docs/source/user_guide/calc_gulp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GULP Calculations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `gulp.single` (for single point energy calculations) and `gulp.optimize` (for geometry optimisation calculations) plugins will run the [General Utility Lattice Program (GULP)](http://gulp.curtin.edu.au/gulp/).\n",
    "They are designed to create the input `.gin` file,\n",
    "from a set of AiiDA :py:class:`~aiida.orm.nodes.data.Data` nodes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. note::\n",
    "\n",
    "    It is likely that these calculations will eventually be moved to a separate repository."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run a computation, first ensure AiiDA is running:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m ✓ \u001b[0mprofile:     On profile test_crystal17\u001b[0m\n",
      "\u001b[32m ✓ \u001b[0mrepository:  /Users/cjs14/GitHub/aiida-cjs-working/databases/aiida/.aiida/repository/test_crystal17\u001b[0m\n",
      "\u001b[32m ✓ \u001b[0mpostgres:    Connected as cjs14@localhost:5432\u001b[0m\n",
      "\u001b[32m ✓ \u001b[0mrabbitmq:    Connected to amqp://127.0.0.1?heartbeat=600\u001b[0m\n",
      "\u001b[32m ✓ \u001b[0mdaemon:      Daemon is running as PID 28308 since 2019-07-07 04:06:37\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!verdi status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. seealso::\n",
    "\n",
    "    AiiDA documentation: :ref:`aiida:quick_installation`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If `aiida-crystal17` is installed,\n",
    "the `gulp.single` and `gulp.optimize` computations should be available:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31m\u001b[1mInputs\u001b[0m\n",
      "\u001b[1m           code:  required  Code                The Code to use for this job.\u001b[0m\n",
      "\u001b[1m      potential:  required  EmpiricalPotential  parameters to create the potential section of the .gin file content.\u001b[0m\n",
      "\u001b[1m      structure:  required  StructureData       atomic structure used to create the geometry section of .gin file content.\u001b[0m\n",
      "       metadata:  optional                      \u001b[0m\n",
      "     parameters:  optional  Dict                additional input parameters to create the .gin file content.\u001b[0m\n",
      "\u001b[31m\u001b[1mOutputs\u001b[0m\n",
      "\u001b[1m  remote_folder:  required  RemoteData          Input files necessary to run the process will be stored in this folder node ...\u001b[0m\n",
      "\u001b[1m        results:  required  Dict                the data extracted from the main output file\u001b[0m\n",
      "\u001b[1m      retrieved:  required  FolderData          Files that are retrieved by the daemon will be stored in this node. By defa ...\u001b[0m\n",
      "\u001b[31m\u001b[1mExit codes\u001b[0m\n",
      "              1:  The process has failed with an unspecified error.\u001b[0m\n",
      "              2:  The process failed with legacy failure mode.\u001b[0m\n",
      "             10:  The process returned an invalid output.\u001b[0m\n",
      "             11:  The process did not register a required output.\u001b[0m\n",
      "            200:  The retrieved folder data node could not be accessed.\u001b[0m\n",
      "            210:  The main output file was not found\u001b[0m\n",
      "            300:  An error was flagged trying to parse the main gulp output file\u001b[0m\n",
      "            301:  The stdout file is empty\u001b[0m\n",
      "            400:  The main gulp output file flagged an error not handled elsewhere\u001b[0m\n",
      "            410:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n",
      "            411:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n",
      "            412:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!verdi plugin list aiida.calculations gulp.single"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31m\u001b[1mInputs\u001b[0m\n",
      "\u001b[1m           code:  required  Code                The Code to use for this job.\u001b[0m\n",
      "\u001b[1m      potential:  required  EmpiricalPotential  parameters to create the potential section of the .gin file content.\u001b[0m\n",
