{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "89b4f78a-ba2c-4013-872c-f22d7d726126",
   "metadata": {},
   "outputs": [],
   "source": [
    "# useful to autoreload the module without restarting the kernel\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0d23bfcf-76e0-466f-a445-6ceb60586032",
   "metadata": {},
   "outputs": [],
   "source": [
    "from mppi import InputFiles as I, Calculators as C, Datasets as D, Utilities as U, Parsers as P\n",
    "from mppi.Calculators import Tools\n",
    "from mppi.Datasets import PostProcessing as PP\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5f09db40-b2df-4ea1-8c1f-5fe90f51fa5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "omp = 1\n",
    "mpi = 4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a889ff5-5679-43c1-9654-f2736e22bf74",
   "metadata": {},
   "source": [
    "# Analysis of the electron-phonon coupling "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbd61412-64c3-4daf-ae14-ead1a879cd07",
   "metadata": {},
   "source": [
    "We analyze the effects of the electron-phonon coupling in the electronic and optical properties\n",
    "of bulk Si.\n",
    "\n",
    "This analysis is base on the web page : https://www.yambo-code.eu/wiki/index.php/Electron_Phonon_Coupling\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c4e2fed2-62d6-46e4-a229-5f3818034f61",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_dir = 'Electron_phonon_Si'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de06e44f-401e-4ae4-9b3c-abde112760ae",
   "metadata": {},
   "source": [
    "Due to the way in which the ph.x is implemented it is more convenient to run each step of the calculations\n",
    "in a specific folder. So the prefix of all the computations is the same but they are exectuded in differen paths. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17d09de0-c03a-44ba-ba60-c3fcfef00088",
   "metadata": {},
   "source": [
    "## SCF and NSCF calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "62b8132b-6053-42d4-a75c-ff786e9f963c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize a QuantumESPRESSO calculator with scheduler direct\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'scheduler': 'direct',\n",
       " 'mpi': 4,\n",
       " 'omp_num_threads': 1,\n",
       " 'executable': 'pw.x',\n",
       " 'skip': True,\n",
       " 'clean_restart': True,\n",
       " 'dry_run': False,\n",
       " 'wait_end_run': True,\n",
       " 'activate_BeeOND': False,\n",
       " 'verbose': True}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rr = C.RunRules(mpi=mpi,omp_num_threads=omp)\n",
    "code = C.QeCalculator(rr)\n",
    "code.global_options()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9cf96e5-2b3d-4c99-a0df-c235345c7788",
   "metadata": {},
   "source": [
    "First we perform a scf calculation on a 8x8x8 k grid to ensure that the electronic density of the GS is converged.\n",
    "\n",
    "The convergence threshold is set to 1e-12, this value and k grid are loosend w.r.t. the paramteres used in the original\n",
    "tutorial to redcue computational time.\n",
    "\n",
    "Note that, following the Yambo tutorial, the geometry of the lattice is set using ibrav=0 with the explicit values of the cell\n",
    "parameters. This is done to avoid possible incompatibility between the PW and Yambo conventions for the FCC lattice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "60227f7e-f279-4668-85f4-cf1d73b2eb07",
   "metadata": {},
   "outputs": [],
   "source": [
    "prefix = 'si'\n",
    "name = 'si.scf'\n",
    "inp= I.PwInput(file='IO_files/Input_for_electron_phonon_Si_tutorial/si.scf.in')\n",
    "inp.set_prefix(prefix)\n",
    "inp.set_pseudo_dir('pseudos',abs_path=True)\n",
    "#print(inp.convert_string())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0ad15249-6ddb-475e-92cf-5e498ab3e92d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skip the run of si.scf\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/home/marco/Applications/MPPI/sphinx_source/tutorials/Electron_phonon_Si/scf/si.save/data-file-schema.xml'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scf_run_dir = os.path.join(run_dir,'scf')\n",
