新建
OpenLAM Structure Optimization Tool
Peng
推荐镜像 :lam-crystal-philately:openlam
推荐机型 :c12_m92_1 * NVIDIA V100
赞
目录
数据集
lam-crystal-model(v3)
Installation
First, download the OpenLAM structure optimization tool project to your local machine.
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[1]
!git clone https://github.com/deepmodeling/openlam
Cloning into 'openlam'... remote: Enumerating objects: 66, done. remote: Counting objects: 100% (66/66), done. remote: Compressing objects: 100% (45/45), done. remote: Total 66 (delta 28), reused 49 (delta 17), pack-reused 0 Receiving objects: 100% (66/66), 26.82 KiB | 5.36 MiB/s, done. Resolving deltas: 100% (28/28), done.
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Installation of the project.
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[2]
!pip install ./openlam
Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Processing /openlam Installing build dependencies ... done Getting requirements to build wheel ... done Installing backend dependencies ... done Preparing metadata (pyproject.toml) ... done Requirement already satisfied: pydflow>=1.7.23 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from lam-crystal-philately==0.1.dev12+gbabbdec) (1.8.73) Requirement already satisfied: ase==3.22.1 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from lam-crystal-philately==0.1.dev12+gbabbdec) (3.22.1) Requirement already satisfied: numpy==1.26.4 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from lam-crystal-philately==0.1.dev12+gbabbdec) (1.26.4) Requirement already satisfied: tqdm==4.66.2 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from lam-crystal-philately==0.1.dev12+gbabbdec) (4.66.2) Requirement already satisfied: pymatgen==2024.3.1 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from lam-crystal-philately==0.1.dev12+gbabbdec) (2024.3.1) Requirement already satisfied: matplotlib>=3.1.0 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from ase==3.22.1->lam-crystal-philately==0.1.dev12+gbabbdec) (3.8.3) Requirement already satisfied: scipy>=1.1.0 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from ase==3.22.1->lam-crystal-philately==0.1.dev12+gbabbdec) (1.12.0) Requirement already satisfied: monty>=2024.2.2 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from pymatgen==2024.3.1->lam-crystal-philately==0.1.dev12+gbabbdec) (2024.2.26) Requirement already satisfied: networkx>=2.2 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from pymatgen==2024.3.1->lam-crystal-philately==0.1.dev12+gbabbdec) (3.2.1) Requirement already satisfied: palettable>=3.1.1 in /opt/mamba/envs/matbench/lib/python3.11/site-packages (from pymatgen==2024.3.1->lam-crystal-philately==0.1.dev12+gbabbdec) (3.3.3) Requirement already satisfied: pandas in 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filename=lam_crystal_philately-0.1.dev12+gbabbdec-py3-none-any.whl size=31171 sha256=8d2114da987c4dee054a8f8d752feca83457546a63118a2a6722a5ee8614fd0a Stored in directory: /tmp/pip-ephem-wheel-cache-avxt1x14/wheels/61/47/de/ef330879f8aedf68b464ac99bcc69a236487ada5c119f4671e Successfully built lam-crystal-philately Installing collected packages: lam-crystal-philately Attempting uninstall: lam-crystal-philately Found existing installation: lam-crystal-philately 0.1.dev9+g384656b.d20240604 Uninstalling lam-crystal-philately-0.1.dev9+g384656b.d20240604: Successfully uninstalled lam-crystal-philately-0.1.dev9+g384656b.d20240604 Successfully installed lam-crystal-philately-0.1.dev12+gbabbdec WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
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The DP model already exists in the dataset of this notebook, symlink it to the current directory.
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[3]
!ln -s /bohr/lam-crystal-model-01oe/v3/dp0529.pth dp.pth
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Local Structure Optimization
Directly use the command line tool to optimize the sample structures lo cally.
By default, after optimizing the structure, it will check the convergence of the optimized structure (can be skipped using the parameter --skip-check-convergence), and whether it is duplicated in the OpenLAM database (can be s kipped using the parameter --skip-check-duplicate). The checked structures will be saved as cif format files.
To check if the structure is duplicated in the OpenLAM database, the environment variable BOHRIUM_ACCESS_KEY needs to be configured, which can be generated through the https://bohrium.dp.tech/settings/user page.
