Lobster_summary.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1893ba24",
   "metadata": {},
   "source": [
    "<h1><center>Dataset overview</center></h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "157da7f8",
   "metadata": {},
   "source": [
    "At the moment LOBSTER data available for 1520 compounds. \n",
    "\n",
    "All the computational data (including raw unprocessed data) is available to download from our Zenodo communuity : https://zenodo.org/communities/automated-bonding-analysis/?page=1&size=20\n",
    "\n",
    "Dataset size:\n",
    "\n",
    "- Unprocess raw data : ~345 GB\n",
    "- Lightweight jsons (Could be directly used for material project website) : ~ 716 MB\n",
    "- Computational data in pydantic schema (as per atomate2 workflow) : ~80 GB\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a2e444a",
   "metadata": {},
   "source": [
    "<h2><center>Top level keys to access data from LOBSTER lightweight JSON files</center></h2>\n",
    "<table>\n",
    "    <thead>\n",
    "    <tr>\n",
    "        <th>Root Keys</th>\n",
    "        <th>Data type</th>\n",
    "        <th>Description</th>\n",
    "    </tr>\n",
    "    </thead>\n",
    "    <tbody>\n",
    "    <tr>\n",
    "        <td>all_bonds</td>\n",
    "        <td>dict</td>\n",
    "        <td>Summarized relevant bonds data (See table 2 of the manuscript for details)</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>cation_anion_bonds</td>\n",
    "        <td>dict</td>\n",
    "        <td>Summarized relevant cation-anion bonds data (See table 2 of the manuscript forfor details)</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>madelung_energies</td>\n",
    "        <td>dict</td>\n",
    "        <td>Total electrostatic energy for the structure as calculated from the Mulliken and Löwdin charges</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>charges</td>\n",
    "        <td>dict</td>\n",
    "        <td>Atomic charges with Mulliken and Löwdin population analysis methods as keys. <br>\n",
    "            Each keys corresponding list follows the order of sites in the crystal structure.</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>calc_quality_summary</td>\n",
    "        <td>dict</td>\n",
    "        <td>Dict summarizing results of technical validation tests like charge spillings, <br>\n",
    "             band overlaps, DOS and charge comparisons</td>\n",
    "    </tr>\n",
    "    </tbody>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff4ea7b7",
   "metadata": {},
   "source": [
    "<h1><center>Top level keys to access data from Computational data JSON files </center></h1>\n",
    "<table>\n",
    "<thead>\n",
    "  <tr>\n",
    "    <th>Root Keys</th>\n",
    "    <th>Data type</th>\n",
    "    <th>Description</th>\n",
    "  </tr>\n",
    "</thead>\n",
    "<tbody>\n",
    "  <tr>\n",
    "    <td>structure</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of the pymatgen structure object<br>used for the LOBSTER calculation</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>charges</td>\n",
    "    <td>dict</td>\n",
    "    <td>Atomic charges dict from LOBSTER based on <br>Mulliken and Loewdin charge analysis</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterin</td>\n",
    "    <td>dict</td>\n",
    "    <td>LOBSTER calculation inputs</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterout</td>\n",
    "    <td>dict</td>\n",
    "    <td>Information of LOBSTER calculation output</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterpy_data</td>\n",
    "    <td>dict</td>\n",
    "    <td>Summarized bonding analysis data from Lobsterpy <br>(all bonds mode). It also includes Cohp objects <br>to plot the COHP curves from the automatic analysis</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterpy_text</td>\n",
    "    <td>dict</td>\n",
    "    <td>LobsterPy automatic analysis summary text (all bonds mode)</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icohp</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest ICOHP bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icoop</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest ICOOP bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icobi</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest ICOBI bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterpy_data_cation_anion</td>\n",
    "    <td>dict</td>\n",
    "    <td>Summarized bonding analysis data from Lobsterpy <br>(cation-anion bonds mode). It also includes Cohp objects <br>to plot the COHP curves from the automatic analysis</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lobsterpy_text_cation_anion</td>\n",
    "    <td>dict</td>\n",