      "\u001b[1m      structure:  required  StructureData       atomic structure used to create the geometry section of .gin file content.\u001b[0m\n",
      "       metadata:  optional                      \u001b[0m\n",
      "     parameters:  optional  Dict                additional input parameters to create the .gin file content.\u001b[0m\n",
      "       symmetry:  optional  SymmetryData        parameters to create the symmetry section of the .gin file content (for con ...\u001b[0m\n",
      "\u001b[31m\u001b[1mOutputs\u001b[0m\n",
      "\u001b[1m  remote_folder:  required  RemoteData          Input files necessary to run the process will be stored in this folder node ...\u001b[0m\n",
      "\u001b[1m        results:  required  Dict                the data extracted from the main output file\u001b[0m\n",
      "\u001b[1m      retrieved:  required  FolderData          Files that are retrieved by the daemon will be stored in this node. By defa ...\u001b[0m\n",
      "\u001b[1m      structure:  required  StructureData       the optimized structure output from the calculation\u001b[0m\n",
      "\u001b[31m\u001b[1mExit codes\u001b[0m\n",
      "              1:  The process has failed with an unspecified error.\u001b[0m\n",
      "              2:  The process failed with legacy failure mode.\u001b[0m\n",
      "             10:  The process returned an invalid output.\u001b[0m\n",
      "             11:  The process did not register a required output.\u001b[0m\n",
      "            200:  The retrieved folder data node could not be accessed.\u001b[0m\n",
      "            210:  The main output file was not found\u001b[0m\n",
      "            250:  The output cif file was not found\u001b[0m\n",
      "            251:  An input structure is required to create the output structure of an optimisation\u001b[0m\n",
      "            252:  The output cif file was not consistent with the input structure\u001b[0m\n",
      "            253:  The final structure coordinates were not parsed from the output file\u001b[0m\n",
      "            300:  An error was flagged trying to parse the main gulp output file\u001b[0m\n",
      "            301:  The stdout file is empty\u001b[0m\n",
      "            400:  The main gulp output file flagged an error not handled elsewhere\u001b[0m\n",
      "            410:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n",
      "            411:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n",
      "            412:  The main gulp output file did not signal that an expected optimisation completed\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!verdi plugin list aiida.calculations gulp.optimize"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use the python interface,\n",
    "first ensure a profile is loaded in the python kernel,\n",
    "and import the required modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "init_cell": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'test_crystal17'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from aiida import load_profile\n",
    "profile = load_profile()\n",
    "profile.name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "init_cell": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from aiida.orm import Code\n",
    "from aiida.plugins import (\n",
    "    DataFactory, WorkflowFactory, CalculationFactory)\n",
    "from aiida.engine import run_get_node\n",
    "from aiida_crystal17.common import display_json\n",
    "from aiida_crystal17.tests import TEST_FILES\n",
    "from aiida.tools.visualization import Graph\n",
    "from jsonextended import edict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input Node Creation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. seealso::\n",
    "\n",
    "    [GULP Help File](http://gulp.curtin.edu.au/gulp/help/help_45_txt.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. seealso::\n",
    "\n",
    "    AiiDA documentation: :ref:`aiida:setup_code`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An :py:class:aiida.orm.nodes.data.code.Code node should be set up in advance, to use the gulp calculation plugin, and call the gulp executable (or mock_gulp used here for test purposes)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['PK', 10],\n",
