From 043187722271392c0a37024f1733c385fa5701cc Mon Sep 17 00:00:00 2001 From: Killian Date: Wed, 13 Mar 2024 10:52:01 -0400 Subject: [PATCH] examples --- .gitignore | 1 + examples/doi-TBD/__init__.py | 0 ...meworks_second_paper.py => _frameworks.py} | 10 +- examples/doi-TBD/bcc_quaternary_system.ipynb | 653 ++++++++++++++++++ 4 files changed, 659 insertions(+), 5 deletions(-) create mode 100644 examples/doi-TBD/__init__.py rename examples/doi-TBD/{_frameworks_second_paper.py => _frameworks.py} (83%) create mode 100644 examples/doi-TBD/bcc_quaternary_system.ipynb diff --git a/.gitignore b/.gitignore index 0c2ac4e..d59f5b0 100644 --- a/.gitignore +++ b/.gitignore @@ -2,6 +2,7 @@ .ruff_cache examples/_frameworks_second_paper.py examples/doi-10.48550-arXiv.2311.01545/data +examples/doi-TBD/data #Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] diff --git a/examples/doi-TBD/__init__.py b/examples/doi-TBD/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/doi-TBD/_frameworks_second_paper.py b/examples/doi-TBD/_frameworks.py similarity index 83% rename from examples/doi-TBD/_frameworks_second_paper.py rename to examples/doi-TBD/_frameworks.py index 9945d29..7060405 100644 --- a/examples/doi-TBD/_frameworks_second_paper.py +++ b/examples/doi-TBD/_frameworks.py @@ -7,9 +7,9 @@ BaseSyntheticChemicalMotifIdentifier, ) -# Model used in LINK +# Model used in DOI-TBD -INPUT_GDOWN_LINK = '' # Folder with model weights, sample graphs etc. +INPUT_GDOWN_LINK = 'https://drive.google.com/drive/folders/1Eu2-3-UALS75t12I0DeTyrl7thzVd7y7?usp=sharing' # Folder with model weights, sample graphs etc. class SyntheticChemicalMotifIdentifier(BaseSyntheticChemicalMotifIdentifier): """Just a class that re use the framework above but that matches the parameters of the first paper. @@ -35,7 +35,7 @@ def import_model_config(self): "lmax": lmax, "net_number": number, "irreps_node_attr": "5x0e", - "model_load": f"/home/ksheriff/PAPERS/second_paper/02_1nn_synthetic/data/nets/net_{lmax}-{layers}-{outlength}_{number}.pt", #!!! + "model_load": f"data/inputs_doi-TBD/net.pt", "mul": 3, # 50 } self.model_config = model_config @@ -47,7 +47,7 @@ def __init__(self, **kwargs): def import_synthetic(self): """Import chemical shell synthetic dataset pandas dataframe""" self.df_synthetic = pd.read_pickle( - f"/home/ksheriff/PAPERS/second_paper/02_1nn_synthetic/data/output/df_{self.crystal_structure}.pkl" # !!! + f"data/inputs_doi-TBD/df_{self.crystal_structure}.pkl" ) def import_model_config(self): lmax, layers, outlength, number = 2, 2, 4, 0 # 2,2,4,0 @@ -63,7 +63,7 @@ def import_model_config(self): "lmax": lmax, "net_number": number, "irreps_node_attr": "5x0e", - "model_load": f"/home/ksheriff/PAPERS/second_paper/02_1nn_synthetic/data/nets/net_{lmax}-{layers}-{outlength}_{number}.pt", #!!! + "model_load": f"data/inputs_doi-TBD/net.pt", "mul": 3, # 50 } self.model_config = model_config \ No newline at end of file diff --git a/examples/doi-TBD/bcc_quaternary_system.ipynb b/examples/doi-TBD/bcc_quaternary_system.ipynb new file mode 100644 index 0000000..023d9e1 --- /dev/null +++ b/examples/doi-TBD/bcc_quaternary_system.ipynb @@ -0,0 +1,653 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# ChemicalMotifIdentifier\n", + "\n", + "**To reviewers:** As we are keeping these codes private untill acceptance of the work, the PyPi installation of the package will not work. Please follow the instructions below to install all packages and dependencies.\n", + "\n", + "This is a quick tutorial on:\n", + "1. Analytically obtaining a pattern inventory for a ternary system (CrCoNi) in the fcc crystal structure. \n", + "1. Obtaining the pattern inventory with ML and creating a physically constrained embedding space from which we can compute dissimilarities between motifs. \n", + "1. Computing dissimilarity between motifs in atomistic data." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "%%capture \n", + "! pip install gdown\n", + "\n", + "# Downling private packages\n", + "import gdown\n", + "\n", + "gdown.download_folder(\n", + " \"https://drive.google.com/drive/folders/1jqf5LNeN-SDBuXJinHIlZa54YKbkAk6y?usp=drive_link\",\n", + " output=\"./\",\n", + " quiet=True,\n", + ")\n", + "\n", + "\n", + "! cd _additional_packages/Polya && pip install -e . && cd .. \n", + "! cd _additional_packages/NshellFinder && pip install -e . && cd .. \n", + "! cd _additional_packages/Simplex && pip install -e . && cd .. \n", + "\n", + "# # Installing chemicalmotifidentifier\n", + "! cd .. && pip install -e . \n", + "\n", + "! pip install rich" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "%%capture\n", + "from polya import Polya\n", + "from rich import print\n", + "from sympy import init_printing, symbols # For latex formatting\n", + "import numpy as np\n", + "import pandas as pd\n", + "import os\n", + "import matplotlib.pyplot as plt\n", + "\n", + "%matplotlib inline\n", + "\n", + "from _frameworks import INPUT_GDOWN_LINK\n", + "\n", + "# Downloading neceassry inputs (model weights, dump files, ...)\n", + "import gdown\n", + "\n", + "os.makedirs(\"data/\", exist_ok=True)\n", + "gdown.download_folder(INPUT_GDOWN_LINK, output=\"data/\", quiet=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Ternary system pattern inventory" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
The pattern inventory for the fcc first coordination polyhedron of the CrCoNi system is given by: \n",
+       "\n",
+       "
