demonstration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# first calculation with pyiron "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## project object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyiron import Project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pr = Project('demonstration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pr.remove_jobs(recursive=True)  # to have a fresh start every time we execute the notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/jan/pyiron/projects/2019/2019-12-11-lanl-tutorial/demonstration/'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## structure object "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "structure = pr.create_structure('Al', 'fcc', 4.05)  # compatible to the ASE structure object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Al: [0. 0. 0.]\n",
       "Al: [2.025 2.025 0.   ]\n",
       "Al: [2.02500000e+00 1.23995488e-16 2.02500000e+00]\n",
       "Al: [2.47990977e-16 2.02500000e+00 2.02500000e+00]\n",
       "pbc: [ True  True  True]\n",
       "cell: \n",
       "[[4.05000000e+00 0.00000000e+00 0.00000000e+00]\n",
       " [2.47990977e-16 4.05000000e+00 0.00000000e+00]\n",
       " [2.47990977e-16 2.47990977e-16 4.05000000e+00]]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "16be0ad1a8a9434d837838b92c4f1c68",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "_ColormakerRegistry()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c1bb97b3aded470e95e2760c288158d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "structure.plot3d()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## job object "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps = pr.create_job(pr.job_type.Lammps, 'job_lammps_1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.structure = structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Config</th>\n",
       "      <th>Filename</th>\n",
       "      <th>Model</th>\n",
       "      <th>Name</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[pair_style eam/fs \\n, pair_coeff * * Al-Mg.eam.fs Al Mg\\n]</td>\n",
       "      <td>[NISTiprpy/2009--Mendelev-M-I--Al-Mg--LAMMPS--ipr1/Al-Mg.eam.fs]</td>\n",
       "      <td>EAM</td>\n",
       "      <td>Al_Mg_Mendelev_eam</td>\n",
       "      <td>[Al, Mg]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[pair_style eam/alloy \\n, pair_coeff * * Zope-Ti-Al-2003.eam.alloy Ti Al\\n]</td>\n",
       "      <td>[NISTiprpy/2003--Zope-R-R--Ti-Al--LAMMPS--ipr1/Zope-Ti-Al-2003.eam.alloy]</td>\n",
       "      <td>EAM</td>\n",
       "      <td>Zope_Ti_Al_2003_eam</td>\n",
       "      <td>[Ti, Al]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[pair_style eam/alloy \\n, pair_coeff * * NiAlH_jea.eam.alloy Ni Al H\\n]</td>\n",
       "      <td>[NISTiprpy/1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1/NiAlH_jea.eam.alloy]</td>\n",
       "      <td>EAM</td>\n",
       "      <td>Al_H_Ni_Angelo_eam</td>\n",
       "      <td>[Ni, Al, H]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>[pair_style meam/c\\n, pair_coeff * * MgAlZn.library.meam Mg Al MgAlZn.parameter.meam Mg Al Zn\\n]</td>\n",
       "      <td>[NISTiprpy/2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1/MgAlZn.parameter.meam, NISTiprpy/2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1/MgAlZn.library.meam]</td>\n",
       "      <td>NISTiprpy</td>\n",
       "      <td>2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1</td>\n",
       "      <td>[Mg, Al, Zn]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>[pair_style eam/alloy\\n, pair_coeff * * alpb-setfl.eam.alloy Al Pb\\n]</td>\n",
       "      <td>[NISTiprpy/2000--Landa-A--Al-Pb--LAMMPS--ipr1/alpb-setfl.eam.alloy]</td>\n",
       "      <td>NISTiprpy</td>\n",
       "      <td>2000--Landa-A--Al-Pb--LAMMPS--ipr1</td>\n",
       "      <td>[Al, Pb]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>649</th>\n",
       "      <td>[pair_style kim Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000\\n, pair_coeff * * Al Si Mg Cu Fe\\n]</td>\n",
       "      <td>[]</td>\n",
       "      <td>OpenKIM</td>\n",
       "      <td>Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000</td>\n",
       "      <td>[Al, Si, Mg, Cu, Fe]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>[pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000\\n, pair_coeff * * Al U\\n]</td>\n",
       "      <td>[]</td>\n",
       "      <td>OpenKIM</td>\n",
       "      <td>Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000</td>\n",
       "      <td>[Al, U]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>660</th>\n",
       "      <td>[pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000\\n, pair_coeff * * Al\\n]</td>\n",
       "      <td>[]</td>\n",
       "      <td>OpenKIM</td>\n",
       "      <td>Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000</td>\n",
       "      <td>[Al]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>679</th>\n",
       "      <td>[pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000\\n, pair_coeff * * Al O\\n]</td>\n",
       "      <td>[]</td>\n",
       "      <td>OpenKIM</td>\n",
