yambo_wannier90/1_Band_interpolation_W90_DFT.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b07f7d9f",
   "metadata": {},
   "source": [
    "# Automated DFT band interpolation via Wannierization\n",
    "\n",
    "In this example we show how to obtain the DFT interpolated bands by means of the `aiida-wannier90` plugin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dc9bce04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Profile<uuid='3745313b017b418697d37cbf16c4e7ef' name='generic'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from aiida import orm, load_profile\n",
    "load_profile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a4f798fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "from aiida_wannier90_workflows.utils.workflows.builder.serializer import print_builder \n",
    "from aiida_wannier90_workflows.utils.kpoints import get_explicit_kpoints_from_mesh\n",
    "from aiida_wannier90_workflows.utils.workflows.builder.setter import set_parallelization, set_num_bands, set_kpoints\n",
    "from aiida_wannier90_workflows.utils.workflows.builder.submit import submit_and_add_group \n",
    "from aiida_wannier90_workflows.common.types import WannierProjectionType\n",
    "from aiida_wannier90_workflows.workflows import Wannier90BandsWorkChain"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "102b6aef",
   "metadata": {},
   "source": [
    "## minimal inputs needed for protocols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a6909c34",
   "metadata": {},
   "outputs": [],
   "source": [
    "import yaml,io\n",
    "\n",
    "# Read YAML file\n",
    "with open(\"../configuration/codes_localhost_yw90.yaml\", 'r') as stream:\n",
    "    codes = yaml.safe_load(stream)\n",
    "    \n",
    "with open(\"../configuration/resources_localhost.yaml\", 'r') as stream:\n",
    "    resources = yaml.safe_load(stream)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "05b41e3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from aiida.orm import QueryBuilder\n",
    "qb = QueryBuilder()\n",
    "qb.append(orm.Group, filters={'label': 'Silicon/bulk'}, tag='group')\n",
    "qb.append(orm.StructureData, with_group='group')\n",
    "\n",
    "loaded_structure_id = qb.all()[0][0].pk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "72641b00",
   "metadata": {},
   "outputs": [],
   "source": [
    "options = {\n",
    "    'pseudo_family':\"PseudoDojo/0.4/PBE/SR/standard/upf\",\n",
    "    'protocol':'fast',\n",
    "    #'parent_id':274, #not necessary to set; if you want it, take ytheour previously nscf id (pk) to skip the DFT part.\n",
    "    'structure_id':loaded_structure_id,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2ab7a336",
   "metadata": {},
   "outputs": [],
   "source": [
    "projections=\"analytic\"\n",
    "\n",
    "if projections==\"analytic\":\n",
    "    wannier_projection_type=WannierProjectionType.ANALYTIC\n",
    "else:\n",
    "    WannierProjectionType.ATOMIC_PROJECTORS_QE \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b9b44aed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summary of key input parameters:\n",
      "  Formula: Si2\n",
      "  PseudoFamily: PseudoDojo/0.4/PBE/SR/standard/upf\n",
      "  ElectronicType: METAL\n",
      "  SpinType: NONE\n",
      "  WannierProjectionType: ANALYTIC\n",
      "  WannierDisentanglementType: SMV\n",
      "  WannierFrozenType: ENERGY_FIXED\n",
      "  num_bands: 12\n",
      "  num_wann: 8\n",
      "  mp_grid: [5, 5, 5]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "builder = Wannier90BandsWorkChain.get_builder_from_protocol(\n",
    "        codes=codes,\n",
    "        structure=orm.load_node(options[\"structure_id\"]),\n",
    "        pseudo_family=options[\"pseudo_family\"],\n",
    "        protocol=\"fast\",\n",
    "        projection_type=wannier_projection_type,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "70437464",
   "metadata": {},
   "outputs": [],
   "source": [
    "parallelization = dict(\n",
    "    max_wallclock_seconds=24 * 3600,\n",
    "    # num_mpiprocs_per_machine=48,\n",
