diff --git a/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb b/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb
index be8da8fe6b0c701481b25453b0259efd5483fbf9..87c58092610214e213be6340867b91c4f508d6b7 100644
--- a/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb
+++ b/Workshop4/workshop_files_mark_1/Testing_MACE_ver1.ipynb
@@ -1 +1 @@
-{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyNvN9nnYfKf73I3mANhscW7"},"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 about 1 min to 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":1730391537798,"user_tz":0,"elapsed":51623,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"3e4f9d37-0179-4feb-c7ef-f4467e055a9b"},"execution_count":3,"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-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"," 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widgetsnbextension, uri-template, 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"]}]},{"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":1730391474654,"user_tz":0,"elapsed":16646,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"a687ba24-948b-4015-e9bd-db049e77e5fd"},"execution_count":1,"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"," '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()))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":417},"id":"-auaCKHkuBkH","executionInfo":{"status":"ok","timestamp":1730391554727,"user_tz":0,"elapsed":320,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"f488d74e-f8a9-42d3-a24b-7bb439c74bb3"},"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"image/png":"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\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{},"execution_count":4}]},{"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","print(\"Information stored in config.info: \\n\", db[10].info) #check info\n","print(\"Information stored in config.arrays: \\n\", db[10].arrays)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"t10UIWq-td3r","executionInfo":{"status":"ok","timestamp":1730391561513,"user_tz":0,"elapsed":3245,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"966dfaca-2681-4688-b262-b19561a5b927"},"execution_count":5,"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(\"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])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kO-NWJlwvg6W","executionInfo":{"status":"ok","timestamp":1730391564457,"user_tz":0,"elapsed":262,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"a11405c0-dfa6-4992-cf10-97f473e0bc2b"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","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"]}]},{"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."],"metadata":{"id":"_ubUs6-9Lcr8"}},{"cell_type":"code","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"],"metadata":{"id":"290avtLoJv8F","executionInfo":{"status":"ok","timestamp":1730391569922,"user_tz":0,"elapsed":2968,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":7,"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 Ã… do not directly communicate in a single layer. When the model has multiple message-passing layers, atoms further than 5.0 Ã… 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 Ã… and 7.0 Ã….\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":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"qkoQFwdrQC9a","executionInfo":{"status":"ok","timestamp":1730306025562,"user_tz":0,"elapsed":257,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"5a150d51-491b-4265-e8c1-26744720b2a9"},"execution_count":51,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'\\nmodel: \"MACE\"\\nnum_channels: 16\\nmace_L: 0\\nr_max: 4.0\\ncorrelation: 2\\nnum_interactions: 2\\nmax_ell: 2\\n'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":51}]},{"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. 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"],"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":{"colab":{"base_uri":"https://localhost:8080/","height":53},"id":"SN1W_dviQbLs","executionInfo":{"status":"ok","timestamp":1730306027451,"user_tz":0,"elapsed":229,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"0605adc9-a8a1-4181-ef78-c53bc4934ace"},"execution_count":52,"outputs":[{"output_type":"execute_result","data":{"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'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":52}]},{"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":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"fx8242I4QljL","executionInfo":{"status":"ok","timestamp":1730306011486,"user_tz":0,"elapsed":254,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"435927e1-1776-4a5f-9984-52aea40d6bdd"},"execution_count":50,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'\\ndevice: cpu\\nbatch_size: 5\\nmax_num_epochs: 20\\nswa: True\\nseed: 1234\\n'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":50}]},{"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":1730391621421,"user_tz":0,"elapsed":312,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"aa95be83-6348-49e3-dcbf-12f17865f15d"},"execution_count":11,"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","\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()"],"metadata":{"id":"bg4aPR-PzaDb","executionInfo":{"status":"ok","timestamp":1730391622952,"user_tz":0,"elapsed":315,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":12,"outputs":[]},{"cell_type":"markdown","source":["### 2.2.3 Run!