       "      <td>Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000</td>\n",
       "      <td>[Al, O]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>680</th>\n",
       "      <td>[pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000\\n, pair_coeff * * Al\\n]</td>\n",
       "      <td>[]</td>\n",
       "      <td>OpenKIM</td>\n",
       "      <td>Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000</td>\n",
       "      <td>[Al]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>93 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                                                                              Config  \\\n",
       "0                                                                        [pair_style eam/fs \\n, pair_coeff * * Al-Mg.eam.fs Al Mg\\n]   \n",
       "1                                                        [pair_style eam/alloy \\n, pair_coeff * * Zope-Ti-Al-2003.eam.alloy Ti Al\\n]   \n",
       "2                                                            [pair_style eam/alloy \\n, pair_coeff * * NiAlH_jea.eam.alloy Ni Al H\\n]   \n",
       "13                                  [pair_style meam/c\\n, pair_coeff * * MgAlZn.library.meam Mg Al MgAlZn.parameter.meam Mg Al Zn\\n]   \n",
       "34                                                             [pair_style eam/alloy\\n, pair_coeff * * alpb-setfl.eam.alloy Al Pb\\n]   \n",
       "..                                                                                                                               ...   \n",
       "649  [pair_style kim Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000\\n, pair_coeff * * Al Si Mg Cu Fe\\n]   \n",
       "659                         [pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000\\n, pair_coeff * * Al U\\n]   \n",
       "660                            [pair_style kim Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000\\n, pair_coeff * * Al\\n]   \n",
       "679                  [pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000\\n, pair_coeff * * Al O\\n]   \n",
       "680                     [pair_style kim Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000\\n, pair_coeff * * Al\\n]   \n",
       "\n",
       "                                                                                                                                               Filename  \\\n",
       "0                                                                                      [NISTiprpy/2009--Mendelev-M-I--Al-Mg--LAMMPS--ipr1/Al-Mg.eam.fs]   \n",
       "1                                                                             [NISTiprpy/2003--Zope-R-R--Ti-Al--LAMMPS--ipr1/Zope-Ti-Al-2003.eam.alloy]   \n",
       "2                                                                               [NISTiprpy/1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1/NiAlH_jea.eam.alloy]   \n",
       "13   [NISTiprpy/2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1/MgAlZn.parameter.meam, NISTiprpy/2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1/MgAlZn.library.meam]   \n",
       "34                                                                                  [NISTiprpy/2000--Landa-A--Al-Pb--LAMMPS--ipr1/alpb-setfl.eam.alloy]   \n",
       "..                                                                                                                                                  ...   \n",
       "649                                                                                                                                                  []   \n",
       "659                                                                                                                                                  []   \n",
       "660                                                                                                                                                  []   \n",
       "679                                                                                                                                                  []   \n",
       "680                                                                                                                                                  []   \n",
       "\n",
       "         Model  \\\n",
       "0          EAM   \n",
       "1          EAM   \n",
       "2          EAM   \n",
       "13   NISTiprpy   \n",
       "34   NISTiprpy   \n",
       "..         ...   \n",
       "649    OpenKIM   \n",
       "659    OpenKIM   \n",
       "660    OpenKIM   \n",
       "679    OpenKIM   \n",
       "680    OpenKIM   \n",
       "\n",
       "                                                                            Name  \\\n",
       "0                                                             Al_Mg_Mendelev_eam   \n",
       "1                                                            Zope_Ti_Al_2003_eam   \n",
       "2                                                             Al_H_Ni_Angelo_eam   \n",
       "13                                      2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1   \n",