    "    #npool=4,\n",
    "    num_machines=1,\n",
    ")\n",
    "\n",
    "set_parallelization(\n",
    "    builder,\n",
    "    parallelization=parallelization,\n",
    "    process_class=Wannier90BandsWorkChain,\n",
    ")\n",
    "\n",
    "\n",
    "#### START computational resources settings.\n",
    "\n",
    "builder['nscf']['pw']['metadata']['options'] = resources\n",
    "\n",
    "builder['scf']['pw']['metadata']['options'] = resources\n",
    "\n",
    "builder['pw2wannier90']['pw2wannier90']['metadata']['options'] = resources\n",
    "\n",
    "builder['wannier90']['wannier90']['metadata']['options'] = resources\n",
    "\n",
    "#### END computational resources settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1c37339d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use 4x4x4 kmesh\n",
    "kpoints = get_explicit_kpoints_from_mesh(builder.structure, [8,8,8])\n",
    "set_kpoints(builder, kpoints, process_class=Wannier90BandsWorkChain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c8bffcf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# START projections settings:\n",
    "    \n",
    "set_num_bands(\n",
    "    builder=builder, \n",
    "    num_bands=14,                   # KS states used in the Wannierization\n",
    "    #exclude_bands=range(1,5), \n",
    "    process_class=Wannier90BandsWorkChain)\n",
    "\n",
    "params = builder.wannier90.wannier90.parameters.get_dict()\n",
    "\n",
    "## START explicit atomic projections:\n",
    "if projections==\"analytic\":\n",
    "\n",
    "    del builder.projwfc\n",
    "    builder.wannier90.auto_energy_windows = False\n",
    "    builder.wannier90.shift_energy_windows = True\n",
    "    params['num_wann'] = 8\n",
    "    builder.wannier90.wannier90.projections = orm.List(list=['Si:s','Si:p'])\n",
    "    params.pop('auto_projections', None) # Uncomment this if you want analytic atomic projections\n",
    "\n",
    "    #\n",
    "    # The following line can be also deleted.\n",
    "    builder['pw2wannier90']['pw2wannier90']['parameters'] = orm.Dict(dict={'inputpp': {'atom_proj': False}})\n",
    "\n",
    "## END explicit atomic projections:\n",
    "\n",
    "# optional settings.\n",
    "#params.pop('dis_proj_min', None)\n",
    "#params.pop('dis_proj_max', None)\n",
    "#params['num_wann'] = 16\n",
    "#params['dis_froz_max'] = 2\n",
    "\n",
    "params = orm.Dict(dict=params)\n",
    "builder.wannier90.wannier90.parameters = params\n",
    "\n",
    "# END projections settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e4b78093",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'clean_workdir': False,\n",
      " 'nscf': {'kpoints': '512 kpts<None>',\n",
      "          'kpoints_force_parity': False,\n",
      "          'pw': {'code': 'pw_develop@local_slurm<365>',\n",
      "                 'metadata': {'options': {'max_wallclock_seconds': 3600,\n",
      "                                          'prepend_text': 'export '\n",
      "                                                          'OMP_NUM_THREADS=1',\n",
      "                                          'resources': {'num_cores_per_mpiproc': 1,\n",
      "                                                        'num_machines': 1,\n",
      "                                                        'num_mpiprocs_per_machine': 1}}},\n",
      "                 'parallelization': {'npool': 1},\n",
      "                 'parameters': {'CONTROL': {'calculation': 'nscf',\n",
      "                                            'etot_conv_thr': 0.0002,\n",
      "                                            'forc_conv_thr': 0.001,\n",
      "                                            'restart_mode': 'from_scratch',\n",
      "                                            'tprnfor': True,\n",
      "                                            'tstress': True},\n",
      "                                'ELECTRONS': {'conv_thr': 8e-10,\n",
      "                                              'diago_full_acc': True,\n",
      "                                              'electron_maxstep': 80,\n",
