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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"mount_file_id":"1w7lcqTAYIBf_EPWxmSx9i7S-mUyh6oC5","authorship_tag":"ABX9TyPmDOX53T6xe4eGE4ZuExhI"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# MolCal - AI/ML Workshop 4\n","# MACE - Generating Machine Learning Interatomic Potentials"],"metadata":{"id":"BX_zbYBBHLhF"}},{"cell_type":"markdown","source":[" The materials in this workbook are adapted from the MACE-tutorials from the Advanced Machine Learning Course from the CCP5 Summer School 2023."],"metadata":{"id":"wO8QNOgGHeJt"}},{"cell_type":"markdown","source":["***\n","# 1.0 Getting Started\n","\n","## 1.1 Gathering required packages\n","#### This cell should take less than 2 minutes run"],"metadata":{"id":"MOD1c7XzLXxY"}},{"cell_type":"code","source":["!pip install git+https://github.com/imagdau/aseMolec@main\n","!pip install git+https://github.com/acesuit/mace@develop\n","!pip install xtb nglview ipywidgets rdkit x3dase"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1ZiMMasNvWFW","executionInfo":{"status":"ok","timestamp":1731490254720,"user_tz":0,"elapsed":82526,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"d327d60a-0282-451b-8f63-14c6ed488b38"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting git+https://github.com/imagdau/aseMolec@main\n","  Cloning https://github.com/imagdau/aseMolec (to revision main) to /tmp/pip-req-build-fk69kwg9\n","  Running command git clone --filter=blob:none --quiet https://github.com/imagdau/aseMolec /tmp/pip-req-build-fk69kwg9\n","  Resolved https://github.com/imagdau/aseMolec to commit 2633a672eb235c49a5c7d7161f76f52f4e218e99\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Building wheels for collected packages: aseMolec\n","  Building wheel for aseMolec (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for aseMolec: filename=aseMolec-1.0.0-py3-none-any.whl size=22903 sha256=1249f356da04fe3e6d7d7b4efa3bfabda9397376317bf659f8df578164462bdd\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-du_ek8j8/wheels/10/16/19/ce149a666d77660d5e227a2ca8a93a159e7d85349b63716cfd\n","Successfully built aseMolec\n","Installing collected packages: aseMolec\n","Successfully installed aseMolec-1.0.0\n","Collecting git+https://github.com/acesuit/mace@develop\n","  Cloning https://github.com/acesuit/mace (to revision develop) to /tmp/pip-req-build-zwgw6jlj\n","  Running command git clone --filter=blob:none --quiet https://github.com/acesuit/mace /tmp/pip-req-build-zwgw6jlj\n","  Running command git checkout -b develop --track origin/develop\n","  Switched to a new branch 'develop'\n","  Branch 'develop' set up to track remote branch 'develop' from 'origin'.\n","  Resolved https://github.com/acesuit/mace to commit 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This behaviour is the source of the following dependency conflicts.\n","google-colab 1.0.0 requires ipykernel==5.5.6, but you have ipykernel 6.29.5 which is incompatible.\n","google-colab 1.0.0 requires notebook==6.5.5, but you have notebook 7.2.2 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed arrow-1.3.0 async-lru-2.0.4 comm-0.2.2 fqdn-1.5.1 ipykernel-6.29.5 ipywidgets-8.1.5 isoduration-20.11.0 jedi-0.19.2 json5-0.9.28 jupyter-client-8.6.3 jupyter-events-0.10.0 jupyter-lsp-2.2.5 jupyter-server-2.14.2 jupyter-server-terminals-0.5.3 jupyterlab-4.2.5 jupyterlab-server-2.27.3 nglview-3.1.2 notebook-7.2.2 overrides-7.7.0 python-json-logger-2.0.7 rdkit-2024.3.6 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 types-python-dateutil-2.9.0.20241003 uri-template-1.3.0 widgetsnbextension-4.0.13 x3dase-1.1.4 xtb-22.1\n"]}]},{"cell_type":"markdown","source":["***\n","## 1.2 Mounting onto google drive & redirecting to the notebooks directory.\n","### This location may differ depending on where you put this notebook so please adjust accordingly"],"metadata":{"id":"6ChbweLSLc6_"}},{"cell_type":"code","source":["import os\n","from google.colab import drive\n","\n","WORK_DRIVE = '/gdrive'\n","# You may need to change this path, it depends on where you put the notebooks\n","WORK_AREA = WORK_DRIVE + '/MyDrive/Colab Notebooks/workshop_files'\n","\n","drive.mount(WORK_DRIVE)\n","os.chdir(WORK_AREA)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nJYuE1leLTdq","executionInfo":{"status":"ok","timestamp":1731490306619,"user_tz":0,"elapsed":11095,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"b95b2f74-6eaa-4cf8-edbe-b9a4ea6bf7cf"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /gdrive\n"]}]},{"cell_type":"markdown","source":["***\n","\n","## 1.3 Looking at datasets\n"],"metadata":{"id":"KRo4y6zbLVcQ"}},{"cell_type":"markdown","source":["  As explained in the accompanying lecture, the well-known saying of \"garbage-in, garbage-out\" applies very much when it comes to training interactomic potentials from your simulation data.\n","\n","  The data we will use today is a subset from [this work](https://doi.org/10.1021/acs.jpcb.2c03746) which contains a mixture of 6 different types of molecules:\n","  - cyclic carbonates\n","      - (Vinylene carbonate VC, Ethylene carbonate EC, Propylene carbonate PC)\n","\n","  - linear carbonates\n","    - (Dimethyl carbonate DMC, Ethyl Methyl Carbonate EMC, Diethyl carbonate DEC)\n"],"metadata":{"id":"4aymMv6Nt-HH"}},{"cell_type":"markdown","source":["***\n","###Lets have a look at what the molecules look like!"],"metadata":{"id":"XIcwK81LHBkc"}},{"cell_type":"code","source":["from rdkit import Chem\n","from rdkit.Chem import Draw\n","\n","# SMILES strings for each molecule\n","sm_dict = {\n","    'Vinylene Carbonate (VC)': 'c1coc(=O)o1',\n","    'Ethylene Carbonate (EC)': 'C1COC(=O)O1',\n","    'Propylene Carbonate (PC)': 'CC1COC(=O)O1',\n","    'Dimethyl Carbonate (DMC)': 'COC(=O)OC',\n","    'Ethyl Menthyl Carbonate(EMC)': 'CCOC(=O)OC',\n","    'Diethyl Carbonate (DEC)': 'CCOC(=O)OCC'\n","}\n","\n","Draw.MolsToGridImage([Chem.MolFromSmiles(sm_dict[mol]) for mol in sm_dict], legends=list(sm_dict.keys()))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":417},"id":"-auaCKHkuBkH","executionInfo":{"status":"ok","timestamp":1731490311561,"user_tz":0,"elapsed":859,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"98376286-a96e-4436-e2ed-c6278ea68e91"},"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"image/png":"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\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{},"execution_count":3}]},{"cell_type":"markdown","source":[" ***\n"," You can directly open these .xyz files and look at the contents, alternatively, you can also use the ase functions to get information such as number of configurations, etc."],"metadata":{"id":"-Zcn3m5iIwQb"}},{"cell_type":"code","source":["from ase.io import read, write\n","import numpy as np\n","\n","db = read('data/solvent_xtb.xyz', ':') #read in list of configs\n","\n","print(\"Number of configs in database: \", len(db))\n","print(\"Number of atoms in each config: \", np.array([len(at) for at in db]))\n","print(\"Number of atoms in the smallest config: \", np.min([len(at) for at in db])) #test if database contains isolated atoms\n","\n","# Rather than looking at the whole file we can choose to only look at config 10\n","print(\"Information stored in config.info: \\n\", db[10].info) #check config properties: Energy, composistion, cell, etc\n","print(\"Information stored in config.arrays: \\n\", db[10].arrays) # check POS, molID, and  forces"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"t10UIWq-td3r","executionInfo":{"status":"ok","timestamp":1731490320403,"user_tz":0,"elapsed":5348,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"bfd74960-61d3-4e27-c5c1-1d463860c079"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of configs in database:  5003\n","Number of atoms in each config:  [ 1  1  1 ... 25 32 40]\n","Number of atoms in the smallest config:  1\n","Information stored in config.info: \n"," {'Nmols': 3, 'Comp': 'DEC(2):EC(1)', 'energy_xtb': -2083.807425680116}\n","Information stored in config.arrays: \n"," {'numbers': array([6, 8, 8, 8, 6, 6, 6, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 6, 8, 8, 8,\n","       6, 6, 6, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 6, 8, 6, 8, 6, 1, 1, 8,\n","       1, 1]), 'positions': array([[ 1.12228513,  2.57065392,  3.0555315 ],\n","       [ 0.89510715,  3.33680701,  3.90915251],\n","       [ 0.83131516,  1.22789502,  3.08354163],\n","       [ 1.4791671 ,  2.80396104,  1.8400346 ],\n","       [ 0.86742717,  0.93730795,  4.75010538],\n","       [ 1.98150611,  4.01263905,  1.23323762],\n","       [ 0.80585617, -0.588741  ,  4.48594856],\n","       [ 1.87435615,  1.08331895,  5.15053034],\n","       [-0.02357686,  1.61593997,  5.1062746 ],\n","       [ 0.86050314,  4.98110104,  1.04421353],\n","       [ 2.59138203,  4.60207987,  2.06282258],\n","       [ 2.49448419,  3.56533098,  0.39430356],\n","       [ 1.30257308,  5.96039391,  0.89348656],\n","       [ 0.26657715,  4.8989749 ,  0.20957758],\n","       [ 0.17814614,  5.04733515,  1.87895453],\n","       [ 1.16012108, -1.13257897,  5.37814569],\n","       [-0.23201686, -0.73150504,  4.21799374],\n","       [ 1.59177709, -0.83813405,  3.75746059],\n","       [-3.41360188, -0.98489702, -1.42369044],\n","       [-4.55164003, -0.98675704, -1.68807948],\n","       [-2.50612378, -1.95843303, -1.43353546],\n","       [-2.91195083, -0.18129502, -0.62358844],\n","       [-2.94922781, -3.16452909, -2.04602051],\n","       [-3.65715981,  0.89645898, -0.14776742],\n","       [-1.73851287, -4.02535009, -1.99297738],\n","       [-3.87312388, -3.66752005, -1.60215044],\n","       [-3.32941294, -2.82905102, -3.10723448],\n","       [-2.66523385,  1.63324594,  0.88361657],\n","       [-3.91746187,  1.44909501, -0.9763664 ],\n","       [-4.52412081,  0.520657  ,  0.48019758],\n","       [-3.43014789,  2.24482489,  1.47997653],\n","       [-2.09312892,  0.970191  ,  1.50268054],\n","       [-1.89375591,  2.26521993,  0.49221757],\n","       [-2.0911088 , -5.09659481, -2.20086837],\n","       [-0.93603188, -3.68115592, -2.69023538],\n","       [-1.35541391, -4.14123487, -0.96314341],\n","       [ 2.30126524, -3.24978709, -3.27970552],\n","       [ 3.00183821, -1.84303808, -3.55832553],\n","       [ 2.96121526, -1.04488206, -2.52093434],\n","       [ 2.09142613, -1.54451299, -1.57714641],\n","       [ 1.89760613, -2.98708797, -1.72157145],\n","       [ 1.30514014, -3.13057709, -3.81170249],\n","       [ 3.03420115, -4.0624938 , -3.52643442],\n","       [ 3.41751218,  0.01574698, -2.43227243],\n","       [ 0.90290713, -3.12530494, -1.3425734 ],\n","       [ 2.63837409, -3.52872992, -1.04472041]]), 'molID': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2], dtype=int32), 'forces_xtb': array([[-1.2097741 , -2.39165186, -1.96402866],\n","       [ 0.07389339,  1.87891231,  2.12228931],\n","       [ 1.07191842,  2.09452527,  4.46538507],\n","       [ 0.98623913, -0.46858633, -1.97824022],\n","       [-0.81319099, -0.85065789, -3.67144715],\n","       [ 0.02161256,  0.42583203,  3.30068805],\n","       [ 0.13114651,  0.64504394,  1.715764  ],\n","       [-0.46296685,  1.07036558, -0.26466142],\n","       [ 1.84082445, -1.74825154, -0.32262755],\n","       [ 0.45615048,  1.59126832,  0.22788044],\n","       [-0.14130671, -1.54446403, -1.60113504],\n","       [ 0.28973623,  0.76188372, -0.25665782],\n","       [ 0.19919606,  0.41216994,  0.30117612],\n","       [-1.32638563, -1.03440365, -2.1056199 ],\n","       [ 0.22857485, -0.2076416 ,  0.5223718 ],\n","       [-0.8190369 ,  0.08294068, -0.03044869],\n","       [ 0.32696534, -0.98221704, -0.27996942],\n","       [-0.9020746 ,  0.24867543, -0.19557377],\n","       [ 0.27889267, -2.38447354,  1.18833662],\n","       [-3.02753642, -0.71764787, -2.39685745],\n","       [-0.70843182, -1.31741138, -1.16796403],\n","       [ 3.22462813,  3.26672367,  2.67299997],\n","       [-1.27077314,  0.76728944, -1.5691325 ],\n","       [ 1.67943183, -0.19823206,  3.72783325],\n","       [ 0.21330814, -2.70580929, -0.4196204 ],\n","       [ 1.1242505 ,  0.89133705,  0.11339771],\n","       [ 0.84407016, -0.9783896 ,  1.30383604],\n","       [-2.79177186,  0.67497055, -0.05093687],\n","       [-0.99201483,  1.68221122, -1.34781737],\n","       [ 0.61961995,  0.37959238, -0.94350639],\n","       [ 1.54819533, -0.59847384, -0.41156578],\n","       [-0.47345881, -0.69687105,  0.30502411],\n","       [-0.17821229,  0.44937622, -0.83310846],\n","       [ 0.79553288,  1.27893502, -0.37777   ],\n","       [-0.78725616, -0.49660666,  0.66042116],\n","       [-0.10895674,  0.65930865, -0.46156861],\n","       [-0.70069159,  3.44734292,  1.26018599],\n","       [-0.41289933, -3.40948673, -0.35966592],\n","       [-2.58537908, -2.03375425,  0.55880003],\n","       [ 0.62031903, -1.38191785,  0.06174988],\n","       [ 2.47026606,  0.75839265, -0.60444044],\n","       [ 1.516843  , -0.68772363, -0.05388566],\n","       [-1.05763411,  0.99043854,  0.26563726],\n","       [ 1.36045106,  2.20161277,  0.02612078],\n","       [-0.43058241, -0.45109369, -0.49130924],\n","       [-0.72173176,  0.62661712, -0.64033879]])}\n"]}]},{"cell_type":"markdown","source":["\n","***\n","## 1.4 Considering energies\n","\n","When training on systems with multiple atoms, the input of atomic energy as part of the dataset is significant. You can see that the first few configurations of the data/solvent_xtb.xyz datafile consists of a single atom.