{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize modulated structures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "962bf063b664449192a3b90ce346efe0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import phonopy\n",
    "from phonopy import Phonopy\n",
    "from phonopy.interface.vasp import write_vasp\n",
    "from pymatgen.core import Structure\n",
    "from pymatgen.io.phonopy import get_pmg_structure, get_phonopy_structure\n",
    "\n",
    "from spgrep_modulation.modulation import Modulation\n",
    "from spgrep_modulation.visualize import viewer, get_local_and_ghost_sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = Path().resolve().parent.parent / \"tests\" / \"phonopy_mp-2998.yaml.xz\"\n",
    "ph = phonopy.load(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "qpoint = [0.5, 0, 0]  # X point\n",
    "dimension = [2, 2, 2]\n",
    "\n",
    "md = Modulation.with_supercell_and_symmetry_search(\n",
    "    dynamical_matrix=ph.dynamical_matrix,\n",
    "    supercell_matrix=dimension,\n",
    "    qpoint=qpoint,\n",
    "    factor=ph.unit_conversion_factor,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Frequency (THz): -4.88\n",
      "Irrep shape: (16, 2, 2)\n"
     ]
    }
   ],
   "source": [
    "# Degenerated imaginary mode\n",
    "frequency_index = 0\n",
    "dim = md.eigenspaces[frequency_index][2].shape[1]\n",
    "print(f\"Frequency (THz): {md.eigvals_to_frequencies(md.eigenspaces[frequency_index][0]):.2f}\")\n",
    "print(f\"Irrep shape: {md.eigenspaces[frequency_index][2].shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_modulated_cells(md: Modulation, frequency_index, idx, max_amplitude, num):\n",
    "    argument = 0\n",
    "    symmetry_adapted_eigvec = md.eigenspaces[frequency_index][1][idx]\n",
    "    amplitudes = np.linspace(-max_amplitude, max_amplitude, num=num, endpoint=True)\n",
    "    modulated_cells = []\n",
    "    for amplitude in amplitudes:\n",
    "        modulation = md._get_displacements(symmetry_adapted_eigvec, amplitude, argument=0)\n",
    "        scaled_modulation = amplitude / np.max(np.abs(modulation)) * modulation\n",
    "        modulated = md.apply_modulation_to_supercell(scaled_modulation)\n",
    "        modulated_cells.append(modulated)\n",
    "    return amplitudes, modulated_cells\n",
    "\n",
    "\n",
    "def save_modulated_cells(modulated_cells, root_dir: str):\n",
    "    root = Path(root_dir)\n",
    "    root.mkdir(exist_ok=True)\n",
    "\n",
    "    num = len(modulated_cells)\n",
    "    # shift list to start with non-modulated cell\n",
    "    shifted = modulated_cells[-num // 2 :] + modulated_cells[: num // 2]\n",
    "    for i, cell in enumerate(shifted):\n",
    "        structure = get_pmg_structure(cell)\n",
    "        structure_with_ghosts = Structure.from_sites(get_local_and_ghost_sites(structure))\n",
    "        cell_with_ghosts = get_phonopy_structure(structure_with_ghosts)\n",
    "\n",
    "        write_vasp(root / f\"POSCAR-{i:03d}\", cell_with_ghosts)\n",
    "        write_vasp(root / f\"POSCAR-{2 * num - 1 - i:03d}\", cell_with_ghosts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "amplitude = 1.0\n",
    "num = 16\n",
    "for idx in range(dim):\n",
    "    _, modulated_cells = get_modulated_cells(md, frequency_index, idx, amplitude, num=num)\n",
    "    save_modulated_cells(modulated_cells, f\"disp-{idx}\")"
   ]
  }
 ],
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