    "results = code.run(input=inp,run_dir=scf_run_dir,name=name)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "021a202d-1642-4e85-8a87-f6f6392d641b",
   "metadata": {},
   "source": [
    "Then we perform a nscf calculation on a smaller 4x4x4 grid with 12 bands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ecf97276-2b7c-4d33-a822-683fecf601fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "inp.set_nscf(12,force_symmorphic=True,conv_thr=1e-12)\n",
    "inp.set_kpoints(points=[4,4,4])\n",
    "#print(inp.convert_string())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ec8f159c-c221-4c66-95c1-fd2b25ae11ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skip the run of si\n",
      "The folder /home/marco/Applications/MPPI/sphinx_source/tutorials/Electron_phonon_Si/nscf/si.save already exists. Source_dir Electron_phonon_Si/scf/si.save not copied\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/home/marco/Applications/MPPI/sphinx_source/tutorials/Electron_phonon_Si/nscf/si.save/data-file-schema.xml'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nscf_run_dir = os.path.join(run_dir,'nscf')\n",
    "results = code.run(input=inp,run_dir=nscf_run_dir,name=prefix,source_dir=os.path.join(scf_run_dir,prefix+'.save'))\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6ac47e50-5e84-4bd1-b5db-5e079ea9840e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse file : /home/marco/Applications/MPPI/sphinx_source/tutorials/Electron_phonon_Si/nscf/si.save/data-file-schema.xml\n"
     ]
    }
   ],
   "source": [
    "data = P.PwParser(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a5233c63-d450-4584-a2d4-0de1ac124e52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.   , -0.   , -0.   ],\n",
       "       [-0.125, -0.125,  0.125],\n",
       "       [ 0.25 ,  0.25 , -0.25 ],\n",
       "       [-0.25 , -0.   , -0.   ],\n",
       "       [ 0.125,  0.375, -0.375],\n",
       "       [-0.   ,  0.25 , -0.25 ],\n",
       "       [ 0.5  , -0.   , -0.   ],\n",
       "       [ 0.5  , -0.25 , -0.   ]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kpoints=-data.kpoints\n",
    "#kpoints[4] = np.array([-0.375000000,-0.125000000,0.125000000])\n",
    "kpoints"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74a943db-4638-46ce-a7bb-4fdd1341a177",
   "metadata": {},
   "source": [
    "## Phonon calculations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42ce8e88-d4ca-49bb-841e-b90c1209a377",
   "metadata": {},
   "source": [
    "With this calculation we can compute the dynamical matrix elements and the dvscf files, these quantities are the \n",
    "analougous of the GS density for the phonon calculations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "ba1a585f-c7fa-4f45-ba3f-7878777e8199",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize a QuantumESPRESSO calculator with scheduler direct\n"
     ]
    }
   ],
   "source": [
    "rr = C.RunRules(mpi=mpi,omp_num_threads=omp)\n",
    "code_ph = C.QeCalculator(rr,executable='ph.x')\n",
    "#code_ph.global_options()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6182f23b-8f43-40da-a274-2e67c45d9d31",
   "metadata": {},
   "outputs": [],
   "source": [
    "prefix = 'si'\n",
    "name = 'si.phonon'\n",
    "inp = I.PhInput()\n",
    "inp.set_prefix(prefix)\n",
    "inp['inputph']['fildvscf'] = \"'si-dvscf'\"\n",
    "inp['inputph']['fildyn'] = \"'si.dyn'\"\n",
    "inp['inputph']['electron_phonon'] = \"'dvscf'\"\n",
    "inp['inputph']['epsil'] = '.true.'\n",
    "inp.set_kpoints(Tools.build_pw_klist(kpoints))\n",
    "#print(inp.convert_string())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "85032ef7-0de0-473e-8cd2-01e115d3ac6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "create the run_dir folder : 'Electron_phonon_Si/phonon'\n",
      "copy source_dir Electron_phonon_Si/scf/si.save in the /home/marco/Applications/MPPI/sphinx_source/tutorials/Electron_phonon_Si/phonon/si.save\n",