\n","\n","1 minute for 20 epochs to"],"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":1730391716521,"user_tz":0,"elapsed":91716,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"8195cad4-7c95-434c-d5f9-543565e25155"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stdout","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"]}]},{"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":1730391777664,"user_tz":0,"elapsed":271,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":14,"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","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":1730391780525,"user_tz":0,"elapsed":251,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":15,"outputs":[]},{"cell_type":"markdown","source":["Evaluating these 3 takes about 10 to 20 seconds"],"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":1730391832138,"user_tz":0,"elapsed":10455,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"26cbb468-1783-4d01-b60a-7e011fe00b56"},"execution_count":17,"outputs":[{"output_type":"stream","name":"stdout","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"]}]},{"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","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","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'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"4cb6lr-Z2sVT","executionInfo":{"status":"error","timestamp":1730391845341,"user_tz":0,"elapsed":1608,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"6aff2d76-06d4-49a9-bc6d-2d27679a54a0"},"execution_count":18,"outputs":[{"output_type":"error","ename":"KeyError","evalue":"'energy_xtb'","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 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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 Interatomic Forces"],"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","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":473},"id":"R9aub3IBsNaS","executionInfo":{"status":"ok","timestamp":1730299359553,"user_tz":0,"elapsed":9382,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"69bd6aa9-b87d-43a1-f2e4-54289d8e53b7"},"execution_count":27,"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!"],"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), and size of datasets to see how that affects the efficiency and preformance of the resulting models!\n"," ***"],"metadata":{"id":"91y-wd0bSTjQ"}},{"cell_type":"markdown","source":["# 5.0 Molecular Dynamics with a MACE model\n","\n","## 5.1 Setting up simulation parameters"],"metadata":{"id":"uyPZd9QZ4oiS"}},{"cell_type":"code","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))"],"metadata":{"id":"idsj28n54qxR","executionInfo":{"status":"ok","timestamp":1730299483280,"user_tz":0,"elapsed":248,"user":{"displayName":"C A","userId":"06557553969992929141"}}},"execution_count":28,"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","simpleMD(init_conf, temp=1200, calc=mace_calc, fname='mace_md.xyz', s=10, T=2000)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"rgtHyDiJ4tJb","executionInfo":{"status":"ok","timestamp":1730299984792,"user_tz":0,"elapsed":27817,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"ad76373c-c233-411e-e21b-9d8bb36fa597"},"execution_count":35,"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 0.40 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","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)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"r5SMzTJU5wCP","executionInfo":{"status":"ok","timestamp":1730299926291,"user_tz":0,"elapsed":14846,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"b4b1ac27-0935-49d1-a053-a29316e8a2cc"},"execution_count":34,"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 0.18 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?"],"metadata":{"id":"elZWKIgdUoxY"}},{"cell_type":"markdown","source":["***\n","## 5.2 Dynamics"],"metadata":{"id":"nTxha_cJ6BwH"}},{"cell_type":"code","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":{"base_uri":"https://localhost:8080/","height":889},"id":"ofqbbdtq6twa","executionInfo":{"status":"ok","timestamp":1730300341236,"user_tz":0,"elapsed":3158,"user":{"displayName":"C A","userId":"06557553969992929141"}},"outputId":"1b0fa25b-5466-404d-8392-675b731d09e1"},"execution_count":43,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}]}]}
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+{"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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torchmetrics, torch-ema, opt-einsum-fx, ase, matscipy, e3nn, mace-torch\n","Successfully installed ase-3.23.0 configargparse-1.7 e3nn-0.4.4 lightning-utilities-0.11.8 mace-torch-0.3.7 matscipy-1.1.1 opt-einsum-fx-0.1.4 python-hostlist-2.0.0 torch-ema-0.3 torchmetrics-1.5.1\n","Collecting xtb\n"," Downloading xtb-22.1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.metadata (4.6 kB)\n","Collecting nglview\n"," Downloading nglview-3.1.2.tar.gz (5.5 MB)\n","\u001b[2K \u001b[90mâ”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”\u001b[0m \u001b[32m5.5/5.5 MB\u001b[0m \u001b[31m59.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h 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: ipywidgets in /usr/local/lib/python3.10/dist-packages 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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 Ã… do not directly communicate in a single layer. When the model has multiple message-passing layers, atoms further than 5.0 Ã… 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 Ã… and 7.0 Ã….