    "    <td>LobsterPy automatic analysis summary text <br>(cation-anion bonds mode)</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icohp_cation_anion</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest cation-anion ICOHP bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icoop_cation_anion</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest cation-anion ICOOP bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>strongest_bonds_icobi_cation_anion</td>\n",
    "    <td>dict</td>\n",
    "    <td>Describes the strongest cation-anion ICOBI bonds</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>cohp_data</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of pymatgen CompleteCohp object <br>including data to plot COHP curves</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>coop_data</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of pymatgen CompleteCohp object <br>including data to plot COOP curves</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>cobi_data</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of pymatgen CompleteCohp object <br>including data to plot COBI curves</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>dos</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of pymatgen LobsterCompleteDos object <br>including the DOSCAR.lobster data</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>lso_dos</td>\n",
    "    <td>dict</td>\n",
    "    <td>Dict representation of pymatgen LobsterCompleteDos object <br>including the DOSCAR.LSO.lobster data</td>\n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>madelung_energies</td>\n",
    "    <td>dict</td>\n",
    "    <td>Consists of the Madelung energies of the structure derived from <br>the Mulliken and Löwdin charges</td>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>site_potentials</td>\n",
    "    <td>dict</td>\n",
    "    <td>Site potentials dict based on Mulliken and Loewdin charges</td>\n",
    "  </tr>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>gross_populations</td>\n",
    "    <td>dict</td>\n",
    "    <td>Gross populations dict based on Mulliken and Loewdin charges <br>with each site as a key and the gross population as a value.</td>\n",
    "  </tr>\n",
    "  </tr>\n",
    "    <tr>\n",
    "    <td>band_overlaps</td>\n",
    "    <td>dict</td>\n",
    "    <td>Band overlaps data for each k-point from bandOverlaps.lobster <br>file if it exists</td>\n",
    "  </tr>\n",
    "</tbody>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc6bb29e",
   "metadata": {},
   "source": [
    "### Parsers / Plotters - Pymatgen\n",
    "\n",
    "Parsers for all the LOBSTER output files are already implemented in pymatgen namely : \n",
    "- COHPCAR.lobster / COBICAR.lobster / COBICAR.lobster\n",
    "- ICOHPLIST.lobster / ICOOPLIST.lobster / ICOBILIST.lobster\n",
    "- DOSCAR.lobster / DOSCAR.LSO.lobster\n",
    "- MadelungEnergies.lobster \n",
    "- CHARGE.lobster\n",
    "\n",
    "Plotters for DOSCAR, COHP(ICOHP)/COBI (ICOBI)/COOP (ICOOP) are also readily available. Pymatgen DOS plotter now also has option to plot DOS in convention followed in chemistry:\n",
    "https://github.com/materialsproject/pymatgen/blob/d621490d5d6742b4c7e432d3144dec6858236c79/pymatgen/electronic_structure/plotter.py#L131\n",
    "\n",
    "### Parsers / Plotters - Lobsterpy\n",
    "\n",
    "Interactive plotter for COHP/ICOHP are being implemented in Lobsterpy package (Useful for website)\n",
    "\n",
    "### Scripts for generating and reading the output files -  Lightweight JSONS / Computational data JSONS\n",
    "- Data generation : https://github.com/naik-aakash/lobster-database-paper-analysis-scripts/tree/main/Data_generation\n",
    "- Data reading : https://github.com/naik-aakash/lobster-database-paper-analysis-scripts/tree/main/Read_data_records"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c555520",
   "metadata": {},
   "source": [
    "## DOS comparison / Visualizer app  \n",
    "\n",
    "We have implemented methods in pymatgen that can easily compare DOS using Tanimoto index as similarity measure. (Could be useful to demonstrate it on website) :\n",
    "- Fingerprint: https://github.com/materialsproject/pymatgen/blob/d621490d5d6742b4c7e432d3144dec6858236c79/pymatgen/electronic_structure/dos.py#L1180\n",
    "- Compare two DOS fingerprints (Tanimoto index): https://github.com/materialsproject/pymatgen/blob/d621490d5d6742b4c7e432d3144dec6858236c79/pymatgen/electronic_structure/dos.py#L1284\n",
    "\n",
    "- We also have created a dash app that helps in visualizing the DOS benchmark for our dataset and is available on zenodo : https://doi.org/10.5281/zenodo.7795903"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}