{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mppi import Parsers as P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial of the PwParser class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial describes the usage of the class PwParser of mppi used to extract information for the XML output file data-file-schema produced\n",
    "by pw."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parse of a output file of Silicon "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Follow the tutorial for the QeCalculator to produce the xml file used by the PwParser.__\n",
    "\n",
    "The class is initialized by specifying the name of the xml file including its relative path "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse file : QeCalculator_test/ecut_40.save/data-file-schema.xml\n"
     ]
    }
   ],
   "source": [
    "results = P.PwParser('QeCalculator_test/ecut_40.save/data-file-schema.xml')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When the object is initialized several attributes are set, for instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hartree atomic units'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "{'Si': ['2.808600000000000e1', 'Si.pbe-mt_fhi.UPF']}\n",
      "[['Si', [-1.2875, 1.2875, 1.2875]], ['Si', [1.2875, -1.2875, -1.2875]]]\n",
      "4\n",
      "32\n",
      "2\n"
     ]
    }
   ],
   "source": [
    "print(results.natoms)\n",
    "print(results.atomic_species)\n",
    "print(results.atomic_positions)\n",
    "print(results.nbands)\n",
    "print(results.nkpoints)\n",
    "print(results.spin_degen)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can print the ks energies and weight for each kpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0. 0. 0.] [-0.21237932  0.22480586  0.22480586  0.22480586] [0.00925926]\n",
      "[-0.16666667  0.16666667 -0.16666667] [-0.19919102  0.13751175  0.20843984  0.20843984] [0.05555556]\n",
      "[-0.33333333  0.33333333 -0.33333333] [-0.16220083  0.02987301  0.18835642  0.18835642] [0.05555556]\n",
      "[ 0.5 -0.5  0.5] [-0.12757113 -0.02957086  0.18109825  0.18109825] [0.02777778]\n",
      "[0.         0.33333333 0.        ] [-0.19470782  0.14932662  0.18151751  0.18151751] [0.05555556]\n",
      "[-0.16666667  0.5        -0.16666667] [-0.16499801  0.06224724  0.15213876  0.16134166] [0.11111111]\n",
      "[ 0.66666667 -0.33333333  0.66666667] [-0.12170161 -0.01655811  0.1235651   0.16017894] [0.11111111]\n",
      "[ 0.5        -0.16666667  0.5       ] [-0.13567139  0.00519533  0.11383623  0.1775689 ] [0.11111111]\n",
      "[3.33333333e-01 2.77555756e-17 3.33333333e-01] [-0.17775389  0.08840259  0.137224    0.20418049] [0.05555556]\n",
      "[0.         0.66666667 0.        ] [-0.1429486   0.04085118  0.13689062  0.13689062] [0.05555556]\n",
      "[ 0.83333333 -0.16666667  0.83333333] [-0.10058122 -0.01575679  0.09290269  0.13189392] [0.11111111]\n",
      "[ 6.66666667e-01 -5.55111512e-17  6.66666667e-01] [-0.09353762 -0.02311024  0.06458375  0.1479812 ] [0.05555556]\n",
      "[ 0. -1.  0.] [-0.06133252 -0.06133252  0.1210312   0.1210312 ] [0.02777778]\n",
      "[ 0.66666667 -0.33333333  1.        ] [-0.12894983  0.01788475  0.09513755  0.14145801] [0.11111111]\n",
      "[ 0.5        -0.16666667  0.83333333] [-0.09319151 -0.02566662  0.07905522  0.12455972] [0.11111111]\n",
      "[-0.33333333 -1.          0.        ] [-0.05705807 -0.05705807  0.0924765   0.09247651] [0.11111111]\n",
      "[-0.16666667  0.16666667  0.16666667] [-0.19919102  0.13751175  0.20843984  0.20843984] [0.01851852]\n",
      "[-0.33333333  0.33333333  0.33333333] [-0.16220083  0.02987301  0.18835642  0.18835642] [0.01851852]\n",
      "[ 0.5 -0.5 -0.5] [-0.12757113 -0.02957086  0.18109825  0.18109825] [0.00925926]\n",
      "[ 0.16666667 -0.16666667  0.5       ] [-0.16499801  0.06224724  0.15213876  0.16134165] [0.05555556]\n",
      "[-0.16666667  0.16666667  0.5       ] [-0.16499801  0.06224724  0.15213877  0.16134165] [0.05555556]\n",
      "[-0.66666667  0.66666667 -0.33333333] [-0.12170161 -0.01655811  0.1235651   0.16017894] [0.05555556]\n",
      "[ 0.66666667 -0.66666667 -0.33333333] [-0.12170161 -0.01655811  0.1235651   0.16017894] [0.05555556]\n",
      "[-0.5         0.5        -0.16666667] [-0.13567139  0.00519533  0.11383624  0.1775689 ] [0.05555556]\n",
      "[ 0.5        -0.5        -0.16666667] [-0.13567139  0.00519533  0.11383624  0.1775689 ] [0.05555556]\n",
      "[-0.33333333  0.33333333  0.        ] [-0.17775389  0.08840259  0.137224    0.20418049] [0.05555556]\n",
      "[-0.83333333  0.83333333 -0.16666667] [-0.10058122 -0.01575679  0.09290269  0.13189392] [0.05555556]\n",
      "[ 0.83333333 -0.83333333 -0.16666667] [-0.10058122 -0.01575679  0.0929027   0.13189392] [0.05555556]\n",
      "[-0.66666667  0.66666667  0.        ] [-0.09353762 -0.02311024  0.06458376  0.14798119] [0.05555556]\n",
      "[-0.66666667  1.         -0.33333333] [-0.12894983  0.01788475  0.09513755  0.14145801] [0.11111111]\n",
      "[0.5        0.83333333 0.16666667] [-0.09319151 -0.02566662  0.07905522  0.12455972] [0.05555556]\n",
      "[ 0.5        -0.83333333 -0.16666667] [-0.09319151 -0.02566662  0.07905522  0.12455972] [0.05555556]\n"
     ]
    }
   ],
   "source": [
    "for k,e,w in zip(results.kpoints,results.evals,results.weights):\n",
    "    print(k,e,w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are also several get methods, for instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.117279040435398"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.get_fermi()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The method get_evals  return an array with the ks energies for each kpoint. The energies are expressed in eV and the \n",