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[20]
%env BOHRIUM_ACCESS_KEY=xxx
env: BOHRIUM_ACCESS_KEY=xxx
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[6]
!lam-opt relax -i openlam/examples/data -m dp.pth -o results.json --skip-check-convergence
To get the best performance, it is recommended to adjust the number of threads by setting the environment variables OMP_NUM_THREADS, DP_INTRA_OP_PARALLELISM_THREADS, and DP_INTER_OP_PARALLELISM_THREADS. See https://deepmd.rtfd.io/parallelism/ for more information. Start to relax structures. Relaxing: 0it [00:00, ?it/s] Step Time Energy fmax BFGS: 0 11:59:39 -3.432330 1.4856 BFGS: 1 11:59:42 -3.462572 1.2149 BFGS: 2 11:59:52 -3.474138 1.2986 BFGS: 3 11:59:56 -3.499632 0.2218 BFGS: 4 11:59:56 -3.500611 0.0249 BFGS: 5 11:59:56 -3.500631 0.0114 BFGS: 6 11:59:56 -3.500635 0.0110 BFGS: 7 11:59:56 -3.500739 0.0496 BFGS: 8 11:59:57 -3.500918 0.0937 BFGS: 9 11:59:57 -3.501440 0.1756 BFGS: 10 11:59:57 -3.502467 0.2799 BFGS: 11 11:59:57 -3.504224 0.3837 BFGS: 12 11:59:57 -3.540719 0.7027 BFGS: 13 11:59:57 -3.545436 0.2616 BFGS: 14 11:59:57 -3.546308 0.1420 BFGS: 15 11:59:57 -3.546664 0.0037 BFGS: 16 11:59:57 -3.546664 0.0000 Relaxing: 1it [00:22, 22.67s/it] Step Time Energy fmax BFGS: 0 11:59:57 -5.405985 0.7214 BFGS: 1 12:00:07 -5.421183 0.7691 BFGS: 2 12:00:07 -5.421177 2.1633 BFGS: 3 12:00:07 -5.503029 0.4127 BFGS: 4 12:00:07 -5.515699 0.5083 BFGS: 5 12:00:07 -5.550243 0.5736 BFGS: 6 12:00:07 -5.302219 3.1964 BFGS: 7 12:00:08 -5.563675 0.8995 BFGS: 8 12:00:08 -5.438606 0.7443 BFGS: 9 12:00:08 -5.545653 0.3734 BFGS: 10 12:00:08 -5.563606 1.3026 BFGS: 11 12:00:08 -5.564468 0.3407 BFGS: 12 12:00:08 -5.577429 0.3208 BFGS: 13 12:00:08 -5.247499 2.8527 BFGS: 14 12:00:08 -5.588167 0.5249 BFGS: 15 12:00:08 -5.569788 0.3426 BFGS: 16 12:00:08 -5.586407 0.2904 BFGS: 17 12:00:08 -5.291737 2.2892 BFGS: 18 12:00:08 -5.568543 1.3995 BFGS: 19 12:00:09 -5.467279 0.7000 BFGS: 20 12:00:09 -5.541057 0.4039 BFGS: 21 12:00:09 -5.550354 1.7077 BFGS: 22 12:00:09 -5.561118 0.3295 BFGS: 23 12:00:09 -5.571989 0.3297 BFGS: 24 12:00:09 -5.325982 1.6277 BFGS: 25 12:00:09 -5.590947 0.4720 BFGS: 26 12:00:09 -5.559236 0.3329 BFGS: 27 12:00:09 -5.581635 0.3157 BFGS: 28 12:00:09 -5.310092 2.1232 BFGS: 29 12:00:09 -5.582313 0.9937 BFGS: 30 12:00:09 -5.460432 0.7097 BFGS: 31 12:00:10 -5.551491 0.3550 BFGS: 32 12:00:10 -5.578869 1.1455 BFGS: 33 12:00:10 -5.568943 0.3095 BFGS: 34 12:00:10 -5.579210 0.3042 BFGS: 35 12:00:10 -5.317244 1.7866 BFGS: 36 12:00:10 -5.587033 0.7966 BFGS: 37 12:00:10 -5.461176 0.7112 BFGS: 38 12:00:10 -5.559699 0.3170 BFGS: 39 12:00:10 -5.592966 0.3663 BFGS: 40 12:00:10 -5.583208 0.2907 BFGS: 41 12:00:11 -5.592933 0.1862 BFGS: 42 12:00:11 -5.545587 1.7609 BFGS: 43 12:00:11 -5.594824 0.1668 BFGS: 44 12:00:11 -5.595295 0.1689 BFGS: 45 12:00:11 -5.595634 0.1508 BFGS: 46 12:00:11 -5.595848 0.1382 BFGS: 47 12:00:11 -5.596218 0.0995 BFGS: 48 12:00:11 -5.596359 0.0997 BFGS: 49 12:00:11 -5.596817 0.1094 BFGS: 50 12:00:11 -5.597326 0.1168 BFGS: 51 12:00:11 -5.598318 0.1175 BFGS: 52 12:00:12 -5.552859 0.4600 BFGS: 53 12:00:12 -5.574159 0.7846 BFGS: 54 12:00:12 -5.588147 0.5505 BFGS: 55 12:00:12 -5.595027 0.2559 BFGS: 56 12:00:12 -5.602665 0.1604 BFGS: 57 12:00:12 -5.604079 0.0749 BFGS: 58 12:00:12 -5.604216 0.1023 BFGS: 59 12:00:12 -5.604481 0.0826 BFGS: 60 12:00:12 -5.605446 0.0526 BFGS: 61 12:00:12 -5.606199 0.0744 BFGS: 62 12:00:13 -5.605357 0.4217 BFGS: 63 12:00:13 -5.607068 0.0346 BFGS: 64 12:00:13 -5.607500 0.0342 BFGS: 65 12:00:13 -5.581688 1.1910 BFGS: 66 12:00:13 -5.607893 0.0296 BFGS: 67 12:00:13 -5.608146 0.0301 BFGS: 68 12:00:13 -5.608311 0.1705 BFGS: 69 12:00:13 -5.608587 0.0554 BFGS: 70 12:00:13 -5.608691 0.0569 BFGS: 71 12:00:13 -5.609182 0.0947 BFGS: 72 12:00:13 -5.609566 0.0651 BFGS: 73 12:00:14 -5.600396 0.7815 BFGS: 74 12:00:14 -5.612574 0.1182 BFGS: 75 12:00:14 -5.614660 0.0937 BFGS: 76 12:00:14 -5.620260 0.0549 BFGS: 77 12:00:14 -5.619484 0.1918 BFGS: 78 12:00:14 -5.620855 0.0646 BFGS: 79 12:00:14 -5.620925 0.0391 BFGS: 80 12:00:14 -5.620993 0.0274 BFGS: 81 12:00:14 -5.621018 0.0179 BFGS: 82 12:00:14 -5.621036 0.0132 BFGS: 83 12:00:14 -5.621049 0.0236 BFGS: 84 12:00:15 -5.621061 0.0309 BFGS: 85 12:00:15 -5.621082 0.0386 BFGS: 86 12:00:15 -5.621136 0.0500 BFGS: 87 12:00:15 -5.621274 0.0678 BFGS: 88 12:00:15 -5.621747 0.0900 BFGS: 89 12:00:15 -5.626878 0.1020 BFGS: 90 12:00:15 -5.626784 0.2829 BFGS: 91 12:00:15 -5.630610 0.1543 BFGS: 92 12:00:15 -5.631596 0.0634 BFGS: 93 12:00:15 -5.631780 0.0422 BFGS: 94 12:00:16 -5.631856 0.0149 BFGS: 95 12:00:16 -5.631868 0.0015 BFGS: 96 12:00:16 -5.631869 0.0004 BFGS: 97 12:00:16 -5.631869 0.0001 Relaxing: 2it [00:41, 20.62s/it] Saved to df.
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The result file contains the optimized structure and energy.