\n","\n","If you do not have the atomic energy, MACE is also able to approximate the atomic energies based on the total energy and the energy of each atom in a vacuum. This can be called using \"E0s='average'\" in the training configurations that you will see later.\n","\n","The energies from the dataset in this tutorial was obtained using the Semiempirical Tight Binding level of theory with XTB.\n","(More information: https://xtb-docs.readthedocs.io/en/latest/)\n","\n","As mentioned from the lectures, we would generally derive training data from DFT or more accurate quantum methods. For efficienct, the less accurate but quicker XTB was used for this."],"metadata":{"id":"DueUp2OyJmt4"}},{"cell_type":"code","source":["from aseMolec import extAtoms as ea\n","\n","db = read('data/solvent_xtb.xyz', ':15')\n","\n","print(\"E0s: \\n\", ea.get_E0(db, tag='_xtb'))\n","print(\"\\n Total energy per config: \\n\", ea.get_prop(db, 'info', 'energy_xtb', peratom=False)[13])\n","print(\"\\n Total energy per atom: \\n\", ea.get_prop(db, 'info', 'energy_xtb', peratom=True)[13])\n","print(\"\\n Atomisation energy per config: \\n\", ea.get_prop(db, 'bind', prop='_xtb', peratom=False)[13])\n","print(\"\\n Atomisation energy per atom: \\n\", ea.get_prop(db, 'bind', prop='_xtb', peratom=True)[13])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kO-NWJlwvg6W","executionInfo":{"status":"ok","timestamp":1731490324730,"user_tz":0,"elapsed":248,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"0df85389-4ce8-451f-d4f4-dab2a7d5c8d0"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["E0s: \n"," {'H': -10.707211383396714, 'C': -48.847445262804705, 'O': -102.57117256025786}\n","\n"," Total energy per config: \n"," -1323.8105075135763\n","\n"," Total energy per atom: \n"," -47.278946696913444\n","\n"," Atomisation energy per config: \n"," -167.70295068203745\n","\n"," Atomisation energy per atom: \n"," -5.9893910957870515\n"]}]},{"cell_type":"markdown","source":["***\n","## 1.5 Splitting Dataset\n","\n","#### There are 3 main types of datasets that is required to train a machine learning model:\n","  - The training set\n","  - The validation set\n","  - The test set\n","\n","Therefore, we must split our data accordingly. You will see later that MACE has a function that allows a fraction of the training data to be used as the validation data, hence, we will only split our big dataset into 2 seperate files.\n","\n","\n","Note: MACE is capable of handling periodic and non-perioding data"],"metadata":{"id":"_ubUs6-9Lcr8"}},{"cell_type":"code","source":["# Splitting the dataset\n","\n","# Importing ase library\n","from ase.io import read, write\n","\n","#Readind our data file\n","db = read('data/solvent_xtb.xyz', ':')\n","\n","# Writing into seperate train and test files\n","write('data/solvent_xtb_train_200.xyz', db[:203]) #first 200 configs plus the 3 E0s\n","write('data/solvent_xtb_test.xyz', db[-1000:]) #last 1000 configs"],"metadata":{"id":"290avtLoJv8F","executionInfo":{"status":"ok","timestamp":1731490349707,"user_tz":0,"elapsed":3729,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":6,"outputs":[]},{"cell_type":"markdown","source":["***\n","\n","# 2.0 Training\n","\n","## 2.1 Training inputs\n","\n"," ### When it comes to training your data, you must give MACE 3 types of information:\n","####  - The training parameters (hyper parameters)\n","####  - Location of the datasets and outputs  \n","####  - Optimiser parameters"],"metadata":{"id":"V2cuyjP9tmUi"}},{"cell_type":"markdown","source":["***\n","\n","### 2.1.1 Hyper Parameters\n","#### These parameters specify the model size which translates to how accurate your model. As with many computational techniques, there is a trade off between training speed and efficiency against the accuracy of the model"],"metadata":{"id":"_DwQYDpGNhdT"}},{"cell_type":"markdown","source":["- **`--model`: What type of model are we training**\n","\n","\n","- **`--num_channels`: Number of channels**\n","  \n","  Determines the size of the model. The higher the value, the more accurate the resulting model is. it can take values such as 16, 32, 64, 128, 256.\n","  \n","  \n","- **`max_L`: Symmetry of the messages**\n","\n","  Determines the symmetry of the messages. A value of `--max_L=0` means MACE will pass only invariant information between neigborhoods. It is the parameter **that affects the most the computational speed and the accuracy of the model**. `--max_L=0` are the fastest model, use them to train cheap model to run large and long simulations. `--max_L=1` is the default value, it is a good compromise between speed and accuracy. It is recommended to start with that value for a new project. `--max_L=2` are the most accurate models, use them to train very accurate but slower models.\n","  \n","\n","\n","- **`--r_max`: The cutoff radius**\n","  \n","  The cutoff used to create the local environment in each layer. `r_max=5.0` means atoms separated by a distance of more than 5.0 Å do not directly communicate in a single layer. When the model has multiple message-passing layers, atoms further than 5.0 Å can still communicate through later messages if intermediate proxy atoms exist. The effective receptive field of the model is `num_interactions * r_max`. The larger the `r_max`, the slower the model will be. It is recommended to use values between 4.0 Å and 7.0 Å.\n","\n","- **`--num_interactions`: Message-passing layers**\n","  \n","  Controls the number of message-passing layers in the model. It should always be 2, and it is recommended not to modify it.\n","\n","\n","- **`--correlation`: The order of the many-body expansion**\n","\n","  The body order that MACE induces at each layer. Choosing `--correlation=3` will create basis functions of up to 4-body (ijkl) indices, for each layer. If the model has multiple layers, the effective correlation order is higher. For example, a two-layer MACE with `--correlation=3` has an effective body order of 13.\n","\n","\n","- **`--max_ell`: Angular resolution**\n","\n","  The angular resolution describes how well the model can describe angles. This is controlled by `max_ell` of the spherical harmonics basis (not to be confused with `max_L`). Larger values will result in more accurate but slower models. The default is `max_ell=3`, which is appropriate in most cases.\n"],"metadata":{"id":"eqNR4YFeOVKe"}},{"cell_type":"code","source":["## Typically, the num_interactions, correlation, and max_ell are kept as constants\n","'''\n","model: \"MACE\"\n","num_channels: 16\n","max_L: 0\n","r_max: 4.0\n","correlation: 2\n","num_interactions: 2\n","max_ell: 2\n","'''"],"metadata":{"id":"qkoQFwdrQC9a"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["***\n","## 2.1.2 Specifying Directory Locations\n","\n","- ##### `--name`: the name of the model\n","    This name will be used to form file names (model, log, checkpoints, results), so choose a distinct name for each experiment\n","\n","- ##### `--model_dir, --log_dir, --checkpoints_dir, --results_dir`: directory paths\n","    These are the directories where each type of file is saved.\n","    For simplicity, we will save all files in the same directory.\n","\n","***\n","## 2.1.3 Data management:\n","\n","- ##### `--train_file`: name of training dataset\n","\n","    These are the configurations that will be use to train the model.\n","\n","- ##### `--valid_file`: name of validation dataset\n","    An alternative way to choose the validation set is by using the `--valid_fraction` keyword. These data configs are used to estimate the model accuracy during training, but not for parameter optimization. The validation set also controls the stopping of the training. At each `--eval_interval` the model is tested on the validation set. The evaluation of these configs takes place in batches, which can be controlled by `--valid_batch_size`. If the accuracy of the model stops improving on the validation set for `--patience` number of epochs, the model will undergo **early stopping**.\n","\n","- ##### `--test_file`: name of testing dataset\n","\n","    This set is entirely independent and only gets evaluated at the end of the training process to estimate the model accuracy on an independent set.\n","\n","- ##### `--E0s`: isolated atom energies\n","\n","    Controls how `E0s` should be determined. The strongly recommended approach is to add these values to the training set with `config_type=IsolatedAtom` in `atoms.info` and set `E0s=\"isolated\"`. If these values are not available, MACE can estimate them by least square regression over the available data `E0s=\"average\"` which can lead to unintended consequences depending on how representative the data is.\n","\n","- ##### `--energy_key, --forces_key` the key where these values are stored in the data files\n"],"metadata":{"id":"VAAStuoQPpBx"}},{"cell_type":"code","source":["# Examply of above arguments\n","'''\n","name: \"mace01\"\n","model_dir: \"MACE_models\"\n","log_dir: \"MACE_models\"\n","checkpoints_dir: \"MACE_models\"\n","results_dir: \"MACE_models\"\n","train_file: \"data/solvent_xtb_train_200.xyz\"\n","valid_fraction: 0.10\n","test_file: \"data/solvent_xtb_test.xyz\"\n","energy_key: \"energy_xtb\"\n","forces_key: \"forces_xtb\"\n","'''"],"metadata":{"id":"SN1W_dviQbLs"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["***\n","## 2.1.4 Optimisation Options:\n","\n","- ##### `--device` computing device to use\n","    Can be CPU (`cpu`), GPU (`cuda`) or Apple Silicon (`mps`). Here we will use `cpu` since both the model and dataset are small. If you want to try out the GPU on CoLab, change the argument to \"cuda\" and click on the \"RAM Disk\" icon on the top right of the browser, click on \"Change runtime type\" and select \"T4 GPU\" from the menu Hardware accelerator and save.\n","\n","- ##### `--batch_size` number of configs evaluated in one batch\n","    Number of configs used to compute the gradients for each full update of the network parameters. This training strategy is called stochastic gradient descent because only a subset of the data (`batch_size`) is used to change the parameters at each update.\n","\n","- ##### `--max_num_epochs` number of passes through the data\n","    An `epoch` is completed when the entire training data has been used once in updating the weights `batch` by `batch`. A new epoch begins, and the process repeats.\n","\n","- ##### `--swa` protocol for loss weights\n","    During training you will notice energy errors are at first much higher than force errors, MACE implements a special protocol that increases the weight on the energy in the loss function (`--swa_energy_weight`) once the forces are sufficiently accurate. The starting epoch for this special protocol can be controlled by changing `--start_swa`.\n","\n","- ##### `--seed` random number generator seed\n","    Useful for preparing committee of models.\n"],"metadata":{"id":"xaoJnGXxQhAz"}},{"cell_type":"code","source":["# Example of above arguments:\n","'''\n","device: cpu\n","batch_size: 5\n","max_num_epochs: 20\n","swa: True\n","seed: 1234\n","'''"],"metadata":{"id":"fx8242I4QljL"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["***\n","# 2.2 Starting the training!\n","### 2.2.1 With the arguments detailed above, we can put them all together and write them into a configuration file\n","Note, if you are re-running this with new parameters, make sure to either change the name of the model or the directory name so your old version does not get overwritten"],"metadata":{"id":"0SGjCfLEQo40"}},{"cell_type":"code","source":["%%writefile training_params.yml\n","\n","model: \"MACE\"\n","num_channels: 16\n","max_L: 0\n","r_max: 4.0\n","correlation: 2\n","num_interactions: 2\n","max_ell: 2\n","name: \"mace01\"\n","model_dir: \"MACE_models\"\n","log_dir: \"MACE_models\"\n","checkpoints_dir: \"MACE_models\"\n","results_dir: \"MACE_models\"\n","train_file: \"data/solvent_xtb_train_200.xyz\"\n","valid_fraction: 0.10\n","test_file: \"data/solvent_xtb_test.xyz\"\n","energy_key: \"energy_xtb\"\n","forces_key: \"forces_xtb\"\n","device: cpu\n","batch_size: 5\n","max_num_epochs: 20\n","swa: True\n","seed: 1234"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ntXdRdDczFOr","executionInfo":{"status":"ok","timestamp":1731490393414,"user_tz":0,"elapsed":464,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"9cf0bf37-e558-4b9f-e8aa-7305441c7e18"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["Overwriting training_params.yml\n"]}]},{"cell_type":"markdown","source":["### 2.2.2 In order to run this within python, we specify the function below"],"metadata":{"id":"jmEblBviR1qp"}},{"cell_type":"code","source":["# Normally the command to train is mace_run_train\n","import warnings\n","warnings.filterwarnings(\"ignore\")\n","from mace.cli.run_train import main as mace_run_train_main\n","import sys\n","import logging\n","\n","# Defining a function that starts the training based on the .yml file we give to the function.\n","def train_mace(config_file_path):\n","    logging.getLogger().handlers.clear()\n","    sys.argv = [\"program\", \"--config\", config_file_path]\n","    mace_run_train_main()"],"metadata":{"id":"bg4aPR-PzaDb","executionInfo":{"status":"ok","timestamp":1731490418034,"user_tz":0,"elapsed":14707,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":10,"outputs":[]},{"cell_type":"markdown","source":["### 2.2.3 Run!