ParticleGrid is a SIMD accelerated 3D grid generation library. 3D grids are generated from conformed molecular points and can be used with conventional 3D deep learning tools.
2021 ELLIS Machine Learning for Molecule Discovery Workshop, our contribution.
Install via pip with:
pip install git+https://github.com/ParticleGrid/ParticleGrid.git
Clone and build repo with:
git clone https://github.com/ParticleGrid/ParticleGrid.git
cd ParticleGrid
pip install .
Generating a grid from 3D coordinates:
import numpy as np
from ParticleGrid import coord_to_grid
# points are in the format (channel, x, y, z)
test_points = np.array([0, 0.5, 0.5, 0.5],
[1, 0.0, 0.1, 0.2])
grid = coord_to_grid(test_points,
width=1,
height=1,
depth=1,
num_channels=2,
grid_size=32,
variance=0.05)
print(grid.shape) # Generates a (2,32,32,32) gridMore example uses of ParticleGrid can be found in the examples directory.
- Discretization
- Per-atom weights and variance
- 2D grids
- Periodic crystal grids
- Multi-threading support
- GPU support
- PyTorch integration
ParticleGrid has a BSD-style license, as found in the LICENSE file.