\n" + ], + "text/plain": [ + "The pattern inventory for the fcc first coordination polyhedron of the CrCoNi system is given by: \n", + "\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/latex": [ + "$\\displaystyle Co^{12} + Co^{11} Cr + Co^{11} Ni + 4 Co^{10} Cr^{2} + 4 Co^{10} Cr Ni + 4 Co^{10} Ni^{2} + 9 Co^{9} Cr^{3} + 18 Co^{9} Cr^{2} Ni + 18 Co^{9} Cr Ni^{2} + 9 Co^{9} Ni^{3} + 18 Co^{8} Cr^{4} + 47 Co^{8} Cr^{3} Ni + 76 Co^{8} Cr^{2} Ni^{2} + 47 Co^{8} Cr Ni^{3} + 18 Co^{8} Ni^{4} + 24 Co^{7} Cr^{5} + 92 Co^{7} Cr^{4} Ni + 182 Co^{7} Cr^{3} Ni^{2} + 182 Co^{7} Cr^{2} Ni^{3} + 92 Co^{7} Cr Ni^{4} + 24 Co^{7} Ni^{5} + 30 Co^{6} Cr^{6} + 126 Co^{6} Cr^{5} Ni + 318 Co^{6} Cr^{4} Ni^{2} + 408 Co^{6} Cr^{3} Ni^{3} + 318 Co^{6} Cr^{2} Ni^{4} + 126 Co^{6} Cr Ni^{5} + 30 Co^{6} Ni^{6} + 24 Co^{5} Cr^{7} + 126 Co^{5} Cr^{6} Ni + 372 Co^{5} Cr^{5} Ni^{2} + 606 Co^{5} Cr^{4} Ni^{3} + 606 Co^{5} Cr^{3} Ni^{4} + 372 Co^{5} Cr^{2} Ni^{5} + 126 Co^{5} Cr Ni^{6} + 24 Co^{5} Ni^{7} + 18 Co^{4} Cr^{8} + 92 Co^{4} Cr^{7} Ni + 318 Co^{4} Cr^{6} Ni^{2} + 606 Co^{4} Cr^{5} Ni^{3} + 768 Co^{4} Cr^{4} Ni^{4} + 606 Co^{4} Cr^{3} Ni^{5} + 318 Co^{4} Cr^{2} Ni^{6} + 92 Co^{4} Cr Ni^{7} + 18 Co^{4} Ni^{8} + 9 Co^{3} Cr^{9} + 47 Co^{3} Cr^{8} Ni + 182 Co^{3} Cr^{7} Ni^{2} + 408 Co^{3} Cr^{6} Ni^{3} + 606 Co^{3} Cr^{5} Ni^{4} + 606 Co^{3} Cr^{4} Ni^{5} + 408 Co^{3} Cr^{3} Ni^{6} + 182 Co^{3} Cr^{2} Ni^{7} + 47 Co^{3} Cr Ni^{8} + 9 Co^{3} Ni^{9} + 4 Co^{2} Cr^{10} + 18 Co^{2} Cr^{9} Ni + 76 Co^{2} Cr^{8} Ni^{2} + 182 Co^{2} Cr^{7} Ni^{3} + 318 Co^{2} Cr^{6} Ni^{4} + 372 Co^{2} Cr^{5} Ni^{5} + 318 Co^{2} Cr^{4} Ni^{6} + 182 Co^{2} Cr^{3} Ni^{7} + 76 Co^{2} Cr^{2} Ni^{8} + 18 Co^{2} Cr Ni^{9} + 4 Co^{2} Ni^{10} + Co Cr^{11} + 4 Co Cr^{10} Ni + 18 Co Cr^{9} Ni^{2} + 47 Co Cr^{8} Ni^{3} + 92 Co Cr^{7} Ni^{4} + 126 Co Cr^{6} Ni^{5} + 126 Co Cr^{5} Ni^{6} + 92 Co Cr^{4} Ni^{7} + 47 Co Cr^{3} Ni^{8} + 18 Co Cr^{2} Ni^{9} + 4 Co Cr Ni^{10} + Co Ni^{11} + Cr^{12} + Cr^{11} Ni + 4 Cr^{10} Ni^{2} + 9 Cr^{9} Ni^{3} + 18 Cr^{8} Ni^{4} + 24 Cr^{7} Ni^{5} + 30 Cr^{6} Ni^{6} + 24 Cr^{5} Ni^{7} + 18 Cr^{4} Ni^{8} + 9 Cr^{3} Ni^{9} + 4 Cr^{2} Ni^{10} + Cr Ni^{11} + Ni^{12}$" + ], + "text/plain": [ + " 12 11 11 10 2 10 10 2 9 3 \n", + "Co + Co â‹…Cr + Co â‹…Ni + 4â‹…Co â‹…Cr + 4â‹…Co â‹…Crâ‹…Ni + 4â‹…Co â‹…Ni + 9â‹…Co â‹…Cr \n", + "\n", + " 9 2 9 2 9 3 8 4 8 3 \n", + "+ 18â‹…Co â‹…Cr â‹…Ni + 18â‹…Co â‹…Crâ‹…Ni + 9â‹…Co â‹…Ni + 18â‹…Co â‹…Cr + 47â‹…Co â‹…Cr â‹…Ni + 76â‹…\n", + "\n", + " 8 2 2 8 3 8 4 7 5 7 4 \n", + "Co â‹…Cr â‹…Ni + 47â‹…Co â‹…Crâ‹…Ni + 18â‹…Co â‹…Ni + 24â‹…Co â‹…Cr + 92â‹…Co â‹…Cr â‹…Ni + 182â‹…Co\n", + "\n", + "7 3 2 7 2 3 7 4 7 5 6 6 \n", + " â‹…Cr â‹…Ni + 182â‹…Co â‹…Cr â‹…Ni + 92â‹…Co â‹…Crâ‹…Ni + 24â‹…Co â‹…Ni + 30â‹…Co â‹…Cr + 126â‹…Co\n", + "\n", + "6 5 6 4 2 6 3 3 6 2 4 6 \n", + " â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 408â‹…Co â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 126â‹…Co â‹…Crâ‹…Ni\n", + "\n", + "5 6 6 5 7 5 6 5 5 2 5 4 \n", + " + 30â‹…Co â‹…Ni + 24â‹…Co â‹…Cr + 126â‹…Co â‹…Cr â‹…Ni + 372â‹…Co â‹…Cr â‹…Ni + 606â‹…Co â‹…Cr â‹…N\n", + "\n", + " 3 5 3 4 5 2 5 5 6 5 7 4 \n", + "i + 606â‹…Co â‹…Cr â‹…Ni + 372â‹…Co â‹…Cr â‹…Ni + 126â‹…Co â‹…Crâ‹…Ni + 24â‹…Co â‹…Ni + 18â‹…Co â‹…\n", + "\n", + " 8 4 7 4 6 2 4 5 3 4 4 4 \n", + "Cr + 92â‹…Co â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 606â‹…Co â‹…Cr â‹…Ni + 768â‹…Co â‹…Cr â‹…Ni + 60\n", + "\n", + " 4 3 5 4 2 6 4 7 4 8 3 9 \n", + "6â‹…Co â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 92â‹…Co â‹…Crâ‹…Ni + 18â‹…Co â‹…Ni + 9â‹…Co â‹…Cr + 47â‹…\n", + "\n", + " 3 8 3 7 2 3 6 3 3 5 4 3 4\n", + "Co â‹…Cr â‹…Ni + 182â‹…Co â‹…Cr â‹…Ni + 408â‹…Co â‹…Cr â‹…Ni + 606â‹…Co â‹…Cr â‹…Ni + 606â‹…Co â‹…Cr \n", + "\n", + " 5 3 3 6 3 2 7 3 8 3 9 2 \n", + "â‹…Ni + 408â‹…Co â‹…Cr â‹…Ni + 182â‹…Co â‹…Cr â‹…Ni + 47â‹…Co â‹…Crâ‹…Ni + 9â‹…Co â‹…Ni + 4â‹…Co â‹…C\n", + "\n", + " 10 2 9 2 8 2 2 7 3 2 6 4 \n", + "r + 18â‹…Co â‹…Cr â‹…Ni + 76â‹…Co â‹…Cr â‹…Ni + 182â‹…Co â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 372\n", + "\n", + " 2 5 5 2 4 6 2 3 7 2 2 8 2 \n", + "â‹…Co â‹…Cr â‹…Ni + 318â‹…Co â‹…Cr â‹…Ni + 182â‹…Co â‹…Cr â‹…Ni + 76â‹…Co â‹…Cr â‹…Ni + 18â‹…Co â‹…Crâ‹…\n", + "\n", + " 9 2 10 11 10 9 2 8 3 \n", + "Ni + 4â‹…Co â‹…Ni + Coâ‹…Cr + 4â‹…Coâ‹…Cr â‹…Ni + 18â‹…Coâ‹…Cr â‹…Ni + 47â‹…Coâ‹…Cr â‹…Ni + 92\n", + "\n", + " 7 4 6 5 5 6 4 7 3 8 \n", + "â‹…Coâ‹…Cr â‹…Ni + 126â‹…Coâ‹…Cr â‹…Ni + 126â‹…Coâ‹…Cr â‹…Ni + 92â‹…Coâ‹…Cr â‹…Ni + 47â‹…Coâ‹…Cr â‹…Ni \n", + "\n", + " 2 9 10 11 12 11 10 2 9\n", + "+ 18â‹…Coâ‹…Cr â‹…Ni + 4â‹…Coâ‹…Crâ‹…Ni + Coâ‹…Ni + Cr + Cr â‹…Ni + 4â‹…Cr â‹…Ni + 9â‹…Cr \n", + "\n", + " 3 8 4 7 5 6 6 5 7 4 8 3 \n", + "â‹…Ni + 18â‹…Cr â‹…Ni + 24â‹…Cr â‹…Ni + 30â‹…Cr â‹…Ni + 24â‹…Cr â‹…Ni + 18â‹…Cr â‹…Ni + 9â‹…Cr â‹…\n", + "\n", + " 9 2 10 11 12\n", + "Ni + 4â‹…Cr â‹…Ni + Crâ‹…Ni + Ni " + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "init_printing()\n", + "\n", + "pl = Polya(graph_name=\"fcc\")\n", + "\n", + "ntypes = 3\n", + "p_g, nms = pl.get_gt(ntypes=ntypes)\n", + "\n", + "# Replacing t1, t2 and t3 with Cr, Co, Ni.\n", + "p_g = p_g.subs(\n", + " {\n", + " symbols(\"t1\"): symbols(\"Cr\"),\n", + " symbols(\"t2\"): symbols(\"Co\"),\n", + " symbols(\"t3\"): symbols(\"Ni\"),\n", + " }\n", + ")\n", + "\n", + "print(\n", + " \"The pattern inventory for the fcc first coordination polyhedron of the CrCoNi system is given by: \\n\"\n", + ")\n", + "\n", + "p_g" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n",
+       " We have a total of 12111 distinct coordination polyhedron, which in turns yield 36333 distinct local chemical \n",
+       "motifs. \n",
+       "