\n","\n","It should take about 1 minute for 20 epochs complete, using a CPU."],"metadata":{"id":"_qsnHlMDR6ZP"}},{"cell_type":"code","source":["train_mace(\"training_params.yml\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xR2343d5zbKy","executionInfo":{"status":"ok","timestamp":1731490577392,"user_tz":0,"elapsed":152993,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"3056ddb1-dd3b-4b51-cb47-b675986d5fa2"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["2024-11-13 09:33:44.338 INFO: ===========VERIFYING SETTINGS===========\n","2024-11-13 09:33:44.925 INFO: MACE version: 0.3.8\n","2024-11-13 09:33:44.928 INFO: Using CPU\n","2024-11-13 09:33:45.161 INFO: ===========LOADING INPUT DATA===========\n","2024-11-13 09:33:45.165 INFO: Using heads: ['default']\n","2024-11-13 09:33:45.168 INFO: =============    Processing head default     ===========\n","2024-11-13 09:33:45.346 INFO: Using isolated atom energies from training file\n","2024-11-13 09:33:45.364 INFO: Training set [200 configs, 200 energy, 17418 forces] loaded from 'data/solvent_xtb_train_200.xyz'\n","2024-11-13 09:33:45.650 INFO: Using random 10% of training set for validation with indices saved in: ./valid_indices_1234.txt\n","2024-11-13 09:33:45.660 INFO: Validaton set contains 20 configurations [20 energy, 1611 forces]\n","2024-11-13 09:33:46.419 INFO: Test set (1000 configs) loaded from 'data/solvent_xtb_test.xyz':\n","2024-11-13 09:33:46.425 INFO: Default_Default: 1000 configs, 1000 energy, 90228 forces\n","2024-11-13 09:33:46.430 INFO: Total number of configurations: train=180, valid=20, tests=[Default_Default: 1000],\n","2024-11-13 09:33:46.436 INFO: Atomic Numbers used: [1, 6, 8]\n","2024-11-13 09:33:46.440 INFO: Atomic Energies used (z: eV) for head default: {1: -10.707211383396714, 6: -48.847445262804705, 8: -102.57117256025786}\n","2024-11-13 09:33:46.934 INFO: Computing average number of neighbors\n","2024-11-13 09:33:47.146 INFO: Average number of neighbors: 9.869045359650787\n","2024-11-13 09:33:47.150 INFO: During training the following quantities will be reported: energy, forces\n","2024-11-13 09:33:47.153 INFO: ===========MODEL DETAILS===========\n","2024-11-13 09:33:47.320 INFO: Building model\n","2024-11-13 09:33:47.322 INFO: Message passing with 16 channels and max_L=0 (16x0e)\n","2024-11-13 09:33:47.325 INFO: 2 layers, each with correlation order: 2 (body order: 3) and spherical harmonics up to: l=2\n","2024-11-13 09:33:47.327 INFO: 8 radial and 5 basis functions\n","2024-11-13 09:33:47.330 INFO: Radial cutoff: 4.0 A (total receptive field for each atom: 8.0 A)\n","2024-11-13 09:33:47.333 INFO: Distance transform for radial basis functions: None\n","2024-11-13 09:33:47.337 INFO: Hidden irreps: 16x0e\n","2024-11-13 09:33:49.348 INFO: Total number of parameters: 29904\n","2024-11-13 09:33:49.351 INFO: \n","2024-11-13 09:33:49.355 INFO: ===========OPTIMIZER INFORMATION===========\n","2024-11-13 09:33:49.358 INFO: Using ADAM as parameter optimizer\n","2024-11-13 09:33:49.361 INFO: Batch size: 5\n","2024-11-13 09:33:49.363 INFO: Number of gradient updates: 720\n","2024-11-13 09:33:49.365 INFO: Learning rate: 0.01, weight decay: 5e-07\n","2024-11-13 09:33:49.367 INFO: WeightedEnergyForcesLoss(energy_weight=1.000, forces_weight=100.000)\n","2024-11-13 09:33:49.371 INFO: Stage Two (after 15 epochs) with loss function: WeightedEnergyForcesLoss(energy_weight=1000.000, forces_weight=100.000), with energy weight : 1000.0, forces weight : 100.0 and learning rate : 0.001\n","2024-11-13 09:33:49.554 INFO: Using gradient clipping with tolerance=10.000\n","2024-11-13 09:33:49.557 INFO: \n","2024-11-13 09:33:49.561 INFO: ===========TRAINING===========\n","2024-11-13 09:33:49.563 INFO: Started training, reporting errors on validation set\n","2024-11-13 09:33:49.567 INFO: Loss metrics on validation set\n","2024-11-13 09:33:50.808 INFO: Initial: head: default, loss=55.70939822, RMSE_E_per_atom= 6012.90 meV, RMSE_F= 2309.77 meV / A\n","2024-11-13 09:33:56.014 INFO: Epoch 0: head: default, loss=18.74634768, RMSE_E_per_atom= 4823.18 meV, RMSE_F= 1295.47 meV / A\n","2024-11-13 09:34:01.783 INFO: Epoch 1: head: default, loss=5.60983553, RMSE_E_per_atom= 4076.49 meV, RMSE_F=  633.56 meV / A\n","2024-11-13 09:34:09.662 INFO: Epoch 2: head: default, loss=4.82427819, RMSE_E_per_atom= 3712.09 meV, RMSE_F=  592.25 meV / A\n","2024-11-13 09:34:16.670 INFO: Epoch 3: head: default, loss=3.03876151, RMSE_E_per_atom= 3092.87 meV, RMSE_F=  460.03 meV / A\n","2024-11-13 09:34:24.165 INFO: Epoch 4: head: default, loss=3.20081515, RMSE_E_per_atom= 2491.69 meV, RMSE_F=  509.22 meV / A\n","2024-11-13 09:34:30.242 INFO: Epoch 5: head: default, loss=2.45894795, RMSE_E_per_atom= 1834.85 meV, RMSE_F=  462.52 meV / A\n","2024-11-13 09:34:37.108 INFO: Epoch 6: head: default, loss=1.77123335, RMSE_E_per_atom= 1314.76 meV, RMSE_F=  400.26 meV / A\n","2024-11-13 09:34:42.128 INFO: Epoch 7: head: default, loss=1.32547025, RMSE_E_per_atom= 1001.98 meV, RMSE_F=  350.98 meV / A\n","2024-11-13 09:34:47.911 INFO: Epoch 8: head: default, loss=1.41373345, RMSE_E_per_atom=  859.58 meV, RMSE_F=  366.09 meV / A\n","2024-11-13 09:34:53.609 INFO: Epoch 9: head: default, loss=1.44154010, RMSE_E_per_atom=  685.39 meV, RMSE_F=  374.21 meV / A\n","2024-11-13 09:34:58.580 INFO: Epoch 10: head: default, loss=2.36428947, RMSE_E_per_atom=  731.49 meV, RMSE_F=  483.30 meV / A\n","2024-11-13 09:35:04.912 INFO: Epoch 11: head: default, loss=1.49921235, RMSE_E_per_atom=  448.43 meV, RMSE_F=  384.77 meV / A\n","2024-11-13 09:35:09.895 INFO: Epoch 12: head: default, loss=1.53504980, RMSE_E_per_atom=  296.68 meV, RMSE_F=  390.62 meV / A\n","2024-11-13 09:35:15.182 INFO: Epoch 13: head: default, loss=1.21502638, RMSE_E_per_atom=  341.63 meV, RMSE_F=  348.17 meV / A\n","2024-11-13 09:35:21.189 INFO: Epoch 14: head: default, loss=1.03975415, RMSE_E_per_atom=  204.23 meV, RMSE_F=  322.21 meV / A\n","2024-11-13 09:35:21.232 INFO: Changing loss based on Stage Two Weights\n","2024-11-13 09:35:26.341 INFO: Epoch 15: head: default, loss=0.84034747, RMSE_E_per_atom=   45.00 meV, RMSE_F=  252.70 meV / A\n","2024-11-13 09:35:32.748 INFO: Epoch 16: head: default, loss=0.60699950, RMSE_E_per_atom=   22.52 meV, RMSE_F=  236.35 meV / A\n","2024-11-13 09:35:37.816 INFO: Epoch 17: head: default, loss=0.58071945, RMSE_E_per_atom=   17.92 meV, RMSE_F=  234.92 meV / A\n","2024-11-13 09:35:43.136 INFO: Epoch 18: head: default, loss=0.55116782, RMSE_E_per_atom=   19.60 meV, RMSE_F=  227.20 meV / A\n","2024-11-13 09:35:49.400 INFO: Epoch 19: head: default, loss=0.52621480, RMSE_E_per_atom=   21.26 meV, RMSE_F=  219.97 meV / A\n","2024-11-13 09:35:49.435 INFO: Training complete\n","2024-11-13 09:35:49.437 INFO: \n","2024-11-13 09:35:49.440 INFO: ===========RESULTS===========\n","2024-11-13 09:35:49.444 INFO: Computing metrics for training, validation, and test sets\n","2024-11-13 09:35:50.399 INFO: Loading checkpoint: MACE_models/mace01_run-1234_epoch-14.pt\n","2024-11-13 09:35:50.454 INFO: Loaded Stage one model from epoch 14 for evaluation\n","2024-11-13 09:35:50.461 INFO: Evaluating train_default ...\n","2024-11-13 09:35:52.217 INFO: Evaluating valid_default ...\n","2024-11-13 09:35:52.368 INFO: Error-table on TRAIN and VALID:\n","+---------------+---------------------+------------------+-------------------+\n","|  config_type  | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+---------------+---------------------+------------------+-------------------+\n","| train_default |          267.6      |        302.5     |         13.65     |\n","| valid_default |          204.2      |        322.2     |         13.80     |\n","+---------------+---------------------+------------------+-------------------+\n","2024-11-13 09:35:52.371 INFO: Evaluating Default_Default ...\n","2024-11-13 09:36:01.817 INFO: Error-table on TEST:\n","+-----------------+---------------------+------------------+-------------------+\n","|   config_type   | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+-----------------+---------------------+------------------+-------------------+\n","| Default_Default |          274.8      |        344.3     |         15.03     |\n","+-----------------+---------------------+------------------+-------------------+\n","2024-11-13 09:36:01.819 INFO: Saving model to MACE_models/mace01_run-1234.model\n","2024-11-13 09:36:02.582 INFO: Compiling model, saving metadata to MACE_models/mace01_compiled.model\n","2024-11-13 09:36:03.798 INFO: Loading checkpoint: MACE_models/mace01_run-1234_epoch-19_swa.pt\n","2024-11-13 09:36:03.821 INFO: Loaded Stage two model from epoch 19 for evaluation\n","2024-11-13 09:36:03.825 INFO: Evaluating train_default ...\n","2024-11-13 09:36:05.514 INFO: Evaluating valid_default ...\n","2024-11-13 09:36:05.668 INFO: Error-table on TRAIN and VALID:\n","+---------------+---------------------+------------------+-------------------+\n","|  config_type  | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+---------------+---------------------+------------------+-------------------+\n","| train_default |           24.3      |        231.7     |         10.45     |\n","| valid_default |           21.3      |        220.0     |          9.42     |\n","+---------------+---------------------+------------------+-------------------+\n","2024-11-13 09:36:05.670 INFO: Evaluating Default_Default ...\n","2024-11-13 09:36:14.920 INFO: Error-table on TEST:\n","+-----------------+---------------------+------------------+-------------------+\n","|   config_type   | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+-----------------+---------------------+------------------+-------------------+\n","| Default_Default |           25.3      |        270.3     |         11.80     |\n","+-----------------+---------------------+------------------+-------------------+\n","2024-11-13 09:36:14.925 INFO: Saving model to MACE_models/mace01_run-1234_stagetwo.model\n","2024-11-13 09:36:15.812 INFO: Compiling model, saving metadata MACE_models/mace01_stagetwo_compiled.model\n","2024-11-13 09:36:17.051 INFO: Done\n"]}]},{"cell_type":"code","source":["#remove checkpoints since they may cause errors on retraining a model with the same name but a different architecture\n","import glob\n","import os\n","for file in glob.glob(\"MACE_models/*.pt\"):\n","    os.remove(file)"],"metadata":{"id":"0egZEEKX1xtn","executionInfo":{"status":"ok","timestamp":1731491099005,"user_tz":0,"elapsed":245,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":12,"outputs":[]},{"cell_type":"markdown","source":["***\n","\n","# 3.0 Evaluation of Model\n","\n","### Now that we have a trained model, it is important to evaluate the preformance of the model\n","\n","### 3.1 Evaluating against the training data, the testing data, and a volume scan"],"metadata":{"id":"YEJseSqmQFJO"}},{"cell_type":"code","source":["# As with the training, this cell defines the function that allow us to use mace_eval_configs via python\n","\n","import warnings\n","warnings.filterwarnings(\"ignore\")\n","\n","os.makedirs(\"tests/mace01/\", exist_ok=True)\n","\n","from mace.cli.eval_configs import main as mace_eval_configs_main\n","import sys\n","\n","# Similar to above, we are defining a function that allows us to evaluate our model against a given dataset\n","def eval_mace(configs, model, output):\n","    sys.argv = [\"program\", \"--configs\", configs, \"--model\", model, \"--output\", output]\n","    mace_eval_configs_main()"],"metadata":{"id":"CEQ5Acq02hrS","executionInfo":{"status":"ok","timestamp":1731491103053,"user_tz":0,"elapsed":236,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":13,"outputs":[]},{"cell_type":"markdown","source":["Evaluating these 3 takes about 10 to 20 seconds\n","\n","Remember to check if the model that you are evaluating exist and whether the name matches what the output tells you."],"metadata":{"id":"yaNvYRB9Y12r"}},{"cell_type":"code","source":["#evaluate the training set\n","eval_mace(configs=\"data/solvent_xtb_train_200.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_train.xyz\")\n","\n","#evaluate the test set\n","eval_mace(configs=\"data/solvent_xtb_test.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_test.xyz\")\n","\n","#evaluate the volume scan\n","eval_mace(configs=\"data/volumeScan.