MPF.2021.2.8
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[Reverting back to v1, please make sure to use an earlier pymatgen version.] <br> This dataset contains the MPF.2021.2.8 data used to train the m3gnet model reported in `https://arxiv.org/abs/2202.02450` <br> I have split the dataset into two pickle files. To load the data, you can use example code as below. <br> ``` import pickle with open('block_0.p', 'rb') as f: data = pickle.load(f) <br> with open('block_1.p', 'rb') as f: data.update(pickle.load(f)) ``` <br> where `data` will be a dictionary with `material_id` as the key and an inner dictionary as the value. <br> The inner dictionary contains the snapshots of this `material_id`, with the following keys. ``` - structure - energy - force - stress - id ``` The `structure` is a list of pymatgen structures. <br> Each id in the `id` list is of format `material_id-calc_id-ionic_step_id`, where `calc_id` is 0 (second) or 1 (first) in the double relaxation process. <br> The `stress` here is the raw output from VASP, meaning that it is really the negative stress using the convention in our paper. Hence to train the model, please multiply stress with -0.1 (kBa to GPa and change sign) <br> The units for energy, force and stress in the data are eV, eV/A, and kBa. Remember to convert the stress to GPa and take the negative sign to work with m3gnet training.
【回退至v1版本，请务必使用较早版本的pymatgen库】 本数据集包含用于训练论文`https://arxiv.org/abs/2202.02450`中所报道的m3gnet模型的MPF.2021.2.8数据集。 本数据集已拆分为两个pickle格式文件。如需加载数据，可使用如下示例代码： import pickle with open('block_0.p', 'rb') as f: data = pickle.load(f) with open('block_1.p', 'rb') as f: data.update(pickle.load(f)) 其中`data`为以`material_id`为键、内层字典为值的字典对象。该内层字典包含对应`material_id`的快照数据，包含以下键： - `structure`：pymatgen结构列表 - `energy`：能量 - `force`：原子受力 - `stress`：应力 - `id`：计算标识 `id`列表中的每个标识均遵循`material_id-calc_id-ionic_step_id`格式，其中`calc_id`为0（对应第二次弛豫）或1（对应第一次弛豫），对应双弛豫过程。 此处的`stress`为VASP的原始输出结果，即遵循本文所用约定的负应力值。因此若要用于模型训练，请将应力值乘以-0.1（完成单位从kBa到GPa的转换并修正符号）。 本数据集中能量、受力与应力的单位分别为eV、eV/Å与kBa。请务必将应力转换为GPa并取负号，以适配m3gnet模型的训练需求。
