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  1. .gitattributes +698 -32
  2. README.md +78 -0
  3. README_zh.md +78 -0
  4. data/MatPL/AuAg/AuAg-5762.xyz +3 -0
  5. data/MatPL/AuAg/pwdata/Ag10Au22/train/atom_type.npy +3 -0
  6. data/MatPL/AuAg/pwdata/Ag10Au22/train/ei.npy +3 -0
  7. data/MatPL/AuAg/pwdata/Ag10Au22/train/energies.npy +3 -0
  8. data/MatPL/AuAg/pwdata/Ag10Au22/train/forces.npy +3 -0
  9. data/MatPL/AuAg/pwdata/Ag10Au22/train/image_type.npy +3 -0
  10. data/MatPL/AuAg/pwdata/Ag10Au22/train/lattice.npy +3 -0
  11. data/MatPL/AuAg/pwdata/Ag10Au22/train/position.npy +3 -0
  12. data/MatPL/AuAg/pwdata/Ag10Au22/train/virials.npy +3 -0
  13. data/MatPL/AuAg/pwdata/Ag10Au38/train/atom_type.npy +3 -0
  14. data/MatPL/AuAg/pwdata/Ag10Au38/train/ei.npy +3 -0
  15. data/MatPL/AuAg/pwdata/Ag10Au38/train/energies.npy +3 -0
  16. data/MatPL/AuAg/pwdata/Ag10Au38/train/forces.npy +3 -0
  17. data/MatPL/AuAg/pwdata/Ag10Au38/train/image_type.npy +3 -0
  18. data/MatPL/AuAg/pwdata/Ag10Au38/train/lattice.npy +3 -0
  19. data/MatPL/AuAg/pwdata/Ag10Au38/train/position.npy +3 -0
  20. data/MatPL/AuAg/pwdata/Ag10Au38/train/virials.npy +3 -0
  21. data/MatPL/AuAg/pwdata/Ag10Au38/valid/atom_type.npy +3 -0
  22. data/MatPL/AuAg/pwdata/Ag10Au38/valid/ei.npy +3 -0
  23. data/MatPL/AuAg/pwdata/Ag10Au38/valid/energies.npy +3 -0
  24. data/MatPL/AuAg/pwdata/Ag10Au38/valid/forces.npy +3 -0
  25. data/MatPL/AuAg/pwdata/Ag10Au38/valid/image_type.npy +3 -0
  26. data/MatPL/AuAg/pwdata/Ag10Au38/valid/lattice.npy +3 -0
  27. data/MatPL/AuAg/pwdata/Ag10Au38/valid/position.npy +3 -0
  28. data/MatPL/AuAg/pwdata/Ag10Au38/valid/virials.npy +3 -0
  29. data/MatPL/AuAg/pwdata/Ag10Au6/train/atom_type.npy +3 -0
  30. data/MatPL/AuAg/pwdata/Ag10Au6/train/ei.npy +3 -0
  31. data/MatPL/AuAg/pwdata/Ag10Au6/train/energies.npy +3 -0
  32. data/MatPL/AuAg/pwdata/Ag10Au6/train/forces.npy +3 -0
  33. data/MatPL/AuAg/pwdata/Ag10Au6/train/image_type.npy +3 -0
  34. data/MatPL/AuAg/pwdata/Ag10Au6/train/lattice.npy +3 -0
  35. data/MatPL/AuAg/pwdata/Ag10Au6/train/position.npy +3 -0
  36. data/MatPL/AuAg/pwdata/Ag10Au6/train/virials.npy +3 -0
  37. data/MatPL/AuAg/pwdata/Ag11Au21/train/atom_type.npy +3 -0
  38. data/MatPL/AuAg/pwdata/Ag11Au21/train/ei.npy +3 -0
  39. data/MatPL/AuAg/pwdata/Ag11Au21/train/energies.npy +3 -0
  40. data/MatPL/AuAg/pwdata/Ag11Au21/train/forces.npy +3 -0
  41. data/MatPL/AuAg/pwdata/Ag11Au21/train/image_type.npy +3 -0
  42. data/MatPL/AuAg/pwdata/Ag11Au21/train/lattice.npy +3 -0
  43. data/MatPL/AuAg/pwdata/Ag11Au21/train/position.npy +3 -0
  44. data/MatPL/AuAg/pwdata/Ag11Au21/train/virials.npy +3 -0
  45. data/MatPL/AuAg/pwdata/Ag11Au21/valid/atom_type.npy +3 -0
  46. data/MatPL/AuAg/pwdata/Ag11Au21/valid/ei.npy +3 -0
  47. data/MatPL/AuAg/pwdata/Ag11Au21/valid/energies.npy +3 -0
  48. data/MatPL/AuAg/pwdata/Ag11Au21/valid/forces.npy +3 -0
  49. data/MatPL/AuAg/pwdata/Ag11Au21/valid/image_type.npy +3 -0
  50. data/MatPL/AuAg/pwdata/Ag11Au21/valid/lattice.npy +3 -0
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README.md ADDED
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1
+ ---
2
+ license: gpl-3.0
3
+ # User-Defined Tags
4
+ tags:
5
+ - MatPL
6
+ - NEP
7
+ - machine learning potential
8
+ - materials science
9
+ - pwmat
10
+ - pwmlff
11
+ - extxyz
12
+ language:
13
+ - en
14
+ - zh
15
+ ---
16
+
17
+ <p align="center">
18
+ <strong>
19
+ <span style="font-size: 30px;">MatPL</span>
20
+ </strong>
21
+ </p>
22
+
23
+ ## Dataset Description
24
+
25
+ The MatPL dataset is an example dataset for training material potentials with `OneScience/NEP`. It contains multiple material systems, including AuAg, Cu, HfO2, and LiSiC, and covers the `pwmat/movement`, `pwmlff/npy`, and `extxyz` data formats. The data include atomic coordinates, simulation cell information, energies, and forces for different material systems in different configurations, and serve as a standard benchmark dataset for learning and validating machine-learning interatomic potential methods such as NEP.