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_volume_scan.xyz\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4J3j5S4i2mN5","executionInfo":{"status":"ok","timestamp":1731491123480,"user_tz":0,"elapsed":17816,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"11272781-a99f-4cd5-cf4e-f677a53efeab"},"execution_count":14,"outputs":[{"output_type":"stream","name":"stdout","text":["2024-11-13 09:45:05.580 INFO: Using CPU\n","2024-11-13 09:45:08.725 INFO: Using CPU\n","2024-11-13 09:45:21.837 INFO: Using CPU\n"]}]},{"cell_type":"markdown","source":["### 3.2 Plotting Results\n","#### 3.2.1 Energies and Forces"],"metadata":{"id":"srVnaeFgUBGX"}},{"cell_type":"code","source":["from aseMolec import pltProps as pp\n","from ase.io import read\n","import matplotlib.pyplot as plt\n","from aseMolec import extAtoms as ea\n","import numpy as np\n","\n","# Defining a function to extract the XTB and MACE energies and forces, and plotting them against each other in order to evaluate the model\n","def plot_RMSEs(db, labs):\n","    ea.rename_prop_tag(db, 'MACE_energy', 'energy_mace') #Backward compatibility\n","    ea.rename_prop_tag(db, 'MACE_forces', 'forces_mace') #Backward compatibility\n","\n","    plt.figure(figsize=(9,6), dpi=100)\n","    plt.subplot(1,3,1)\n","    plt.title(\"Against Training Data\")\n","    pp.plot_prop(ea.get_prop(db, 'info', 'energy_xtb', True).flatten(), \\\n","                 ea.get_prop(db, 'info', 'energy_mace', True).flatten(), \\\n","                 title=r'Energy $(\\rm eV/atom)$ ', labs=labs, rel=False)\n","    plt.subplot(1,3,2)\n","    plt.title(\"Against Testing Data\")\n","    pp.plot_prop(np.concatenate(ea.get_prop(db, 'arrays', 'forces_xtb')).flatten(), \\\n","                 np.concatenate(ea.get_prop(db, 'arrays', 'forces_mace')).flatten(), \\\n","                 title=r'Forces $\\rm (eV/\\AA)$ ', labs=labs, rel=False)\n","    plt.tight_layout()\n","    return\n","\n","# Reading our evaluated data and assigning them to a variable\n","train_data = read('tests/mace01/solvent_train.xyz', ':')\n","test_data = train_data[:3]+read('tests/mace01/solvent_test.xyz', ':') # The first part appends the E0 energies to the validation\n","volume_data= read(\"tests/mace01/solvent_volume_scan.xyz\", \":\")\n","\n","# Calling function to plot our evaluated data\n","plot_RMSEs(train_data, labs=['XTB', 'MACE'])\n","plot_RMSEs(test_data, labs=['XTB', 'MACE'])\n","plot_RMSEs(volume_data, labs=['XTB', 'MACE'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":948},"id":"4cb6lr-Z2sVT","executionInfo":{"status":"ok","timestamp":1731491144822,"user_tz":0,"elapsed":4066,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"afb329ca-c5b4-4548-9f61-7d4744998269"},"execution_count":15,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 900x600 with 2 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure size 900x600 with 2 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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#### 3.2.2 Inter- and Intra- Molecular Forces\n","\n","We can look at the forces, previously plotted, as atomic forces that act upon each atom in the 3 cartesianal directions.\n","With that definition, we can also think about how the intermolecular and intramolecular force components by considering how they change per from one configuration to another.\n","Under, we decompose the total force into its inter- (translational and rotational) and its intra-(vibrational) components."],"metadata":{"id":"zxdnn048UOYv"}},{"cell_type":"code","source":["from aseMolec import pltProps as pp\n","from aseMolec import anaAtoms as aa\n","\n","db1 = read('tests/mace01/solvent_test.xyz', ':')\n","ea.rename_prop_tag(db1, 'energy_xtb', 'energy') #Backward compatibility\n","ea.rename_prop_tag(db1, 'forces_xtb', 'forces') #Backward compatibility\n","\n","db2 = read('tests/mace01/solvent_test.xyz', ':')\n","ea.rename_prop_tag(db2, 'MACE_energy', 'energy') #Backward compatibility\n","ea.rename_prop_tag(db2, 'MACE_forces', 'forces') #Backward compatibility\n","\n","# This function from the aseMolec library seperates the forces into each component\n","aa.extract_molecs(db1, intra_inter=True)\n","aa.extract_molecs(db2, intra_inter=True)\n","\n","pp.plot_trans_rot_vib(db1, db2, labs=['XTB', 'MACE'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":422},"id":"R9aub3IBsNaS","executionInfo":{"status":"ok","timestamp":1731491170645,"user_tz":0,"elapsed":7402,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"be62da9d-df49-4264-f734-223d7ae95ee4"},"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 3200x1000 with 4 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Congratulations, you have trained and evaluated a MACE model!\n","\n","Hopefully now you have a good feel on how to to input training parameters and evaluate the resulting model.\n","\n","Note: When we seperate the forces into the different components, we see that this MACE model performs well on the overall and vibrational forces but falls short on the translational and rotational forces. This is a well-known feature that inter-molecular forces are more difficult to capture, nevertheless, our model does a good job in capturing it"],"metadata":{"id":"GRIMk6BrSNkQ"}},{"cell_type":"markdown","source":[" ***\n"," # 4.0 Task  \n"," #### Try and change some of the hyper parameters such as the cutoff radius (r_max), model size (num_channels), number of epochs (max_num_epochs), and size of the datasets to see how that affects the efficiency and performance of the resulting models!\n"," ***"],"metadata":{"id":"91y-wd0bSTjQ"}},{"cell_type":"markdown","source":["# 5.0 Molecular Dynamics with a MACE model\n","The background should be covered in the accompanying lecture\n","\n","## 5.1 Setting up simulation parameters"],"metadata":{"id":"uyPZd9QZ4oiS"}},{"cell_type":"code","source":["# Importing all the importantly libraries needed for MD simulations\n","from ase.io import read, write\n","from ase import units\n","from ase.md.langevin import Langevin\n","from ase.md.velocitydistribution import Stationary, ZeroRotation, MaxwellBoltzmannDistribution\n","\n","import random\n","import os\n","import time\n","import numpy as np\n","import pylab as pl\n","from IPython import display\n","\n","# Definining the intialisation of the MD simulation as well as a constantly updating plot to show the progress of the MD\n","def simpleMD(init_conf, temp, calc, fname, s, T):\n","\n","    #The MD section\n","    init_conf.set_calculator(calc)\n","\n","    #initialize the temperature\n","    random.seed(701) #just making sure the MD is reproducible\n","    MaxwellBoltzmannDistribution(init_conf, temperature_K=300) #initialize temperature at 300\n","    Stationary(init_conf)\n","    ZeroRotation(init_conf)\n","\n","    dyn = Langevin(init_conf, 1.0*units.fs, temperature_K=temp, friction=0.1) #drive system to desired temperature\n","\n","    # The plotting section\n","    %matplotlib inline\n","\n","    time_fs = []\n","    temperature = []\n","    energies = []\n","\n","    #remove previously stored trajectory with the same name\n","    os.system('rm -rfv '+fname)\n","\n","    fig, ax = pl.subplots(2, 1, figsize=(6,6), sharex='all', gridspec_kw={'hspace': 0, 'wspace': 0})\n","\n","    # Defining the function to write every frame/timestep as it runs\n","    def write_frame():\n","            dyn.atoms.write(fname, append=True)\n","            time_fs.append(dyn.get_time()/units.fs)\n","            temperature.append(dyn.atoms.get_temperature())\n","            energies.append(dyn.atoms.get_potential_energy()/len(dyn.atoms))\n","\n","            ax[0].plot(np.array(time_fs), np.array(energies), color=\"b\")\n","            ax[0].set_ylabel('E (eV/atom)')\n","\n","            # plot the temperature of the system as subplots\n","            ax[1].plot(np.array(time_fs), temperature, color=\"r\")\n","            ax[1].set_ylabel('T (K)')\n","            ax[1].set_xlabel('Time (fs)')\n","\n","            display.clear_output(wait=True)\n","            display.display(pl.gcf())\n","            time.sleep(0.01)\n","\n","    dyn.attach(write_frame, interval=s)\n","    t0 = time.time()\n","    dyn.run(T)\n","    t1 = time.time()\n","\n","    # Gives us a feel on efficiency\n","    print(\"MD finished in {0:.2f} minutes!\".format((t1-t0)/60))"],"metadata":{"id":"idsj28n54qxR","executionInfo":{"status":"ok","timestamp":1731491296492,"user_tz":0,"elapsed":320,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":17,"outputs":[]},{"cell_type":"markdown","source":["### 5.2.1 Simulation based on MACE model"],"metadata":{"id":"6Aqh6wMCUdcg"}},{"cell_type":"code","source":["# Let us start with a single molecule\n","init_conf = ea.sel_by_info_val(read('data/solvent_molecs.xyz',':'), 'Nmols', 1)[0].copy()\n","\n","# we can use MACE as a calculator in ASE!\n","from mace.calculators import MACECalculator\n","mace_calc = MACECalculator(model_paths=['MACE_models/mace01_stagetwo.model'], device='cpu', default_dtype=\"float32\")\n","\n","# Calling the defined function, usingthe MACE calculator\n","simpleMD(init_conf, temp=1200, calc=mace_calc, fname='md/mace_md.xyz', s=10, T=2000)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"rgtHyDiJ4tJb","executionInfo":{"status":"ok","timestamp":1731491480552,"user_tz":0,"elapsed":171273,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"d8697078-bd3e-4725-a47e-d232090ce247"},"execution_count":18,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 2 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["MD finished in 2.75 minutes!\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 2 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### 5.2.2 Simulation based on XTB model"],"metadata":{"id":"HgLjwBe1UkXA"}},{"cell_type":"code","source":["# reinitialize the original config\n","init_conf = ea.sel_by_info_val(read('data/solvent_molecs.xyz',':'), 'Nmols', 1)[0].copy()\n","\n","# Using an XTB level of theory with an ase calculator\n","from xtb.ase.calculator import XTB\n","xtb_calc = XTB(method=\"GFN2-xTB\")\n","\n","# Same function as above but calling the xtb calculator\n","simpleMD(init_conf, temp=1200, calc=xtb_calc, fname='md/xtb_md.xyz', s=10, T=2000)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"r5SMzTJU5wCP","executionInfo":{"status":"ok","timestamp":1730455180490,"user_tz":0,"elapsed":207261,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"4ca1a9b1-517a-41f1-9523-1fb89488f7e5"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 2 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["MD finished in 3.36 minutes!\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 600x600 with 2 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### How do they compare to each other?\n","If you changed the mace model you used the simulation based on your hyper parameters, what differences does it make to the outputs?\n","\n","Try running the MD using another model that have improved/worse preformances when evaluated and compare the resulting MD outputs.  "],"metadata":{"id":"elZWKIgdUoxY"}},{"cell_type":"markdown","source":["***\n","##  5.2 Dynamics\n","\n","A good way to study the dynamics in the system is to look at how teh positions vary with time. But when you have a lot of atoms, we have to be a bit more picky about which atoms to look at and what kind of information we want to get from them.\n","\n","Radial distribution function (RDF) is a good method to learn about proximities, bonding, intra/inter molecular information when it is normalised over the number of simulation frames"],"metadata":{"id":"nTxha_cJ6BwH"}},{"cell_type":"code","source":["from aseMolec import anaAtoms as aa\n","\n","tag = 'HH_intra' #choose one of 'HH_intra', 'HC_intra', 'HO_intra', 'CC_intra', 'CO_intra', 'OO_intra'\n","\n","for f in ['xtb_md', 'mace_md']:\n","    traj = read(f+'.xyz', ':')\n","    for at in traj:\n","        at.pbc = True\n","        at.cell = [100,100,100]\n","    rdf = aa.compute_rdfs_traj_avg(traj, rmax=5, nbins=50) #aseMolec provides functionality to compute RDFs\n","    plt.plot(rdf[1], rdf[0][tag], label=f, alpha=0.7, linewidth=3)\n","\n","plt.legend();\n","plt.yticks([]);\n","plt.xlabel(r'Radius ($\\rm \\AA$)');\n","plt.ylabel('RDF '+tag);\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":453},"id":"ofqbbdtq6twa","executionInfo":{"status":"ok","timestamp":1731084319720,"user_tz":0,"elapsed":8484,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"e088f71a-73cd-43ec-abbb-01210d70c282"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]}]}
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diff --git a/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb b/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb
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index 87c58092610214e213be6340867b91c4f508d6b7..0000000000000000000000000000000000000000
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@@ -1 +0,0 @@