      "                                              'mixing_beta': 0.4,\n",
      "                                              'startingpot': 'file'},\n",
      "                                'SYSTEM': {'degauss': 0.01,\n",
      "                                           'ecutrho': 144.0,\n",
      "                                           'ecutwfc': 36.0,\n",
      "                                           'nbnd': 14,\n",
      "                                           'noinv': True,\n",
      "                                           'nosym': True,\n",
      "                                           'occupations': 'smearing',\n",
      "                                           'smearing': 'cold'}},\n",
      "                 'pseudos': {'Si': 'Si.upf<331>'}}},\n",
      " 'pw2wannier90': {'pw2wannier90': {'code': 'pw2wannier90_develop@local_slurm<366>',\n",
      "                                   'metadata': {'options': {'max_wallclock_seconds': 3600,\n",
      "                                                            'prepend_text': 'export '\n",
      "                                                                            'OMP_NUM_THREADS=1',\n",
      "                                                            'resources': {'num_cores_per_mpiproc': 1,\n",
      "                                                                          'num_machines': 1,\n",
      "                                                                          'num_mpiprocs_per_machine': 1}}},\n",
      "                                   'parameters': {'inputpp': {'atom_proj': False}},\n",
      "                                   'settings': {'cmdline': ['-nk', '1']}}},\n",
      " 'scf': {'kpoints': '512 kpts<None>',\n",
      "         'kpoints_distance': 0.2,\n",
      "         'kpoints_force_parity': False,\n",
      "         'pw': {'code': 'pw_develop@local_slurm<365>',\n",
      "                'metadata': {'options': {'max_wallclock_seconds': 3600,\n",
      "                                         'prepend_text': 'export '\n",
      "                                                         'OMP_NUM_THREADS=1',\n",
      "                                         'resources': {'num_cores_per_mpiproc': 1,\n",
      "                                                       'num_machines': 1,\n",
      "                                                       'num_mpiprocs_per_machine': 1}}},\n",
      "                'parallelization': {'npool': 1},\n",
      "                'parameters': {'CONTROL': {'calculation': 'scf',\n",
      "                                           'etot_conv_thr': 0.0002,\n",
      "                                           'forc_conv_thr': 0.001,\n",
      "                                           'tprnfor': True,\n",
      "                                           'tstress': True},\n",
      "                               'ELECTRONS': {'conv_thr': 8e-10,\n",
      "                                             'electron_maxstep': 80,\n",
      "                                             'mixing_beta': 0.4},\n",
      "                               'SYSTEM': {'degauss': 0.01,\n",
      "                                          'ecutrho': 144.0,\n",
      "                                          'ecutwfc': 36.0,\n",
      "                                          'nosym': False,\n",
      "                                          'occupations': 'smearing',\n",
      "                                          'smearing': 'cold'}},\n",
      "                'pseudos': {'Si': 'Si.upf<331>'}}},\n",
      " 'structure': 'Si2<371>',\n",
      " 'wannier90': {'auto_energy_windows': False,\n",
      "               'auto_energy_windows_threshold': 0.9,\n",
      "               'shift_energy_windows': True,\n",
      "               'wannier90': {'code': 'wannier90@local_slurm<369>',\n",
      "                             'kpoints': '512 kpts<None>',\n",
      "                             'metadata': {'options': {'max_wallclock_seconds': 3600,\n",