       " ['UUID', '5c9c53b5-bd8d-4bec-8b56-6c99bfd08a9b'],\n",
       " ['Label', 'gulp.optimize-mock_gulp@localhost'],\n",
       " ['Description', ''],\n",
       " ['Default plugin', 'gulp.optimize'],\n",
       " ['Type', 'remote'],\n",
       " ['Remote machine', 'localhost'],\n",
       " ['Remote absolute path', '//anaconda/envs/aiida-workshop/bin/mock_gulp'],\n",
       " ['Prepend text', 'No prepend text'],\n",
       " ['Append text', 'No append text']]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from aiida_crystal17.tests.utils import get_or_create_local_computer, get_or_create_code\n",
    "computer = get_or_create_local_computer('work_directory', 'localhost')\n",
    "code_single = get_or_create_code('gulp.single', computer, 'mock_gulp')\n",
    "code_opt = get_or_create_code('gulp.optimize', computer, 'mock_gulp')\n",
    "code_opt.get_full_text_info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. note::\n",
    "\n",
    "    The calculations are tested against GULP v4.5.3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Atomic Structure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``structure`` refers to a standard\n",
    ":py:class:`~aiida.StructureData` node, and is used to create the `main.gui`.\n",
    "\n",
    "Structures consist of:\n",
    "\n",
    "- A cell with a basis vectors and whether it is periodic, for each dimension\n",
    "- ``Site`` with a cartesian coordinate and reference to a kind\n",
    "- ``Kind`` which details the species and composition at one or more sites\n",
    "\n",
    "The simplest way to create a structure is *via* :py:mod:`ase`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<StructureData: uuid: bd478628-22e1-4c7f-a9ed-b1f93d8b0d5a (unstored)>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from ase.spacegroup import crystal\n",
    "atoms = crystal(\n",
    "    symbols=[12, 8],\n",
    "    basis=[[0, 0, 0], [0.5, 0.5, 0.5]],\n",
    "    spacegroup=225,\n",
    "    cellpar=[4.21, 4.21, 4.21, 90, 90, 90])\n",
    "struct_cls = DataFactory('structure')\n",
    "structure = struct_cls(ase=atoms)\n",
    "structure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These structures can be visualised using standard ASE methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from ase.visualize.plot import plot_atoms\n",
    "atoms = structure.get_ase()\n",
    "fig, ax = plt.subplots()\n",
    "plot_atoms(atoms.repeat((2,2,2)), \n",
    "           ax, radii=0.8, show_unit_cell=True, \n",
    "           rotation=('45x,0y,0z'));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As default, one kind is created per atomic species\n",
    "(named as the atomic symbol):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Mg', 'Mg', 'Mg', 'Mg', 'O1', 'O1', 'O1', 'O1']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "structure.get_site_kindnames()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, we may want to specify more than one kind per species (for example to setup anti-ferromagnetic spin). We can achieve this by tagging the atoms:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Mg1', 'Mg1', 'Mg2', 'Mg2', 'O', 'O', 'O', 'O']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atoms_afm = atoms.copy()\n",
    "atoms_afm.set_tags([1, 1, 2, 2, 0, 0, 0, 0])\n",
    "structure_afm = struct_cls(ase=atoms_afm)\n",
    "structure_afm.get_site_kindnames()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inter-Atomic Potential"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inter-atomic potentials are supplied in the form of a py:class:`~aiida.orm.nodes.data.dict.Dict` node with keys `pair_style` and `data`, with the form of the `data` dictated by the pair_style.\n",
    "Pair styles are created by sub-classing :py:class:`~aiida_crystal17.gulp.potentials.base.PotentialWriterAbstract` and adding an entry point to `gulp.potentials`. Available pair styles and data schema can be found by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[22mRegistered entry points for gulp.potentials:\u001b[0m\r\n",
      "\u001b[22m* lj\u001b[0m\r\n",
      "\u001b[22m* reaxff\u001b[0m\r\n",