-{"cells":[{"cell_type":"markdown","metadata":{"id":"BX_zbYBBHLhF"},"source":["# MolCal - AI/ML Workshop 4\n","# MACE - Generating Machine Learning Interatomic Potentials"]},{"cell_type":"markdown","metadata":{"id":"wO8QNOgGHeJt"},"source":[" The materials in this workbook are adapted from the MACE-tutorials from the Advanced Machine Learning Course from the CCP5 Summer School 2023."]},{"cell_type":"markdown","metadata":{"id":"MOD1c7XzLXxY"},"source":["***\n","# 1.0 Getting Started\n","\n","## 1.1 Gathering required packages\n","#### This cell should take about 1 min to run"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":51623,"status":"ok","timestamp":1730391537798,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"1ZiMMasNvWFW","outputId":"3e4f9d37-0179-4feb-c7ef-f4467e055a9b"},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting git+https://github.com/imagdau/aseMolec@main\n","  Cloning https://github.com/imagdau/aseMolec (to revision main) to /tmp/pip-req-build-l42vvi0n\n","  Running command git clone --filter=blob:none --quiet https://github.com/imagdau/aseMolec /tmp/pip-req-build-l42vvi0n\n","  Resolved https://github.com/imagdau/aseMolec to commit 2633a672eb235c49a5c7d7161f76f52f4e218e99\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Building wheels for collected packages: aseMolec\n","  Building wheel for aseMolec (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for aseMolec: filename=aseMolec-1.0.0-py3-none-any.whl size=22903 sha256=b0b2a237ce507e945a29440f61d0c45c60ffc28ae713fc378f70583a1bce02cf\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-vl5bqlmh/wheels/10/16/19/ce149a666d77660d5e227a2ca8a93a159e7d85349b63716cfd\n","Successfully built aseMolec\n","Installing collected packages: aseMolec\n","Successfully installed aseMolec-1.0.0\n","Collecting git+https://github.com/acesuit/mace@develop\n","  Cloning https://github.com/acesuit/mace (to revision develop) to /tmp/pip-req-build-siz64c7z\n","  Running command git clone --filter=blob:none --quiet https://github.com/acesuit/mace /tmp/pip-req-build-siz64c7z\n","  Running command git checkout -b develop --track origin/develop\n","  Switched to a new branch 'develop'\n","  Branch 'develop' set up to track remote branch 'develop' from 'origin'.\n","  Resolved https://github.com/acesuit/mace to commit f6124f24c7a46c2781b2e6a2af16b69735fb9dc0\n","  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n","  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n","  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: torch>=1.12 in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (2.5.0+cu121)\n","Collecting e3nn==0.4.4 (from mace-torch==0.3.7)\n","  Downloading e3nn-0.4.4-py3-none-any.whl.metadata (5.1 kB)\n","Requirement already satisfied: numpy<2.0 in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (1.26.4)\n","Requirement already satisfied: opt-einsum in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (3.4.0)\n","Collecting ase (from mace-torch==0.3.7)\n","  Downloading ase-3.23.0-py3-none-any.whl.metadata (3.8 kB)\n","Collecting torch-ema (from mace-torch==0.3.7)\n","  Downloading torch_ema-0.3-py3-none-any.whl.metadata (415 bytes)\n","Requirement already satisfied: prettytable in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (3.11.0)\n","Collecting matscipy (from mace-torch==0.3.7)\n","  Downloading matscipy-1.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (37 kB)\n","Requirement already satisfied: h5py in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (3.11.0)\n","Collecting torchmetrics (from mace-torch==0.3.7)\n","  Downloading torchmetrics-1.5.1-py3-none-any.whl.metadata (20 kB)\n","Collecting python-hostlist (from mace-torch==0.3.7)\n","  Downloading python-hostlist-2.0.0.tar.gz (37 kB)\n","  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Collecting configargparse (from mace-torch==0.3.7)\n","  Downloading ConfigArgParse-1.7-py3-none-any.whl.metadata (23 kB)\n","Requirement already satisfied: GitPython in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (3.1.43)\n","Requirement already satisfied: pyYAML in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (6.0.2)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (4.66.5)\n","Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (3.7.1)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from mace-torch==0.3.7) (2.2.2)\n","Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from 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types-python-dateutil, rfc3986-validator, rfc3339-validator, rdkit, python-json-logger, overrides, json5, jedi, fqdn, comm, async-lru, xtb, jupyter-server-terminals, jupyter-client, arrow, isoduration, ipywidgets, ipykernel, x3dase, jupyter-events, jupyter-server, jupyterlab-server, jupyter-lsp, jupyterlab, notebook, nglview\n","  Attempting uninstall: widgetsnbextension\n","    Found existing installation: widgetsnbextension 3.6.10\n","    Uninstalling widgetsnbextension-3.6.10:\n","      Successfully uninstalled widgetsnbextension-3.6.10\n","  Attempting uninstall: jupyter-client\n","    Found existing installation: jupyter-client 6.1.12\n","    Uninstalling jupyter-client-6.1.12:\n","      Successfully uninstalled jupyter-client-6.1.12\n","  Attempting uninstall: ipywidgets\n","    Found existing installation: ipywidgets 7.7.1\n","    Uninstalling ipywidgets-7.7.1:\n","      Successfully uninstalled ipywidgets-7.7.1\n","  Attempting uninstall: ipykernel\n","    Found existing installation: ipykernel 5.5.6\n","    Uninstalling ipykernel-5.5.6:\n","      Successfully uninstalled ipykernel-5.5.6\n","  Attempting uninstall: jupyter-server\n","    Found existing installation: jupyter-server 1.24.0\n","    Uninstalling jupyter-server-1.24.0:\n","      Successfully uninstalled jupyter-server-1.24.0\n","  Attempting uninstall: notebook\n","    Found existing installation: notebook 6.5.5\n","    Uninstalling notebook-6.5.5:\n","      Successfully uninstalled notebook-6.5.5\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","google-colab 1.0.0 requires ipykernel==5.5.6, but you have ipykernel 6.29.5 which is incompatible.\n","google-colab 1.0.0 requires notebook==6.5.5, but you have notebook 7.2.2 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed arrow-1.3.0 async-lru-2.0.4 comm-0.2.2 fqdn-1.5.1 ipykernel-6.29.5 ipywidgets-8.1.5 isoduration-20.11.0 jedi-0.19.1 json5-0.9.25 jupyter-client-8.6.3 jupyter-events-0.10.0 jupyter-lsp-2.2.5 jupyter-server-2.14.2 jupyter-server-terminals-0.5.3 jupyterlab-4.2.5 jupyterlab-server-2.27.3 nglview-3.1.2 notebook-7.2.2 overrides-7.7.0 python-json-logger-2.0.7 rdkit-2024.3.5 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 types-python-dateutil-2.9.0.20241003 uri-template-1.3.0 widgetsnbextension-4.0.13 x3dase-1.1.4 xtb-22.1\n"]}],"source":["!pip install git+https://github.com/imagdau/aseMolec@main\n","!pip install git+https://github.com/acesuit/mace@develop\n","!pip install xtb nglview ipywidgets rdkit x3dase"]},{"cell_type":"markdown","metadata":{"id":"6ChbweLSLc6_"},"source":["***\n","## 1.2 Mounting onto google drive & redirecting to the notebooks directory.\n","### This location may differ depending on where you put this notebook so please adjust accordingly"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":16646,"status":"ok","timestamp":1730391474654,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"nJYuE1leLTdq","outputId":"a687ba24-948b-4015-e9bd-db049e77e5fd"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /gdrive\n"]}],"source":["import os\n","from google.colab import drive\n","\n","WORK_DRIVE = '/gdrive'\n","# You may need to change this path, it depends on where you put the notebooks\n","WORK_AREA = WORK_DRIVE + '/MyDrive/Colab Notebooks/workshop_files'\n","\n","drive.mount(WORK_DRIVE)\n","os.chdir(WORK_AREA)"]},{"cell_type":"markdown","metadata":{"id":"KRo4y6zbLVcQ"},"source":["***\n","\n","## 1.3 Looking at datasets\n"]},{"cell_type":"markdown","metadata":{"id":"4aymMv6Nt-HH"},"source":["  As explained in the accompanying lecture, the well-known saying of \"garbage-in, garbage-out\" applies very much when it comes to training interactomic potentials from your simulation data.\n","\n","  The data we will use today is a subset from [this work](https://doi.org/10.1021/acs.jpcb.2c03746) which contains a mixture of 6 different types of molecules:\n","  - cyclic carbonates\n","      - (Vinylene carbonate VC, Ethylene carbonate EC, Propylene carbonate PC)\n","\n","  - linear carbonates\n","    - (Dimethyl carbonate DMC, Ethyl Methyl Carbonate EMC, Diethyl carbonate DEC)\n"]},{"cell_type":"markdown","metadata":{"id":"XIcwK81LHBkc"},"source":["***\n","###Lets have a look at what the molecules look like!"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":417},"executionInfo":{"elapsed":320,"status":"ok","timestamp":1730391554727,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"-auaCKHkuBkH","outputId":"f488d74e-f8a9-42d3-a24b-7bb439c74bb3"},"outputs":[{"data":{"image/png":"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","text/plain":["<IPython.core.display.Image object>"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from rdkit import Chem\n","from rdkit.Chem import Draw\n","\n","# SMILES strings for each molecule\n","sm_dict = {\n","    'VC': 'c1coc(=O)o1',\n","    'EC': 'C1COC(=O)O1',\n","    'PC': 'CC1COC(=O)O1',\n","    'DMC': 'COC(=O)OC',\n","    'EMC': 'CCOC(=O)OC',\n","    'DEC': 'CCOC(=O)OCC'\n","}\n","\n","Draw.MolsToGridImage([Chem.MolFromSmiles(sm_dict[mol]) for mol in sm_dict], legends=list(sm_dict.keys()))"]},{"cell_type":"markdown","metadata":{"id":"-Zcn3m5iIwQb"},"source":[" ***\n"," You can directly open these .xyz files and look at the contents, alternatively, you can also use the ase functions to get information such as number of configurations, etc."]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3245,"status":"ok","timestamp":1730391561513,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"t10UIWq-td3r","outputId":"966dfaca-2681-4688-b262-b19561a5b927"},"outputs":[{"name":"stdout","output_type":"stream","text":["Number of configs in database:  5003\n","Number of atoms in each config:  [ 1  1  1 ... 25 32 40]\n","Number of atoms in the smallest config:  1\n","Information stored in config.info: \n"," {'Nmols': 3, 'Comp': 'DEC(2):EC(1)', 'energy_xtb': -2083.807425680116}\n","Information stored in config.arrays: \n"," {'numbers': array([6, 8, 8, 8, 6, 6, 6, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 6, 8, 8, 8,\n","       6, 6, 6, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 6, 8, 6, 8, 6, 1, 1, 8,\n","       1, 1]), 'positions': array([[ 1.12228513,  2.57065392,  3.0555315 ],\n","       [ 0.89510715,  3.33680701,  3.90915251],\n","       [ 0.83131516,  1.22789502,  3.08354163],\n","       [ 1.4791671 ,  2.80396104,  1.8400346 ],\n","       [ 0.86742717,  0.93730795,  4.75010538],\n","       [ 1.98150611,  4.01263905,  1.23323762],\n","       [ 0.80585617, -0.588741  ,  4.48594856],\n","       [ 1.87435615,  1.08331895,  5.15053034],\n","       [-0.02357686,  1.61593997,  5.1062746 ],\n","       [ 0.86050314,  4.98110104,  1.04421353],\n","       [ 2.59138203,  4.60207987,  2.06282258],\n","       [ 2.49448419,  3.56533098,  0.39430356],\n","       [ 1.30257308,  5.96039391,  0.89348656],\n","       [ 0.26657715,  4.8989749 ,  0.20957758],\n","       [ 0.17814614,  5.04733515,  1.87895453],\n","       [ 1.16012108, -1.13257897,  5.37814569],\n","       [-0.23201686, -0.73150504,  4.21799374],\n","       [ 1.59177709, -0.83813405,  3.75746059],\n","       [-3.41360188, -0.98489702, -1.42369044],\n","       [-4.55164003, -0.98675704, -1.68807948],\n","       [-2.50612378, -1.95843303, -1.43353546],\n","       [-2.91195083, -0.18129502, -0.62358844],\n","       [-2.94922781, -3.16452909, -2.04602051],\n","       [-3.65715981,  0.89645898, -0.14776742],\n","       [-1.73851287, -4.02535009, -1.99297738],\n","       [-3.87312388, -3.66752005, -1.60215044],\n","       [-3.32941294, -2.82905102, -3.10723448],\n","       [-2.66523385,  1.63324594,  0.88361657],\n","       [-3.91746187,  1.44909501, -0.9763664 ],\n","       [-4.52412081,  0.520657  ,  0.48019758],\n","       [-3.43014789,  2.24482489,  1.47997653],\n","       [-2.09312892,  0.970191  ,  1.50268054],\n","       [-1.89375591,  2.26521993,  0.49221757],\n","       [-2.0911088 , -5.09659481, -2.20086837],\n","       [-0.93603188, -3.68115592, -2.69023538],\n","       [-1.35541391, -4.14123487, -0.96314341],\n","       [ 2.30126524, -3.24978709, -3.27970552],\n","       [ 3.00183821, -1.84303808, -3.55832553],\n","       [ 2.96121526, -1.04488206, -2.52093434],\n","       [ 2.09142613, -1.54451299, -1.57714641],\n","       [ 1.89760613, -2.98708797, -1.72157145],\n","       [ 1.30514014, -3.13057709, -3.81170249],\n","       [ 3.03420115, -4.0624938 , -3.52643442],\n","       [ 3.41751218,  0.01574698, -2.43227243],\n","       [ 0.90290713, -3.12530494, -1.3425734 ],\n","       [ 2.63837409, -3.52872992, -1.04472041]]), 'molID': array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,\n","       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,\n","       2, 2], dtype=int32), 'forces_xtb': array([[-1.2097741 , -2.39165186, -1.96402866],\n","       [ 0.07389339,  1.87891231,  2.12228931],\n","       [ 1.07191842,  2.09452527,  4.46538507],\n","       [ 0.98623913, -0.46858633, -1.97824022],\n","       [-0.81319099, -0.85065789, -3.67144715],\n","       [ 0.02161256,  0.42583203,  3.30068805],\n","       [ 0.13114651,  0.64504394,  1.715764  ],\n","       [-0.46296685,  1.07036558, -0.26466142],\n","       [ 1.84082445, -1.74825154, -0.32262755],\n","       [ 0.45615048,  1.59126832,  0.22788044],\n","       [-0.14130671, -1.54446403, -1.60113504],\n","       [ 0.28973623,  0.76188372, -0.25665782],\n","       [ 0.19919606,  0.41216994,  0.30117612],\n","       [-1.32638563, -1.03440365, -2.1056199 ],\n","       [ 0.22857485, -0.2076416 ,  0.5223718 ],\n","       [-0.8190369 ,  0.08294068, -0.03044869],\n","       [ 0.32696534, -0.98221704, -0.27996942],\n","       [-0.9020746 ,  0.24867543, -0.19557377],\n","       [ 0.27889267, -2.38447354,  1.18833662],\n","       [-3.02753642, -0.71764787, -2.39685745],\n","       [-0.70843182, -1.31741138, -1.16796403],\n","       [ 3.22462813,  3.26672367,  2.67299997],\n","       [-1.27077314,  0.76728944, -1.5691325 ],\n","       [ 1.67943183, -0.19823206,  3.72783325],\n","       [ 0.21330814, -2.70580929, -0.4196204 ],\n","       [ 1.1242505 ,  0.89133705,  0.11339771],\n","       [ 0.84407016, -0.9783896 ,  1.30383604],\n","       [-2.79177186,  0.67497055, -0.05093687],\n","       [-0.99201483,  1.68221122, -1.34781737],\n","       [ 0.61961995,  0.37959238, -0.94350639],\n","       [ 1.54819533, -0.59847384, -0.41156578],\n","       [-0.47345881, -0.69687105,  0.30502411],\n","       [-0.17821229,  0.44937622, -0.83310846],\n","       [ 0.79553288,  1.27893502, -0.37777   ],\n","       [-0.78725616, -0.49660666,  0.66042116],\n","       [-0.10895674,  0.65930865, -0.46156861],\n","       [-0.70069159,  3.44734292,  1.26018599],\n","       [-0.41289933, -3.40948673, -0.35966592],\n","       [-2.58537908, -2.03375425,  0.55880003],\n","       [ 0.62031903, -1.38191785,  0.06174988],\n","       [ 2.47026606,  0.75839265, -0.60444044],\n","       [ 1.516843  , -0.68772363, -0.05388566],\n","       [-1.05763411,  0.99043854,  0.26563726],\n","       [ 1.36045106,  2.20161277,  0.02612078],\n","       [-0.43058241, -0.45109369, -0.49130924],\n","       [-0.72173176,  0.62661712, -0.64033879]])}\n"]}],"source":["from ase.io import read, write\n","import numpy as np\n","\n","db = read('data/solvent_xtb.xyz', ':') #read in list of configs\n","\n","print(\"Number of configs in database: \", len(db))\n","print(\"Number of atoms in each config: \", np.array([len(at) for at in db]))\n","print(\"Number of atoms in the smallest config: \", np.min([len(at) for at in db])) #test if database contains isolated atoms\n","print(\"Information stored in config.info: \\n\", db[10].info) #check info\n","print(\"Information stored in config.arrays: \\n\", db[10].arrays)"]},{"cell_type":"markdown","metadata":{"id":"DueUp2OyJmt4"},"source":["\n","***\n","## 1.4 Considering energies\n","\n","When training on systems with multiple atoms, the input of atomic energy as part of the dataset is significant. You can see that the first few configurations of the data/solvent_xtb.xyz datafile consists of a single atom.