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[9]
!cat results.json
{"final_structure":{"MP_mp-1006815":{"@module":"pymatgen.core.structure","@class":"Structure","charge":0,"lattice":{"matrix":[[7.230147594,-0.6129705837,-0.2359834023],[-4.1459218943,7.1809473651,0.4719668046],[-0.4390057784,0.760380313,14.2020498528]],"pbc":[true,true,true],"a":7.2599211658,"b":8.3052649614,"c":14.2291645685,"alpha":83.2045861827,"beta":93.8807974416,"gamma":124.8894017167,"volume":698.8008411647},"properties":{},"sites":[{"species":[{"element":"Cs","occu":1}],"abc":[-0.0,-0.0,0.0],"xyz":[0.0,-0.0,0.0],"properties":{},"label":"Cs"},{"species":[{"element":"H","occu":1}],"abc":[-0.0,0.1209169629,0.7997949989],"xyz":[-0.8524269099,1.4764467177,11.4157972395],"properties":{},"label":"H"},{"species":[{"element":"H","occu":1}],"abc":[0.0,0.8790830371,0.2002050011],"xyz":[-3.7325007628,6.4648809604,3.258219418],"properties":{},"label":"H"}]},"MP_mp-1093779":{"@module":"pymatgen.core.structure","@class":"Structure","charge":0,"lattice":{"matrix":[[16.0670444689,-0.0,-0.0],[-0.0,14.2111,-0.0],[-0.0,-0.0,20.0251]],"pbc":[true,true,true],"a":16.0670444689,"b":14.2111,"c":20.0251,"alpha":90.0000000001,"beta":90.0,"gamma":90.0,"volume":4572.3386054619},"properties":{},"sites":[{"species":[{"element":"K","occu":1}],"abc":[0.0,0.0,0.0],"xyz":[0.0,0.0,0.0],"properties":{},"label":"K"},{"species":[{"element":"Na","occu":1}],"abc":[0.1905935253,0.5,0.5],"xyz":[3.0622746457,7.10555,10.01255],"properties":{},"label":"Na"},{"species":[{"element":"Na","occu":1}],"abc":[0.8094064747,0.5,0.5],"xyz":[13.0047698232,7.10555,10.01255],"properties":{},"label":"Na"},{"species":[{"element":"Tl","occu":1}],"abc":[0.0,0.5,0.5],"xyz":[0.0,7.10555,10.01255],"properties":{},"label":"Tl"}]}},"final_energy":{"MP_mp-1006815":-5.6318688293,"MP_mp-1093779":-3.5466640916}}代码
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The relaxed folder contains validated cif files.
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[7]
!ls relaxed
final-CsH2.cif final-KNa2Tl.cif
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Submit to Structure Optimization Workflow
First, create a workflow configuration file. After optimizing the structure, the convergence of the optimized structure will be checked by default (can be skipped by setting the parameter "check_convergence": false in inputs), as well as whether it is a duplicate in the OpenLAM database (can be skipped by setting the parameter "check_duplicate": false in inputs). The checked structures will be saved as CIF files. To check for duplicates in the OpenLAM database, the environment variable BOHRIUM_ACCESS_KEY needs to be configured. You can generate an access key on the https://bohrium.dp.tech/settings/user page.
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[ ]
%env BOHRIUM_ACCESS_KEY=xxx
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[16]
%%file input.json
{
"relax": {
"inputs": {
"check_convergence": false
},
"image": "registry.dp.tech/dptech/prod-26832/lam-crystal-philately:dp-mptraj-ase-utype",
"executor": {
"image_pull_policy": "IfNotPresent",
"machine_dict": {
"batch_type": "Bohrium",
"context_type": "Bohrium",
"remote_profile": {
"input_data": {
"job_type": "container",
"platform": "ali",
"scass_type": "1 * NVIDIA T4_16g",
"maxRescheduleTimes": 10
}
}
},
"retry_on_submission_error": 10
}
}
}
Overwriting input.json
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Divide the structure in the project sample into 2 folders, and we will optimize them with 2 parallel tasks.
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[9]
!mkdir -p part0 part1
!cp openlam/examples/data/MP_mp-1006815.cif part0
!cp openlam/examples/data/MP_mp-1093779.cif part1
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Set up workflow environment variables.