      "\u001b[22m\u001b[0m\r\n",
      "\u001b[34m\u001b[1mInfo: \u001b[0m\u001b[22mPass the entry point as an argument to display detailed information\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!verdi data gulp.potentials list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1mLennard-Jones potential, of the form; E = A/r**m - B/r**n\u001b[0m\n",
      "\u001b[22mData Schema:\u001b[0m\n",
      "\u001b[22m\u001b[34m$id\u001b[0m: potential.base.schema\u001b[0m\n",
      "\u001b[22m\u001b[34m$schema\u001b[0m: http://json-schema.org/draft-07/schema\u001b[0m\n",
      "\u001b[22m\u001b[34mdescription\u001b[0m: a schema for storing an empirical potential\u001b[0m\n",
      "\u001b[22m\u001b[34mproperties\u001b[0m: \u001b[0m\n",
      "\u001b[22m  \u001b[34m2body\u001b[0m: \u001b[0m\n",
      "\u001b[22m    \u001b[34madditionalProperties\u001b[0m: False\u001b[0m\n",
      "\u001b[22m    \u001b[34mdescription\u001b[0m: parameters that depend on two species\u001b[0m\n",
      "\u001b[22m    \u001b[34mpatternProperties\u001b[0m: \u001b[0m\n",
      "\u001b[22m      \u001b[34m[0-9]+\\-[0-9]+\u001b[0m: \u001b[0m\n",
      "\u001b[22m        \u001b[34mdescription\u001b[0m: mapping of '<idx1>-<idx2>' to properties\u001b[0m\n",
      "\u001b[22m        \u001b[34mproperties\u001b[0m: \u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_A\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: fist coefficient (in ev*Angs**m)\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m: number\u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_B\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: second coefficient (in ev*Angs**m)\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m: number\u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_m\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdefault\u001b[0m: 12\u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: first exponent\u001b[0m\n",
      "\u001b[22m            \u001b[34mexclusiveMinimum\u001b[0m: 0\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m:    integer\u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_n\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdefault\u001b[0m: 6\u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: second exponent\u001b[0m\n",
      "\u001b[22m            \u001b[34mexclusiveMinimum\u001b[0m: 0\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m:    integer\u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_rmax\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: maximum radius cut-off (Angs)\u001b[0m\n",
      "\u001b[22m            \u001b[34mexclusiveMinimum\u001b[0m: 0\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m:    number\u001b[0m\n",
      "\u001b[22m          \u001b[34mlj_rmin\u001b[0m: \u001b[0m\n",
      "\u001b[22m            \u001b[34mdefault\u001b[0m: 0\u001b[0m\n",
      "\u001b[22m            \u001b[34mdescription\u001b[0m: minimum radius cut-off (Angs)\u001b[0m\n",
      "\u001b[22m            \u001b[34mminimum\u001b[0m: 0\u001b[0m\n",
      "\u001b[22m            \u001b[34mtype\u001b[0m: number\u001b[0m\n",
      "\u001b[22m        \u001b[34mrequired\u001b[0m: [lj_A, lj_B, lj_rmax]\u001b[0m\n",
      "\u001b[22m        \u001b[34mtype\u001b[0m: object\u001b[0m\n",
      "\u001b[22m    \u001b[34mtype\u001b[0m:        object\u001b[0m\n",
      "\u001b[22m  \u001b[34mdescription\u001b[0m: \u001b[0m\n",
      "\u001b[22m    \u001b[34mtype\u001b[0m: string\u001b[0m\n",
      "\u001b[22m  \u001b[34mspecies\u001b[0m: \u001b[0m\n",
      "\u001b[22m    \u001b[34mdescription\u001b[0m: the list of species\u001b[0m\n",
      "\u001b[22m    \u001b[34mitems\u001b[0m: \u001b[0m\n",
      "\u001b[22m      \u001b[34mpattern\u001b[0m: ^[a-zA-Z]+ (core|shell)$\u001b[0m\n",
      "\u001b[22m      \u001b[34mtype\u001b[0m: string\u001b[0m\n",
      "\u001b[22m    \u001b[34mtype\u001b[0m: array\u001b[0m\n",
      "\u001b[22m    \u001b[34muniqueItems\u001b[0m: True\u001b[0m\n",
      "\u001b[22m\u001b[34mrequired\u001b[0m: [species, 2body]\u001b[0m\n",
      "\u001b[22m\u001b[34mtype\u001b[0m: object\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!verdi data gulp.potentials list lj -d 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of fitted parameters: 2\n",