      "run command: mpirun -np 4 ph.x -inp si.phonon.in > si.phonon.log\n",
      "computation si.phonon is running...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Note: The following floating-point exceptions are signalling: IEEE_DENORMAL\n",
      "Note: The following floating-point exceptions are signalling: IEEE_DENORMAL\n",
      "Note: The following floating-point exceptions are signalling: IEEE_DENORMAL\n",
      "Note: The following floating-point exceptions are signalling: IEEE_UNDERFLOW_FLAG IEEE_DENORMAL\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computation si.phonon ended\n"
     ]
    }
   ],
   "source": [
    "ph_run_dir = os.path.join(run_dir,'phonon')\n",
    "results = code_ph.run(input=inp,run_dir=ph_run_dir,name=name,source_dir=os.path.join(scf_run_dir,prefix+'.save'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "427735a2-07bd-484c-9259-2cd70b26b2e0",
   "metadata": {},
   "source": [
    "Once that the si.dyn* files and the dvscf files in the _ph0_ have been computed we can calculate the electron-phonon matrix elements. \n",
    "\n",
    "We copy these files in the run_dir of the dvscf computation for the evaluation of the electron-phonon matrix elements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "83bbcef2-31e5-49b2-9d7c-5f766a73e296",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dvscf_run_dir = os.path.join(run_dir,'dvscf')\n",
    "if not os.path.isdir(dvscf_run_dir) : os.mkdir(dvscf_run_dir)\n",
    "os.system('cp -r Electron_phonon_Si/phonon/_ph0/ Electron_phonon_Si/phonon/si.dyn* Electron_phonon_Si/dvscf')\n",
    "os.system('cp -r Electron_phonon_Si/nscf/si.save/ Electron_phonon_Si/dvscf/')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "befcf0db-3b5e-470f-855a-6e5848ce9ae9",
   "metadata": {},
   "source": [
    "In this case we use the nscf computations as starting point for the electronic quantities. Note that the calculator \n",
    "uses the option clean_restart=False. otherwise the dyn and ph0 files are erased."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5847605b-9aec-45ab-b4aa-67a26cff3be7",
   "metadata": {},
   "outputs": [],
   "source": [
    "prefix = 'si'\n",
    "name = 'si.dvscf'\n",
    "inp = I.PhInput()\n",
    "inp.set_prefix(prefix)\n",
    "inp['inputph']['fildvscf'] = \"'si-dvscf'\"\n",
    "inp['inputph']['fildyn'] = \"'si.dyn'\"\n",
    "inp['inputph']['electron_phonon'] = \"'yambo'\"\n",
    "inp['inputph']['trans'] = '.false.'\n",
    "inp.set_kpoints(Tools.build_pw_klist(kpoints))\n",
    "#print(inp.convert_string())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7720aa30-f891-440b-9ae5-ce01a3030927",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run performed starting from existing results\n",
      "run command: mpirun -np 4 ph.x -inp si.dvscf.in > si.dvscf.log\n",
      "computation si.dvscf is running...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Note: The following floating-point exceptions are signalling: IEEE_DENORMAL\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computation si.dvscf ended\n"
     ]
    }
   ],
   "source": [
    "results = code_ph.run(input=inp,run_dir=dvscf_run_dir,name=name,clean_restart=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "157f8ae2-4134-404e-ba2b-780ee96bae94",
   "metadata": {},
   "source": [
    "## Import in yambo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55a0ce14-bb5e-4bd4-8980-10de400ed605",
   "metadata": {},
   "source": [
    "We create the yambo dir using the make_p2y function of the module Tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "db38f24a-cd41-45eb-b79a-b962b3703ec9",
   "metadata": {},
   "outputs": [],
   "source": [
    "yambo_dir = 'Electron_phonon_Si/yambo'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d30255dc-2782-4cbe-83e9-250fb9ea5b42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Create the folder path Electron_phonon_Si/yambo\n",
      "Executing command: cd Electron_phonon_Si/yambo; p2y -I ../nscf/si.save\n"
     ]