\n","\n","If you do not have the atomic energy, MACE is also able to approximate the atomic energies based on the total energy and the energy of each atom in a vacuum. This can be called using \"E0s='average'\" in the training configurations that you will see later.\n","\n","The energies from the dataset in this tutorial was obtained using the Semiempirical Tight Binding level of theory with XTB.\n","(More information: https://xtb-docs.readthedocs.io/en/latest/)\n","\n","As mentioned from the lectures, we would generally derive training data from DFT or more accurate quantum methods. For efficienct, the less accurate but quicker XTB was used for this."]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":262,"status":"ok","timestamp":1730391564457,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"kO-NWJlwvg6W","outputId":"a11405c0-dfa6-4992-cf10-97f473e0bc2b"},"outputs":[{"name":"stdout","output_type":"stream","text":["E0s: \n"," {'H': -10.707211383396714, 'C': -48.847445262804705, 'O': -102.57117256025786}\n","Total energy per config: \n"," -1323.8105075135763\n","Toal energy per atom: \n"," -47.278946696913444\n","Atomization energy per config: \n"," -167.70295068203745\n","Atomization energy per atom: \n"," -5.9893910957870515\n"]}],"source":["from aseMolec import extAtoms as ea\n","\n","db = read('data/solvent_xtb.xyz', ':15')\n","\n","print(\"E0s: \\n\", ea.get_E0(db, tag='_xtb'))\n","print(\"Total energy per config: \\n\", ea.get_prop(db, 'info', 'energy_xtb', peratom=False)[13])\n","print(\"Toal energy per atom: \\n\", ea.get_prop(db, 'info', 'energy_xtb', peratom=True)[13])\n","print(\"Atomization energy per config: \\n\", ea.get_prop(db, 'bind', prop='_xtb', peratom=False)[13])\n","print(\"Atomization energy per atom: \\n\", ea.get_prop(db, 'bind', prop='_xtb', peratom=True)[13])"]},{"cell_type":"markdown","metadata":{"id":"_ubUs6-9Lcr8"},"source":["***\n","## 1.5 Splitting Dataset\n","\n","#### There are 3 main types of datasets that is required to train a machine learning model:\n","  - The training set\n","  - The validation set\n","  - The test set\n","\n","Therefore, we must split our data accordingly. You will see later that MACE has a function that allows a fraction of the training data to be used as the validation data, hence, we will only split our big dataset into 2 seperate files."]},{"cell_type":"code","execution_count":7,"metadata":{"executionInfo":{"elapsed":2968,"status":"ok","timestamp":1730391569922,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"290avtLoJv8F"},"outputs":[],"source":["# Splitting the dataset\n","from ase.io import read, write\n","#non-periodic data is handled correctly by MACE, so we do not need to change anything\n","db = read('data/solvent_xtb.xyz', ':')\n","write('data/solvent_xtb_train_200.xyz', db[:203]) #first 200 configs plus the 3 E0s\n","write('data/solvent_xtb_test.xyz', db[-1000:]) #last 1000 configs"]},{"cell_type":"markdown","metadata":{"id":"V2cuyjP9tmUi"},"source":["***\n","\n","# 2.0 Training\n","\n","## 2.1 Training inputs\n","\n"," ### When it comes to training your data, you must give MACE 3 types of information:\n","####  - The training parameters (hyper parameters)\n","####  - Location of the datasets and outputs  \n","####  - Optimiser parameters"]},{"cell_type":"markdown","metadata":{"id":"_DwQYDpGNhdT"},"source":["***\n","\n","### 2.1.1 Hyper Parameters\n","#### These parameters specify the model size which translates to how accurate your model. As with many computational techniques, there is a trade off between training speed and efficiency against the accuracy of the model"]},{"cell_type":"markdown","metadata":{"id":"eqNR4YFeOVKe"},"source":["- **`--model`: What type of model are we training**\n","\n","\n","- **`--num_channels`: Number of channels**\n","  \n","  Determines the size of the model. The higher the value, the more accurate the resulting model is. it can take values such as 16, 32, 64, 128, 256.\n","  \n","  \n","- **`max_L`: Symmetry of the messages**\n","\n","  Determines the symmetry of the messages. A value of `--max_L=0` means MACE will pass only invariant information between neigborhoods. It is the parameter **that affects the most the computational speed and the accuracy of the model**. `--max_L=0` are the fastest model, use them to train cheap model to run large and long simulations. `--max_L=1` is the default value, it is a good compromise between speed and accuracy. It is recommended to start with that value for a new project. `--max_L=2` are the most accurate models, use them to train very accurate but slower models.\n","  \n","\n","\n","- **`--r_max`: The cutoff radius**\n","  \n","  The cutoff used to create the local environment in each layer. `r_max=5.0` means atoms separated by a distance of more than 5.0 Å do not directly communicate in a single layer. When the model has multiple message-passing layers, atoms further than 5.0 Å can still communicate through later messages if intermediate proxy atoms exist. The effective receptive field of the model is `num_interactions * r_max`. The larger the `r_max`, the slower the model will be. It is recommended to use values between 4.0 Å and 7.0 Å.\n","\n","- **`--num_interactions`: Message-passing layers**\n","  \n","  Controls the number of message-passing layers in the model. It should always be 2, and it is recommended not to modify it.\n","\n","\n","- **`--correlation`: The order of the many-body expansion**\n","\n","  The body order that MACE induces at each layer. Choosing `--correlation=3` will create basis functions of up to 4-body (ijkl) indices, for each layer. If the model has multiple layers, the effective correlation order is higher. For example, a two-layer MACE with `--correlation=3` has an effective body order of 13.\n","\n","\n","- **`--max_ell`: Angular resolution**\n","\n","  The angular resolution describes how well the model can describe angles. This is controlled by `max_ell` of the spherical harmonics basis (not to be confused with `max_L`). Larger values will result in more accurate but slower models. The default is `max_ell=3`, which is appropriate in most cases.\n"]},{"cell_type":"code","execution_count":51,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"executionInfo":{"elapsed":257,"status":"ok","timestamp":1730306025562,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"qkoQFwdrQC9a","outputId":"5a150d51-491b-4265-e8c1-26744720b2a9"},"outputs":[{"data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'\\nmodel: \"MACE\"\\nnum_channels: 16\\nmace_L: 0\\nr_max: 4.0\\ncorrelation: 2\\nnum_interactions: 2\\nmax_ell: 2\\n'"]},"execution_count":51,"metadata":{},"output_type":"execute_result"}],"source":["## Typically, the num_interactions, correlation, and max_ell are kept as constants\n","'''\n","model: \"MACE\"\n","num_channels: 16\n","max_L: 0\n","r_max: 4.0\n","correlation: 2\n","num_interactions: 2\n","max_ell: 2\n","'''"]},{"cell_type":"markdown","metadata":{"id":"VAAStuoQPpBx"},"source":["***\n","## 2.1.2 Specifying Directory Locations\n","\n","- ##### `--name`: the name of the model\n","    This name will be used to form file names (model, log, checkpoints, results), so choose a distinct name for each experiment\n","\n","- ##### `--model_dir, --log_dir, --checkpoints_dir, --results_dir`: directory paths\n","    These are the directories where each type of file is saved. For simplicity, we will save all files in the same directory.\n","\n","***\n","## 2.1.3 Data management:\n","\n","- ##### `--train_file`: name of training dataset\n","\n","    These are the configurations that will be use to train the model.\n","\n","- ##### `--valid_file`: name of validation dataset\n","    An alternative way to choose the validation set is by using the `--valid_fraction` keyword. These data configs are used to estimate the model accuracy during training, but not for parameter optimization. The validation set also controls the stopping of the training. At each `--eval_interval` the model is tested on the validation set. The evaluation of these configs takes place in batches, which can be controlled by `--valid_batch_size`. If the accuracy of the model stops improving on the validation set for `--patience` number of epochs, the model will undergo **early stopping**.\n","\n","- ##### `--test_file`: name of testing dataset\n","\n","    This set is entirely independent and only gets evaluated at the end of the training process to estimate the model accuracy on an independent set.\n","\n","- ##### `--E0s`: isolated atom energies\n","\n","    Controls how `E0s` should be determined. The strongly recommended approach is to add these values to the training set with `config_type=IsolatedAtom` in `atoms.info` and set `E0s=\"isolated\"`. If these values are not available, MACE can estimate them by least square regression over the available data `E0s=\"average\"` which can lead to unintended consequences depending on how representative the data is.\n","\n","- ##### `--energy_key, --forces_key` the key where these values are stores\n","    This key must coincide with the `ase.Atoms.info[key]/ase.Atoms.arrays[key]` where the energies and forces are stored in the ase.Atoms object. **It is very important to get them right**.\n"]},{"cell_type":"code","execution_count":52,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":53},"executionInfo":{"elapsed":229,"status":"ok","timestamp":1730306027451,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"SN1W_dviQbLs","outputId":"0605adc9-a8a1-4181-ef78-c53bc4934ace"},"outputs":[{"data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'\\nname: \"mace01\"\\nmodel_dir: \"MACE_models\"\\nlog_dir: \"MACE_models\"\\ncheckpoints_dir: \"MACE_models\"\\nresults_dir: \"MACE_models\"\\ntrain_file: \"data/solvent_xtb_train_200.xyz\"\\nvalid_fraction: 0.10\\ntest_file: \"data/solvent_xtb_test.xyz\"\\nenergy_key: \"energy_xtb\"\\nforces_key: \"forces_xtb\"\\n'"]},"execution_count":52,"metadata":{},"output_type":"execute_result"}],"source":["# Examply of above arguments\n","'''\n","name: \"mace01\"\n","model_dir: \"MACE_models\"\n","log_dir: \"MACE_models\"\n","checkpoints_dir: \"MACE_models\"\n","results_dir: \"MACE_models\"\n","train_file: \"data/solvent_xtb_train_200.xyz\"\n","valid_fraction: 0.10\n","test_file: \"data/solvent_xtb_test.xyz\"\n","energy_key: \"energy_xtb\"\n","forces_key: \"forces_xtb\"\n","'''"]},{"cell_type":"markdown","metadata":{"id":"xaoJnGXxQhAz"},"source":["***\n","## 2.1.4 Optimisation Options:\n","\n","- ##### `--device` computing device to use\n","    Can be CPU (`cpu`), GPU (`cuda`) or Apple Silicon (`mps`). Here we will use `cpu` since both the model and dataset are small. If you want to try out the GPU on CoLab, change the argument to \"cuda\" and click on the \"RAM Disk\" icon on the top right of the browser, click on \"Change runtime type\" and select \"T4 GPU\" from the menu Hardware accelerator and save.\n","\n","- ##### `--batch_size` number of configs evaluated in one batch\n","    Number of configs used to compute the gradients for each full update of the network parameters. This training strategy is called stochastic gradient descent because only a subset of the data (`batch_size`) is used to change the parameters at each update.\n","\n","- ##### `--max_num_epochs` number of passes through the data\n","    An `epoch` is completed when the entire training data has been used once in updating the weights `batch` by `batch`. A new epoch begins, and the process repeats.\n","\n","- ##### `--swa` protocol for loss weights\n","    During training you will notice energy errors are at first much higher than force errors, MACE implements a special protocol that increases the weight on the energy in the loss function (`--swa_energy_weight`) once the forces are sufficiently accurate. The starting epoch for this special protocol can be controlled by changing `--start_swa`.\n","\n","- ##### `--seed` random number generator seed\n","    Useful for preparing committee of models.\n"]},{"cell_type":"code","execution_count":50,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"executionInfo":{"elapsed":254,"status":"ok","timestamp":1730306011486,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"fx8242I4QljL","outputId":"435927e1-1776-4a5f-9984-52aea40d6bdd"},"outputs":[{"data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'\\ndevice: cpu\\nbatch_size: 5\\nmax_num_epochs: 20\\nswa: True\\nseed: 1234\\n'"]},"execution_count":50,"metadata":{},"output_type":"execute_result"}],"source":["# Example of above arguments:\n","'''\n","device: cpu\n","batch_size: 5\n","max_num_epochs: 20\n","swa: True\n","seed: 1234\n","'''"]},{"cell_type":"markdown","metadata":{"id":"0SGjCfLEQo40"},"source":["***\n","# 2.2 Starting the training!