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[21]
%env DFLOW_HOST=https://workflows.deepmodeling.com
%env DFLOW_K8S_API_SERVER=https://workflows.deepmodeling.com
%env DFLOW_S3_REPO_KEY=oss-bohrium
%env DFLOW_S3_STORAGE_CLIENT=dflow.plugins.bohrium.TiefblueClient
%env BOHRIUM_USERNAME=xxx
%env BOHRIUM_PASSWORD=xxx
%env BOHRIUM_PROJECT_ID=xxx
env: DFLOW_HOST=https://workflows.deepmodeling.com env: DFLOW_K8S_API_SERVER=https://workflows.deepmodeling.com env: DFLOW_S3_REPO_KEY=oss-bohrium env: DFLOW_S3_STORAGE_CLIENT=dflow.plugins.bohrium.TiefblueClient env: BOHRIUM_USERNAME=xxx env: BOHRIUM_PASSWORD=xxx env: BOHRIUM_PROJECT_ID=xxx
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Submitting workflow.
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[18]
!lam-opt submit input.json -i part0 part1 -m dp.pth
Workflow has been submitted (ID: parallel-relax-ghxnh, UID: d391313a-d9e5-4947-ab11-da0b7c88b13c) Workflow link: https://workflows.deepmodeling.com/workflows/argo/parallel-relax-ghxnh
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Click on the workflow link to view the status of the workflow. After the workflow is completed, download the result.
Download the result.
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[19]
!lam-opt download parallel-relax-ghxnh -o outputs
!tree outputs
100%|█████████████████████████████████████████████| 5/5 [00:00<00:00, 7.92it/s] 100%|█████████████████████████████████████████████| 5/5 [00:00<00:00, 7.87it/s] outputs ├── 0 │ ├── relaxed │ │ └── final-CsH2.cif │ └── results.json └── 1 ├── relaxed │ └── final-KNa2Tl.cif └── results.json 4 directories, 4 files
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Querying crystal structures from the OpenLAM database
Configure the environment variable BOHRIUM_ACCESS_KEY. You can generate the access key through the page https://bohrium.dp.tech/settings/user .
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[13]
%env BOHRIUM_ACCESS_KEY=xxx
env: BOHRIUM_ACCESS_KEY=xxx
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Query crystal structure through Python interface.
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[10]
from lam_optimize import CrystalStructure
data = CrystalStructure.query_by_page()
print(data)
{'page': 1, 'pageSize': 10, 'total': 59, 'items': [<lam_optimize.db.CrystalStructure object at 0x7f83f05f35b0>, <lam_optimize.db.CrystalStructure object at 0x7f838fbe39d0>, <lam_optimize.db.CrystalStructure object at 0x7f838fa30130>, <lam_optimize.db.CrystalStructure object at 0x7f838fa30880>, <lam_optimize.db.CrystalStructure object at 0x7f838fa30f70>, <lam_optimize.db.CrystalStructure object at 0x7f838fa31660>, <lam_optimize.db.CrystalStructure object at 0x7f838fa31d50>, <lam_optimize.db.CrystalStructure object at 0x7f838fa32440>, <lam_optimize.db.CrystalStructure object at 0x7f838fa331c0>, <lam_optimize.db.CrystalStructure object at 0x7f838fa546a0>]}
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The query_by_page method accepts the following parameters as query conditions
formula: Optional[str] = None
min_energy: Optional[float] = None
max_energy: Optional[float] = None
min_submission_time: Optional[datetime.datetime] = None
max_submission_time: Optional[datetime.datetime] = None
page: int = 1
The data returned contains a list of CrystalStructure objects as items, in addition to the pagination information. Each CrystalStructure object has the following attributes
class CrystalStructure:
formula: str
structure: pymatgen.core.Structure
energy: float
submission_time: datetime.datetime
The query method is also provided to automatically merge the results from multiple pages.
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[12]
structures = CrystalStructure.query(formula="Sr2YSbO6")
print(structures)
[<lam_optimize.db.CrystalStructure object at 0x7f83f0526e30>]
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The returned is a list of CrystalStructure objects.
NOTE: Calling non-paginated methods without query conditions is very slow.
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