    }
   ],
   "source": [
    "Tools.make_p2y(yambo_dir=yambo_dir,input_dir='Electron_phonon_Si/nscf/si.save')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43091693-582a-46a5-85e9-d1829a4a54e0",
   "metadata": {},
   "source": [
    "Then a link of the elph_dir in the yambo run_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0d9bd2a3-2234-4f3f-9fb7-12b30b909194",
   "metadata": {},
   "outputs": [],
   "source": [
    "elph_dir = 'Electron_phonon_Si/dvscf/elph_dir'\n",
    "if not os.path.isdir('Electron_phonon_Si/yambo/elph_dir'):\n",
    "    src = os.path.abspath(elph_dir)\n",
    "    dest = os.path.abspath('Electron_phonon_Si/yambo/elph_dir')\n",
    "    os.symlink(src,dest,target_is_directory=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8126c5f8-9f2d-412a-a831-6e4807757655",
   "metadata": {},
   "source": [
    "and we build the r_setup "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2369b087-354a-43aa-a061-49a7bb0170b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Build the r_setup in the yambo_dir path Electron_phonon_Si/yambo\n"
     ]
    }
   ],
   "source": [
    "Tools.build_r_setup(yambo_dir=yambo_dir,yambo_command='yambo_ph -J elph_dir')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b00324d3-3e49-4a0d-8ad5-8f5d23f3bc45",
   "metadata": {},
   "source": [
    "We use ypp_ph to generate the electron-phonon database that can be used by yambo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e65f02b8-74ad-4d04-a96c-5edf37a03053",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'args': 'ypp_ph -g g',\n",
       " 'folder': 'Electron_phonon_Si/yambo',\n",
       " 'filename': 'yambo.in',\n",
       " 'arguments': ['gkkp'],\n",
       " 'variables': {'PHfreqF': 'none', 'PHmodeF': 'none', 'DBsPATH': 'elph_dir/'}}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inp = I.YamboInput(args='ypp_ph -g g',folder=yambo_dir)\n",
    "inp.set_scalar_variables(DBsPATH='elph_dir/')\n",
    "inp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0b1fd995-f99b-4d86-9c75-9a83997ed7e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize a Yambo calculator with scheduler direct\n"
     ]
    }
   ],
   "source": [
    "rr = C.RunRules(mpi=mpi,omp_num_threads=omp)\n",
    "code = C.YamboCalculator(rr,executable='ypp_ph')\n",
    "#code.global_options()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3e479a5c-d7bc-4e7a-9930-865a95817cb3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run command: mpirun -np 4 ypp_ph -F GKKP.in -J GKKP -C GKKP\n",
      "computation GKKP is running...\n",
      "computation GKKP ended\n",
      "\n",
      "        There are no o-* files.\n",
      "        Maybe you have performed a computation that does not create any output file or wait_end_run\n",
      "        and/or the dry_run option are active.\n",
      "        Otherwise a possible error has occured during the computation\n",
      "        \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'output': {},\n",
       " 'report': 'Electron_phonon_Si/yambo/GKKP/r-GKKP_gkkp_gkkp_db',\n",
       " 'dft': 'Electron_phonon_Si/yambo/SAVE/ns.db1',\n",
       " 'elph_gkkp': 'Electron_phonon_Si/yambo/GKKP/ndb.elph_gkkp'}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name= 'GKKP'\n",
    "code.run(input=inp,name=name,run_dir=yambo_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df4d2bae-0417-4681-b654-46d9d9d46e10",
   "metadata": {},
   "source": [
    "## Quasi-particle band structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "73707a9a-e8b2-4ef9-b012-39a1ab74ea7b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize a Yambo calculator with scheduler direct\n"
     ]
    }
   ],
   "source": [
    "rr = C.RunRules(mpi=mpi,omp_num_threads=omp)\n",
    "code = C.YamboCalculator(rr,executable='yambo_ph')\n",
    "#code.global_options()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7086a347-d954-4da9-81d9-ab8ff076da00",
   "metadata": {},
   "source": [
    "We include the path of the folder with e-p matrix elements using the -J option. Alternatively we could copy the\n",