      "lennard 12 6\n",
      "H core  He core 1.00000000E+00 2.00000000E+00 12.00000\n"
     ]
    }
   ],
   "source": [
    "from aiida.plugins import load_entry_point\n",
    "writer = load_entry_point('gulp.potentials', 'lj')()\n",
    "data = {\n",
    "    \"species\": [\"H core\", \"He core\"],\n",
    "    \"2body\": {\n",
    "        \"0-1\": {\n",
    "            \"lj_A\": 1.0,\n",
    "            \"lj_B\": 2.0,\n",
    "            \"lj_rmax\": 12.0\n",
    "        }\n",
    "    }\n",
    "}\n",
    "content = writer.create_content(data)\n",
    "print(\"Number of fitted parameters:\", content.number_of_flags)\n",
    "print(content.content)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ReaxFF data can be created from the standard LAMMPS style potential file, using"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m1body\u001b[0m:\n",
      "  \u001b[34m0\u001b[0m: {...}\n",
      "  \u001b[34m1\u001b[0m: {...}\n",
      "\u001b[34m2body\u001b[0m:\n",
      "  \u001b[34m0-0\u001b[0m: {...}\n",
      "  \u001b[34m0-1\u001b[0m: {...}\n",
      "  \u001b[34m1-1\u001b[0m: {...}\n",
      "\u001b[34m3body\u001b[0m:\n",
      "  \u001b[34m0-0-1\u001b[0m: {...}\n",
      "  \u001b[34m0-1-0\u001b[0m: {...}\n",
      "  \u001b[34m0-1-1\u001b[0m: {...}\n",
      "  \u001b[34m1-0-1\u001b[0m: {...}\n",
      "  \u001b[34m1-1-1\u001b[0m: {...}\n",
      "\u001b[34m4body\u001b[0m:\n",
      "  \u001b[34m1-1-1-1\u001b[0m: {...}\n",
      "\u001b[34mdescription\u001b[0m: Reactive MD-force field: Cr/O/Fe/S/C/H force field 2014\n",
      "\u001b[34mglobal\u001b[0m:\n",
      "  \u001b[34mC2-correction\u001b[0m:           60.485\n",
      "  \u001b[34mLower Taper-radius\u001b[0m:      0.0\n",
      "  \u001b[34mNot used 2\u001b[0m:              6.1431\n",
      "  \u001b[34mNot used 3\u001b[0m:              -2.4837\n",
      "  \u001b[34mNot used 4\u001b[0m:              -1.2327\n",
      "  \u001b[34mNot used 5\u001b[0m:              0.5\n",
      "  \u001b[34mNot used 6\u001b[0m:              20.0\n",
      "  \u001b[34mNot used 7\u001b[0m:              5.0\n",
      "  \u001b[34mNot used 8\u001b[0m:              0.0\n",
      "  \u001b[34mTriple bond stabilisation\u001b[0m: 4.6\n",
      "  \u001b[34mTriple bond stabilisation 1\u001b[0m: 1.7224\n",
      "  \u001b[34mTriple bond stabilisation 2\u001b[0m: 6.8702\n",
      "  \u001b[34mTriple bond stabilization energy\u001b[0m: -70.5044\n",
      "  \u001b[34mUpper Taper-radius\u001b[0m:      10.0\n",
      "  \u001b[34mbond order cutoff\u001b[0m:       0.1\n",
      "  \u001b[34mreaxff0_boc1\u001b[0m:            50.0\n",
      "  \u001b[34mreaxff0_boc2\u001b[0m:            9.5469\n",
      "  \u001b[34mreaxff0_cot2\u001b[0m:            2.1645\n",
      "  \u001b[34mreaxff0_lp1\u001b[0m:             6.0891\n",
      "  \u001b[34mreaxff0_ovun3\u001b[0m:           50.0\n",
      "  \u001b[34mreaxff0_ovun4\u001b[0m:           0.6991\n",
      "  \u001b[34mreaxff0_ovun6\u001b[0m:           1.0588\n",
      "  \u001b[34mreaxff0_ovun7\u001b[0m:           12.1176\n",
      "  \u001b[34mreaxff0_ovun8\u001b[0m:           13.3056\n",
      "  \u001b[34mreaxff0_pen2\u001b[0m:            6.929\n",
      "  \u001b[34mreaxff0_pen3\u001b[0m:            0.3989\n",
      "  \u001b[34mreaxff0_pen4\u001b[0m:            3.9954\n",
      "  \u001b[34mreaxff0_tor2\u001b[0m:            5.7796\n",
      "  \u001b[34mreaxff0_tor3\u001b[0m:            10.0\n",
      "  \u001b[34mreaxff0_tor4\u001b[0m:            1.9487\n",
      "  \u001b[34mreaxff0_val7\u001b[0m:            33.8667\n",
      "  \u001b[34mreaxff0_val8\u001b[0m:            1.8512\n",
      "  \u001b[34mreaxff0_val9\u001b[0m:            1.0563\n",
      "  \u001b[34mreaxff0_val10\u001b[0m:           2.0384\n",
      "  \u001b[34mreaxff0_vdw1\u001b[0m:            1.5591\n",
      "  \u001b[34mreaxff2_pen2\u001b[0m:            2.8793\n",
      "  \u001b[34mreaxff2_pen3\u001b[0m:            1.0\n",
      "  \u001b[34mreaxff3_coa2\u001b[0m:            26.5405\n",
      "  \u001b[34mreaxff3_coa3\u001b[0m:            2.6962\n",
      "  \u001b[34mreaxff3_coa4\u001b[0m:            2.1365\n",
      "\u001b[34mspecies\u001b[0m: [Fe core, S core]\n"
