{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Intermediate Tutorial\n",
    "\n",
    "In this tutorial you will learn how to define the non-analytical constants for the Data types presented in the [previous tutorial](./basic.ipynb).\n",
    "\n",
    "## Polar insulators\n",
    "\n",
    "The phonon band structure of bulk polar insulators, which we define to be insulators with different atomic species (e.g. AlAs, BaTiO{sub}`3`),\n",
    "needs extra quantities to be interpolated correctly around the gamma point. These quantities are the so called __non-analytical constants__. They are composed by two tensors:\n",
    "\n",
    "1. __Dielectric tensor__: this is the high-frequency dielectric tensor of the material, $\\epsilon^{\\infty}_{ij}$.\n",
    "2. __Born effective charges tensor__: these are effective charges of the nuclei, usually expressed in unit of charge $e$, $Z^{*}_{I,ij}$\n",
    "\n",
    "The indices $i$ and $j$ refer to the three Cartesian axes, while $I$ is the atomic index.\n",
    "\n",
    "```{important}\n",
    "The tensors $Z^{*}_{I,ij}$ are not symmetric with the exchange of $i$ and $j$!\n",
    "```\n",
    "\n",
    "```{admonition} Convention\n",
    ":class: important \n",
    "In `Phonopy` and `aiida-phonopy`, the convention for $Z^{*}_{I,ij}$ indices is as follow:\n",
    "\n",
    "1. Atomic index.\n",
    "2. Polarization index.\n",
    "3. Atomic displacement index.\n",
    "```\n",
    "\n",
    "Let's show this with _AlAs_. On the same lines of the [basic tutorial](./basic.ipynb), we define \n",
    "{py:class}`~aiida_phonopy.data.preprocess.PreProcessData`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:64: AiidaDeprecationWarning: The `Code` class is deprecated. To create an instance, use the `aiida.orm.nodes.data.code.installed.InstalledCode` or `aiida.orm.nodes.data.code.portable.PortableCode` for a \"remote\" or \"local\" code, respectively. If you are using this class to compare type, e.g. in `isinstance`, use `aiida.orm.nodes.data.code.abstract.AbstractCode`. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:77: AiidaDeprecationWarning: The `Code` plugin is deprecated, use the `InstalledCode` (`core.code.remote`) instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:487: AiidaDeprecationWarning: `Code.set_remote_computer_exec` method is deprecated, use `InstalledCode`. (this will be removed in v3)\n",
      "  warn_deprecation('`Code.set_remote_computer_exec` method is deprecated, use `InstalledCode`.', version=3)\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:556: AiidaDeprecationWarning: `Code.is_local` method is deprecated, use a `PortableCode` instance and check the type. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:517: AiidaDeprecationWarning: `Code.get_remote_computer` method is deprecated, use the `computer` attribute instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:507: AiidaDeprecationWarning: `Code.get_remote_exec_path` method is deprecated, use `InstalledCode.filepath_executable` instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# ================= IMPORTS ======================== #\n",
    "from local_module import load_temp_profile\n",
    "from aiida.plugins import DataFactory, CalculationFactory\n",
    "from aiida.orm import load_code, Dict\n",
    "# If you download this file, you can run it with your own profile.\n",
    "# Put these lines instead:\n",
    "# from aiida import load_profile\n",
    "# load_profile()\n",
    "load_temp_profile(\n",
    "    name=\"intermidiate-tutorial\",\n",
    "    add_computer=True,\n",
    "    add_phonopy_code=True,\n",
    ")\n",
    "\n",
    "StructureData = DataFactory(\"core.structure\")\n",
    "PreProcessData = DataFactory(\"phonopy.preprocess\")\n",
    "PhonopyData = DataFactory(\"phonopy.phonopy\")\n",
    "PhonopyCalculation = CalculationFactory(\"phonopy.phonopy\")\n",
    "# ============== STRUCTURE DATA ==================== #\n",
    "a = 2.839\n",
    "cell = [[0,a,a],[a,0,a],[a,a,0]]\n",
    "structure = StructureData(cell=cell)\n",
    "structure.append_atom(position=(0,0,0), symbols=\"Al\")\n",
    "structure.append_atom(position=(0.5*a,0.5*a,0.5*a), symbols=\"As\")\n",
    "# ============= PREPROCESS DATA ==================== #\n",
    "supercell_matrix = [[-1,1,1],[1,-1,1],[1,1,-1]] # standard cell 8 atoms\n",
    "preprocess_data =  PreProcessData(structure=structure, supercell_matrix=supercell_matrix)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could go through and compute the forces for the displaced structure. The result would be:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_of_forces = {\n",
    "    \"forces_1\": \n",
    "    [\n",
    "        [-0.0988347466,    0.0000000000,    0.0000000000],\n",
    "        [-0.0200237511,    0.0000000000,    0.0000000000],\n",
    "        [ 0.0135502277,    0.0000000000,    0.0000000000],\n",
    "        [ 0.0135502277,    0.0000000000,    0.0000000000],\n",
    "        [ 0.0230530248,    0.0183687320,    0.0183687320],\n",
    "        [ 0.0230530248,   -0.0183687320,   -0.0183687320],\n",
    "        [ 0.0228262535,    0.0179280450,   -0.0179280450],\n",
    "        [ 0.0228262535,   -0.0179280450,    0.0179280450],\n",
    "    ],\n",
    "    \"forces_2\": \n",
    "    [\n",
    "        [ 0.0228136551,    0.0179285592,    0.0179285592],\n",
    "        [ 0.0228136551,   -0.0179285592,   -0.0179285592],\n",
    "        [ 0.0230645948,   -0.0183682178,    0.0183682178],\n",
    "        [ 0.0230645948,    0.0183682178,   -0.0183682178],\n",
    "        [-0.1025024252,    0.0000000000,    0.0000000000],\n",
    "        [-0.0044662632,    0.0000000000,    0.0000000000],\n",
    "        [ 0.0076060944,    0.0000000000,    0.0000000000],\n",
    "        [ 0.0076060944,    0.0000000000,    0.0000000000],\n",
    "    ]\n",
    "}\n",
    "\n",
    "phonopy_data =  PhonopyData(preprocess_data=preprocess_data)\n",