    "e-p database in the SAVE folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "03e6e872-c107-4ed5-b325-03819f74ff9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "run_dir = 'Electron_phonon_Si/yambo'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e2b68b8b-75e9-439c-b5ee-a80b9d84b6a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'args': 'yambo_ph -g n -p fan -c ep -V gen -J GKKP',\n",
       " 'folder': 'Electron_phonon_Si/yambo',\n",
       " 'filename': 'yambo.in',\n",
       " 'arguments': ['gw0', 'el_ph_corr', 'ExtendOut'],\n",
       " 'variables': {'Nelectro': [8.0, ''],\n",
       "  'ElecTemp': [0.0, 'eV'],\n",
       "  'BoseTemp': [-1.0, 'eV'],\n",
       "  'OccTresh': [1e-05, ''],\n",
       "  'MEM_tresh': [51200.0, 'Kb'],\n",
       "  'SE_Threads': [0.0, ''],\n",
       "  'GDamping': [0.01, 'eV'],\n",
       "  'RandQpts': [0.0, ''],\n",
       "  'DysSolver': 'n',\n",
       "  'GphBRnge': [[1, 12], ''],\n",
       "  'ElPhModes': [[1, 6], ''],\n",
       "  'QPkrange': [[1, 1, 1, 12], '']}}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inp = I.YamboInput(args='yambo_ph -g n -p fan -c ep -V gen -J GKKP',folder=run_dir)\n",
    "inp.set_extendOut()\n",
    "inp.set_array_variables(units='eV',GDamping=0.01)\n",
    "inp.set_kRange(1,1)\n",
    "inp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f10246b6-eed5-4914-9a88-d18ccf6d656f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialize a Dataset with 2 parallel tasks\n"
     ]
    }
   ],
   "source": [
    "Temp = [0,50,100,150,200,250,300]\n",
    "\n",
    "study = D.Dataset(run_dir=run_dir,num_tasks=2,verbose=True,skip=True)\n",
    "study.set_postprocessing_function(PP.yambo_parse_data)\n",
    "\n",
    "for T in Temp:\n",
    "    inp.set_array_variables(units='K',BoseTemp=T)\n",
    "    idd = 'elph_T%s'%T\n",
    "    study.append_run(id=idd,input=inp,runner=code,jobname =[idd,'GKKP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "676268d6-dbb8-4f8a-a571-8a1f1463ce15",
   "metadata": {},
   "outputs": [],
   "source": [
    "#study.runs[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c04bb3cc-7634-468b-ab41-3dba722fe457",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run the selection [0, 1, 2, 3, 4, 5, 6] with the parallel task_groups [[0, 1], [2, 3], [4, 5], [6]] \n",
      "\n",
      "Run the task [0, 1] \n",
      "Skip the run of elph_T50\n",
      "delete folder: Electron_phonon_Si/yambo/elph_T0\n",
      "run command: mpirun -np 4 yambo_ph -F elph_T0.in -J \"elph_T0,GKKP\" -C elph_T0\n",
      "computation elph_T0 is running...\n",
      "computation elph_T0 ended\n",
      "Task [0, 1] ended \n",
      " \n",
      "Run the task [2, 3] \n",
      "Skip the run of elph_T100Skip the run of\n",
      " elph_T150\n",
      "Task [2, 3] ended \n",
      " \n",
      "Run the task [4, 5] \n",
      "Skip the run of elph_T200\n",
      "Skip the run of elph_T250\n",
      "Task [4, 5] ended \n",
      " \n",
      "Run the task [6] \n",
      "Skip the run of elph_T300\n",
      "Task [6] ended \n",
      " \n"
     ]
    }
   ],
   "source": [
    "results = study.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "89e9a98b-01de-406e-841e-4db0a7178e40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2.474098,\n",
       " 2.4741519999999997,\n",
       " 2.473849,\n",
       " 2.472833,\n",
       " 2.4709570000000003,\n",
       " 2.4683100000000002,\n",
       " 2.465083]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gap_G = [results[ind].data.get_gap(k_full=1,band_full=4,verbose=False) for ind in range(len(Temp))]\n",
    "gap_G"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a725d945-6c03-4610-b949-437e2ad5f8e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f7a9902fbb0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Temp,gap_G)\n",
    "plt.scatter(Temp,gap_G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a59e98f-44ee-4e65-843e-cb811b2131b1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}