       "34                                            2000--Landa-A--Al-Pb--LAMMPS--ipr1   \n",
       "..                                                                           ...   \n",
       "649  Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000   \n",
       "659               Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000   \n",
       "660                Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000   \n",
       "679        Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000   \n",
       "680         Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000   \n",
       "\n",
       "                  Species  \n",
       "0                [Al, Mg]  \n",
       "1                [Ti, Al]  \n",
       "2             [Ni, Al, H]  \n",
       "13           [Mg, Al, Zn]  \n",
       "34               [Al, Pb]  \n",
       "..                    ...  \n",
       "649  [Al, Si, Mg, Cu, Fe]  \n",
       "659               [Al, U]  \n",
       "660                  [Al]  \n",
       "679               [Al, O]  \n",
       "680                  [Al]  \n",
       "\n",
       "[93 rows x 5 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.view_potentials()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Al_Mg_Mendelev_eam',\n",
       " 'Zope_Ti_Al_2003_eam',\n",
       " 'Al_H_Ni_Angelo_eam',\n",
       " '2018--Dickel-D-E--Mg-Al-Zn--LAMMPS--ipr1',\n",
       " '2000--Landa-A--Al-Pb--LAMMPS--ipr1',\n",
       " '2004--Zhou-X-W--Al--LAMMPS--ipr2',\n",
       " '2003--Zope-R-R--Al--LAMMPS--ipr1',\n",
       " '2015--Mendelev-M-I--Al-Sm--LAMMPS--ipr1',\n",
       " '1997--Liu-X-Y--Al-Mg--LAMMPS--ipr1',\n",
       " '2004--Zhou-X-W--Al--LAMMPS--ipr1',\n",
       " '1995--Angelo-J-E--Ni-Al-H--LAMMPS--ipr1',\n",
       " '2015--Pascuet-M-I--Al-U--LAMMPS--ipr2',\n",
       " '1999--Liu-X-Y--Al-Cu--LAMMPS--ipr1',\n",
       " '2015--Pascuet-M-I--Al--LAMMPS--ipr1',\n",
       " '1998--Liu-X-Y--Al-Mg--LAMMPS--ipr1',\n",
       " '2015--Purja-Pun-G-P--Ni-Al-Co--LAMMPS--ipr2',\n",
       " '2009--Mendelev-M-I--Al-Mg--LAMMPS--ipr1',\n",
       " '2002--Mishin-Y--Ni-Al--LAMMPS--ipr1',\n",
       " '2012--Schopf-D--Al-Mn-Pd--LAMMPS--ipr1',\n",
       " '2000--Sturgeon-J-B--Al--LAMMPS--ipr1',\n",
       " '2003--Zope-R-R--Ti-Al--LAMMPS--ipr1',\n",
       " '2009--Zhakhovskii-V-V--Al--LAMMPS--ipr1',\n",
       " '2015--Purja-Pun-G-P--Ni-Al-Co--LAMMPS--ipr1',\n",
       " '1996--Farkas-D--Nb-Ti-Al--LAMMPS--ipr1',\n",
       " '2015--Purja-Pun-G-P--Al-Co--LAMMPS--ipr1',\n",
       " '2015--Purja-Pun-G-P--Al-Co--LAMMPS--ipr2',\n",
       " '2015--Pascuet-M-I--Al-U--LAMMPS--ipr1',\n",
       " '2010--Winey-J-M--Al--LAMMPS--ipr1',\n",
       " '2005--Mendelev-M-I--Al-Fe--LAMMPS--ipr1',\n",
       " '1999--Mishin-Y--Al--LAMMPS--ipr1',\n",
       " '2008--Mendelev-M-I--Al--LAMMPS--ipr1',\n",
       " '2009--Purja-Pun-G-P--Ni-Al--LAMMPS--ipr1',\n",
       " '2004--Mishin-Y--Ni-Al--LAMMPS--ipr1',\n",
       " '2004--Liu-X-Y--Al--LAMMPS--ipr1',\n",
       " '2016--Zhou-X-W--Al-Cu--LAMMPS--ipr1',\n",
       " '2017--Botu-V--Al--LAMMPS--ipr1',\n",
       " '2011--Apostol-F--Al-Cu--LAMMPS--ipr1',\n",
       " '2015--Botu-V--Al--LAMMPS--ipr1',\n",
       " '2015--Choudhary-K--Al--LAMMPS--ipr1',\n",
       " '2018--Zhou-X-W--Al-Cu-H--LAMMPS--ipr1',\n",
       " '2015--Kumar-A--Al-Ni-O--LAMMPS--ipr1',\n",
       " '2015--Kumar-A--Al-Ni--LAMMPS--ipr1',\n",
       " 'EAM_CubicNaturalSpline_ErcolessiAdams_1994_Al__MO_800509458712_002',\n",
       " 'EAM_Dynamo_AngeloMoodyBaskes_1995_NiAlH__MO_418978237058_005',\n",
       " 'EAM_Dynamo_CaiYe_1996_AlCu__MO_942551040047_005',\n",
       " 'EAM_Dynamo_ErcolessiAdams_1994_Al__MO_123629422045_005',\n",
       " 'EAM_Dynamo_FarkasJones_1996_NbTiAl__MO_042691367780_000',\n",
       " 'EAM_Dynamo_JacobsenNorskovPuska_1987_Al__MO_411692133366_000',\n",
       " 'EAM_Dynamo_LandaWynblattSiegel_2000_AlPb__MO_699137396381_005',\n",
       " 'EAM_Dynamo_LiuAdams_1998_AlMg__MO_019873715786_000',\n",
       " 'EAM_Dynamo_LiuErcolessiAdams_2004_Al__MO_051157671505_000',\n",
       " 'EAM_Dynamo_LiuLiuBorucki_1999_AlCu__MO_020851069572_000',\n",
       " 'EAM_Dynamo_LiuOhotnickyAdams_1997_AlMg__MO_559870613549_000',\n",
       " 'EAM_Dynamo_MendelevAstaRahman_2009_AlMg__MO_658278549784_005',\n",
       " 'EAM_Dynamo_MendelevFangYe_2015_AlSm__MO_338600200739_000',\n",
       " 'EAM_Dynamo_MendelevKramerBecker_2008_Al__MO_106969701023_005',\n",
       " 'EAM_Dynamo_MendelevSrolovitzAckland_2005_AlFe__MO_577453891941_005',\n",
       " 'EAM_Dynamo_MishinFarkasMehl_1999_Al__MO_651801486679_005',\n",
       " 'EAM_Dynamo_MishinMehlPapaconstantopoulos_2002_NiAl__MO_109933561507_005',\n",
       " 'EAM_Dynamo_Mishin_2004_NiAl__MO_101214310689_005',\n",
       " 'EAM_Dynamo_PunMishin_2009_NiAl__MO_751354403791_005',\n",
       " 'EAM_Dynamo_PunYamakovMishin_2013_AlCo__MO_678952612413_000',\n",
       " 'EAM_Dynamo_PunYamakovMishin_2013_NiAlCo__MO_826591359508_000',\n",
       " 'EAM_Dynamo_SchopfBrommerFrigan_2012_AlMnPd__MO_137572817842_000',\n",
       " 'EAM_Dynamo_SturgeonLaird_2000_Al__MO_120808805541_005',\n",
       " 'EAM_Dynamo_VailheFarkas_1997_CoAl__MO_284963179498_005',\n",