\n" + ], + "text/plain": [ + "\n", + " We have a total of \u001b[1;36m12111\u001b[0m distinct coordination polyhedron, which in turns yield \u001b[1;36m36333\u001b[0m distinct local chemical \n", + "motifs. \n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "print(\n", + " f\"\\n We have a total of {nms} distinct coordination polyhedron, which in turns yield {nms*ntypes} distinct local chemical motifs. \"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Model expressivity on the fcc ternary synthetic dataset and physically constrained embedding space" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "%%capture \n", + "from _frameworks import SyntheticChemicalMotifIdentifier\n", + "\n", + "eca = SyntheticChemicalMotifIdentifier(crystal_structure=\"fcc\")\n", + "df = eca.predict(\n", + " root=\"data/synthetic/fcc_graph_datasets/\",\n", + " skeleton_graph_path=\"data/inputs_doi-10.48550-arXiv.2311.01545/fcc_1nn.pt\",\n", + " atom_types_paths=[\n", + " \"data/inputs_doi-10.48550-arXiv.2311.01545/fcc_nelement3_generators.pt\"\n", + " ],\n", + " nelement=3,\n", + ")\n", + "os.makedirs(\"data/synthetic/outputs/\", exist_ok=True)\n", + "df.to_pickle(\"data/synthetic/outputs/df_fcc.pkl\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
The machine learning pattern inventory is given by:\n",
+       "
\n" + ], + "text/plain": [ + "The machine learning pattern inventory is given by:\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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+ "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
We have a total of 12111 distinct 1CP.\n",
+       "
\n" + ], + "text/plain": [ + "We have a total of \u001b[1;36m12111\u001b[0m distinct 1CP.\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Obtaining the ML pattern inventory\n", + "df = pd.read_pickle(\"data/synthetic/outputs/df_fcc.pkl\")\n", + "\n", + "shell_concentrations, counts = (\n", + " np.array(list(df.shell_concentration)),\n", + " np.array(list(df.counts)),\n", + ")\n", + "unique_concentrations, counts = np.unique(\n", + " shell_concentrations, axis=0, return_counts=True\n", + ")\n", + "\n", + "pattern = {\n", + " tuple(unique_concentrations[i]): counts[i]\n", + " for i in range(len(unique_concentrations))\n", + "}\n", + "print(\"The machine learning pattern inventory is given by:\")\n", + "print(pattern)\n", + "print(f\"We have a total of {np.sum(counts)} distinct 1CP.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Chemical motif identification in atomistic data" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "%%capture \n", + "from _frameworks import MonteCarloChemicalMotifIdentifier\n", + "\n", + "dump_files = [\n", + " f\"data/inputs_doi-10.48550-arXiv.2311.01545/dumps/ordered_relaxation_20_{i}_300K.dump\"\n", + " for i in range(1, 5 + 1)\n", + "]\n", + "\n", + "eca = MonteCarloChemicalMotifIdentifier(crystal_structure=\"fcc\")\n", + "df = eca.predict(root=\"data/mc/outputs/eca_id/300K/\", dump_file=dump_files)\n", + "kl = eca.get_kl(df)\n", + "df.to_pickle(\"data/mc/outputs/eca_id/300K/df_microstates.pkl\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's compute the dissimilarity between motif $\\mathcal{M}_0$ and $\\mathcal{M}_1$ shown below: " + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from chemicalmotifidentifier