11. `h5py`: ``` conda install h5py ``` 12. `deepchem`: Clone the `deepchem` github repo: 8. `deepchem`: Clone the `deepchem` github repo: ```bash git clone https://github.com/deepchem/deepchem.git ``` Loading @@ -109,9 +84,9 @@ Installation from source is the only currently supported format. ```deepchem``` python setup.py install ``` 13. To run test suite, install `nosetests`: 9. To run test suite, install `nosetests`: ```bash pip install nose --user pip install nose ``` Make sure that the correct version of `nosetests` is active by running ```bash Loading @@ -120,7 +95,7 @@ Installation from source is the only currently supported format. ```deepchem``` You might need to uninstall a system install of `nosetests` if there is a conflict. 14. If installation has been successful, all tests in test suite should pass: 10. If installation has been successful, all tests in test suite should pass: ```bash nosetests -v deepchem --nologcapture ``` Loading Loading @@ -181,10 +156,12 @@ Environmental Protection Agency, Environmental Research Laboratory, 1987. 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 DeepChem loader class ``dc.load.DataLoader``. Instances of this class must be passed a ``Featurizer`` object. DeepChem provides a number of different subclasses of ``Featurizer`` for convenience: transform lists of molecules into vectors, we need to subclasses of DeepChem loader class ```dc.data.DataLoader``` such as ```dc.data.CSVLoader``` or ```dc.data.SDFLoader```. Users can subclass ```dc.data.DataLoader``` to load arbitrary file formats. All loaders must be passed a ```dc.feat.Featurizer``` object. DeepChem provides a number of different subclasses of ```dc.feat.Featurizer``` for convenience. ### Performances * Classification Loading Loading
README.md +33 −56 Original line number Diff line number Diff line Loading @@ -46,48 +46,28 @@ Installation from source is the only currently supported format. ```deepchem``` conda install -c omnia openbabel=2.4.0 ``` 3. `pandas` ```bash conda install pandas ``` 4. `rdkit` 3. `rdkit` ```bash conda install -c omnia rdkit ``` 5. `boost` ```bash conda install -c omnia boost=1.59.0 ``` 6. `joblib` 4. `joblib` ```bash conda install joblib ``` 7. `keras` ```bash pip install keras --user ``` `deepchem` only supports the `tensorflow` backend for keras. To set the backend to `tensorflow`, add the following line to your `~/.bashrc` 5. `keras` ```bash export KERAS_BACKEND=tensorflow pip install keras ``` See [keras docs](https://keras.io/backend/) for more details and alternate methods of setting backend. `deepchem` only supports the `tensorflow` (default) backend for keras. 8. `mdtraj` 6. `mdtraj` ```bash conda install -c omnia mdtraj ``` 9. `scikit-learn` ```bash conda install scikit-learn ``` 10. `tensorflow`: Installing `tensorflow` on older versions of Linux (which 7. `tensorflow`: Installing `tensorflow` on older versions of Linux (which have glibc < 2.17) can be very challenging. For these older Linux versions, contact your local sysadmin to work out a custom installation. If your version of Linux is recent, then the following command will work: Loading @@ -95,12 +75,7 @@ Installation from source is the only currently supported format. ```deepchem``` conda install -c https://conda.anaconda.org/jjhelmus tensorflow ``` 11. `h5py`: ``` conda install h5py ``` 12. `deepchem`: Clone the `deepchem` github repo: 8. `deepchem`: Clone the `deepchem` github repo: ```bash git clone https://github.com/deepchem/deepchem.git ``` Loading @@ -109,9 +84,9 @@ Installation from source is the only currently supported format. ```deepchem``` python setup.py install ``` 13. To run test suite, install `nosetests`: 9. To run test suite, install `nosetests`: ```bash pip install nose --user pip install nose ``` Make sure that the correct version of `nosetests` is active by running ```bash Loading @@ -120,7 +95,7 @@ Installation from source is the only currently supported format. ```deepchem``` You might need to uninstall a system install of `nosetests` if there is a conflict. 14. If installation has been successful, all tests in test suite should pass: 10. If installation has been successful, all tests in test suite should pass: ```bash nosetests -v deepchem --nologcapture ``` Loading Loading @@ -181,10 +156,12 @@ Environmental Protection Agency, Environmental Research Laboratory, 1987. 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 DeepChem loader class ``dc.load.DataLoader``. Instances of this class must be passed a ``Featurizer`` object. DeepChem provides a number of different subclasses of ``Featurizer`` for convenience: transform lists of molecules into vectors, we need to subclasses of DeepChem loader class ```dc.data.DataLoader``` such as ```dc.data.CSVLoader``` or ```dc.data.SDFLoader```. Users can subclass ```dc.data.DataLoader``` to load arbitrary file formats. All loaders must be passed a ```dc.feat.Featurizer``` object. DeepChem provides a number of different subclasses of ```dc.feat.Featurizer``` for convenience. ### Performances * Classification Loading