       " 'EAM_Dynamo_WineyKubotaGupta_2010_Al__MO_149316865608_005',\n",
       " 'EAM_Dynamo_Zhakhovsky_2009_Al__MO_519613893196_000',\n",
       " 'EAM_Dynamo_ZhouJohnsonWadley_2004_Al__MO_131650261510_005',\n",
       " 'EAM_Dynamo_ZhouWadleyJohnson_2001NISTretabulation_Al__MO_060567868558_000',\n",
       " 'EAM_Dynamo_ZhouWadleyJohnson_2001_Al__MO_049243498555_000',\n",
       " 'EAM_Dynamo_ZopeMishin_2003_Al__MO_664470114311_005',\n",
       " 'EAM_Dynamo_ZopeMishin_2003_TiAl__MO_117656786760_005',\n",
       " 'EAM_ErcolessiAdams_1994_Al__MO_324507536345_002',\n",
       " 'EAM_IMD_BrommerGaehler_2006A_AlNiCo__MO_122703700223_003',\n",
       " 'EAM_IMD_BrommerGaehler_2006B_AlNiCo__MO_128037485276_003',\n",
       " 'EAM_IMD_SchopfBrommerFrigan_2012_AlMnPd__MO_878712978062_003',\n",
       " 'EAM_QuinticClampedSpline_ErcolessiAdams_1994_Al__MO_450093727396_002',\n",
       " 'EAM_QuinticHermiteSpline_ErcolessiAdams_1994_Al__MO_781138671863_002',\n",
       " 'EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_AlAgAuCuNiPdPt__MO_115316750986_001',\n",
       " 'EMT_Asap_Standard_JacobsenStoltzeNorskov_1996_Al__MO_623376124862_001',\n",
       " 'Morse_Shifted_GirifalcoWeizer_1959HighCutoff_Al__MO_140175748626_003',\n",
       " 'Morse_Shifted_GirifalcoWeizer_1959LowCutoff_Al__MO_411898953661_003',\n",
       " 'Morse_Shifted_GirifalcoWeizer_1959MedCutoff_Al__MO_279544746097_003',\n",
       " 'Sim_LAMMPS_ADP_ApostolMishin_2011_AlCu__SM_667696763561_000',\n",
       " 'Sim_LAMMPS_AGNI_BotuBatraChapman_2017_Al__SM_666183636896_000',\n",
       " 'Sim_LAMMPS_BOP_ZhouWardFoster_2016_AlCu__SM_566399258279_000',\n",
       " 'Sim_LAMMPS_MEAM_AlmyrasSangiovanniSarakinos_2019_NAlTi__SM_871795249052_000',\n",
       " 'Sim_LAMMPS_MEAM_JelinekGrohHorstemeyer_2012_AlSiMgCuFe__SM_656517352485_000',\n",
       " 'Sim_LAMMPS_MEAM_PascuetFernandez_2015_AlU__SM_721930391003_000',\n",
       " 'Sim_LAMMPS_MEAM_PascuetFernandez_2015_Al__SM_811588957187_000',\n",
       " 'Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_AlO__SM_853967355976_000',\n",
       " 'Sim_LAMMPS_SMTBQ_SallesPolitanoAmzallag_2016_Al__SM_404097633924_000']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.list_potentials()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.potential = 'Al_Mg_Mendelev_eam'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Value</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>units</td>\n",
       "      <td>metal</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dimension</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>boundary</td>\n",
       "      <td>p p p</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>atom_style</td>\n",
       "      <td>atomic</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>read_data</td>\n",
       "      <td>structure.inp</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>include</td>\n",
       "      <td>potential.inp</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fix___ensemble</td>\n",
       "      <td>all nve</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>variable___dumptime</td>\n",
       "      <td>equal 100</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>dump___1</td>\n",
       "      <td>all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>dump_modify___1</td>\n",
       "      <td>sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>thermo_style</td>\n",
       "      <td>custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>thermo_modify</td>\n",
       "      <td>format float %20.15g</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>thermo</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>run</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Parameter  \\\n",
       "0                 units   \n",
       "1             dimension   \n",
       "2              boundary   \n",
       "3            atom_style   \n",
       "4             read_data   \n",
       "5               include   \n",
       "6        fix___ensemble   \n",
       "7   variable___dumptime   \n",
       "8              dump___1   \n",
       "9       dump_modify___1   \n",
       "10         thermo_style   \n",
       "11        thermo_modify   \n",
       "12               thermo   \n",
       "13                  run   \n",
       "\n",
       "                                                                          Value  \\\n",
       "0                                                                         metal   \n",
       "1                                                                             3   \n",
       "2                                                                         p p p   \n",
       "3                                                                        atomic   \n",
       "4                                                                 structure.inp   \n",
       "5                                                                 potential.inp   \n",
       "6                                                                       all nve   \n",
       "7                                                                     equal 100   \n",
       "8                  all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz   \n",
