Data, models, and additional code for MDtrajNet training and validation

Data, models, and additional code for training and validating MDtrajNet for publication Fuchun Ge, Pavlo O. Dral*. Artificial Intelligence for Direct Prediction of Molecular Dynamics Across Chemical Space. 2025. Preprint on arXiv: https://arxiv.org/abs/2505.16301 (2025.05.22). This repository contains: MD trajectory files propagated with MLatom, in Python npz format. The file names are descriptive. The files contain trajectory snapshots with xyz coordinates, species, and time. They can be loaded as, e.g., trajs = [dict(np.load(f'/mlatom/projects/4D/datasets/trajs/ethanol/traj{i+1}.npz')) for i in range(3)]; model.train(trajectories=trajs,...). The MDtrajNet model files in .pt format. They can be loaded with MLatom (https://github.com/dralgroup/mlatom). The custom code lj.py for generating the reference trajectory with the LJ potential. It uses the custom model class passed to MLatom. The file names are self-descriptive.用于发表级MDtrajNet模型训练与验证的数据集、模型及补充代码 葛富春，帕夫洛·O·德拉尔*。《跨化学空间直接预测分子动力学的人工智能》. 2025. arXiv预印本：https://arxiv.org/abs/2505.16301（2025.05.22）。 本仓库包含以下内容： 采用MLatom生成的Python npz格式分子动力学（Molecular Dynamics, MD）轨迹文件。文件名均具有明确语义，文件内存储了轨迹快照，包含xyz坐标、物种信息与时间步信息，可通过如下方式加载：例如，`trajs = [dict(np.load(f'/mlatom/projects/4D/datasets/trajs/ethanol/traj{i+1}.npz')) for i in range(3)]; model.train(trajectories=trajs,...)`。 格式为.pt的MDtrajNet模型文件，可通过MLatom（https://github.com/dralgroup/mlatom）加载。 用于生成朗道-琼斯（Lennard-Jones, LJ）势参考轨迹的自定义代码lj.py，其调用了传入MLatom的自定义模型类。 所有文件名均具备自解释性。