    "phonopy_data.set_forces(dict_of_forces=dict_of_forces)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We may want to try to compute the band structure of the phonons directly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder = PhonopyCalculation.get_builder()\n",
    "builder.code = load_code(\"phonopy@local_direct\") # WARNING! You may redefine this\n",
    "builder.phonopy_data = phonopy_data\n",
    "builder.parameters = Dict({\"band\":\"auto\"})"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Submit the calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:556: AiidaDeprecationWarning: `Code.is_local` method is deprecated, use a `PortableCode` instance and check the type. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:517: AiidaDeprecationWarning: `Code.get_remote_computer` method is deprecated, use the `computer` attribute instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:556: AiidaDeprecationWarning: `Code.is_local` method is deprecated, use a `PortableCode` instance and check the type. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:507: AiidaDeprecationWarning: `Code.get_remote_exec_path` method is deprecated, use `InstalledCode.filepath_executable` instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are the final results:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'remote_folder': <RemoteData: uuid: b97d1cf8-f241-4842-8d94-ec6256e31ff2 (pk: 5)>,\n",
       " 'retrieved': <FolderData: uuid: bbc1905e-3dbe-402e-95b2-36e76859508c (pk: 6)>,\n",
       " 'output_parameters': <Dict: uuid: c1ff23d4-21e6-491c-821d-cbdef6c16178 (pk: 7)>,\n",
       " 'phonon_bands': <BandsData: uuid: bdd6ba48-fd08-4b56-8b5f-9a9b1f1f26dc (pk: 8)>}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from aiida.engine import run_get_node\n",
    "\n",
    "results, node = run_get_node(builder)\n",
    "print(\"These are the final results:\")\n",
    "results"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the phonon dispersion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "node.outputs.phonon_bands.show_mpl()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks fine, isn't it?\n",
    "\n",
    "Actually, there is a subtle discrepancy. If one would compare this with experiments, a phonon mode seems to miss at $\\Gamma$! \n",
    "Try to answer the following question before continuing the tutorial.\n",
    "\n",
    "```{admonition} Question: Can you explain why? \n",
    ":class: tip dropdown\n",
    "\n",
    "The interpolation is missing the _long-range_ contributions. An analytical model can be devised to account for these interactions, often called **dipole-dipole** approximation. This accounts for up to the dipole expansion, meaning accounting for the dielectric and Born effective charges (the dipoles) tensors. Higher order contribution can be added, such as quadrupoles and octupoles (see e.g. [Royo et al., Phys. Rev. Lett., **125** (2020)](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.125.217602)).\n",
    "```\n",
    "\n",
    "Let's now add the non-analytical contribution (NAC). Imagine we have already computed such quantities.\n",
    "\n",
    ":::{admonition} NAC calculation\n",
    ":class: tip dropdown\n",
    "\n",
    "The calculation of these quantities can be done in different ways. Usually DFPT implementations are used, or alternatively finite differences upon small electric fields.\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "phonopy_data_nac = phonopy_data.clone() # the `phonopy_data` is now immutable in AiiDA!\n",
    "\n",
    "born_charges = [\n",
    "    [\n",
    "        [+2.1576, 0, 0], \n",
    "        [0, +2.1576, 0], \n",
    "        [0, 0, +2.1576]\n",
    "    ],\n",
    "    [\n",
    "        [-2.1576, 0, 0],\n",
    "        [0, -2.1576, 0],\n",
    "        [0, 0, -2.1576]\n",
    "    ],\n",
    "]\n",
    "\n",
    "dielectric = [\n",
    "    [9.4626, 0, 0],\n",
    "    [0, 9.4626, 0],\n",
    "    [0, 0, 9.4626],\n",
    "]\n",
    "\n",
    "phonopy_data_nac.set_born_charges(born_charges)\n",
    "phonopy_data_nac.set_dielectric(dielectric)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Does it have the NAC now? Let's ask!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phonopy_data_nac.has_nac_parameters()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hurray!\n",
    "\n",
    "Now we can recompute the band structure and see if something changes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:556: AiidaDeprecationWarning: `Code.is_local` method is deprecated, use a `PortableCode` instance and check the type. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:517: AiidaDeprecationWarning: `Code.get_remote_computer` method is deprecated, use the `computer` attribute instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:556: AiidaDeprecationWarning: `Code.is_local` method is deprecated, use a `PortableCode` instance and check the type. (this will be removed in v3)\n",
      "  warn_deprecation(\n",
      "/opt/conda/lib/python3.10/site-packages/aiida/orm/nodes/data/code/legacy.py:507: AiidaDeprecationWarning: `Code.get_remote_exec_path` method is deprecated, use `InstalledCode.filepath_executable` instead. (this will be removed in v3)\n",
      "  warn_deprecation(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "builder.phonopy_data = phonopy_data_nac\n",
    "\n",
    "results, node = run_get_node(builder)\n",
    "node.outputs.phonon_bands.show_mpl()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A huge splitting at $\\Gamma$ appeared! This is often referred to as __LO-TO splitting__. \n",
    "\n",
    "If you want to learn more features, continue with the [next tutorial](./advanced.ipynb)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": "3.10.18"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "d4d1e4263499bec80672ea0156c357c1ee493ec2b1c70f0acce89fc37c4a6abe"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}