\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 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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":"iVBORw0KGgoAAAANSUhEUgAAAhcAAAG0CAYAAACBuQWVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABfuUlEQVR4nO3dd3hUZfo+8PucmTlTUkkDQkvoHQQUsaJgxcKqrGJDV3dXV9fCV9fVteDa1nWxrK6o+xO7YllBVxFlQRBFuiBIh9AT0kibPuec3x8nM8mZmYRJMi3J/bkurs2caS9Zydx5y/MIqqqqICIiIooSMdEDICIioo6F4YKIiIiiiuGCiIiIoorhgoiIiKKK4YKIiIiiiuGCiIiIoorhgoiIiKLKmIg3VRQFR44cQVpaGgRBSMQQiIiIqIVUVUVtbS3y8/Mhik3PTyQkXBw5cgS9evVKxFsTERFRGx08eBA9e/Zs8v6EhIu0tDQA2uDS09MTMQQiIiJqoZqaGvTq1SvwOd6UhIQL/1JIeno6wwUREVE7c7wtDdzQSURERFHFcEFERERRxXBBREREUZWQPRdERNSxyLIMr9eb6GFQG5lMJhgMhja/DsMFERG1mqqqKCkpQVVVVaKHQlGSmZmJbt26takOFcMFERG1mj9Y5OXlwWazsTBiO6aqKhwOB0pLSwEA3bt3b/VrMVwQEVGryLIcCBbZ2dmJHg5FgdVqBQCUlpYiLy+v1Usk3NBJRESt4t9jYbPZEjwSiib//59t2UPDcEFERG3CpZCOJRr/fzJcEBERUVQxXBAREVFUMVwQtReyF3DXJnoURJ2WIAhYsGBBooeBG264AVOnTk30MJrFcEHUHlTsAT6/A/jPzcD3zwOqmugREXVYs2bNwujRoxM9jHaNR1GJ2oNf5gPOSu3rAz8CA84Bug5L7JiIgqiqilq3L2Hvn2Y2cnNpkmC4IGoPag7rb1cfZrigpFPr9uHueRsT9v7PXTUa6RbTcR9XVlaGESNG4I477sADDzwAAFi5ciUmTpyIOXPm4NFHHwXQcGrijTfewA033AAAKC4uxgUXXIBly5ahe/fu+Pvf/44rrrjiuO+5b98+FBYW4sMPP8SLL76IdevWYfjw4XjvvfdQXV2NW2+9Fdu3b8fpp5+Ot99+G7m5uQC0WiL33nsv5s6dC4PBgJtuuglqO5i55LIIUXvgsQfdrkvMOIg6gNzcXMydOxezZs3CunXrUFtbi+uuuw633347rr76avzf//0fhg0bhuLiYhQXF+PKK68MPPehhx7C5Zdfjk2bNuGaa67BVVddhW3btkX83o888ggefPBBbNiwAUajEVdffTX+9Kc/4YUXXsCKFSuwe/duPPzww4HHz549G2+++Sbmzp2L77//HpWVlZg/f35Uvx+xwJkLovaA4YIoqi688EL89re/xTXXXINx48YhJSUFTz31FMxmM1JTU2E0GtGtW7eQ502bNg0333wzAOCxxx7D4sWL8eKLL+Lll1+O6H3vuecenHfeeQCAO++8E9OnT8eSJUtw6qmnAgBuuukmvPnmm4HHP//887j//vtx2WWXAQBeeeUVfP311235q8cFZy6Ikp3PAyhB69huhguitvrHP/4Bn8+Hjz/+GO+99x7MZvNxnzNhwoSQ2y2ZuRg5cmTg665duwIARowYobvm7+1RXV2N4uJijB8/PnC/0WjEuHHjIn6/ROHMBVGyCzdLETyTQZQE0sxGPHfV6IS+f0vs2bMHR44cgaIo2Ldvn+5DPlZMpoY9If49HcHXFEWJ+ThijeGCKNl5HaHXuCxCSUgQhIg2VCYDj8eDa6+9FldeeSUGDRqEm2++GZs3b0ZeXh4kSYIsy2Gft2rVKlx//fW62yeccEJMxpiRkYHu3btj9erVOOOMMwAAPp8P69evx5gxY2LyntHCcEGU7MLNUjBcELXJX/7yF1RXV+Of//wnUlNTsXDhQvzmN7/BF198gYKCAhQVFWHjxo3o2bMn0tLSAksmH3/8McaNG4fTTjsN7733HtasWYPXX389ZuO888478be//Q0DBgzA4MGD8eyzz6Kqqipm7xct3HNBlOzChgsuixC11rJly/D888/jnXfeQXp6OkRRxDvvvIMVK1Zgzpw5uPzyy3H++efjrLPOQm5uLj744IPAcx999FHMmzcPI0eOxNtvv40PPvgAQ4cOjdlY/+///g/XXXcdZsyYgQkTJiAtLQ2/+tWvYvZ+0SKoCTgwW1NTg4yMDFRXVyM9PT3eb0/UvhStAH58SX9NNAJXvguwYBAlkMvlQlFREQoLC2GxWBI9HIqS5v5/jfTzmzMXRMku3J4LxQfInviPhYgoAgwXRMmuqf0VXBohShpPPvkkUlNTw/654IILEj28uOOGTqJk5wkzcwFoHVJtWfEdCxGFdcstt+DXv/512PusVmucR5N4DBdEya6pGQrOXBAljaysLGRlMez7cVmEKNl5mwoXPI5KRMmJ4YIo2TU5c8FwQUTJieGCKNlxWYSI2hmGC6JkVx8ial0+lNe54ZXr+w6weRkRJSlu6CRKdh47KuxuHKx0AgBKql0Y0j0dBi6LEFGS4swFUTJTVcDrRKW9oWCWT1FR7fRyzwURtYogCFiwYEFM34PhgiiZeR0AVHhlfZV+j0/hsggRJS0uixAls/oCWrISFC5khRs6KfmoKuCuSdz7m9PZbydJMFwQJTNPHVRVDQ0XPgXw1CZoUERNcNcAn/4uce9/2WuAJSOih06cOBEjRoyAwWDAW2+9BUmS8Pjjj+Pqq6/G7bffjk8++QRdu3bFiy++iAsuuACyLON3v/sdli5dipKSEvTu3Rt/+MMfcOedd+ped+7cuZg9ezZ2796NrKwsXH755XjpJa3xYFVVFe655x589tlncLvdGDduHJ577jmMGjXquOOdNWsWFixYgDvuuAOzZs1CZWUlrr/+erz44ouYPXs2nn32WSiKgjvvvBN/+ctfAs/btWsXbrrpJqxZswZ9+/bFCy+80IJvaOtxWYQomXnsIcEC4MwFUTS89dZbyMnJwZo1a/DHP/4Rt956K6ZNm4ZTTjkFGzZswLnnnovrrrsODocDiqKgZ8+e+Pjjj7F161Y8/PDDeOCBB/DRRx8FXm/OnDm47bbb8Lvf/Q6bN2/G559/jv79+wfunzZtGkpLS/HVV19h/fr1GDNmDCZNmoTKysqIxrtnzx589dVXWLRoET744AO8/vrrmDJlCg4dOoTly5fj6aefxoMPPojVq1cDABRFwWWXXQZJkrB69Wq88soruO+++6L7TWwCW64TJbODa+Ba+ndsL9HPUggARvbMgHDV+4CBE5CUGCGtuV3V7WrmQpZlrFixAgAgyzIyMjJw2WWX4e233wYAlJSUoHv37vjxxx9x8sknh7zG7bffjpKSEnzyyScAgB49euDGG2/E448/HvLY77//HlOmTEFpaSnMZnPgev/+/fGnP/0Jv/td89+3WbNm4ZlnnkFJSQnS0tIAAOeffz527NiBPXv2QBS1uYLBgwfjhhtuwJ///Gd88803mDJlCvbv34/8/HwAwKJFi3DBBRdg/vz5mDp1atj3ikbLdf5UIkpmnjrIYfK/CsArq5C8dsAQ2Q9TItIbOXJk4GuDwYDs7GyMGDEicK1r164AgNLSUgDAv/71L8ydOxcHDhyA0+mEx+PB6NGjA485cuQIJk2aFPa9Nm3ahLq6OmRnZ+uuO51O7NmzJ6LxFhQUBIKFf3wGgyEQLPzX/OPdtm0bevXqFQgWADBhwoSI3qutGC6IkpnHAVkOP7nokRVIHnvEv6kRxZw5XZs9SOT7t4DJZNLdFgRBd02o3xyqKArmzZuHe+65B7Nnz8aECROQlpaGZ555JrAEcbzOp3V1dejevTuWLVsWcl9mZmZUxuu/pihKRK8XSwwXRMnM64AvzJ4LwL+pk/suKIkIQocNuz/88ANOOeUU/OEPfwhcazzjkJaWhoKCAixZsgRnnXVWyPPHjBmDkpISGI1GFBQUxGPIGDJkCA4ePIji4mJ0794dALBq1aq4vDc3dBIlM09d2A2dQP2mTjdPjBDFw4ABA7Bu3Tp8/fXX2LlzJx566CGsXbtW95hZs2Zh9uzZ+Oc//4ldu3Zhw4YNePHFFwEAkydPxoQJEzB16lR888032LdvH1auXIm//OUvWLduXUzGPHnyZAwcOBAzZszApk2bsGLFCt1JklhiuCBKZh5H0+HCp7BKJ1Gc/P73v8dll12GK6+8EuPHj0dFRYVuFgMAZsyYgeeffx4vv/wyhg0bhosuugi7du0CoC1XLFy4EGeccQZuvPFGDBw4EFdddRX2798f2NsRbaIoYv78+XA6nTjppJNw880344knnojJewXjaRGiZLbsaRz+5QeU1blD7kq1GNH//NuBQRckYGBEzZ8qoPYrGqdFOHNBlMyaOC0CAF7uuSCiJMVwQZTMvA745Iad3z6hYWe4R1aguLjngqgjGDZsGFJTU8P+ee+99xI9vBbjaRGiZBZUobPakIVs31EAWhsHl70GtkSNjYiiZuHChfB6vWHvi9WejFhiuCBKZh47fI2WRWoMXQLhAgAcdVUMF0QdQJ8+fRI9hKjisghRspJ9gOzRFdGqNmTpHuJ2VMd7VEQhkqFoE0VPNP7/5MwFUbLy2qFCDVkW0T3EwaOolDiSJEEURRw5cgS5ubmQJClQ1ZLaH1VV4fF4UFZWBlEUIUlSq1+L4YIoWXnsUBStj4hftaGL7iEyN3RSAomiiMLCQhQXF+PIkSOJHg5Fic1mQ+/evXU9S1qK4YIoWQVt5pQFI+ximu4hqrtO29nJ3xYpQSRJQu/eveHz+SDLcqKHQ21kMBhgNBrbPAPFcEGUrDx2+BqtfboEK9yivjmS1+cDvE5A4rZOShx/A63gJlrUeXFDJ1GyCpq58IgWuAR9iPDIClSWACeiJMNwQZSsvPq+Ii7BCqPZCrXRP1tVBWqqqxIwOCKipjFcECUrT52u3bpHtKB7phUeg372orr6WLxHRkTULIYLomTlCZ25SDWbAHOK7mE1DBdElGQYLoiSVdCeC7dgQYrZAINZf2LEXstCWkSUXBguiJKV1x6yLJJiNsJo1YcLZx3DBRElF4YLomQVNHPhEqxIMRsh2dJ1D3PZa+I9MiKiZjFcECWroD0XbtGKFMkAS4o+XHidDBdElFwYLoiSlacuzJ4LI2xpmbqH+Zy1UFUVRETJguGCKFkFVejUZi6MSE3L0D1MUhyodnrjPToioiYxXBAlI1UNKaLlFiywmQ1IScvQtRKxKE6U13kSMEgiovAYLoiSkc8FRZHRKFvALVqRajZCMKdBMjT80zWrLlTUuRMwSCKi8BguiJKRx6E7hgo07LmAlArJ2PBP16I4OHNBREmF4YIoGXnqIMuNw4WgLYuYDICUopu5MKpeHKtl8zIiSh4MF0TJyGOH3OgEiEcww2o2QhSFkJkLgM3LiCi5MFwQJSOvflnELVqQajZqN6QUmAz6f7q1tVVxHBwRUfMYLoiSkacOcuNjqPXVOQEAogEma6ru4a66Gta6IKKkwXBBlIw8DsgN2QJu0YIUyRC4LQWFC4PPjhqnL16jIyJqFsMFUTLyOnQzF67GMxcAJFt6aK0LO4+jElFyYLggSkaeupCOqLZG4SK41oVFcaKCx1GJKEkwXBAlo6CmZS7BqlsWgZSir3WhOlDOQlpElCQYLoiSUVC7dY+/gJaflKo7MWJWnKzSSURJg+GCKBl57fA1KqLlqi/9HRBU68Kssr8IESUPhguiZBRURMstWGBrvCxiTg3Zc8FlESJKFgwXRMkoaFlEV0QLCLPnQtvQyVoXRJQMGC6IkpDiDgoXQUdRIaWFNC/zygpq3ax1QUSJx3BBlGwUGbLHobukFdHSz1yYRCFQ68KsugAA5bVcGiGixGO4IEo2Xv0xVECbubCZ9UdRBUEI7LswKy4IqoIKOzd1ElHiMVwQJZug/RYAoEo2fbMycxoAwBRYGlFhVl08jkpESYHhgijZeOy66pyKYIDZbNU/RtJ6i0hBtS7KeByViJIAwwVRsgk+KRJcQAsAjBJgMIU5McKZCyJKPIYLomQTEi6soeEC0AppGfQnRljrgoiSAcMFUbLxBte4aCpcpARV6XSx1gURJQWGC6Jk47HD16jduluw6JuW+YWZufD4FNSx1gURJRjDBVGyCe6IKobZcwHUNy9rqHVhUZwAwB4jRJRwDBdEycZT13xHVD9zKgRBCBxRNatauOCmTiJKNIYLomQTVESr6T0X+uOoFkWr6smZCyJKNIYLomQTVOfCLViQag635yJF+x+jf+aivgQ4Zy6IKMEYLoiSTZg6FzYp8pmLCs5cEFGCMVwQJRk1KFy4RKu+aZmfuT5c1M9cWPx7LuycuSCixGK4IEoysqsWjStVaEW0wh9FBRqFi8BpETdrXRBRQjFcECUTVYXstusuuZs8ilq/56LxaRFVhdurwO6RYz5UIqKmMFwQJRPZA9nn1V3yGWwwG8P8U62fuTAZBAgARFWGUdWey+OoRJRIDBdEySTopAgAGCxaPYsQ9XsuBEEItF7377vgiREiSiSGC6JkElTjAgBM1pTwjzXZAGihg7UuiCiZMFwQJZOgkyI+QYLNbA7/WEEIqXURODHCcEFECcRwQZRMgkp/u5qqzuln1te6MCtcFiGixGO4IEomYapz2sJ1RPULPo7K/iJElAQYLoiSSUhHVCtSm5u5CJwYCdpzYfew1gURJQzDBVEyCdMR1dZsuAjfX8TlkeFgrQsiShCGC6Jk4nXApyiBm002LfMz62td+GcuAG7qJKLEYbggSiaeMO3Ww/UV8atfFhEFASaDqAsXZdx3QUQJwnBBlEyClkXcQhOlv/2khhoYklEMLIsA3NRJRInDcEGURFSPQ3da5LhHUetnLgAtXPiblwFApZ3LIkSUGAwXRElEdtei8SEPj2BBSnNHUc0N4cIgCrCoDcsibF5GRInCcEGURGRXne52S2YuDIKgm7lweRkuiCgxGC6Ikojs0rdb94jHK6LVsOfCIAowqh6IqhYqnJy5IKIEYbggShaqCtmjDxeCuYmOqH6SflkEAMz1VTqdnLkgogRhuCBKFl4H5EY1LgDAaElt4sH1GoULsf5fs39phOGCiBKF4YIoWXjskGV9ye7jhguDETBqXVMN9TMc/loXXBYhokRhuCBKFkHt1lUIMFtSmnlCPSkNQJhlEYYLIkoQhguiZOGxw6c2rs55nAJafvWbOsXAzIUWLryyAp+sNPk0IqJYYbggShZByyJu4TjHUP3qa10Ez1wA3HdBRInBcEGULLx2XXVO9/HarfvVz1z4w0XjWhdcGiGiRGC4IEoWHjtkVd9XpNkaF371ey4EQftjURsX0uKyCBHFH8MFUbLwOPTLIserzulXvywiQKiv0tlQAtzh9UV9mEREx8NwQZQsWtoR1c9kC3xpEAWYuSxCRAnGcEGULLwOyGrDMoZbsCLVHMGySKPmZaIgwNKo7To3dBJRIjBcECUJ2VWHxidH3aIFNimSDZ1pgS+1mYuGZRHOXBBRIjBcECUJX1BH1IiXRYKalzVuu86ZCyJKBIYLoiThc9XqbrtFK1IiOS1i1jcvsyguoP7UCWcuiCgRGC6IkoTs1ndEVUw2GA0R/BNt3LxMAAAVUv2+C85cEFEiMFwQJQnFrV8WMZiP07TML0zbdf+mTs5cEFEiMFwQJQPZC8Xr0V0yWNKaeHAQoxkQtb0ZYnBnVM5cEFECMFwQJYOgjqgAYLRGOHMhCCElwP21LjhzQUSJwHBBlAzChAspknbrgQfrm5f5S4Bz5oKIEoHhgigZeB3wKQ1FLmTBCJvVGvnzQ9qua8siDs5cEFECMFwQJYOg0t+uSNut+0nh2667OHNBRAnAcEGUDDwOXbt1j2iJrMaFX/3JEoOgb7vu8spQVbXJpxERxQLDBVEyCNpz0daZC/+eC1Vl23Uiij+GC6JkENwRVbQiJZKmZX5Bp0Uat13npk4iijeGC6Jk4NUvi0TcV8SvfuaiPlvo264zXBBRnDFcECUB1V0HJXjmIpKOqH71ey4EQYBBBMyN2657fFEbJxFRJBguiJKA11WHxtsuWz5z0VATQxRE/bKIh3suiCi+GC6IkoDXGdxu3QpbS06LSA2lwg1iw4ZOgMsiRBR/LfjVSM/hcODAgQPwePT9EEaOHNnmQRF1Nj6XPlx4DRaYjS3I/o3brgsCDKoPBtULWTDBwWURIoqzFoeLsrIy3Hjjjfjqq6/C3i/L/C2JqKXkoI6oojkVQn3Niog0XhZpdGLEbsjgUVQiirsWL4vcddddqKqqwurVq2G1WrFo0SK89dZbGDBgAD7//PNYjJGow1OCZi7ElvQVAQBTw+ND2q57OXNBRPHV4pmLpUuX4rPPPsO4ceMgiiL69OmDc845B+np6XjqqacwZcqUWIyTqONSVageu+6SMdJ2636iCJhsgNfRqEpnfdt1bugkojhr8cyF3W5HXl4eAKBLly4oKysDAIwYMQIbNmyI7uiIOgOfC7KiDwCmloYLoKEEeHDbdW7oJKI4a3G4GDRoEHbs2AEAGDVqFF599VUcPnwYr7zyCrp37x71ARJ1eGHarZtsrQgX9SdGxOC269zQSURx1uJlkTvvvBPFxcUAgEceeQTnn38+3nvvPUiShDfffDPa4yPq+ELChQCLtYV7LgBAsgFoaF7GmQsiSpQWh4trr7028PXYsWOxf/9+bN++Hb1790ZOTk5UB0fUKQSFC49ghs1savnrNNG8jHsuiCjeWrQs4vV60a9fP2zbti1wzWazYcyYMQwWRK3ldcDXaM+FS7QitSXVOf3q91yI9f+qAxs6eVqEiOKsReHCZDLB5XId/4FEFLmgjqgewdKy6px+9cdRDYL2z1ryH0X1cFmEiOKrxRs6b7vtNjz99NPw+fjbEFFUBC2LuERry/qK+Pn3XNT/qzYr/joXDBdEFF8t/gm2du1aLFmyBN988w1GjBiBlBT9xrNPP/00aoMj6gxUj71t7db96mcuREFfRMsnq/DKCkwGthIiovho8U+wzMxMXH755bEYC1Gn5HPWQm10WMQtWpFibsWySH0JcP+GTimoeRnDBRHFS4vDxRtvvBGLcRB1Wp6QjqiW1m3oDCyL+I+iNuyPcnlkpFtacQKFiKgVWvyrzNlnn42qqqqQ6zU1NTj77LOjMSaiTsXrrNXd9ogWWE2t39ApCNofs9oQLhzc1ElEcdTicLFs2bKQNusA4HK5sGLFiqgMiqgz8bn1fUVUqYUdUf3qZy4ECLq26wA3dRJRfEU89/rzzz8Hvt66dStKSkoCt2VZxqJFi9CjR4/ojo6oE1Bc+pkL0dyK6pyAru26QRTgU1RIihtOg4nhgojiKuJwMXr0aAiCAEEQwi5/WK1WvPjii1EdHFFnoHgcutuG1oYLky3wpf/EiFl1wYlU1rogoriKOFwUFRVBVVX07dsXa9asQW5ubuA+SZKQl5cHg6EV68REnZzq1m/obHG7dT+DSfsjexs2dQZKgDNcEFH8RBwu+vTpAwBQFPYpIIoaRYbq1Ve9NbamaZmflAo4j4WcGOGyCBHFUyvOuwG7du3Ct99+i9LS0pCw8fDDD0dlYESdgtcR0m5dsrZy5gLQlkYahwuWACeiBGhxuPj3v/+NW2+9FTk5OejWrZtuV7sgCAwXRC3hdemqcwKA2Zra+teT/FU661+LbdeJKAFaHC4ef/xxPPHEE7jvvvtiMR6izsVrD5q5EGBt07KIvkpnYOaC4YKI4qjFdS6OHTuGadOmxWIsRJ2PxxHUEdWMFEurVis19SdGDAKXRYgocVocLqZNm4ZvvvkmFmMh6nx8Tn24EM1IkdoQLuoLaYmBDZ1cFiGi+GvxT7H+/fvjoYcewqpVqzBixAiYTPp+BXfccUfUBkfU4Xkc8DXaFO0WLOjWmr4ifpK2X6OheRlnLogo/lr8U+y1115Damoqli9fjuXLl+vuEwSB4YKoBWS3HY23XHgEM2xSG+rFBC+L8CgqESVAi8NFUVFRLMZB1Cm5Xfq+Ih7REpVlEf/MhYUzF0SUAC3ec0FE0eNx6sOFWzDD2qaZi/qjqIFlEW3PhcsrQ1XVJp9GRBRNEf2KNHPmTDz22GNISUnBzJkzm33ss88+G5WBEXUG3qCmZbLBAsnYhszvP4oatCwCaEsjtrbMihARRSiinzQ//fQTvF5v4OumtKpNNFEn5nM59RcaNR9rlSbqXADa0gjDBRHFQ0Q/ab799tuwXzfn0KFDyM/Phyhy5YWoKbJH37TMv2ei1Uz+o6jaTYPqg0H1QhbYdp2I4idmn/xDhw7Fvn37YvXyRB2C4g5qty5Z2/aC9eFEgNBwHFVxA9D2XRARxUPMwgU3jxEdn+LRhwtBakNfESCwoRNo2Hdhqd/U6eCJESKKE65ZECVSULgwmNu4LGIwAgYJQOMTIzyOSkTxxXBBlECqVx8ujJY2NC3zC2zq1G5aWAKciOKM4YIoUVQVgld/WsQUjXDB5mVElGAxCxc8lkp0HLIXiuzTXZIsbdxzAQRmLgLLIiwBTkRxxg2dRInitUMO+ndiskYvXITMXDBcEFGctKqiTlVVFXbv3g1A65KamZkZ8pitW7ciPz+/TYMj6tC8+nbrAGCxRnFZROSyCBElRotmLvbt24cpU6YgJycH48ePx/jx45GTk4OLLroopKZFr169YDC0oUcCUUcXFC5kwQirpY11LoBArQv/sojZv6GT4YKI4iTimYuDBw/i5JNPhslkwmOPPYYhQ4YA0GYo5syZgwkTJmDt2rXo2bNnzAZL1KF4Hbpw4RHMyDRHIZDX18rgsggRJUrE4WLWrFkYNGgQvv76a1gslsD1qVOn4u6778b555+PWbNm4f/9v/8Xk4ESdTQ+Vx0ar4p4BDNsbemI6he8LFK/oZNFtIgoXiIOF4sWLcKHH36oCxZ+VqsVjz32GK666qqoDo6oI3O79DUuPIIFNlMUGos10bzM7WO4IKL4iHjPRXl5OQoKCpq8v2/fvqisrIzGmIg6Ba9T327dLVpgjcbMhf8oqqDfc8GZCyKKl4jDRffu3bF169Ym79+yZQu6desWlUERdQYep113WzaYIRmjcDo8sCyi3Wx8WoRHxIkoHiL+STZ16lTcc889KCsrC7mvtLQU9913H6ZOnRrNsRF1aF6XPlyoxjb2FfELWhbx9xaRFRVemeGCiGIv4gXeRx55BAsXLkS/fv1w7bXXYvDgwVBVFdu2bcP777+Pbt264eGHH47lWIk6FJ+7Tn+hre3WA6+jXxYxqD4YVC9kwQSnV47O7AgRUTMiDhddunTB6tWr8cADD2DevHmoqqoCAGRmZuLqq6/Gk08+iaysrFiNk6jDkd1B7dZNUZq5CDotAmgnRhwGE5weGRlWU3Teh4ioCS3amt6lSxfMmTMHL7/8cmB5JDc3l31EiFpBceuXRQRzFKpzAoFwIQoCRAFQVG3fhQNprHVBRHHRqnNvgiAgLy8v2mMh6lQUj74jqkGK0syFwQgYzYDPDVEQoKhqYN8Fq3QSUTxEHC5OOOGEiGYoNmzY0KYBEXUWqkc/c2GI1swFAJhSAJ8bBlGAT1Fh8ZcA9/qO80QioraLOFw0Pgmiqiqeeuop3HLLLdxnQdRaXv3MhckSxXAh2QBnZUghLZdXid57EBE1oUWnRRqbPXs27rzzTvTt2zfqgyLqDASfPlwYLVFot+5n0jcvk1gCnIjiiGfSiBJBVUPChWSJ0p4LgM3LiCihGC6IEiGoIyoASNYozlxIQc3L/MsinLkgojhguCBKBK8rJFyYrWnRe31/rYuQ/iLc0ElEsRfxnot//vOfuts+nw9vvvkmcnJydNfvuOOO6IyMqCPz2kPChTUlmhs666t01v/6YFH9p0W4oZOIYi/icPHcc8/pbnfr1g3vvPOO7pogCAwXRBHwuexonC18ggSbOYqVMwP9RbR04d/QyT0XRBQPEYeLoqKiWI6DqFNxufR9RdyCBVZTFNqt+wWqdGo3GzqjclmEiGKPey6IEsDj0IcLj2iGTWpVwdzwgjqjmjlzQURxxHBBlAAep746p1e0wGSIYo+e4A2d/j0XHu65IKLYY7ggSgBP0LKIYrRFtwFg8MyF6gJUleW/iSguGC6IEsDn0s9cQLJG9w0Cp0W0cCGqMgzwwe1VoASdUiEiijaGC6IE8Lkd+gvGKFbnBEJmLgAEmpe5fNx3QUSxFXG4ePjhh+FwNPxAPHbsWEwGRNQZyG79zIUY7ZmLoD0XAAJt19lfhIhiLeJw8cQTT6CurmGduE+fPti7d29MBkXU0SlB4UKQolj6GwBEA2A0QxQBf7wInBhhuCCiGIs4XKiq2uxtIoqc4tEvixgtUZ65AAApFQKEwL4LNi8jonjhnguiRPDqw4UoRbH0t1/IcVTOXBBRfERctUcQBNTW1sJisUBVVQiCgLq6OtTU1Ogel56eHvVBEnU4Xn27dZMlBuGicWdUuaF5GWcuiCjWIg4Xqqpi4MCButsnnHCC7rYgCJBl/uAiOh4haOYiJuHCpG9expkLIoqXiMPFt99+G8txEHUqgi9o5sIa5Q2dQMNxVIElwIkoviIOF2eeeWYsx0HUecheQNZXyjRb06L/Po2XRdBwFJUzF0QUay3ulFRdXY3Fixdj3759EAQBhYWFmDx5MvdaEEXK64Ci6nt8mK2xXBbRwoWlvr+IgzMXRBRjLQoX7777Lm6//faQTZwZGRl45ZVXcOWVV0Z1cEQdkc9lhxzUP8xii8WyiP60iFS/LOJmuCCiGIv4KOqGDRtw4403YurUqfjpp5/gdDrhcDiwbt06XHzxxbjuuuuwadOmWI6VqENwOfVNy1SIsFljUeciTPMysEInEcVexDMXL774IqZOnYo333xTd33MmDF4++234XA48MILL2Du3LnRHiNRh+J26MOFWzTDZjZF/42ClkW4oZOI4iXimYsffvgBv//975u8/5ZbbsH3338flUERdWRup770t1e0wGSIYrt1Pym4iFZ9nQvOXBBRjEUcLo4cOaKrcxFs4MCBOHz4cFQGRdSRuV1ByyJGKwQhBuHCpD8tYlZdgKoyXBBRzEUcLhwOBywWS5P3m81muFyuqAyKqCPzBe25UExRbrfuF7TnQlRlGOHlsggRxVyLTot8/fXXyMjICHtfVVVVNMZD1OF5XUEdUY1Nh/Y2qQ8XYqNJEbPigtNrDlTUJSKKhRaFixkzZjR7P39YER2f7NaX/vZvvIy6oGURQCukZVfS4ZEVmI2G2LwvEXV6EYcLRVGO/yAiOi7ZrV8WEaQYLYuIBsBohkFuKDVuURo2dTJcEFGsRLXlutPpPP6DiDo5xRPUbt0co3ABAFJq4Cgq0FAC3OXlLwtEFDtRCRdutxuzZ89GYWFhNF6OqENTPfoQLkoxWhYBAJMNoiAE9l00FNLyNfMkIqK2iThcuN1u3H///Rg3bhxOOeUULFiwAADwxhtvoLCwEM8//zzuvvvuWI2TqMNQg2YujLFot+4X1LyMhbSIKB4i3nPx8MMP49VXX8XkyZOxcuVKTJs2DTfeeCNWrVqFZ599FtOmTYPBwDVcouPy6sOFyRzLcKH1LBEFAYAaKKTlYrggohiKOFx8/PHHePvtt3HJJZdgy5YtGDlyJHw+HzZt2sRTIkQtIPj09WBMseiIGnjx8DMX7C9CRLEU8bLIoUOHMHbsWADA8OHDYTabcffddzNYELWQ6NPPXEiWGHREDbx4+OZlrNJJRLEUcbiQZRmSJAVuG41GpKbG8IciUUekqrqjoQAgxXLmIlBIKyhccFmEiGIo4mURVVVxww03wGw2AwBcLhduueUWpKTofzB++umn0R0hUQfi8zihKKrumsWWFrs3DFkWYfMyIoq9iMNFcHXOa6+9NuqDIeronEHt1gHAYovlskiY5mXgzAURxVbE4eKNN96I5TiIOgW3ozbkmi0lhuGivrS4v+26xKOoRBQHUa3QSUTNcwXNXMiiCSaTKXZv6N9zwQ2dRBRHDBdEceQObrdusMb2xJV/WaRxhU5VZbggophiuCCKI29wuDBZY/uGJv1RVFGVYYSXyyJEFFMMF0Rx5HHpa1yoxhiHi/qZi8bNy8yKi+GCiGKK4YIojnwuu/6CKYYdURu9vkHQd0blsggRxRLDBVEc+dxBR1FjHS5EA2C0BJZFAMCiOOHxKZCD6m0QEUULwwVRHClu/bKIaI5xuAAAKUW3LCKx1gURxRjDBVEcKUHt1sVYz1wAgJSiWxbhcVQiijWGC6I4UoPChSGW7db9TDaIIuCPFxaFbdeJKLYYLojiyasPF0ZLfGYuBAiBpRH/sgjbrhNRrDBcEMWTV98R1RjLdut+QSdG/DMX3HNBRLHCcEEUR4JPHy5Mljgsi0j6QloS91wQUYwxXBDFkRgULszW+IULsf5fu7m+eRn3XBBRrDBcEMWJT1ZglF26a5I1LfZvHLQsYuaeCyKKMYYLojhxuj0wqh7dNYstDnsugpZFzKxzQUQxxnBBFCfB7daBBIULbugkohhjuCCKE4dD31dEEAApHhs665dFxKBlEafHF/v3JqJOieGCKE7cjhrdbYMoQoh1y3UgzMyFC1BVOD1K7N+biDolhguiOPE49TMXssGqTV/EWlC4EKDAqHq5LEJEMcNwQRQnnqB266rREp83DloWAQCz6uSyCBHFDMMFUZx4g8NFPJqWAQ1HUUV98zLOXBBRrDBcEMWJ7A46LRKP/RaAVj3LZNWHC8UFp5d7LogoNhguiOLEFzRzIUhxOCniZwpuu+6E0yNDVdX4jYGIOg2GC6I4UYLarQtSnGYuAECyBcp/A9rMhaqqcPs4e0FE0cdwQRQnilsfLkQpTnsuAEBKgaFRuvDXumB/ESKKBYYLojhRvPpwYTTHd1mk0ZaLQGdU9hcholhguCCKEyEoXBgscSj97SfZIApCIGBYWAKciGKI4YIoXrz6dusmcxyXRYKOo0qBEuAMF0QUfQwXRHEi+vThQrLGc+ZCW4IRG5cAB2cuiCg2GC6I4kBWVBiSIFwYgpqXcUMnEcUCwwVRHDi9cmApws9sjeeGTv2yiFnVgg43dBJRLDBcEMWBw+WFpHp018y2BCyLCEHLIgwXRBQDDBdEceBwuSCqDR/kggBI8Twt0sTMBZdFiCgWGC6I4sDl0PcVMQgChDgX0QIahQvFBagql0WIKCYYLojiwOOs1d02iEJgNiEugjZ0ClBhVL08LUJEMcFwQRQHbmdQ0zKDCTCY4jeA+iAjNirTaVGdXBYhophguCCKA09QuFCMcWxaBtTPXAgwNm67rrpQVuuO7ziIqFNguCCKA59bv+cCpjiHC0EATFZYTYbAJUnRwkWd2xffsRBRh8dwQRQHXpd+5iKu+y38JBvMJjHQX8R/YmRfub2ZJxERtRzDBVEcKO6gD/B4nhTxM6VAFITA7IW/1sW+CoYLIoouhguiOJDd+o6oohTnZREgEGisUn24qK8YypkLIoo2hguiOFA8Qe3WzXEsoOVn0o6j2iQjgIZlkaJyR5NPISJqDYYLojhQvcHhIhF7LvzhQr8sUuXwoMrhafJpREQtxXBBFAdC0MyF0RzHpmV+9csiZqMIg9iwLAIA+yo4e0FE0cNwQRQPQe3WTZYEhIv6ZRFBEGA1GWFWGsbEfRdEFE0MF0QxJisqDEHhQrImYM9FoxMqNsmgm7koYrggoihiuCCKMadXhqTqK2FK1kQsizS8p1UyQNIti9ihqmr8x0REHRLDBVGMOdy+kHBhTsTMhakhXNgkQ2BDJwDUuXyosHNTJxFFB8MFUYw5PDKkRh/kggCYLIldFpGMIlIEfeDhvgsiihaGC6IY02YuGmYFDIIAId69RQBdyXEBAjKNXqDRUgj3XRBRtDBcEMWY21kLoOFD3CAKuv0PcSPpZ0tSJAFG1Ru4zTLgRBQtDBdEMeYKarduEIX4d0UFQvqZ2CQjLGqj46gVDm7qJKKoYLggijG3Q99u3SAKgDFRyyJC4KY16DiqyyPjaI07zBOJiFqG4YIoxnxufbhQjWZATMA/PUE/YyIZRGRLXt1D9pbXBT+LiKjFGC6IYszrCiqtbUxAXxG/oKWRgnT93ftZBpyIooDhgijGfK6gjZKmBIYLk34jac+gE7E8jkpE0cBwQRRjslv/gS0koiOqX9DMRQ+rrLu9v8IBWeGmTiJqG4YLohiTgzqiilIiw4V+5qJrULjwygqOVOn7oBARtRTDBVGMqSHhIgE1LvyClkWscCM7VdJdY70LImorhguiGAsOF8aELosEBRuPAwU5+mvcd0FEbcVwQRRr3qBwYUngzEVwuPDaUZitv1ZUzhMjRNQ2DBdEMSQrKkSfS3fNZE1L0GgQelLFXRcyc3HomANeWYnjoIioozEmegBEHZnTK+uqYAKAlMhlEWum/nbVAfTJ0lcLlRUVh445UZiTwBkWah/KdgI/zwMMZuCEa4CMnokeESUJzlwQxZDD44MUHC5sCWi37pczSH/bUwebsxhdMyy6y9x3QcdVWwIsfQw4+gtwZAPwwwu6LrvUuTFcEMWQ0yNDUhr6dQgCYErknouUbCAlR3+tdDv6Bs1S7GW4oOaoKrD6FUD2NFyrOgBU7EncmCipMFwQxZDDo18WMQgChERW6ASAvKH626Vb0SdoU+d+Hkel5uxcBJRuC71+cFX8x0JJieGCKIa0ZZGGmQuDKISe2Ii3vCH626XbUJit33dxpMoJl1dfYIsIgLYcsvG98Pcd+JFLIwSA4YIophwuNwyqL3DbIOo7kyZEblC4cFWhl1QDQWhox66qwMFKHkmlIKoKrJoDyFo3XZ+iorTGhbJat1Y23l4OVO5N8CApGTBcEMWQ26lfXkiKcJHWDbB20V0yV+5Ej0z9ps4i7rugYDu+Asq2A9BKxe86Wosj1S4crnJie0kNqpxe4ODqBA+SkgHDBVEMeZ11uttauEjwngtBAHIH66+Vbgupd8FwQTo1xcCm9wFox5X3lttRpmbgZ+t4AIBXVrGv3I4tq75BZZ27uVeiToDhgiiGPEHt1kXRABikJh4dR2E2dYaUAa/gsgjVU1VgtbYcoqgq9lXY4fTI+F/6r7DNeoLuob7qYjz/yWIs2XYUCjvsdloMF0Qx5HPpZy5Uk02bOUi0vKCZC3s5+tn09ThKa1xweHwgwo6FQNkOqNAKrNW6fPjZdjIOS31RauyBWkOm7uG9637G+6sP4KmvtnHvTifFcEEUQz6X/gerkOj9Fn4ZvQBJX8yrh6dIW7ZphEsjpC2HfAAAKKl2odLuQY2hC35IORcAkGo1IWvwGTA2+m+nv2sLoKrYW2bHX7/Yiv+sPwSPjyXlOxOGC6IYkt36D2dBSvB+C78w+y4M5TvQK0s/vv1cGuncFAVY9TIge1Fe58bRGm0vxf/SL4NPlGAyiLhj0gAMO/k8DO6ejqwUbckvU65Atu9o/UuoWLi5GI98voVhtRNhuCCKIdUTtOci0TUuGut6/H0X/DDo5HZ+BZTvRLXTi8PHnACATbaTcVgqhCAAt0zsh365qUB2PxhTc9E7y4Z+uakwG0UMcG/RvVRpjRvPLd6JGpc3EX8TijM2LiOKIcWj/83fkMimZcGCT4zUFqN/XxnLGl1iuOignMeA0u2A4tM2GBtM9f/b6GuPHdj0AexuH/ZX2KECqDZkYWX9csi1J/fB6F6Z2usJAtB7PLD9S6RZjBjULQ0W716sEYDGezrtbh8WbS7Br0/sFfe/MsUXwwVRLHmdupvGRPYVCdalADBagEYt4fvhAICGMR6ze1Dt9CLDaor/+Cg2qg8Dix/SwsNxuLwyisrtgYCwJP1X8IkSLh6Vj4mD8vQP7nUysP1LAIAoCCiUavDXU9Px/zbLukZ4S7eX4txhXZFpS4JTUxQzXBYhihFZUSF49TMXRnMShQvREDJ7kePYC8mo/7HADqkdzIa3IwoWXlnB3nI7fPXJwr8ccmr/HFw6Oj/0CTkDAFu27lL36k34/Zl9ddVfvbKChZtL2vZ3oKTHcEEUI06vHNJuPaEdUcMJOpIqlm1D72z90s0+NjHrOMp3AcUbj/swr6xgb5k9cMLDvxwyvEcGrp/QRxcWAgQB6HWS/tqBVchLs+C0/vrQsXxnKSrtHlDHxXBBFCNa0zL9D1CTNbWJRydIcDGtqoMYkKG/tK+cJ0Y6jM2f6G8bJCCtuzbjYE4HjGbYvQp2Hq2Fs75xXY2hC77MuBo9crvg1on9YDQ087HRe4L+ds1hoPoQLhqVrzvm7JNVfLm5OFp/K0pC3HNBFCOVdg/MSsPMhSAk4cxFVj9tA5/s38GvYrCxGF8hLfCQPWV1kBU1pAZGxOrKgLoSrWGagT9yEibcrMXIXwNDLg7cXFNUibnfF8GX7YVR9cEAGS7Bitx0C+6cPAAWk6H598gZqPWtcR5ruHZgFXJGXIHTB+Zi2fbSwOUVO8twwfBuyEk1R+EvR8mGMxdEMfLzwWrdsojFaICQ6L4iwQxG7QOhkT6+/brbdrcPW4/UtO71D28AvrgLWPo48NW9gL2ilQOlSO0tq8MPu8tRVhvU3yN41sKcDvQ/BwCgqioW/HQYry7fA6+sQBUM8IpmuEQb8jIsmHnOwMg29QoC0Gu8/tqBVQCAKSO6w2hoCKiyouLLnxvNXnhdQM0RrbYGtXv8NYIoBlRVxU8Hj+FCteEHfLrVmPimZeHkDgGO/hK4mVa7GwU543UbOX/YU44RPTPCPbtpshdY82/tuCOgfXB8+wRwzqOAOa3551KrrNxdjte/LwKgfc6P6JGJswfnYbj5KITgWYuhlwAmC1xeGXN/KML6fcdCXm9w9zTcOrE/Us0t+KjoNR7YuajhdvVBoPowsjJ64MyBeViy7Wjgru93l+OCEd2Qd2wTsOY1wFMH2HKA4ZcBhWdypqsd48wFUQwUV7tQWuOG1ChcZFhNiW+3Hk7eEP3tyr04vUC/fPPTgWMt7zOydxngrNRfqzkMLH8a8LFrZrTVuLx4f82BwG1VBX4+VIXn/7cTSz5+GWW17sDJD/+sRaXdg799tT1ssJg4KBd3Tx7YsmABaCeQLJn6awe12YsLR3SDqdGeDUVRsfF/HwLfP6cFCwBwlGtB48u7gb3LOZPRTjFcEMXAhgPHAFWFVL/nQjKIsEqG5AwXOQMAsdEHiKrgpLSKkA14a4oqwzy5CbIP+GVB+PvKd2kfJjKbokXTf9YfgtMjh1zv6j2InNptOFzlxNYj1ThY6UB57/Owp8qHx7/YGtJYTBAEXD2+N649uU/zmzebIopArxP11w6sBgBk2iScPbi+PoaqYkLdYnTd+T7cvjD/LdSVaqXHv5wJ7PtBS0vUbjBcEMXAxgNVMKpeCNB+IKZbjRAgAMlU/tvPaAay+uou2ap2YpS/+mK9H/e0YL/Evu+030CbcuQnYM2r/MCIkj1ldfh+V/jv9/i6pYGvFRU45DThL5u746mF21Ht1JfitkoG3H3OAEwa0jX8cdNIBZ8aqdqvNUADcP6IbrAYVEyu+RTj7MuhAiipbmYmq7YYWPlPYOG9WkjhfzPtAsMFUZRVOTwoKrfD3GgzZ2AzXDLOXAChSyOl23BKP31tgt2ldThao6/bEZYiA7/M11/L7B0arIq+Aza+14rBdkBep/bb+eH1LV4GUBQV7606oLtmNom48sReGGUtRR/PLt19622nwydKUIM+pPPSLXhwylAMy2/h3ppwcodoSy+N1S+NpBtk3GaYjyGunwJ3VTk8cHllYOB5QHb/8K9ZfRD4/llg0Z+B4p/bPkaKKYYLoij76WAVAAROihhEASn+dWtjOwkXFbsxopsVqRb9evvKPc3MRvjt+16b0m5s9DXAmfdpx14b2/Zf7U9npapA0Qrgv3dpv50v/zuw7vUWvcSK3eXYH1To7JJRPXDusG74Y94m9M9LRabNBAGAU0zBZutJIa8xND8dD04Zgm4Zljb8ZRoRxbAFteCqBpY+hoHKHjRecVEh4H/pU4FxvwHOfRw4809aefpwju0Dvn1S+75R0mK4IIqyjQeqAAA59S2n0y1GiIKg9fFI1t3vOQMBNJoGV3wwHtuL8YX62YuVuytCfuPVUZTQWYvs/kD3UUDuIOC0uwEh6MfOT+9qsxidTdUBYMmjwI8vAa6qhuu7/6ftS4lAnduH/6w/pLvWLcOCyUPygPJdEIo3IdVsREF2Cobkp0MceilSUvQzSGcNzsOdkwY0BOBo6X2y/vaxfcDXDwAVu2EUhUB9C1kw4ovMazC/epC2/0MQgB5jgfP/Bpw2E8gI1+RM1ZbVKvdGd8wUNQwXRFHk9MjYVqzVhCh0bwcApPuXRIK7kCYTKSX0N8XSrTg1qGxzpd2D7SW1Tb/OgR+1NfLGhl+mfWAA2ofG+N+HPm/VK9o+jM7A49D6e3x1H1C6LfxjNr4X0d6C+T8dht2t3wx59fje2kbMoLoWki0T48+7Cn+/YiRumdgPF4zojpnnDmz9xs3jyRsaeuTY3jDzlZtmgc9ow6eZv0GRWfu38fmmIw2P9XdavfAZ4JQ7tEqijcle4LvZgKuVNVgophguiKJoy5FqrWGZKqPAsxOCAKRb6sNFj7GJHdzxBC+NlG1H7ywbenTRL+WsbGpjp6oCW/6jv9alEMgfo7/WdyIw+mrdJUXxwbX0H7Af2dqKgbcTqqrtq/hyptY9VG1mb0XptuP2ADlQ4cDyHfrlpzF9umh7JsJV4xx6KWA0w2gQcWJBFq4Y2zM6+yuaIhqAnqFLMH7G1FxUnvoQSqTegWsb9h/DgYqgcvOCABScCkyZDfSfrL/PUQ788Ly2z4eSCsMFURRt2K/VC8j3HoBZcSLVbGw40tljTDPPTALBfUbKdkBQZJzSL0d3ef3+Sm3zXbCDq7U6Fo0Nv7xh1qKxIZcAg6cAADw+BTuO1mL74XLseudurHnhavz49kPYsOhN7Nm8Co666rb8rVrtyK6N2L5iPqory9r+YtWHgKWPafsqnKE1JZCSo5XNbmzj+01u7lRVFe+t3q+b3DAZtE2cAMJX4xxwThv+Aq0UvDTil9kbOPcxnDZmJGxByzEfrTuI8rowp0dEAzD2xpCKsjj6i/a9oqSSpAvARO2PT1aw+bD2QehfEgmcEsnso32AJLPcQfrbsgc4VoST+/bBJ+sPBj7I3F4FG/Yfwyn9G/19ws1aZPYGeo4L/16CAJxwHVRXNQ6sWQS3t+FDVHJVAMUVQPEa1G4CagF4rLlQuvSFlDcAvYadjNyeA9r+923GhoVzYdj8IVQAB9a9iX5TZsI28MyWv5DsBTZ/DGz7AlDDBDLRqM0oDL1U2/C46uWG+6oOAPu/BwrPCHnaj3srsLu0Tndtysju2j6GZmYt4i5vqBZs3DX6a2fcA0gpsAE4b1hXzN/QEEq3Fdfgvk9+Ro8uVozsmYnRvTLQNycVoihoe5ZOnwksul8f0rZ/oR2nLjg1fn83ahZnLoiiZMfR2kARo0L3DgCNwkVTH7LJxJIOZPTUXyvdikybFDJ9/kPwqZHD67UPw8aGXRZ+1sJPEPBtxmX4RS087tAkZxksR1ZD3PguDr//R6xa/HHzG0vbYPN38yHWBwsAkD0u1Cx5Flj9GuBrQZvwyiLtQ3DrZ+GDRffRwIX/0JqHGc1Awemhmxd//rBRUzmN0yPj43X6TZy5aWacN6xb/V8gSWYtAC0MnHyL9vcTDEC/s4GzHtAdS548pGvIqSQAOHzMia82F+Ophdtx14cb8f9W7MXafZVwGNKA0/9PX/gNAFbP0TaNUlJguCCKkp/qT4lk+sqRKZfDJhkaSh0n+34Lv5B6F9oMzKn99bMuO0pqUeGfug43a5Heo+kp8XpltW58