       "9   sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"   \n",
       "10                       custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol   \n",
       "11                                                         format float %20.15g   \n",
       "12                                                                          100   \n",
       "13                                                                            0   \n",
       "\n",
       "   Comment  \n",
       "0           \n",
       "1           \n",
       "2           \n",
       "3           \n",
       "4           \n",
       "5           \n",
       "6           \n",
       "7           \n",
       "8           \n",
       "9           \n",
       "10          \n",
       "11          \n",
       "12          \n",
       "13          "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.input.control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.calc_md(temperature=500.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Value</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>units</td>\n",
       "      <td>metal</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dimension</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>boundary</td>\n",
       "      <td>p p p</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>atom_style</td>\n",
       "      <td>atomic</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>read_data</td>\n",
       "      <td>structure.inp</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>include</td>\n",
       "      <td>potential.inp</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fix___ensemble</td>\n",
       "      <td>all nvt temp 500.0 500.0 0.1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>variable___dumptime</td>\n",
       "      <td>equal 100</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>dump___1</td>\n",
       "      <td>all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>dump_modify___1</td>\n",
       "      <td>sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>thermo_style</td>\n",
       "      <td>custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>thermo_modify</td>\n",
       "      <td>format float %20.15g</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>thermo</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>timestep</td>\n",
       "      <td>0.001</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>velocity</td>\n",
       "      <td>all create 1000.0 69850 dist gaussian</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>run</td>\n",
       "      <td>1000</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Parameter  \\\n",
       "0                 units   \n",
       "1             dimension   \n",
       "2              boundary   \n",
       "3            atom_style   \n",
       "4             read_data   \n",
       "5               include   \n",
       "6        fix___ensemble   \n",
       "7   variable___dumptime   \n",
       "8              dump___1   \n",
       "9       dump_modify___1   \n",
       "10         thermo_style   \n",
       "11        thermo_modify   \n",
       "12               thermo   \n",
       "13             timestep   \n",
       "14             velocity   \n",
       "15                  run   \n",
       "\n",
       "                                                                          Value  \\\n",
       "0                                                                         metal   \n",
       "1                                                                             3   \n",
       "2                                                                         p p p   \n",
       "3                                                                        atomic   \n",
       "4                                                                 structure.inp   \n",
       "5                                                                 potential.inp   \n",
       "6                                                  all nvt temp 500.0 500.0 0.1   \n",
       "7                                                                    equal 100    \n",
       "8                  all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz   \n",
       "9   sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"   \n",
       "10                       custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol   \n",
       "11                                                         format float %20.15g   \n",
       "12                                                                          100   \n",
       "13                                                                        0.001   \n",
       "14                                        all create 1000.0 69850 dist gaussian   \n",
       "15                                                                         1000   \n",
       "\n",
       "   Comment  \n",
       "0           \n",
       "1           \n",
       "2           \n",
       "3           \n",
       "4           \n",
       "5           \n",
       "6           \n",
       "7           \n",