26
+
27
+ The current data package contains approximately 636 files and is approximately 38 MB in size.
28
+
29
+ ## Supported Tasks
30
+
31
+ This standardized data repository provides the complete data package for the official MatPL examples, including four material systems. It can be used for:
32
+ - Training and validation of machine-learning interatomic potential models
33
+ - Potential energy surface fitting for material simulations
34
+ - Functional testing and benchmark evaluation of the NEP framework
35
+
36
+ ## Dataset Format and Structure
37
+
38
+ The data files are located in the `data/MatPL/` directory and are organized into shards by material system:
39
+
40
+ | File Path | Format | shape / Content | Description |
41
+ |---|---|---|---|
42
+ | `MatPL/AuAg/AuAg-5762.xyz` | extxyz | `[N_frames, N_atoms]` | Configuration data for the AuAg system |
43
+ | `MatPL/Cu/pwdata/0_300_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Training data for the Cu system (300K) |
44
+ | `MatPL/Cu/pwdata/1_500_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Training data for the Cu system (500K) |
45
+ | `MatPL/Cu/pwdata/valid_movement` | pwmat/movement | `[N_frames, N_atoms]` | Validation data for the Cu system |
46
+ | `MatPL/HfO2/pwdata/init_*/train/atom_type.npy` | npy | `[N_atoms]` | Atomic types for the HfO2 system |
47
+ | `MatPL/HfO2/pwdata/init_*/train/energies.npy` | npy | `[N_frames]` | Total configuration energies for the HfO2 system |
48
+ | `MatPL/HfO2/pwdata/init_*/train/forces.npy` | npy | `[N_frames, N_atoms×3]` | Atomic forces for the HfO2 system |
49
+ | `MatPL/HfO2/pwdata/init_*/train/image_type.npy` | npy | `[N_frames]` | Configuration types for the HfO2 system |
50
+ | `MatPL/HfO2/pwdata/init_*/train/lattice.npy` | npy | `[N_frames, 9]` | Simulation cell matrices for the HfO2 system |
51
+ | `MatPL/HfO2/pwdata/init_*/train/position.npy` | npy | `[N_frames, N_atoms×3]` | Atomic coordinates for the HfO2 system |
52
+ | `MatPL/HfO2/pwdata/init_*/valid/` | npy | Same as above | Validation data shards for the HfO2 system |
53
+ | `MatPL/LiSiC/pwdata/init_*/train/` | npy | Same as above | Training data shards for the LiSiC system |
54
+ | `MatPL/LiSiC/pwdata/init_*/valid/` | npy | Same as above | Validation data shards for the LiSiC system |
55
+ | `metadata/sha256_manifest.txt` | SHA256 | Checksum manifest | File integrity verification |
56
+
57
+
58
+ ## How to Use the Dataset
59
+
60
+
61
+ ```bash
62
+ hf download --dataset OneScience-Sugon/MatPL --local-dir ./data
63
+ ```
64
+
65
+
66
+ ## Official OneScience Information
67
+
68
+ | Platform | OneScience Main Repository | Skills Repository |
69
+ |---|---|---|
70
+ | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
71
+ | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
72
+
73
+ ## Limitations and License
74
+
75
+ This dataset contains the official MatPL example data. No new samples were generated, and the original data content was not modified.