srEECzOmY5PtZMhChBOpqgrzhrn4/H9LICvRDRg7NyyHb9VrIdcr7G4ou/+nnXaoPhTmmY0oMrDlU+CbB4Hqg/DKCirtHtg9PqhQtd4Zp98DTPwzkN5ok6IoAqOn61/LXg7s+kZ36fNNh1ETVPxq+km9IRnF5Jq18OsxFrh8LvCrV7TNvEHHkS0mA351Qo9mX8Lu9uHHPRV4Zdke3DlvI55eJ2N19qVweHwNIVP2At/9A3A3s+GY4obhgigKVFXFxvr6FiGzFpbMkAqYSSs3dFMnFAWje2Vq5cvrqao2NQ9AO+URfCRwePOzFqqq4q2V++D2KvCJEr5Luwiv5D4E33l/g2HCLXAXToIrvQCqEL7FtwAFeRtfxutfrw2//6MVDuzciLolz0AIs9HSK6uocfm0Qk6L7td6XoRTUwwsflibcVB88CkqdpfW4UClAztKnViMU1B19lNaeexw35/8MaGnirZ8Cni0OhaHq5xYvFW/iXNkz0ytmqq9HPj+ef1zEzlr0ZjBqM2MNeHMgbm4+5yBmNAv+7hHYhVFxc6SWrx2uBCf1gzBL0dqsK/Cjoo6NzzVR4Ef/sl+JEmAey6IomB/hQPH7NqUeaEn6AhqjzHNLw8kk+CZC68DqNoPKasQJxVmYfmOhs2NK/dUYMrwbhCCZy3SugG9T2n2bVbsKg8c2fU7fXA3jBtdAOCEwDWf14PSg7tRfmAbvAfWw1i8PrBcYVXsKNw6B89678Rt5wyLrCV4E0oPF6H0v3+FUdHPCOw1D0Fvzx4YVQ8q6tzItJq0vSirXtY2Eo77DWCyaGlr1zfAT+/oljHKal1w+xSUG7vhm/QrUOHphs+/2I1fj+uF0wfkhJbYFgSt4NjihxqueeqAbf+FOvJKvL96v245yCAKmH5SL8BRCSz5a2jJ9UTPWkRIEAQM75GB4T0yoCgq9pbXYePBavx8qAqHjzmbfN53aVOQ6ytBV8dBVDm8AJwwl3+PY8deQtczfoN+uanx+0uQDmcuiKLAP2thVpzI9+yD2SjCYmpnSyIAYMsCUrvqr5VpYSm4HPjRahcObV8DVOzWP37Yr7Qp/iZU2j34cN1B3bUuKRKuGNsz5LFGk4T8vkMxcuLlGHvt48gdOB6N+qkh13cE/YvexZNfbEVJdQSlycOorjiKfR8/AKNPX+XySJcT8WXG1ZiXdSsqjF1R6/LB7Ws0S1K0XFsmKf5ZayW/bq4uWMiKirI6L9alnIkPs25FhUnbE+H0yHhr5T7845sdKK0NM+bcgUBPfeMvzy//xWc//oLtxfop//OHd0Oe5NHev+6o7j5k9QUGnNuK70hiiaKA/nlpuGJsT/z10uF4+oqRuObk3hjeIwNGgz6MyYIRX2ZMh0NsCBFurwLb7i/x0X8+wpc/Fwe/PMUJwwVRFPx0QNu53sezEwJUZFhNWqMygwnoNiLBo2uh4COpmz8Blj2NfocWYIKwGV29h2BS3ICqonrNB/rHpuQCfU5r8qVVVcXbP+6DK6h754wJBbBJx5lIFUXkT7kPfQr6wdgoYQx0bUbv0iV4cuE27C5t2Xq7016L7fMegOTWd3x15ozAWdc/BJvFhGPGXHyYdQu2WE9ERV3Qhs6aw9oHe8nmkNc+LGfgw4yb8WPqOVDCLO9sL67Fwwt+wTe/lEAJ3jsy6iooKnDM4cGesjpsO1iOunXzdA/pkiLhwkHpWins4H0g6T2AifcDRinyb0aSykk14+zBXXH3OQPxwlUn4I5JWmM1f6lyuyEdCzOmQw36ODunZj6Wr1mPlbsjKFlPUcdlEaI2Kqt141D91G1IVc6uI9rFtLRO3mBg77cNtz11wJENEI5swEVOV2CGwC6mQUUdlPx0rbw5oM1aNFPi/Me9Fdh8SF+34pT+ORjRM8JiTlIKMs77C6Qv/4yi4nJ4fNra+ql136DC2BX/+FrBb8/oi7F9uhznhbQll43vPwRrnf6D2ZVegBOufhQWixmn9svG4q1HIQsmfJt+KSqV/rjdsBSi3EwXTwC+fufipb3DUaE2fOClW00hGzG9soIP1x7EmqJK3HBqAXpkWrG33I4fdvtgrRqAAXVrA48d5lyHn2ynosqoba696oQ8WH54BjhWpH/z1K7A2Q82u8ehvbKYDBjVKzPQsbfS7sEvR6rxy5EsrN55CU6uXBB4rFH14Lzqj/D2D9nokiJhSPeO9/1IZpy5IGoj/6yFqMoocO+CURSQ4t/82J6WRPy6jgg95lcvy9bwm3CKUgtZURs+MG05QGHTtSCqHV58sEa/HJJhNTUUfopURg9Yz7wLA/LSYAtsMlVxfvVHSHGXYs6y3fj6lxLUuLxNHldVFQXr5j0Oa6W+/LbHmouh05+ExaodlZw4KE93/yZxGDYO+3PTTbVs2cBZf8H3mRejwq3/8XrHpAG4a/JAdEkJnU0oKrfjr//digfmb8GTX27D8h1lWGGZqDtBI0DFBPv/AADnD8nC2H3/Bsp3Br1/DjDpYW15qxPISpFw+oBc3HJmP/zuN79Hr3EXIjetIcxn+45ifM1i/Ovb3ThS1fTeDYo+zlwQtZG/C2q+dz8k1YV0m9SwUS/Zq3KGk5INjJmh9bfw6fcESEYRqWYj6hr1s6i0e5Fpk7TNg03MWqiqindX74cjqA/GdRP6ILU1DbN6jIVpzHT0++kD7K+wo8blg6S6cFH1u/ioy+/x0dqD+GjtQRgNArJSpPo/ZmTXf23c9A5sR1brXtJnSkXfK55AembD3pJuGRYM7p6m2+uw+JCIMec8Bmx8F9j5dcMLFJwOjLsRitGGr3/UL5MM6Z6OwhwtsDw+dTg+WX8I327Xn/qQFRWljVra2w0Z2Gg7BWPtWlM3gyhgvGEnTjzZgD4lnwClv+i/J5ZMYNJDyV+sLUZEg4jsM28FPEeAom0oq9Vml05wrESReTCe/58Bf7lwKDJsrd/4S5FjuCBqgzq3D7uOah88IVU5uxS2398gB56r9QCpOayt59ccBqoOAjWHkGU/qAsXtS4v3Gm9YO47scmXW7f/WKA0ut9JhVk4offxly+aNHQqDMf2o1BYiUPHnKiwe9DFV47zaj7BFxnXQBVE+GQVpdUuyJUHYPTsR6r3AATvPtjkKt1LKQYJ3S6ZhZz8PiFvM3FQni5c7CypxZE6GfnjfqMFipLNQNdhgQqn6/dVorRGv2xywYhuga8tJgOuPbkPTirMwpsr9+FoMxtRN6ScjlOxEXlmHzJsJhgEAdj0bEhhLUip2lJIWrfwL9RZGCVgwm3Ir/4zPD4F1U4vABXn1PwH7xtvxwtLduFP5w+CxRT+iDNFD8MFURv8fLBKK4utqih0b4cooKHaYHtcEmnMKAFZhdqfRmwuJz7+YCnS3SXo4iuDS7TiaI8LcY7BhHAHbmtdXry3ar/uWqrFiOnje4d5dAsIAjD+Fgi1xegpFMFkFFFS7UKBewfOrP0CdYYMdPceQL5Hm1FqiiqISD/nPvTsH37j7Qm9MpFmMaLW1RColu0ow9XjewM5A7Q//tdSVSzcrD+h0DvbhqFh1vsHdk3DrIuH4fNNR7BoS4luCScv3YxT+uXglH7ZyD5Qpc0i+QUHC5MVOPsvQGYLl5c6qszeEEZNR+8N72BvaR3sHhlpchXOqP0S/xMvx2vf7cXtZ/XXyolTzDBcELWBf0mki1yODLkSadb63y6B9rkkEgGLxYrC/kPw456G/Qibfq7CJ1vWI9NmQhebhC4pErJsEjJtJmwrrtV9MAPANeP7NHSLbQuTBTj9Hghf349u6bWwmEQcrXZjpHMNIq3daTr1D+g/qukTLkaDiNMH5OpCw8o95bh8bA+YjfrfgLcW14R09bxwRPfQehb1JKOIK8b2xEkFWVi+sxRGg4ixfbpgQF5qw3MGng/sXAQ4wnSjNZq1UyHtpUhbvAy+CIbD61Gg/ILdpXVw+xQMcf2EveYh2HRwKD5YewBXn9S7yf9fqO0YLohayeNTsKWpRmXWLh36B/4p/XLwY1DrdVlRUVHnCT2uGWRMny44saANyyHBUnOB02YCSx9HplVCplWCqqrwKiq8PgUeWYFXVuD1qfDICjw+7bbbmAbppBsw/NQpx32LMwbm4qstxYHmbU6PjLVFx3DaAP3+huBZi7x0M8ZGsPTTO9uG6yYUhL/TKAEjpgGrX9FfF43AGX8KbThH2qzWybfBtPAeFOao2FVaB1lRMal2AYpNvbF0G5Cbasa5wzr5MlIMMVwQtdLW4prAUchC93YIANIbL4l04N+KhnRPQ166RbcBMRI2sxHXjI/Bb4xdhwJjbwDWvQ5Aq/goGQRIBhGBFlkpOUDOIK28du4grWtrhOPITTNjWH5GIEwCwLIdpbpwsbesLkyRq+7RmX4vPBPY8RVQVb+8JNZ3B+02vO2v3VGl5gLjboRl1RwU5qRgT1kdLIoDk2vn478Z1+KjdQeRnSphbJ92ui8qyTFcELWS/wiqRXEg33sAKWYjjIFGZR1zScRPEATcemY/vLt6P/aW2SPuUDr9xF7ayZJYGHAO4KkFfv5Yu92lD5AzsD5MDNZOwbTBxEG5unBRVG7H/go7+mRr8eWrLSW6x2fYTCFVTVtNFLVuoj+9q/UZGTaVMxaRKDwTOLQOqYfWoneWDfsrHChw78Aw13r8Yh2Hf39XhIzzJPTPY5nwaGO4IGoFRVGxqX6/RR/3TqC+KicArSpn13ZWlbMVemfb8MCFQ6AoKmpcXhxzeFFp9+CY3YNjDu1Ppd2LY3YPRFFrTjUhWh+24QgCMPxyYMglgKpEvXjZyJ6ZyLRJqHI0LPss31mG6yekoLjaGQibfucO7drQFTcarJnAKbdH7/U6A0EATvotUL4TXVANj09BcbULZ9QuxEFTX9QgC88u3oHbzuqPYfkRFnKjiDBcELXCN1tLApsU+wYaldX/c+o2qkOUXY6UKArItEnItEmBWg4JZYhNHQODKOCMgTn4fOORwLVVeyswbWyv+tMeDY+1SgacOTAvzKtQ3FkytFbvy/+OvHQzPD4FFXYPzq35BP/pcjPcXuCF/+3Czaf3xUmFXCKJFlboJGoBVVXx6YZD+HidVjJaVGX0du+C1WRoODnQwZdEOrMzBuTq9ou4vQq+2lIcsrn17MF5uhb1lGA9xgL9zoYAAT26WJFuMaK79wDGOL4HoG1Gfu27Pfjf1qPHeSGKFMMFUYS0KpMHdJ0W8737IKluXclh5J8Q5tnUEXRJkTC6l376/MufiyE3ajxmMoiYNKRr8FMp0cZcD6TmQRQEFOSkINNmwsn2JcjzHgYAqCrwwZoD+HTDoYj3EFHTGC6IIuCTFbz23V4sCyrZ3Ne9Hd0zLMjy94vI6td+q3JSRIL7jQQ7dUBOw/4bSh4mKzDhdgACREFAn2wb8lIMuOLYv3FS3VIYVK042Zc/F+PNlft0gZFajuGC6DjcPhkvfbsba4r0bbkFqDg38xC6plsaLnJJpMMblp+OnNTwm0UFAThvGGctklbuIGDoJQAQWCLpmW7EePtSXFvxTxTU16v5