     ]
    }
   ],
   "source": [
    "from aiida_crystal17.tests import TEST_FILES\n",
    "from aiida_crystal17.gulp.potentials.raw_reaxff import read_lammps_format\n",
    "from aiida_crystal17.gulp.potentials.common import filter_by_species\n",
    "\n",
    "with open(os.path.join(TEST_FILES, 'gulp', 'potentials', 'FeCrOSCH.reaxff')) as handle:  \n",
    "    data = read_lammps_format(handle.read().splitlines())\n",
    "data = filter_by_species(data, [\"Fe core\", \"S core\"])\n",
    "    \n",
    "edict.pprint(data, depth=2, keycolor='blue')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting Up and Running the Calculations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. seealso::\n",
    "\n",
    "    AiiDA documentation: :ref:`aiida:working_processes`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<StructureData: uuid: ef0e9ca4-c345-486b-b6bc-9931a90b15bb (unstored)>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from aiida_crystal17.symmetry import convert_structure\n",
    "structure_data = {\n",
    "    \"lattice\": [[5.38, 0.000000, 0.000000],\n",
    "                [0.000000, 5.38, 0.000000],\n",
    "                [0.000000, 0.000000, 5.38]],\n",
    "    \"fcoords\": [[0.0, 0.0, 0.0], [0.5, 0.0, 0.5], [0.0, 0.5, 0.5],\n",
    "                [0.5, 0.5, 0.0], [0.338, 0.338, 0.338],\n",
    "                [0.662, 0.662, 0.662], [0.162, 0.662, 0.838],\n",
    "                [0.838, 0.338, 0.162], [0.662, 0.838, 0.162],\n",
    "                [0.338, 0.162, 0.838], [0.838, 0.162, 0.662],\n",
    "                [0.162, 0.838, 0.338]],\n",
    "    \"symbols\": ['Fe'] * 4 + ['S'] * 8,\n",
    "    \"pbc\": [True, True, True]\n",
    "}\n",
    "structure = convert_structure(structure_data, \"aiida\")\n",
    "structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'pair_style': 'lj',\n",
       " 'description': 'Lennard-Jones potential, of the form; E = A/r**m - B/r**n',\n",
       " 'species': ['Fe core', 'S core'],\n",
       " 'input_lines_md5': '35449283e18a3393ba70f925a16ba6a5',\n",
       " 'fitting_flags': False,\n",
       " 'total_flags': 6,\n",
       " 'number_flagged': 0,\n",
       " 'potential_filename': 'potential.pot',\n",
       " 'potential_json': 'potential.json',\n",
       " 'fitting_json': 'fitting.json'}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "potential_data = {\n",
    "    \"species\": [\"Fe core\", \"S core\"],\n",
    "    \"2body\": {\n",
    "        \"0-0\": {\n",
    "            \"lj_A\": 1.0,\n",
    "            \"lj_B\": 1.0,\n",
    "            \"lj_rmax\": 12.0\n",
    "        },\n",
    "        \"0-1\": {\n",
    "            \"lj_A\": 1.0,\n",
    "            \"lj_B\": 1.0,\n",
    "            \"lj_rmax\": 12.0\n",
    "        },\n",
    "        \"1-1\": {\n",
    "            \"lj_A\": 1.0,\n",
    "            \"lj_B\": 1.0,\n",
    "            \"lj_rmax\": 12.0\n",
    "        }\n",
    "    }\n",
    "}\n",
    "potential_lj = DataFactory('gulp.potential')(\n",
    "    pair_style=\"lj\", potential_data=potential_data)\n",
    "potential_lj.attributes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### gulp.single"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "code_single = Code.objects.get(\n",
    "    label=\"gulp.single-mock_gulp@localhost\")\n",
    "builder = code_single.get_builder()\n",
    "builder.metadata.options = {\n",
    "    \"resources\": {\n",
    "        \"num_machines\": 1, \n",
    "        \"num_mpiprocs_per_machine\": 1}}\n",
    "builder.structure = structure\n",
    "builder.potential = potential_lj"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<CalcJobNode: uuid: 047795f9-da9f-44e2-b88b-a69cf2edf6fa (pk: 93) (aiida.calculations:gulp.single)>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result, calcnode = run_get_node(builder)\n",
    "calcnode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "ProcessState.FINISHED\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(calcnode.is_finished_ok)\n",
    "print(calcnode.process_state)\n",
    "print(calcnode.exit_status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ipub": {
     "figure": {
      "caption": "`gulp.single` calculation provenance graph."