       "8           \n",
       "9           \n",
       "10          \n",
       "11          \n",
       "12          \n",
       "13          \n",
       "14          \n",
       "15          "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.input.control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job job_lammps_1 was saved and received the ID: 1\n"
     ]
    }
   ],
   "source": [
    "job_lammps.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>status</th>\n",
       "      <th>chemicalformula</th>\n",
       "      <th>job</th>\n",
       "      <th>subjob</th>\n",
       "      <th>projectpath</th>\n",
       "      <th>project</th>\n",
       "      <th>timestart</th>\n",
       "      <th>timestop</th>\n",
       "      <th>totalcputime</th>\n",
       "      <th>computer</th>\n",
       "      <th>hamilton</th>\n",
       "      <th>hamversion</th>\n",
       "      <th>parentid</th>\n",
       "      <th>masterid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>job_lammps_1</td>\n",
       "      <td>/job_lammps_1</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:45:41.117157</td>\n",
       "      <td>2019-12-10 16:45:42.227282</td>\n",
       "      <td>1.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id    status chemicalformula           job         subjob  \\\n",
       "0   1  finished             Al4  job_lammps_1  /job_lammps_1   \n",
       "\n",
       "                   projectpath                                       project  \\\n",
       "0  /Users/jan/pyiron/projects/  2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "\n",
       "                   timestart                   timestop  totalcputime  \\\n",
       "0 2019-12-10 16:45:41.117157 2019-12-10 16:45:42.227282           1.0   \n",
       "\n",
       "                     computer hamilton hamversion parentid masterid  \n",
       "0  pyiron@MacBook-Pro.local#1   Lammps        0.1     None     None  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.job_table()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyse the job"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'groups': ['generic', 'structure'], 'nodes': []}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps['output']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'groups': [], 'nodes': ['cells', 'energy_pot', 'energy_tot', 'forces', 'indices', 'positions', 'pressures', 'steps', 'temperature', 'time', 'unwrapped_positions', 'volume']}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps['output/generic']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-13.25465158, -13.26236025, -13.28059441, -13.32368955,\n",
       "       -13.34831865, -13.29381065, -13.12583368, -13.04368461,\n",
       "       -13.31347524, -13.40208388, -13.35984575])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps['output/generic/energy_tot']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x181d656160>]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(job_lammps['output/generic/energy_tot'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-13.25465158, -13.26236025, -13.28059441, -13.32368955,\n",
       "       -13.34831865, -13.29381065, -13.12583368, -13.04368461,\n",
       "       -13.31347524, -13.40208388, -13.35984575])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr['job_lammps_1/output/generic/energy_tot']  # access from the project level "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Advanced users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2018.03.13',\n",
       " '2018.03.13_mpi',\n",
       " '2019.06.05',\n",
       " '2019.06.05_default',\n",
       " '2019.06.05_default_mpi',\n",
       " '2019.06.05_mpi']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.executable.list_executables()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.server.list_queues()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.server.view_queues()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.server.cores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/jan/pyiron/projects/2019/2019-12-11-lanl-tutorial/demonstration/job_lammps_1_hdf5/job_lammps_1'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.working_directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['job_lammps_1.tar.bz2']"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(job_lammps.working_directory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps.decompress()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['LAMMPS (12 Dec 2018)\\n',\n",
       " 'units metal\\n',\n",
       " 'dimension 3\\n',\n",
       " 'boundary p p p\\n',\n",
       " 'atom_style atomic\\n',\n",
       " 'read_data structure.inp\\n',\n",
       " '  orthogonal box = (0 0 0) to (4.05 4.05 4.05)\\n',\n",
       " '  1 by 1 by 1 MPI processor grid\\n',\n",
       " '  reading atoms ...\\n',\n",
       " '  4 atoms\\n',\n",
       " 'include potential.inp\\n',\n",
       " 'pair_style eam/fs\\n',\n",
       " 'pair_coeff * * Al-Mg.eam.fs Al Mg\\n',\n",
       " 'fix ensemble all nvt temp 500.0 500.0 0.1\\n',\n",
       " 'variable dumptime  equal 100\\n',\n",
       " 'dump 1 all custom ${dumptime} dump.out id type xsu ysu zsu fx fy fz\\n',\n",