import Plot\n", + "plot = Plot(\n", + " structure=\"fcc\",\n", + " graph_folder=\"data/inputs_doi-10.48550-arXiv.2311.01545/graph_plot_templates\",\n", + ")\n", + "plot.set_colors(np.array([\"#FED700\", \"#21B0FE\", \"#FE218B\"]))\n", + "plot.set_node_size(4)\n", + "plot.set_width(0.2)\n", + "\n", + "for i in [0, 1]:\n", + " df_row = df.iloc[i]\n", + "\n", + " types_with_central_atom = np.concatenate(\n", + " ([df_row.central_atom_type], np.array(list(df_row.shell_atomic_types)))\n", + " )\n", + "\n", + " fig, ax = plt.subplots(figsize=(1, 1))\n", + " plot.plot_ms(new_atom_types=types_with_central_atom)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
The dissimilarity between these two motifs is: 0.15.\n",
+       "\n",
+       "Before weighthing based on the number of bonds of each structure, they have a central atom dissimilarity of 0.00 \n",
+       "since their central atom atomic types are the same. Their chemical composition dissimilarity is of 1.00/12 because \n",
+       "only two atoms are swapped. And their structural dissimilarity is of 0.28.\n",
+       "
\n" + ], + "text/plain": [ + "The dissimilarity between these two motifs is: \u001b[1;36m0.15\u001b[0m.\n", + "\n", + "Before weighthing based on the number of bonds of each structure, they have a central atom dissimilarity of \u001b[1;36m0.00\u001b[0m \n", + "since their central atom atomic types are the same. Their chemical composition dissimilarity is of \u001b[1;36m1.00\u001b[0m/\u001b[1;36m12\u001b[0m because \n", + "only two atoms are swapped. And their structural dissimilarity is of \u001b[1;36m0.28\u001b[0m.\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from chemicalmotifidentifier import Dissimilarity\n", + "\n", + "phys_emb_i = np.concatenate(([df.iloc[0].central_atom_type], df.iloc[0].shell_phys_emb))\n", + "phys_emb_j = np.concatenate(([df.iloc[1].central_atom_type], df.iloc[1].shell_phys_emb))\n", + "\n", + "(\n", + " central_atom_dissim,\n", + " concentration_dissim,\n", + " structural_dissim,\n", + ") = Dissimilarity().get_separate_dissimilarities(3, phys_emb_j, phys_emb_i)\n", + "\n", + "weights = np.array([12.0, 24.0, 24.0])\n", + "weights *= 1 / np.sum(weights)\n", + "d_ij = (\n", + " weights[0] * central_atom_dissim\n", + " + weights[1] * concentration_dissim / 12\n", + " + weights[2] * structural_dissim\n", + ")\n", + "\n", + "\n", + "print(f\"The dissimilarity between these two motifs is: {d_ij[0]:.2f}.\\n\\nBefore weighthing based on the number of bonds of each structure, they have a central atom dissimilarity of {central_atom_dissim[0]:.2f} since their central atom atomic types are the same. Their chemical composition dissimilarity is of {concentration_dissim[0]:.2f}/12 because only two atoms are swapped. And their structural dissimilarity is of {structural_dissim[0]:.2f}.\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}