Commit 056e7745 authored by Bharath Ramsundar's avatar Bharath Ramsundar
Browse files

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

parents dfc445db 214f2e92
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@@ -2,6 +2,7 @@ language: python
python:
- '2.7'
- '3.5'
- '3.6'
sudo: required
dist: trusty
install:
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@@ -16,7 +16,7 @@ RUN conda update -n base conda
RUN export LANG=en_US.UTF-8 && \
    git clone https://github.com/deepchem/deepchem.git && \
    cd deepchem && \
    git checkout 2.0.0 && \
    git checkout 2.1.0 && \
    sed -i -- 's/tensorflow$/tensorflow-gpu/g' scripts/install_deepchem_conda.sh && \
    bash scripts/install_deepchem_conda.sh && \
    python setup.py develop
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@@ -73,7 +73,7 @@ via this installation procedure.
### Easy Install via Conda

```bash
conda install -c deepchem -c rdkit -c conda-forge -c omnia deepchem=2.0.0
conda install -c deepchem -c rdkit -c conda-forge -c omnia deepchem=2.1.0
```
**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).

@@ -183,4 +183,4 @@ DeepChem is supported by a number of corporate partners who use DeepChem to solv


## Version
2.0.0
2.1.0
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@@ -412,5 +412,5 @@ class ImageLoader(DataLoader):
      return NumpyDataset(images)
    else:
      # from_numpy currently requires labels. Make dummy labels
      labels = np.zeros(len(images))
      labels = np.zeros((len(images), 1))
      return DiskDataset.from_numpy(images, labels)
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@@ -86,6 +86,10 @@ class ConvMol(object):
        for deg in range(self.min_deg, self.max_deg + 1)
    ]

    self.degree_list = []
    for i, deg in enumerate(range(self.min_deg, self.max_deg + 1)):
      self.degree_list.extend([deg] * deg_size[i])

    # Get the the start indices for items in each block
    self.deg_start = cumulative_sum(deg_size)

@@ -264,17 +268,11 @@ class ConvMol(object):

    num_mols = len(mols)

    atoms_per_mol = [mol.get_num_atoms() for mol in mols]

    # Get atoms by degree
    atoms_by_deg = [
        mol.get_atoms_with_deg(deg)
        for deg in range(min_deg, max_deg + 1)
        for mol in mols
    ]

    # stack the atoms
    all_atoms = np.vstack(atoms_by_deg)
    # Results should be sorted by (atom_degree, mol_index)
    atoms_by_deg = np.concatenate([x.atom_features for x in mols])
    degree_vector = np.concatenate([x.degree_list for x in mols], axis=0)
    # Mergesort is a "stable" sort, so the array maintains it's secondary sort of mol_index
    all_atoms = atoms_by_deg[degree_vector.argsort(kind='mergesort')]

    # Sort all atoms by degree.
    # Get the size of each atom list separated by molecule id, then by degree
@@ -297,8 +295,7 @@ class ConvMol(object):

    # Determines the membership (atom i belongs to membership[i] molecule)
    membership = [
        k
        for deg in range(min_deg, max_deg + 1) for k in range(num_mols)
        k for deg in range(min_deg, max_deg + 1) for k in range(num_mols)
        for i in range(mol_deg_sz[deg][k])
    ]

@@ -371,7 +368,6 @@ class MultiConvMol(object):
  """

  def __init__(self, nodes, deg_adj_lists, deg_slice, membership, num_mols):

    self.nodes = nodes
    self.deg_adj_lists = deg_adj_lists
    self.deg_slice = deg_slice
@@ -398,7 +394,6 @@ class WeaveMol(object):
  """

  def __init__(self, nodes, pairs):

    self.nodes = nodes
    self.pairs = pairs
    self.num_atoms = self.nodes.shape[0]
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