76
+
77
+ - **Original Source**: Official MatPL repository
78
+ - **License**: Refer to the original MatPL data source, the OneScience repository, and the ModelScope page for applicable terms
README_zh.md ADDED
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1
+ ---
2
+ license: GPLv3
3
+ # 用户自定义标签
4
+ tags:
5
+ - MatPL
6
+ - NEP
7
+ - machine learning potential
8
+ - materials science
9
+ - pwmat
10
+ - pwmlff
11
+ - extxyz
12
+ language:
13
+ - en
14
+ - zh
15
+ ---
16
+
17
+ <p align="center">
18
+ <strong>
19
+ <span style="font-size: 30px;">MatPL</span>
20
+ </strong>
21
+ </p>
22
+
23
+ ## 数据集描述
24
+
25
+ MatPL 数据集是适配 `OneScience/NEP` 的材料势训练示例数据集，包含 AuAg、Cu、HfO2、LiSiC 等多个材料体系，覆盖 `pwmat/movement`、`pwmlff/npy` 和 `extxyz` 数据格式。数据包含不同材料体系在不同构型下的原子坐标、晶胞信息、能量和受力数据，是学习和验证机器学习原子间势（NEP 等）方法的标准基准数据集。
26
+
27
+ 当前数据包包含约 636 个文件，约 38 MB。
28
+
29
+ ## 数据集支持的任务
30
+
31
+ 本标准化数据仓库整理了 MatPL 官方示例的完整数据包，包含四个材料体系，可用于：
32
+ - 机器学习原子间势模型的训练与验证
33
+ - 材料模拟的势能面拟合
34
+ - NEP 框架的功能测试与基准评测
35
+
36
+ ## 数据集的格式和结构
37
+
38
+ 数据文件位于 `data/MatPL/` 目录下，按材料体系分片组织：
39
+
40
+ | 文件路径 | 格式 | shape / 内容 | 说明 |
41
+ |---|---|---|---|
42
+ | `MatPL/AuAg/AuAg-5762.xyz` | extxyz | `[N_frames, N_atoms]` | AuAg 体系构型数据 |
43
+ | `MatPL/Cu/pwdata/0_300_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Cu 体系训练数据（300K） |
44
+ | `MatPL/Cu/pwdata/1_500_MOVEMENT` | pwmat/movement | `[N_frames, N_atoms]` | Cu 体系训练数据（500K） |
45
+ | `MatPL/Cu/pwdata/valid_movement` | pwmat/movement | `[N_frames, N_atoms]` | Cu 体系验证数据 |
46
+ | `MatPL/HfO2/pwdata/init_*/train/atom_type.npy` | npy | `[N_atoms]` | HfO2 体系原子类型 |
47
+ | `MatPL/HfO2/pwdata/init_*/train/energies.npy` | npy | `[N_frames]` | HfO2 体系构型总能量 |
48
+ | `MatPL/HfO2/pwdata/init_*/train/forces.npy` | npy | `[N_frames, N_atoms×3]` | HfO2 体系原子受力 |
49
+ | `MatPL/HfO2/pwdata/init_*/train/image_type.npy` | npy | `[N_frames]` | HfO2 体系构型类型 |
50
+ | `MatPL/HfO2/pwdata/init_*/train/lattice.npy` | npy | `[N_frames, 9]` | HfO2 体系晶胞矩阵 |
51
+ | `MatPL/HfO2/pwdata/init_*/train/position.npy` | npy | `[N_frames, N_atoms×3]` | HfO2 体系原子坐标 |
52
+ | `MatPL/HfO2/pwdata/init_*/valid/` | npy | 同上 | HfO2 体系验证数据分片 |
53
+ | `MatPL/LiSiC/pwdata/init_*/train/` | npy | 同上 | LiSiC 体系训练数据分片 |
54
+ | `MatPL/LiSiC/pwdata/init_*/valid/` | npy | 同上 | LiSiC 体系验证数据分片 |
55
+ | `metadata/sha256_manifest.txt` | SHA256 | 校验清单 | 文件完整性校验 |
56
+
57
+
58
+ ## 数据集使用方式
59
+
60
+
61
+ ```bash
62
+ hf download --dataset OneScience-Sugon/MatPL --local-dir ./data
63
+ ```
64
+
65
+
66
+ ## OneScience 官方信息
67
+
68
+ | 平台 | OneScience 主仓库 | Skills 仓库 |
69
+ |---|---|---|
70
+ | Gitee | https://gitee.com/onescience-ai/onescience | https://gitee.com/onescience-ai/oneskills |
71
+ | GitHub | https://github.com/onescience-ai/OneScience | https://github.com/onescience-ai/oneskills |
72
+
73
+ ## 限制与许可证
74
+
75
+ 本数据集为 MatPL 官方示例数据，未生成新样本或改变原始数据内容。
76
+
77
+ - **原始来源**：MatPL 官方仓库
78
+ - **许可证**：以 MatPL 原始数据来源、OneScience 仓库及 ModelScope 页面说明为准
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