      "                                                      'prepend_text': 'export '\n",
      "                                                                      'OMP_NUM_THREADS=1',\n",
      "                                                      'resources': {'num_cores_per_mpiproc': 1,\n",
      "                                                                    'num_machines': 1,\n",
      "                                                                    'num_mpiprocs_per_machine': 1}}},\n",
      "                             'parameters': {'bands_plot': True,\n",
      "                                            'conv_tol': 2e-05,\n",
      "                                            'conv_window': 1,\n",
      "                                            'dis_conv_tol': 2e-05,\n",
      "                                            'dis_froz_max': 2.0,\n",
      "                                            'dis_num_iter': 400,\n",
      "                                            'mp_grid': [8, 8, 8],\n",
      "                                            'num_bands': 14,\n",
      "                                            'num_cg_steps': 200,\n",
      "                                            'num_iter': 400,\n",
      "                                            'num_wann': 8},\n",
      "                             'projections': ['Si:s', 'Si:p'],\n",
      "                             'settings': {}}}}\n"
     ]
    }
   ],
   "source": [
    "print_builder(builder)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3684e7f",
   "metadata": {},
   "source": [
    "### Computational resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9e1cf68e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from aiida.engine import submit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78614e86",
   "metadata": {},
   "outputs": [],
   "source": [
    "run = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "196e4b6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "uuid: 1da58b0c-67e7-46d9-945b-6a5c32ae4b73 (pk: 1441) (aiida.workflows:wannier90_workflows.bands)\n"
     ]
    }
   ],
   "source": [
    "if run:\n",
    "    print('run is already running -> {}'.format(run.pk))\n",
    "    print('sure that you want to run again?, if so, copy the else instruction in the cell below and run!')\n",
    "else:\n",
    "    run = submit(builder)\n",
    "\n",
    "print(run)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2700857f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[22m2024-02-19 16:59:14 [703 | REPORT]: [1441|Wannier90BandsWorkChain|run_seekpath]: launching seekpath: Si2 -> Si2\n",
      "2024-02-19 16:59:15 [704 | REPORT]: [1441|Wannier90BandsWorkChain|run_scf]: launching PwBaseWorkChain<1449> in scf mode\n",
      "2024-02-19 16:59:16 [705 | REPORT]:   [1449|PwBaseWorkChain|run_process]: launching PwCalculation<1452> iteration #1\n",
      "2024-02-19 17:00:08 [706 | REPORT]:   [1449|PwBaseWorkChain|results]: work chain completed after 1 iterations\n",
      "2024-02-19 17:00:08 [707 | REPORT]:   [1449|PwBaseWorkChain|on_terminated]: remote folders will not be cleaned\n",
      "2024-02-19 17:00:08 [708 | REPORT]: [1441|Wannier90BandsWorkChain|run_nscf]: launching PwBaseWorkChain<1459> in nscf mode\n",
      "2024-02-19 17:00:10 [709 | REPORT]:   [1459|PwBaseWorkChain|run_process]: launching PwCalculation<1462> iteration #1\n",
      "2024-02-19 17:01:52 [710 | REPORT]:   [1459|PwBaseWorkChain|results]: work chain completed after 1 iterations\n",
      "2024-02-19 17:01:52 [711 | REPORT]:   [1459|PwBaseWorkChain|on_terminated]: remote folders will not be cleaned\n",
      "2024-02-19 17:01:53 [712 | REPORT]: [1441|Wannier90BandsWorkChain|run_wannier90_pp]: launching Wannier90BaseWorkChain<1471> in postproc mode\n",
      "2024-02-19 17:01:54 [713 | REPORT]:   [1471|Wannier90BaseWorkChain|run_process]: launching Wannier90Calculation<1473> iteration #1\n",
      "2024-02-19 17:01:59 [714 | REPORT]:   [1471|Wannier90BaseWorkChain|results]: work chain completed after 1 iterations\n",
      "2024-02-19 17:02:00 [715 | REPORT]:   [1471|Wannier90BaseWorkChain|on_terminated]: remote folders will not be cleaned\n",