\n","### 2.2.1 With the arguments detailed above, we can put them all together and write them into a configuration file\n","Note, if you are re-running this with new parameters, make sure to either change the name of the model or the directory name so your old version does not get overwritten"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":312,"status":"ok","timestamp":1730391621421,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"ntXdRdDczFOr","outputId":"aa95be83-6348-49e3-dcbf-12f17865f15d"},"outputs":[{"name":"stdout","output_type":"stream","text":["Overwriting training_params.yml\n"]}],"source":["%%writefile training_params.yml\n","\n","model: \"MACE\"\n","num_channels: 16\n","max_L: 0\n","r_max: 4.0\n","correlation: 2\n","num_interactions: 2\n","max_ell: 2\n","name: \"mace01\"\n","model_dir: \"MACE_models\"\n","log_dir: \"MACE_models\"\n","checkpoints_dir: \"MACE_models\"\n","results_dir: \"MACE_models\"\n","train_file: \"data/solvent_xtb_train_200.xyz\"\n","valid_fraction: 0.10\n","test_file: \"data/solvent_xtb_test.xyz\"\n","energy_key: \"energy_xtb\"\n","forces_key: \"forces_xtb\"\n","device: cpu\n","batch_size: 5\n","max_num_epochs: 20\n","swa: True\n","seed: 1234"]},{"cell_type":"markdown","metadata":{"id":"jmEblBviR1qp"},"source":["### 2.2.2 In order to run this within python, we specify the function below"]},{"cell_type":"code","execution_count":12,"metadata":{"executionInfo":{"elapsed":315,"status":"ok","timestamp":1730391622952,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"bg4aPR-PzaDb"},"outputs":[],"source":["# Normally the command to train is mace_run_train\n","\n","import warnings\n","warnings.filterwarnings(\"ignore\")\n","from mace.cli.run_train import main as mace_run_train_main\n","import sys\n","import logging\n","\n","def train_mace(config_file_path):\n","    logging.getLogger().handlers.clear()\n","    sys.argv = [\"program\", \"--config\", config_file_path]\n","    mace_run_train_main()"]},{"cell_type":"markdown","metadata":{"id":"_qsnHlMDR6ZP"},"source":["### 2.2.3 Run!\n","\n","1 minute for 20 epochs to"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":91716,"status":"ok","timestamp":1730391716521,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"xR2343d5zbKy","outputId":"8195cad4-7c95-434c-d5f9-543565e25155"},"outputs":[{"name":"stdout","output_type":"stream","text":["2024-10-31 16:20:24.905 INFO: ===========VERIFYING SETTINGS===========\n","2024-10-31 16:20:25.560 INFO: MACE version: 0.3.7\n","2024-10-31 16:20:25.562 INFO: Using CPU\n","2024-10-31 16:20:25.714 INFO: ===========LOADING INPUT DATA===========\n","2024-10-31 16:20:25.717 INFO: Using heads: ['default']\n","2024-10-31 16:20:25.719 INFO: =============    Processing head default     ===========\n","2024-10-31 16:20:25.791 INFO: Using isolated atom energies from training file\n","2024-10-31 16:20:25.799 INFO: Training set [200 configs, 200 energy, 17418 forces] loaded from 'data/solvent_xtb_train_200.xyz'\n","2024-10-31 16:20:26.231 INFO: Using random 10% of training set for validation with indices saved in: ./valid_indices_1234.txt\n","2024-10-31 16:20:26.233 INFO: Validaton set contains 20 configurations [20 energy, 1611 forces]\n","2024-10-31 16:20:26.707 INFO: Test set (1000 configs) loaded from 'data/solvent_xtb_test.xyz':\n","2024-10-31 16:20:26.709 INFO: Default_Default: 1000 configs, 1000 energy, 90228 forces\n","2024-10-31 16:20:26.711 INFO: Total number of configurations: train=180, valid=20, tests=[Default_Default: 1000],\n","2024-10-31 16:20:26.715 INFO: Atomic Numbers used: [1, 6, 8]\n","2024-10-31 16:20:26.717 INFO: Atomic Energies used (z: eV) for head default: {1: -10.707211383396714, 6: -48.847445262804705, 8: -102.57117256025786}\n","2024-10-31 16:20:26.901 INFO: Computing average number of neighbors\n","2024-10-31 16:20:27.020 INFO: Average number of neighbors: 9.869045359650787\n","2024-10-31 16:20:27.022 INFO: During training the following quantities will be reported: energy, forces\n","2024-10-31 16:20:27.024 INFO: ===========MODEL DETAILS===========\n","2024-10-31 16:20:27.118 INFO: Building model\n","2024-10-31 16:20:27.120 INFO: Message passing with 16 channels and max_L=0 (16x0e)\n","2024-10-31 16:20:27.123 INFO: 2 layers, each with correlation order: 2 (body order: 3) and spherical harmonics up to: l=2\n","2024-10-31 16:20:27.125 INFO: 8 radial and 5 basis functions\n","2024-10-31 16:20:27.127 INFO: Radial cutoff: 4.0 A (total receptive field for each atom: 8.0 A)\n","2024-10-31 16:20:27.128 INFO: Distance transform for radial basis functions: None\n","2024-10-31 16:20:27.130 INFO: Hidden irreps: 16x0e\n","2024-10-31 16:20:27.969 INFO: Total number of parameters: 29904\n","2024-10-31 16:20:27.971 INFO: \n","2024-10-31 16:20:27.974 INFO: ===========OPTIMIZER INFORMATION===========\n","2024-10-31 16:20:27.976 INFO: Using ADAM as parameter optimizer\n","2024-10-31 16:20:27.978 INFO: Batch size: 5\n","2024-10-31 16:20:27.979 INFO: Number of gradient updates: 720\n","2024-10-31 16:20:27.981 INFO: Learning rate: 0.01, weight decay: 5e-07\n","2024-10-31 16:20:27.985 INFO: WeightedEnergyForcesLoss(energy_weight=1.000, forces_weight=100.000)\n","2024-10-31 16:20:27.989 INFO: Stage Two (after 15 epochs) with loss function: WeightedEnergyForcesLoss(energy_weight=1000.000, forces_weight=100.000), with energy weight : 1000.0, forces weight : 100.0 and learning rate : 0.001\n","2024-10-31 16:20:28.076 INFO: Using gradient clipping with tolerance=10.000\n","2024-10-31 16:20:28.080 INFO: \n","2024-10-31 16:20:28.082 INFO: ===========TRAINING===========\n","2024-10-31 16:20:28.085 INFO: Started training, reporting errors on validation set\n","2024-10-31 16:20:28.087 INFO: Loss metrics on validation set\n","2024-10-31 16:20:28.955 INFO: Initial: head: default, loss=55.70939822, RMSE_E_per_atom= 6012.90 meV, RMSE_F= 2309.77 meV / A\n","2024-10-31 16:20:32.386 INFO: Epoch 0: head: default, loss=18.74634768, RMSE_E_per_atom= 4823.18 meV, RMSE_F= 1295.47 meV / A\n","2024-10-31 16:20:36.198 INFO: Epoch 1: head: default, loss=5.60983553, RMSE_E_per_atom= 4076.49 meV, RMSE_F=  633.56 meV / A\n","2024-10-31 16:20:39.351 INFO: Epoch 2: head: default, loss=4.82427819, RMSE_E_per_atom= 3712.09 meV, RMSE_F=  592.25 meV / A\n","2024-10-31 16:20:42.577 INFO: Epoch 3: head: default, loss=3.03876151, RMSE_E_per_atom= 3092.87 meV, RMSE_F=  460.03 meV / A\n","2024-10-31 16:20:46.135 INFO: Epoch 4: head: default, loss=3.20081515, RMSE_E_per_atom= 2491.69 meV, RMSE_F=  509.22 meV / A\n","2024-10-31 16:20:49.581 INFO: Epoch 5: head: default, loss=2.45894795, RMSE_E_per_atom= 1834.85 meV, RMSE_F=  462.52 meV / A\n","2024-10-31 16:20:52.731 INFO: Epoch 6: head: default, loss=1.77123335, RMSE_E_per_atom= 1314.76 meV, RMSE_F=  400.26 meV / A\n","2024-10-31 16:20:56.072 INFO: Epoch 7: head: default, loss=1.32547025, RMSE_E_per_atom= 1001.98 meV, RMSE_F=  350.98 meV / A\n","2024-10-31 16:21:00.182 INFO: Epoch 8: head: default, loss=1.41373345, RMSE_E_per_atom=  859.58 meV, RMSE_F=  366.09 meV / A\n","2024-10-31 16:21:03.372 INFO: Epoch 9: head: default, loss=1.44154010, RMSE_E_per_atom=  685.39 meV, RMSE_F=  374.21 meV / A\n","2024-10-31 16:21:06.479 INFO: Epoch 10: head: default, loss=2.36428947, RMSE_E_per_atom=  731.49 meV, RMSE_F=  483.30 meV / A\n","2024-10-31 16:21:09.650 INFO: Epoch 11: head: default, loss=1.49921239, RMSE_E_per_atom=  448.43 meV, RMSE_F=  384.77 meV / A\n","2024-10-31 16:21:13.522 INFO: Epoch 12: head: default, loss=1.53504996, RMSE_E_per_atom=  296.68 meV, RMSE_F=  390.62 meV / A\n","2024-10-31 16:21:16.698 INFO: Epoch 13: head: default, loss=1.21502758, RMSE_E_per_atom=  341.63 meV, RMSE_F=  348.17 meV / A\n","2024-10-31 16:21:19.860 INFO: Epoch 14: head: default, loss=1.03977754, RMSE_E_per_atom=  204.23 meV, RMSE_F=  322.21 meV / A\n","2024-10-31 16:21:19.890 INFO: Changing loss based on Stage Two Weights\n","2024-10-31 16:21:23.361 INFO: Epoch 15: head: default, loss=0.84037137, RMSE_E_per_atom=   45.00 meV, RMSE_F=  252.70 meV / A\n","2024-10-31 16:21:26.959 INFO: Epoch 16: head: default, loss=0.60580397, RMSE_E_per_atom=   22.32 meV, RMSE_F=  236.29 meV / A\n","2024-10-31 16:21:30.147 INFO: Epoch 17: head: default, loss=0.59362708, RMSE_E_per_atom=   20.93 meV, RMSE_F=  235.27 meV / A\n","2024-10-31 16:21:33.374 INFO: Epoch 18: head: default, loss=0.53319591, RMSE_E_per_atom=   18.44 meV, RMSE_F=  224.10 meV / A\n","2024-10-31 16:21:37.280 INFO: Epoch 19: head: default, loss=0.51831371, RMSE_E_per_atom=   15.48 meV, RMSE_F=  223.04 meV / A\n","2024-10-31 16:21:37.862 INFO: Training complete\n","2024-10-31 16:21:37.865 INFO: \n","2024-10-31 16:21:37.868 INFO: ===========RESULTS===========\n","2024-10-31 16:21:37.870 INFO: Computing metrics for training, validation, and test sets\n","Default_Default\n","2024-10-31 16:21:38.477 INFO: Loading checkpoint: MACE_models/mace01_run-1234_epoch-14.pt\n","2024-10-31 16:21:38.500 INFO: Loaded Stage one model from epoch 14 for evaluation\n","2024-10-31 16:21:38.505 INFO: Evaluating train_default ...\n","2024-10-31 16:21:39.642 INFO: Evaluating valid_default ...\n","2024-10-31 16:21:39.739 INFO: Error-table on TRAIN and VALID:\n","+---------------+---------------------+------------------+-------------------+\n","|  config_type  | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+---------------+---------------------+------------------+-------------------+\n","| train_default |          267.6      |        302.5     |         13.65     |\n","| valid_default |          204.2      |        322.2     |         13.80     |\n","+---------------+---------------------+------------------+-------------------+\n","2024-10-31 16:21:39.740 INFO: Evaluating Default_Default ...\n","2024-10-31 16:21:44.950 INFO: Error-table on TEST:\n","+-----------------+---------------------+------------------+-------------------+\n","|   config_type   | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+-----------------+---------------------+------------------+-------------------+\n","| Default_Default |          274.8      |        344.3     |         15.03     |\n","+-----------------+---------------------+------------------+-------------------+\n","2024-10-31 16:21:44.953 INFO: Saving model to MACE_models/mace01_run-1234.model\n","2024-10-31 16:21:45.882 INFO: Compiling model, saving metadata to MACE_models/mace01_compiled.model\n","2024-10-31 16:21:47.086 INFO: Loading checkpoint: MACE_models/mace01_run-1234_epoch-19_swa.pt\n","2024-10-31 16:21:47.104 INFO: Loaded Stage two model from epoch 19 for evaluation\n","2024-10-31 16:21:47.107 INFO: Evaluating train_default ...\n","2024-10-31 16:21:48.602 INFO: Evaluating valid_default ...\n","2024-10-31 16:21:48.736 INFO: Error-table on TRAIN and VALID:\n","+---------------+---------------------+------------------+-------------------+\n","|  config_type  | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+---------------+---------------------+------------------+-------------------+\n","| train_default |           19.2      |        232.6     |         10.49     |\n","| valid_default |           15.5      |        223.0     |          9.55     |\n","+---------------+---------------------+------------------+-------------------+\n","2024-10-31 16:21:48.738 INFO: Evaluating Default_Default ...\n","2024-10-31 16:21:54.396 INFO: Error-table on TEST:\n","+-----------------+---------------------+------------------+-------------------+\n","|   config_type   | RMSE E / meV / atom | RMSE F / meV / A | relative F RMSE % |\n","+-----------------+---------------------+------------------+-------------------+\n","| Default_Default |           20.1      |        270.1     |         11.79     |\n","+-----------------+---------------------+------------------+-------------------+\n","2024-10-31 16:21:54.398 INFO: Saving model to MACE_models/mace01_run-1234_stagetwo.model\n","2024-10-31 16:21:55.293 INFO: Compiling model, saving metadata MACE_models/mace01_stagetwo_compiled.model\n","2024-10-31 16:21:56.360 INFO: Done\n"]}],"source":["train_mace(\"training_params.yml\")"]},{"cell_type":"code","execution_count":14,"metadata":{"executionInfo":{"elapsed":271,"status":"ok","timestamp":1730391777664,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"0egZEEKX1xtn"},"outputs":[],"source":["#remove checkpoints since they may cause errors on retraining a model with the same name but a different architecture\n","import glob\n","import os\n","for file in glob.glob(\"MACE_models/*.pt\"):\n","    os.remove(file)"]},{"cell_type":"markdown","metadata":{"id":"YEJseSqmQFJO"},"source":["***\n","\n","# 3.0 Evaluation of Model\n","\n","### Now that we have a trained model, it is important to evaluate the preformance of the model\n","\n","### 3.1 Evaluating against the training data, the testing data, and a volume scan"]},{"cell_type":"code","execution_count":15,"metadata":{"executionInfo":{"elapsed":251,"status":"ok","timestamp":1730391780525,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"CEQ5Acq02hrS"},"outputs":[],"source":["# As with the training, this cell defines the function that allow us to use mace_eval_configs via python\n","\n","import warnings\n","warnings.filterwarnings(\"ignore\")\n","\n","os.makedirs(\"tests/mace01/\", exist_ok=True)\n","\n","from mace.cli.eval_configs import main as mace_eval_configs_main\n","import sys\n","\n","def eval_mace(configs, model, output):\n","    sys.argv = [\"program\", \"--configs\", configs, \"--model\", model, \"--output\", output]\n","    mace_eval_configs_main()"]},{"cell_type":"markdown","metadata":{"id":"yaNvYRB9Y12r"},"source":["Evaluating these 3 takes about 10 to 20 seconds"]},{"cell_type":"code","execution_count":17,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":10455,"status":"ok","timestamp":1730391832138,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"4J3j5S4i2mN5","outputId":"26cbb468-1783-4d01-b60a-7e011fe00b56"},"outputs":[{"name":"stdout","output_type":"stream","text":["2024-10-31 16:23:41.814 INFO: Using CPU\n","2024-10-31 16:23:43.791 INFO: Using CPU\n","2024-10-31 16:23:50.790 INFO: Using CPU\n"]}],"source":["#evaluate the training set\n","eval_mace(configs=\"data/solvent_xtb_train_200.