flc5Xv52d+CoObUcwwVRMxweH55dvDOkTbhBFPDHcVZ0N+jrGrT7kt90XIIg4MxBuWHvO7EgC3lplrD3UZIY8Wsguz8ALWB0TbegVxcrMuRjuLjqXVxU9S7S5WPYeLAKsxfvgD2o2R5FhqdFiJpQ7fTiucU7cbBSX85ZMoq47az+GF71rf4JtuymW3FTh3LagBws+OlwyNT5hSO6J2hEFDGDUWvy9vOHwI5FAFRkp5phNIjYX2FHoXs7ent2Y53tDKxXT8fTi7bjpMIsiPUbebWaaAIEARCghU2jKCA7VUJemgXZqVJ0jyC3Ux0mXJQf2Q9fcEMfolZyeWXMW3MAdXUeNC7ebJWMuGlCAQpSa4Eta/VP6jGmQ1flpAbpFhPG9umiWyob3iMDvbJsCRwVRcxk1Sq69j1Lq+patgMZVhP65qaiqNwOKD6Mty/FENdP+N59AZaVRd7GXhCATKsJ2alm7U+KhOxUCdkpUkORvTjqkpsPsyX+/112mHCx5z8Pw+woOf4DiSJ0ftBtk0FA39xUWFc3ccSQSyKdyq9O6IHNh6vh9MiwSgZceSK7krY7XfoAkx8F9q0AfnoXqahG/9xU7C2vg1dWkS4fw4XV77f5bVQA5W0fbau4L3kSfYbE/2dThwkXRLFkNorom5sS0gUzwGgG8obFd1CUUHnpFvzt8pHYU1qHgpwUnhBprwQBKDxD++Vg88ew7liEAXlp2FNeB7eXGzpbi+GC6DisJgP65qY0v47a86ROVZWTNKlmI0b1ykz0MCgapJT6pZKJkNa+jgHiDpTWuOCuPzHSUPpCReOdNiq0dgAenwIfj68GMFwQNUEQtLX1Xlk2GJvqbCmIQNdhwJjr4js4IoqNLgXAOX+Fseg75G/7HKg+FPFTZUWF2yfD41Pg9ina/8oKPF4FXllBZ4oegpqAUmQ1NTXIyMhAdXU10tPTo/KaqsLpK4q+iFqDcxMnUccVpY/IRFb9FMTobSSN9PO7w8xcRPObR0REBCBqvzxE9ItKB8JPZCIiIooqhgsiIiKKKoYLIiIiiiqGCyIiIooqhgsiIiKKKoYLIiIiiiqGCyIiIooqhgsiIiKKKoYLIiIiiiqGCyIiIooqhgsiIiKKKoYLIiIiiqqENC7zd4erqalJxNsTERFRK/g/t4/X5TUh4aK2thYA0KtXr0S8PREREbVBbW0tMjIymrxfUBPQZF5RFBw5cgRpaWltakNbU1ODXr164eDBg832lafo4Pc7vvj9ji9+v+OL3+/4itb3W1VV1NbWIj8/H6LY9M6KhMxciKKInj17Ru310tPT+R9nHPH7HV/8fscXv9/xxe93fEXj+93cjIUfN3QSERFRVDFcEBERUVS163BhNpvxyCOPwGw2J3oonQK/3/HF73d88fsdX/x+x1e8v98J2dBJREREHVe7nrkgIiKi5MNwQURERFHFcEFERERRxXBBREREUdVuw8W//vUvFBQUwGKxYPz48VizZk2ih9Rhfffdd7j44ouRn58PQRCwYMGCRA+pw3rqqadw4oknIi0tDXl5eZg6dSp27NiR6GF1WHPmzMHIkSMDhYUmTJiAr776KtHD6jT+9re/QRAE3HXXXYkeSoc0a9YsCIKg+zN48OC4vHe7DBcffvghZs6ciUceeQQbNmzAqFGjcN5556G0tDTRQ+uQ7HY7Ro0ahX/961+JHkqHt3z5ctx2221YtWoVFi9eDK/Xi3PPPRd2uz3RQ+uQevbsib/97W9Yv3491q1bh7PPPhuXXnopfvnll0QPrcNbu3YtXn31VYwcOTLRQ+nQhg0bhuLi4sCf77//Pi7v2y6Poo4fPx4nnngiXnrpJQBar5JevXrhj3/8I/785z8neHQdmyAImD9/PqZOnZrooXQKZWVlyMvLw/Lly3HGGWckejidQlZWFp555hncdNNNiR5Kh1VXV4cxY8bg5ZdfxuOPP47Ro0fj+eefT/SwOpxZs2ZhwYIF2LhxY9zfu93NXHg8Hqxfvx6TJ08OXBNFEZMnT8aPP/6YwJERRV91dTUA7QOPYkuWZcybNw92ux0TJkxI9HA6tNtuuw1TpkzR/Ryn2Ni1axfy8/PRt29fXHPNNThw4EBc3jchjcvaory8HLIso2vXrrrrXbt2xfbt2xM0KqLoUxQFd911F0499VQMHz480cPpsDZv3owJEybA5XIhNTUV8+fPx9ChQxM9rA5r3rx52LBhA9auXZvooXR448ePx5tvvolBgwahuLgYjz76KE4//XRs2bIFaWlpMX3vdhcuiDqL2267DVu2bInbGmlnNWjQIGzcuBHV1dX45JNPMGPGDCxfvpwBIwYOHjyIO++8E4sXL4bFYkn0cDq8Cy64IPD1yJEjMX78ePTp0wcfffRRzJf92l24yMnJgcFgwNGjR3XXjx49im7duiVoVETRdfvtt+OLL77Ad999h549eyZ6OB2aJEno378/AGDs2LFYu3YtXnjhBbz66qsJHlnHs379epSWlmLMmDGBa7Is47vvvsNLL70Et9sNg8GQwBF2bJmZmRg4cCB2794d8/dqd3suJEnC2LFjsWTJksA1RVGwZMkSrpNSu6eqKm6//XbMnz8fS5cuRWFhYaKH1OkoigK3253oYXRIkyZNwubNm7Fx48bAn3HjxuGaa67Bxo0bGSxirK6uDnv27EH37t1j/l7tbuYCAGbOnIkZM2Zg3LhxOOmkk/D888/DbrfjxhtvTPTQOqS6ujpd0i0qKsLGjRuRlZWF3r17J3BkHc9tt92G999/H5999hnS0tJQUlICAMjIyIDVak3w6Dqe+++/HxdccAF69+6N2tpavP/++1i2bBm+/vrrRA+tQ0pLSwvZP5SSkoLs7GzuK4qBe+65BxdffDH69OmDI0eO4JFHHoHBYMD06dNj/t7tMlxceeWVKCsrw8MPP4ySkhKMHj0aixYtCtnkSdGxbt06nHXWWYHbM2fOBADMmDEDb775ZoJG1THNmTMHADBx4kTd9TfeeAM33HBD/AfUwZWWluL6669HcXExMjIyMHLkSHz99dc455xzEj00ojY7dOgQpk+fjoqKCuTm5uK0007DqlWrkJubG/P3bpd1LoiIiCh5tbs9F0RERJTcGC6IiIgoqhguiIiIKKoYLoiIiCiqGC6IiIgoqhguiIiIKKoYLoiIiCiqGC6IiIgoqhguiIiIKKoYLoiIiCiqGC6IqN159dVX0bNnT0yaNAmlpaWJHg4RBWFvESJqV2prazFo0CB8+umnmDdvHsxmM55++ulED4uIGuHMBRFFZOLEibjrrrtCvo6liooK5OXlYd++fYFrZrMZmZmZ6N+/P3r06IGsrKyQ51111VWYPXt2zMdHROG1y5brRBTeDTfcgLfeegsAYDQa0bNnT0ybNg1//etfYbFYovY+n376KUwmU9RerylPPPEELr30UhQUFASuSZKEG2+8EV27dkVWVhYOHToU8rwHH3wQZ5xxBm6++WZkZGTEfJxEpMeZC6IO5vzzz0dxcTH27t2L5557Dq+++ioeeeSRqL5HVlYW0tLSovqawRwOB15//XXcdNNNIfetXLkSf/zjH2G327Fz586Q+4cPH45+/frh3XffjekYiSg8hguiDsZsNqNbt27o1asXpk6dismTJ2Px4sWB+xctWoTTTjsNmZmZyM7OxkUXXYQ9e/boXsNut+P6669HamoqunfvHrLEELwsUlBQgOeff173mNGjR2PWrFmB25988glGjBgBq9WK7OxsTJ48GXa7vcm/x8KFC2E2m3HyySfrrpeVleHLL7/ErbfeiksuuQRvvPFG2OdffPHFmDdvXpOvT0Sxw3BB1IFt2bIFK1euhCRJgWt2ux0zZ87EunXrsGTJEoiiiF/96ldQFCXwmHvvvRfLly/HZ599hm+++QbLli3Dhg0bWj2O4uJiTJ8+Hb/5zW+wbds2LFu2DJdddhma20++YsUKjB07NuT6u+++i1GjRmHQoEG49tpr8d5778Hn84U87qSTTsKaNWvgdrtbPW4iah3uuSDqYL744gukpqbC5/PB7XZDFEW89NJLgfsvv/xy3ePnzp2L3NxcbN26FcOHD0ddXR1ef/11vPvuu5g0aRIA4K233kLPnj1bPabi4mL4fD5cdtll6NOnDwBgxIgRzT5n//79yM/PD7n+xhtvBJZKzj//fCiKgi+//BKXXnqp7nH5+fnweDwoKSkJvCcRxQdnLog6mLPOOgsbN27E6tWrMWPGDNx44426QLFr1y5Mnz4dffv2RXp6emCz5IEDBwAAe/bsgcfjwfjx4wPPycrKwqBBg1o9plGjRmHSpEkYMWIEpk2bhn//+984duxYs89xOp0hm1DXr1+PrVu3Yvr06QC0TatXXnll2KURq9UKQNu7QUTxxXBB1MGkpKSgf//+GDVqFObOnYvVq1fj9ddfD9x/8cUXo7KyEv/+97+xevVqrF69GgDg8Xha/Z6iKIYscXi93sDXBoMBixcvxldffYWhQ4fixRdfxKBBg1BUVNTka+bk5IQEkDfeeAOyLCM/Px9GoxFGoxFz5szBwoULUVZWpntsZWUlACA3N7fVfy8iah2GC6IOTBRFPPDAA3jwwQfhdDpRUVGBHTt24MEHH8SkSZMwZMiQkA/wfv36wWQyBUIHABw7dizsqQy/3NxcFBcXB27X1NSEBAdBEHDqqafi0UcfxU8//QRJkjB//vwmX/OEE07A1q1bA7fdbjfef/99zJ49Gxs3bgz82bRpEwoLC0NOhmzZsgU9e/ZETk5O898kIoo6hguiDm7atGkwGAz417/+hS5duiA7OxuvvfYadu/ejaVLl2LmzJm6x6empuKmm27Cvffei6VLl2LLli244YYbIIpN/7g4++yz8c4772DFihXYvHkzZsyYAYPBELh/9erVePLJJ7Fu3TocOHAAn376KcrKyjBkyJAmX/O8887DL7/8Egg/n332Gex2O2666SYMHz5c9+eKK64IWRpZsWIFzj333NZ8y4iojRguiDo4o9GI22+/HX//+9/hdDoxb948rF+/HsOHD8fdd9+NZ555JuQ5zzzzDE4//XRcfPHFmDx5Mk477bSwJzf87r//fpx55pm46KKLMGXKFEydOhX9+vUL3J+eno7vvvsOF154IQYOHIgHH3wQs2fPxgUXXNDka44YMQJjxozBRx99BEBbEpk8eXLYoliXX345Nm/ejPXr1wMAXC4XFixYgN/+9rcRf5+IKHrYW4SIktaXX36Je++9F1u2bGl25iTYnDlzMH/+fHzzzTcxHB0RNYVHUYkoaU2ZMgW7du3C4cOH0atXr4ifZzKZ8OKLL8ZwZETUHM5cEBERUVRxzwURERFFFcMFERERRRXDBREREUUVwwURERFFFcMFERERRRXDBREREUUVwwURERFFFcMFERERRRXDBREREUXV/wdBkFQ5ZCw3AQAAAABJRU5ErkJggg==","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}