      "2024-02-19 17:02:00 [716 | REPORT]: [1441|Wannier90BandsWorkChain|run_pw2wannier90]: launching Pw2wannier90BaseWorkChain<1479>\n",
      "2024-02-19 17:02:01 [717 | REPORT]:   [1479|Pw2wannier90BaseWorkChain|run_process]: launching Pw2wannier90Calculation<1480> iteration #1\n",
      "2024-02-19 17:03:33 [718 | REPORT]:   [1479|Pw2wannier90BaseWorkChain|results]: work chain completed after 1 iterations\n",
      "2024-02-19 17:03:33 [719 | REPORT]:   [1479|Pw2wannier90BaseWorkChain|on_terminated]: remote folders will not be cleaned\n",
      "2024-02-19 17:03:34 [720 | REPORT]: [1441|Wannier90BandsWorkChain|run_wannier90]: launching Wannier90BaseWorkChain<1489>\n",
      "2024-02-19 17:03:35 [721 | REPORT]:   [1489|Wannier90BaseWorkChain|run_process]: launching Wannier90Calculation<1491> iteration #1\n",
      "2024-02-19 17:03:58 [722 | REPORT]:   [1489|Wannier90BaseWorkChain|results]: work chain completed after 1 iterations\n",
      "2024-02-19 17:03:58 [723 | REPORT]:   [1489|Wannier90BaseWorkChain|on_terminated]: remote folders will not be cleaned\n",
      "2024-02-19 17:03:58 [724 | REPORT]: [1441|Wannier90BandsWorkChain|results]: Wannier90BandsWorkChain successfully completed\n",
      "2024-02-19 17:03:59 [725 | REPORT]: [1441|Wannier90BandsWorkChain|on_terminated]: remote folders will not be cleaned\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!verdi process report {run.pk}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9910705",
   "metadata": {},
   "source": [
    "## Plotting results\n",
    "\n",
    "It is also possible to use the command line:\n",
    "\n",
    "```bash\n",
    "aiida-wannier90-workflows plot band 1441 # the Wannier90BandsWorkChain pk\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5353bbba",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#last occupied band index.\n",
    "b = 4 \n",
    "\n",
    "w90_qe = run.outputs.band_structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "6065aa65",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Just a way to have nice plotting.\n",
    "\n",
    "l_x = []\n",
    "l_names = []\n",
    "l_remove = []\n",
    "\n",
    "for i in w90_qe.labels:\n",
    "    if len(l_x)>0:\n",
    "        if i[0] == l_x[-1]+1:\n",
    "            if i[1] == 'GAMMA':\n",
    "                l_names[-1] = l_names[-1]+\"|$\\Gamma$\"\n",
    "            else:\n",
    "                l_names[-1] = l_names[-1]+\"|\"+i[1]\n",
    "            l_remove.append(i[0])\n",
    "        else:    \n",
    "            l_x.append(i[0])\n",
    "            if i[1] == 'GAMMA':\n",
    "                l_names.append(\"$\\Gamma$\")\n",
    "            else:\n",
    "                l_names.append(i[1])\n",
    "    else:    \n",
    "        l_x.append(i[0])\n",
    "        \n",
    "        if i[1] == 'GAMMA':\n",
    "            l_names.append(\"$\\Gamma$\")\n",
    "        else:\n",
    "            l_names.append(i[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8a42e654",
   "metadata": {},
   "outputs": [],
   "source": [
    "w90bands = w90_qe.get_bands()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "148667bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "for j in l_remove:\n",
    "    w90bands = np.delete(w90bands, obj=j, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f800ffa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fcbcd728400>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(figsize=[15,7])\n",
    "plt.plot(w90bands-max(w90_qe.get_bands()[:,b-1]),'--',color='red')\n",
    "\n",
    "plt.plot(w90bands[0,b-1]-max(w90_qe.get_bands()[:,b-1]),'--',color='red',label = 'W90@QE')\n",
    "plt.ylim(-10,10)\n",
    "\n",
    "plt.grid()\n",
    "plt.xticks(l_x,l_names)\n",
    "plt.tick_params(axis='both',labelsize=20)\n",
    "plt.xlim(0,max(l_x))\n",
    "plt.ylabel(\"eV\",fontsize=20)\n",
    "#plt.ylim(-2,5)\n",
    "plt.legend(fontsize=20)\n",
    "\n",
    "#plt.savefig('plot_.pdf')"
   ]
  }
 ],
 "metadata": {
  "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}