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_train.xyz\")\n","\n","#evaluate the test set\n","eval_mace(configs=\"data/solvent_xtb_test.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_test.xyz\")\n","\n","#evaluate the volume scan\n","eval_mace(configs=\"data/volumeScan.xyz\",\n","          model=\"MACE_models/mace01_stagetwo.model\",\n","          output=\"tests/mace01/solvent_volume_scan.xyz\")"]},{"cell_type":"markdown","metadata":{"id":"srVnaeFgUBGX"},"source":["### 3.2 Plotting Results\n","#### 3.2.1 Energies and Forces"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":1608,"status":"error","timestamp":1730391845341,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"4cb6lr-Z2sVT","outputId":"6aff2d76-06d4-49a9-bc6d-2d27679a54a0"},"outputs":[{"ename":"KeyError","evalue":"'energy_xtb'","output_type":"error","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)","\u001b[0;32m<ipython-input-18-0c9fa142e18b>\u001b[0m in \u001b[0;36m<cell line: 30>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0mplot_RMSEs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'XTB'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'MACE'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m \u001b[0mplot_RMSEs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'XTB'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'MACE'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m \u001b[0mplot_RMSEs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvolume_data\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'XTB'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'MACE'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m<ipython-input-18-0c9fa142e18b>\u001b[0m in \u001b[0;36mplot_RMSEs\u001b[0;34m(db, labs)\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Against Training Data\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m     pp.plot_prop(ea.get_prop(db, 'info', 'energy_xtb', True).flatten(), \\\n\u001b[0m\u001b[1;32m     15\u001b[0m                  \u001b[0mea\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_prop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'info'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'energy_mace'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m                  title=r'Energy $(\\rm eV/atom)$ ', labs=labs, rel=False)\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/aseMolec/extAtoms.py\u001b[0m in \u001b[0;36mget_prop\u001b[0;34m(db, type, prop, peratom, 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'energy_xtb'"]},{"data":{"image/png":"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","text/plain":["<Figure 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","text/plain":["<Figure size 900x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["from aseMolec import pltProps as pp\n","from ase.io import read\n","import matplotlib.pyplot as plt\n","from aseMolec import extAtoms as ea\n","import numpy as np\n","\n","def plot_RMSEs(db, labs):\n","    ea.rename_prop_tag(db, 'MACE_energy', 'energy_mace') #Backward compatibility\n","    ea.rename_prop_tag(db, 'MACE_forces', 'forces_mace') #Backward compatibility\n","\n","    plt.figure(figsize=(9,6), dpi=100)\n","    plt.subplot(1,3,1)\n","    pp.plot_prop(ea.get_prop(db, 'info', 'energy_xtb', True).flatten(), \\\n","                 ea.get_prop(db, 'info', 'energy_mace', True).flatten(), \\\n","                 title=r'Energy $(\\rm eV/atom)$ ', labs=labs, rel=False)\n","    plt.subplot(1,3,2)\n","    plt.title(\"Against Testing Data\")\n","    pp.plot_prop(np.concatenate(ea.get_prop(db, 'arrays', 'forces_xtb')).flatten(), \\\n","                 np.concatenate(ea.get_prop(db, 'arrays', 'forces_mace')).flatten(), \\\n","                 title=r'Forces $\\rm (eV/\\AA)$ ', labs=labs, rel=False)\n","    plt.tight_layout()\n","    return\n","\n","train_data = read('tests/mace01/solvent_train.xyz', ':')\n","test_data = train_data[:3]+read('tests/mace01/solvent_test.xyz', ':') # The first part appends the E0 energies to the validation\n","test_data= read(\"tests/mace01/solvent_volume_scan.xyz\", \":\")\n","\n","plot_RMSEs(train_data, labs=['XTB', 'MACE'])\n","plot_RMSEs(test_data, labs=['XTB', 'MACE'])\n","plot_RMSEs(volume_data, labs=['XTB', 'MACE'])"]},{"cell_type":"markdown","metadata":{"id":"zxdnn048UOYv"},"source":["#### 3.2.2 Interatomic Forces"]},{"cell_type":"code","execution_count":27,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":473},"executionInfo":{"elapsed":9382,"status":"ok","timestamp":1730299359553,"user":{"displayName":"C 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size 3200x1000 with 4 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["from aseMolec import pltProps as pp\n","from aseMolec import anaAtoms as aa\n","\n","db1 = read('tests/mace01/solvent_test.xyz', ':')\n","ea.rename_prop_tag(db1, 'energy_xtb', 'energy') #Backward compatibility\n","ea.rename_prop_tag(db1, 'forces_xtb', 'forces') #Backward compatibility\n","\n","db2 = read('tests/mace01/solvent_test.xyz', ':')\n","ea.rename_prop_tag(db2, 'MACE_energy', 'energy') #Backward compatibility\n","ea.rename_prop_tag(db2, 'MACE_forces', 'forces') #Backward compatibility\n","\n","aa.extract_molecs(db1, intra_inter=True)\n","aa.extract_molecs(db2, intra_inter=True)\n","\n","pp.plot_trans_rot_vib(db1, db2, labs=['XTB', 'MACE'])"]},{"cell_type":"markdown","metadata":{"id":"GRIMk6BrSNkQ"},"source":["### Congratulations, you have trained and evaluated a MACE model!"]},{"cell_type":"markdown","metadata":{"id":"91y-wd0bSTjQ"},"source":[" ***\n"," # 4.0 Task  \n"," ### Try and change some of the hyper parameters such as the cutoff radius (r_max), model size (num_channels), and size of datasets to see how that affects the efficiency and preformance of the resulting models!\n"," ***"]},{"cell_type":"markdown","metadata":{"id":"uyPZd9QZ4oiS"},"source":["# 5.0 Molecular Dynamics with a MACE model\n","\n","## 5.1 Setting up simulation parameters"]},{"cell_type":"code","execution_count":28,"metadata":{"executionInfo":{"elapsed":248,"status":"ok","timestamp":1730299483280,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"idsj28n54qxR"},"outputs":[],"source":["from ase.io import read, write\n","from ase import units\n","from ase.md.langevin import Langevin\n","from ase.md.velocitydistribution import Stationary, ZeroRotation, MaxwellBoltzmannDistribution\n","\n","import random\n","import os\n","import time\n","import numpy as np\n","import pylab as pl\n","from IPython import display\n","\n","def simpleMD(init_conf, temp, calc, fname, s, T):\n","    init_conf.set_calculator(calc)\n","\n","    #initialize the temperature\n","    random.seed(701) #just making sure the MD failure is reproducible\n","    MaxwellBoltzmannDistribution(init_conf, temperature_K=300) #initialize temperature at 300\n","    Stationary(init_conf)\n","    ZeroRotation(init_conf)\n","\n","    dyn = Langevin(init_conf, 1.0*units.fs, temperature_K=temp, friction=0.1) #drive system to desired temperature\n","\n","    %matplotlib inline\n","\n","    time_fs = []\n","    temperature = []\n","    energies = []\n","\n","    #remove previously stored trajectory with the same name\n","    os.system('rm -rfv '+fname)\n","\n","    fig, ax = pl.subplots(2, 1, figsize=(6,6), sharex='all', gridspec_kw={'hspace': 0, 'wspace': 0})\n","\n","    def write_frame():\n","            dyn.atoms.write(fname, append=True)\n","            time_fs.append(dyn.get_time()/units.fs)\n","            temperature.append(dyn.atoms.get_temperature())\n","            energies.append(dyn.atoms.get_potential_energy()/len(dyn.atoms))\n","\n","            ax[0].plot(np.array(time_fs), np.array(energies), color=\"b\")\n","            ax[0].set_ylabel('E (eV/atom)')\n","\n","            # plot the temperature of the system as subplots\n","            ax[1].plot(np.array(time_fs), temperature, color=\"r\")\n","            ax[1].set_ylabel('T (K)')\n","            ax[1].set_xlabel('Time (fs)')\n","\n","            display.clear_output(wait=True)\n","            display.display(pl.gcf())\n","            time.sleep(0.01)\n","\n","    dyn.attach(write_frame, interval=s)\n","    t0 = time.time()\n","    dyn.run(T)\n","    t1 = time.time()\n","    print(\"MD finished in {0:.2f} minutes!\".format((t1-t0)/60))"]},{"cell_type":"markdown","metadata":{"id":"6Aqh6wMCUdcg"},"source":["### 5.2.1 Simulation based on MACE model"]},{"cell_type":"code","execution_count":35,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":27817,"status":"ok","timestamp":1730299984792,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"rgtHyDiJ4tJb","outputId":"ad76373c-c233-411e-e21b-9d8bb36fa597"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 600x600 with 2 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["MD finished in 0.40 minutes!\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 600x600 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":[" #let us start with a single molecule\n","init_conf = ea.sel_by_info_val(read('data/solvent_molecs.xyz',':'), 'Nmols', 1)[0].copy()\n","\n","#we can use MACE as a calculator in ASE!\n","from mace.calculators import MACECalculator\n","mace_calc = MACECalculator(model_paths=['MACE_models/mace01_stagetwo.model'], device='cpu', default_dtype=\"float32\")\n","\n","simpleMD(init_conf, temp=1200, calc=mace_calc, fname='mace_md.xyz', s=10, T=2000)\n"]},{"cell_type":"markdown","metadata":{"id":"HgLjwBe1UkXA"},"source":["### 5.2.2 Simulation based on XTB model"]},{"cell_type":"code","execution_count":34,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":14846,"status":"ok","timestamp":1730299926291,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"r5SMzTJU5wCP","outputId":"b4b1ac27-0935-49d1-a053-a29316e8a2cc"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 600x600 with 2 Axes>"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["MD finished in 0.18 minutes!\n"]},{"data":{"image/png":"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","text/plain":["<Figure size 600x600 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# reinitialize the original config\n","init_conf = ea.sel_by_info_val(read('data/solvent_molecs.xyz',':'), 'Nmols', 1)[0].copy()\n","\n","from xtb.ase.calculator import XTB\n","xtb_calc = XTB(method=\"GFN2-xTB\")\n","\n","simpleMD(init_conf, temp=1200, calc=xtb_calc, fname='xtb_md.xyz', s=10, T=2000)"]},{"cell_type":"markdown","metadata":{"id":"elZWKIgdUoxY"},"source":["### How do they compare to each other?\n","### If you changed the mace model you used the simulation based on your hyper parameters, what differences does it make to the outputs?"]},{"cell_type":"markdown","metadata":{"id":"nTxha_cJ6BwH"},"source":["***\n","##  5.2 Dynamics"]},{"cell_type":"code","execution_count":43,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":889},"executionInfo":{"elapsed":3158,"status":"ok","timestamp":1730300341236,"user":{"displayName":"C A","userId":"06557553969992929141"},"user_tz":0},"id":"ofqbbdtq6twa","outputId":"1b0fa25b-5466-404d-8392-675b731d09e1"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure 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","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["from aseMolec import anaAtoms as aa\n","\n","tag = 'HO_intra' #choose one of 'HH_intra', 'HC_intra', 'HO_intra', 'CC_intra', 'CO_intra', 'OO_intra'\n","\n","for f in ['xtb_md', 'mace_md']:\n","    traj = read(f+'.xyz', ':')\n","    for at in traj:\n","        at.pbc = True\n","        at.cell = [100,100,100]\n","    rdf = aa.compute_rdfs_traj_avg(traj, rmax=5, nbins=50) #aseMolec provides functionality to compute RDFs\n","    plt.plot(rdf[1], rdf[0][tag], label=f, alpha=0.7, linewidth=3)\n","\n","plt.legend();\n","plt.yticks([]);\n","plt.xlabel(r'Radius ($\\rm \\AA$)');\n","plt.ylabel('RDF '+tag);\n","plt.show()"]}],"metadata":{"colab":{"authorship_tag":"ABX9TyNvN9nnYfKf73I3mANhscW7","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}
diff --git a/Workshop4/workshop_files_mark_1/mace_md.xyz b/Workshop4/workshop_files_mark_1/md/mace_md.xyz
similarity index 100%
rename from Workshop4/workshop_files_mark_1/mace_md.xyz
rename to Workshop4/workshop_files_mark_1/md/mace_md.xyz
diff --git a/Workshop4/workshop_files_mark_1/xtb_md.xyz b/Workshop4/workshop_files_mark_1/md/xtb_md.xyz
similarity index 100%
rename from Workshop4/workshop_files_mark_1/xtb_md.xyz
rename to Workshop4/workshop_files_mark_1/md/xtb_md.xyz