       " 'dump 1 all custom 100 dump.out id type xsu ysu zsu fx fy fz\\n',\n",
       " 'dump_modify 1 sort id format line \"%d %d %20.15g %20.15g %20.15g %20.15g %20.15g %20.15g\"\\n',\n",
       " 'thermo_style custom step temp pe etotal pxx pxy pxz pyy pyz pzz vol\\n',\n",
       " 'thermo_modify format float %20.15g\\n',\n",
       " 'thermo 100\\n',\n",
       " 'timestep 0.001\\n',\n",
       " 'velocity all create 1000.0 69850 dist gaussian\\n',\n",
       " 'run 1000\\n',\n",
       " 'Neighbor list info ...\\n',\n",
       " '  update every 1 steps, delay 10 steps, check yes\\n',\n",
       " '  max neighbors/atom: 2000, page size: 100000\\n',\n",
       " '  master list distance cutoff = 9.5\\n',\n",
       " '  ghost atom cutoff = 9.5\\n',\n",
       " '  binsize = 4.75, bins = 1 1 1\\n',\n",
       " '  1 neighbor lists, perpetual/occasional/extra = 1 0 0\\n',\n",
       " '  (1) pair eam/fs, perpetual\\n',\n",
       " '      attributes: half, newton on\\n',\n",
       " '      pair build: half/bin/atomonly/newton\\n',\n",
       " '      stencil: half/bin/3d/newton\\n',\n",
       " '      bin: standard\\n',\n",
       " 'Per MPI rank memory allocation (min/avg/max) = 4.239 | 4.239 | 4.239 Mbytes\\n',\n",
       " 'Step Temp PotEng TotEng Pxx Pxy Pxz Pyy Pyz Pzz Volume \\n',\n",
       " '       0                 1000    -13.6424320128801    -13.2546515778801     5811.33462729831    -3854.45323119228     4356.39016846107    -621.038748887569    -3077.46758636693     5449.79641578524            66.430125 \\n',\n",
       " '     100     582.702306216562     -13.488320803082    -13.2623602493018     19272.5377390592    -390.766475669868     2757.48338360488     9211.21496855956    -1233.24087106805      20576.512738308            66.430125 \\n',\n",
       " '     200     229.499909382055    -13.3695899865347     -13.280594411842     25943.6408840172     4620.70985553081     -8607.5938021931     18185.1604277357     6698.31327794928     26575.2066462819            66.430125 \\n',\n",
       " '     300     381.825966704387    -13.4717541868408    -13.3236895473779     17597.3621704412    -2743.39182369787     1385.28892745806     13390.2979126485    -4754.40391555897     13684.2202362752            66.430125 \\n',\n",
       " '     400     336.258885851182    -13.4787132640351    -13.3483186470071     17870.8695466749    -2504.70721458531     8843.16879976338     9944.51929893634    -2623.19083524125     14930.8267228197            66.430125 \\n',\n",
       " '     500     287.501175962573    -13.4052979855416    -13.2938106544638     25259.7112976147     4724.84954980852    -8900.40051839842     13595.1592660193     6226.00430337782     24550.1515923481            66.430125 \\n',\n",
       " '     600     865.064860239937    -13.4612889069809    -13.1258336791739     24343.5962942228    -1305.18067771662     794.753669567708     13963.5152002367     -3413.9118731816     22673.6060830145            66.430125 \\n',\n",
       " '     700     1315.51010517474    -13.5538136878024    -13.0436846069708     16210.5856085173    -4189.01790374302     3662.53956623732     6468.86899554838    -3776.44149636939     19954.3359727284            66.430125 \\n',\n",
       " '     800      477.09117767078    -13.4984818611194    -13.3134752367076     15747.1976916114    -1146.62076630565     3304.31002208207     7208.19322475629     303.296003552599     20358.8715618705            66.430125 \\n',\n",
       " '     900     243.647362387788     -13.496565562211    -13.4020838820376     14738.1319281338     3751.97995779621    -2581.61806526022     9943.92404767703     3478.19973832365      14550.996643728            66.430125 \\n',\n",
       " '    1000     341.965008370376    -13.4924530913355    -13.3598457516349     15276.6481344145    -3114.46187560016    -3090.62935058231     10951.0986282076    -3697.02333680484     12857.9925810629            66.430125 \\n',\n",
       " 'Loop time of 0.0341671 on 1 procs for 1000 steps with 4 atoms\\n',\n",
       " '\\n',\n",
       " 'Performance: 2528.752 ns/day, 0.009 hours/ns, 29267.963 timesteps/s\\n',\n",
       " '86.7% CPU use with 1 MPI tasks x no OpenMP threads\\n',\n",
       " '\\n',\n",
       " 'MPI task timing breakdown:\\n',\n",
       " 'Section |  min time  |  avg time  |  max time  |%varavg| %total\\n',\n",
       " '---------------------------------------------------------------\\n',\n",
       " 'Pair    | 0.024069   | 0.024069   | 0.024069   |   0.0 | 70.44\\n',\n",
       " 'Neigh   | 0          | 0          | 0          |   0.0 |  0.00\\n',\n",
       " 'Comm    | 0.0072689  | 0.0072689  | 0.0072689  |   0.0 | 21.27\\n',\n",
       " 'Output  | 0.0011375  | 0.0011375  | 0.0011375  |   0.0 |  3.33\\n',\n",
       " 'Modify  | 0.00082731 | 0.00082731 | 0.00082731 |   0.0 |  2.42\\n',\n",
       " 'Other   |            | 0.0008647  |            |       |  2.53\\n',\n",
       " '\\n',\n",
       " 'Nlocal:    4 ave 4 max 4 min\\n',\n",
       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
       " 'Nghost:    662 ave 662 max 662 min\\n',\n",
       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
