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Tensorflow + Molecules = TensorMol
| Date | Stars |
|---|---|
| 2026-07-24 | 277 |
| 2026-07-25 | 277 |
| 2026-07-28 | 277 |
| 2026-07-30 | 277 |
| 2026-08-06 | 277 |
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# ►<img src="doc/images/TensorMol.png" width="400">  -Title signature by Alex Graves' handwriting LSTM https://arxiv.org/abs/1308.0850 [](https://badge.fury.io/py/TensorMol)   [](http://tensormol.readthedocs.io/en/latest/?badge=latest) ## Authors: Kun Yao ([email protected]), John Herr ([email protected]), David Toth ([email protected]), Ryker McIntyre([email protected]), Nicolas Casetti, [John Parkhill](http://blogs.nd.edu/parkhillgroup) ([email protected]) ## Model Chemistries: - Behler-Parrinello with electrostatics - Many Body Expansion - Bonds in Molecules NN - Atomwise Forces - Inductive Charges ## Simulation Types: - Optimizations - Molecular Dynamics (NVE,NVT Nose-Hoover) - Monte Carlo - Open/Periodic Boundary Conditions - Meta-Dynamics - Infrared spectra by propagation - Infrared spectra by Harmonic Approximation. - Nudged Elastic Band - Path integral simulations via interface with [I-PI](https://github.com/i-pi/i-pi) MD engine. ## News: - Did we disappear? NO! but TensorMol0.2 is being developed in a private developers branch. It'll be back here soon. - (update 3/29/2018) TensorMol0.2 will arrive before 5/1. It adds additn'l element support, geometrical constraints, conformational search and other features. ## License: GPLv3 By using this software you agree to the terms in COPYING ## Installation: - Install TensorFlow(>1.1), otherwise TensorMol is self-contained. - Works on OSX, Ubuntu, and Windows subsystem for Linux: ``` git clone https://github.com/jparkhill/TensorMol.git cd TensorMol # If you are using python2x sudo pip install -e . # If you are using python3x sudo pip3 install -e . python test.py ``` ## Demo of training a neural network force field using TensorMol: - Copy the training script into the tensormol folder:```cp samples/training_sample.py .``` Run the script: ```python training_sample.py ``` This will train a network force field for water. ## Test example for TensorMol01: - Download our pretrained neural networks (network.tar.gz). [Networks for water and molecules that only contains C, H, O, N](https://drive.google.com/drive/folders/1IfWPs7i5kfmErIRyuhGv95dSVtNFo0e_?usp=sharing) (The file is about 6 Gigabyte. This may take a while) - Copy the zipped trained networks file (network.tar.gz) into TensorMol folder. Unzip it. The networks should be in './networks' folder. - Copy the test script into the tensormol folder:```cp samples/test_tensormol01.py .``` Run the script: ```python test_tensormol01.py``` The test sample contains geometry optimization, molecular dynamic, harmonic IR spectrum and realtime IR spectrum. ## Timing Information TensorMol is robust and fast. You can get an BP+electrostatic energy and force of this monstrous cube of 24,000 atoms in less than 100 seconds on a 2015 MacbookPro (Core i7 2.5Ghz, 16GB mem). Periodic simulations are about 3x more expensive. <img src="doc/images/monster.png" width="400"> <img src="doc/images/Timings.png" width="400"> <img src="doc/images/PeriodicTimings.png" width="400"> ## Usage: - ```import TensorMol as tm``` - We are working on /doc/Tutorials, but it's sparse now. We've done a lot of re-writing, and so if you are looking for good examples, look for /samples files with recent commits. - A collection of tests are located in samples/test_tensormol01.py but this requires first downloading the trained networks from the Arxiv paper. - `python samples/test_tensormol01.py` - IPI interface: start server: ~/i-pi/i-pi samples/i-pi_interface/H2O_cluster.xml > log &; run client: python test_ipi.py ## Sample Results ### Biological molecules Because Neural network force fields do not rely on any specific atom typing or bond topolo
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:708eb9a28c1ac37a, topic:neural-network, topic:tensorflow
matched fp:708eb9a28c1ac37a, topic:simulation
matched fp:708eb9a28c1ac37a, topic:chemistry