    "energy of VBM is used as reference. A gap, both direct or indirect, can be set. In this case the energies of the empty ks states is\n",
    "shifted. This procedure __does not__ update the occupation levels of the empty states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are no empty bands. `Set gap` has not been applied\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1.18964146e+01, -3.99369533e-08, -1.83300486e-09,  0.00000000e+00])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results.get_evals(set_gap=1.2)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are no empty states. Gap cannot be computed.\n"
     ]
    }
   ],
   "source": [
    "results.get_gap()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We test the PwParser using a nscf output file, in this case empty bands are present and the gap can be computed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse file : QeCalculator_test/bands_12.save/data-file-schema.xml\n"
     ]
    }
   ],
   "source": [
    "result_nscf = P.PwParser('QeCalculator_test/bands_12.save/data-file-schema.xml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 1., 1., 1., 0., 0., 0., 0., 0., 0., 0., 0.])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_nscf.occupations[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Indirect gap system\n",
      "===================\n",
      "Gap : 0.7363567574170764 eV\n",
      "Direct gap : 2.5651333558109854 eV\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'gap': 0.7363567574170764,\n",
       " 'direct_gap': 2.5651333558109854,\n",
       " 'position_cbm': 12,\n",
       " 'positon_vbm': 0}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_nscf.get_gap()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Apply a scissor of 0.43486664418901455 eV\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1.18964110e+01, -9.74240383e-07, -9.74234497e-07,  0.00000000e+00,\n",
       "        3.00000000e+00,  3.00000056e+00,  3.00000056e+00,  3.58353139e+00,\n",
       "        8.17161688e+00,  8.17161688e+00,  8.29564293e+00,  1.16527216e+01])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_nscf.get_evals(set_direct_gap=3.0)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we see that in this case the energy of the 5-th states has been shift to 3 eV to implement the set_direct_gap requirement. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is also possible to add an explicit scissor to shift the empty bands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Apply a scissor of 1.0 eV\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([-1.18964110e+01, -9.74240383e-07, -9.74234497e-07,  0.00000000e+00,\n",
       "        3.56513336e+00,  3.56513391e+00,  3.56513391e+00,  4.14866474e+00,\n",
       "        8.73675023e+00,  8.73675023e+00,  8.86077629e+00,  1.22178550e+01])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_nscf.get_evals(set_scissor=1.)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We compute the transition energies from the full to empty bands. Here we show the transition\n",
    "for the first k point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Apply a scissor of 0.43486664418901455 eV\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([14.89641099, 14.89641154, 14.89641154, 15.47994237, 20.06802786,\n",
       "       20.06802786, 20.19205392, 23.54913261,  3.00000097,  3.00000153,\n",
       "        3.00000153,  3.58353236,  8.17161785,  8.17161785,  8.29564391,\n",
       "       11.6527226 ,  3.00000097,  3.00000153,  3.00000153,  3.58353236,\n",
       "        8.17161785,  8.17161785,  8.29564391, 11.6527226 ,  3.        ,\n",
       "        3.00000056,  3.00000056,  3.58353139,  8.17161688,  8.17161688,\n",
       "        8.29564293, 11.65272162])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_nscf.get_transitions(set_direct_gap=3.0)[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parse of a Graphene output file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Run the Analysis_BandStructure notebook to produce the xml file used by the PwParser.__\n",
    "\n",
    "We parse a graphene output file to test if systems without a gap are correctly parsed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parse file : Pw_bands/graphene_nscf.save/data-file-schema.xml\n"
     ]
    }
   ],
   "source": [
    "results_gra = P.PwParser('Pw_bands/graphene_nscf.save/data-file-schema.xml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'smearing'"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_gra.occupations_kind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.00000000e+00, 1.00000000e+00, 1.00000000e+00, 1.00000000e+00,\n",
       "       4.22181265e-29, 6.89778699e-37, 1.76721673e-41, 1.28104982e-57])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_gra.occupations[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1. , 1. , 1. , 0.5, 0.5, 0. , 0. , 0. ])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_gra.occupations[18] #the position of K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Direct gap system\n",
      "=================\n",
      "Gap : 2.715685454290906e-10 eV\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'gap': 2.715685454290906e-10,\n",
       " 'direct_gap': 2.715685454290906e-10,\n",
       " 'position_cbm': 18,\n",
       " 'positon_vbm': 18}"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_gra.get_gap()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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