     }
    }
   },
   "outputs": [
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     },
     "execution_count": 32,
     "metadata": {},
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    }
   ],
   "source": [
    "graph = Graph(graph_attr={'size': \"6,8!\", \"rankdir\": \"LR\"})\n",
    "graph.add_node(calcnode)\n",
    "graph.add_incoming(calcnode, annotate_links=\"both\")\n",
    "graph.add_outgoing(calcnode, annotate_links=\"both\")\n",
    "graph.graphviz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### gulp.optimize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Dict: uuid: 3692d411-5339-4625-b00e-4f997b7f06b1 (unstored)>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt_dict={\n",
    "    \"minimize\": {\"style\": \"cg\", \"max_iterations\": 100},\n",
    "    \"relax\": {\"type\": \"conp\"}}\n",
    "opt_params = DataFactory('dict')(dict=opt_dict)\n",
    "opt_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "code_opt = Code.objects.get(\n",
    "    label=\"gulp.optimize-mock_gulp@localhost\")\n",
    "builder_opt = code_opt.get_builder()\n",
    "builder_opt.metadata.options = {\n",
    "    \"resources\": {\n",
    "        \"num_machines\": 1, \n",
    "        \"num_mpiprocs_per_machine\": 1}}\n",
    "builder_opt.structure = structure\n",
    "builder_opt.potential = potential_lj\n",
    "builder_opt.parameters = opt_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<CalcJobNode: uuid: 131c8123-d81c-4b14-b6d1-aec40eabfa50 (pk: 98) (aiida.calculations:gulp.optimize)>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result, calcnode_opt = run_get_node(builder_opt)\n",
    "calcnode_opt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "ProcessState.FINISHED\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "print(calcnode_opt.is_finished_ok)\n",
    "print(calcnode_opt.process_state)\n",
    "print(calcnode_opt.exit_status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ipub": {
     "figure": {
      "caption": "`gulp.optimize` calculation provenance graph."
     }
    }
   },
   "outputs": [
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       "<title>N97&#45;&gt;N98</title>\n",
       "<path fill=\"none\" stroke=\"#000000\" d=\"M146.2912,-22.0559C189.122,-26.7135 257.1203,-36.8182 312.5749,-57.4558 329.9835,-63.9345 347.8805,-73.4442 363.4443,-82.795\"/>\n",
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       "<text text-anchor=\"middle\" x=\"269.7956\" y=\"-74.2558\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">INPUT_CALC</text>\n",
       "<text text-anchor=\"middle\" x=\"269.7956\" y=\"-60.2558\" font-family=\"Times,serif\" font-size=\"14.00\" fill=\"#000000\">parameters</text>\n",
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       "</svg>\n"
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       "<graphviz.dot.Digraph at 0x122e43160>"
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     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graph = Graph(graph_attr={'size': \"6,8!\", \"rankdir\": \"LR\"})\n",
    "graph.add_node(calcnode_opt)\n",
    "graph.add_incoming(calcnode_opt, annotate_links=\"both\")\n",
    "graph.add_outgoing(calcnode_opt, annotate_links=\"both\")\n",
    "graph.graphviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "```json\n",
       "{\n",
       "  \"errors\": [],\n",
       "  \"opt_type\": \"bulk\",\n",
       "  \"warnings\": [],\n",
       "  \"energy_units\": \"eV\",\n",
       "  \"final_energy\": -17.47113113,\n",
       "  \"gulp_version\": \"4.5.3\",\n",
       "  \"parser_class\": \"GulpOptParser\",\n",
       "  \"opt_succeeded\": true,\n",
       "  \"parser_errors\": [],\n",
       "  \"initial_energy\": -0.32809466,\n",
       "  \"parser_version\": \"0.9.0b5\",\n",
       "  \"opt_time_second\": 0.3676,\n",
       "  \"parser_warnings\": [],\n",
       "  \"total_time_second\": 0.3677,\n",
       "  \"final_primitive_energy\": -17.47113113,\n",
       "  \"peak_dynamic_memory_mb\": 0.54,\n",
       "  \"initial_primitive_energy\": -0.32809466\n",
       "}\n",
       "```"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_json(calcnode_opt.outputs.results.attributes)"
   ]
  }
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