       " 'Neighs:    448 ave 448 max 448 min\\n',\n",
       " 'Histogram: 1 0 0 0 0 0 0 0 0 0\\n',\n",
       " '\\n',\n",
       " 'Total # of neighbors = 448\\n',\n",
       " 'Ave neighs/atom = 112\\n',\n",
       " 'Neighbor list builds = 0\\n',\n",
       " 'Dangerous builds = 0\\n',\n",
       " 'Total wall time: 0:00:00\\n']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps['log.lammps']  # Add you own parser for additional output "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Master jobs - multiple jobs in one job object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps_template = pr.create_job(pr.job_type.Lammps, 'job_lammps_template')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps_template.structure = structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_lammps_template.potential = 'Al_Mg_Mendelev_eam'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "murn = job_lammps_template.create_job(pr.job_type.Murnaghan, 'murn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Value</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>num_points</td>\n",
       "      <td>11</td>\n",
       "      <td>number of sample points</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>fit_type</td>\n",
       "      <td>polynomial</td>\n",
       "      <td>['polynomial', 'birch', 'birchmurnaghan', 'murnaghan', 'pouriertarantola', 'vinet']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fit_order</td>\n",
       "      <td>3</td>\n",
       "      <td>order of the fit polynom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>vol_range</td>\n",
       "      <td>0.1</td>\n",
       "      <td>relative volume variation around volume defined by ref_ham</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Parameter       Value  \\\n",
       "0  num_points          11   \n",
       "1    fit_type  polynomial   \n",
       "2   fit_order           3   \n",
       "3   vol_range         0.1   \n",
       "\n",
       "                                                                               Comment  \n",
       "0                                                              number of sample points  \n",
       "1  ['polynomial', 'birch', 'birchmurnaghan', 'murnaghan', 'pouriertarantola', 'vinet']  \n",
       "2                                                             order of the fit polynom  \n",
       "3                           relative volume variation around volume defined by ref_ham  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "murn.input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job murn was saved and received the ID: 2\n",
      "The job strain_0_9 was saved and received the ID: 3\n",
      "The job strain_0_92 was saved and received the ID: 4\n",
      "The job strain_0_94 was saved and received the ID: 5\n",
      "The job strain_0_96 was saved and received the ID: 6\n",
      "The job strain_0_98 was saved and received the ID: 7\n",
      "The job strain_1_0 was saved and received the ID: 8\n",
      "The job strain_1_02 was saved and received the ID: 9\n",
      "The job strain_1_04 was saved and received the ID: 10\n",
      "The job strain_1_06 was saved and received the ID: 11\n",
      "The job strain_1_08 was saved and received the ID: 12\n",
      "The job strain_1_1 was saved and received the ID: 13\n",
      "job_id:  3 finished\n",
      "job_id:  4 finished\n",
      "job_id:  5 finished\n",
      "job_id:  6 finished\n",
      "job_id:  7 finished\n",
      "job_id:  8 finished\n",
      "job_id:  9 finished\n",
      "job_id:  10 finished\n",
      "job_id:  11 finished\n",
      "job_id:  12 finished\n",
      "job_id:  13 finished\n"
     ]
    }
   ],
   "source": [
    "murn.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+3uegQYNUVXXo0KHaqFEj/fXXX3XDhg2622676dKlS1VVdfvtt1dV1c2bN+uqVatUVXXJkiW69957a0lJScQ6iV7r8GvOFI3zvWpnLinytwq79NJw+dix6emLzBhT8eyxxx4cdthhAJx99tl8+OGHNG7cmKZNmwLQp08fPvnkk4httt9+e4488kjeeOMN5s6dy+bNm2nZsiUAjRs3pnXr1gC0bduWhQsXsmrVKlauXEnnzp1j7vOUU04BoGXLlrRo0YJGjRpRvXp1mjRpws8//xzx3KrKv/71L1q1akXXrl355Zdf+OOPP9L6mlhySUF0c+N//ANCLfQ+/NB10W8JxpjKp6zNoS+66CKefvppRo4cyfnnn/93efXq1f+erlq1Klu2bCl1X6FtqlSpErF9lSpVttl+9OjRLFmyhKlTpzJt2jR23nnntPdyYMklSbHuY9l9d+jUyU2XlMCLL7ppSzDGZF8mK8ZKs2jRIr744gsAxo4dS9euXVm4cCHz588H4Nlnn/37jMOvQ4cO/Pzzz4wZM4bevXsnfI46depQt25dPv3004T7TMaqVato2LAh1apVY+LEifz0U9ye88vMkksSEt0g6X8/jB0bnrYEY0zl0bx5c0aNGkWrVq1Yvnw5AwYMYOTIkfTs2ZOWLVtSpUoV+vbtG3PbM844g8MOO4y6deuW+jyjRo3i2muvpVWrVkybNo1bbrmlTPGeddZZTJkyheLiYkaPHs1+++1Xpv0kFO9iTGV6JLqgX9pF+iVLVAsKwr9xFixIbXtjTNnFusicbQsWLNAWLVqUefsTTzxRP/jggzRGlBl2QT+NkunSpX59OPro8Pzzz0cutzMYY0wsK1eupGnTptSoUYOjjjoq6HDSzpJLApMnJ9ely5lnhqf9VWMhoQQzeXJ64zPGBK+oqIhZs2alvN2OO+7I999/z4uhi7V5xvoWS2DQoOTW69YNCgthwwaYMQNmzYIDDohcp0sX6x7GmExQVeu8MsM0mVYNUezMJQ1q1QKviTkAo0cHF4sxlUlhYSHLli0r05efSY6qG8+lsLAwpe3E/ilQXFys5e1I7vXXwwlmzz1dlzBVLHUbk1E2EmV2xBuJUkSmqmpxrG2sWixNjj0WdtoJli+HRYvgs8/g8MODjsqY/FatWrWURkc02WO/rdNku+3cHfshVjVmjKnMLLmk0VlnhafHjYOoTlCNMabSCCS5iEhPEZktIiUiUuwrby8i07zHdBHpXsp+rhERFZH63nyRiKz37eOxTB+L36GHQlGRm165Et56K5vPbowxuSOoM5dZwGnAJzHKi1W1NXAc8LiIxLwuJCJ7AEcDi6IW/aCqrb1H7P4WMkQk8uzFqsaMMZVVIMlFVeeo6rwY5etUNdR9ZyGQqCnb/cCgUtbJOn9yef11dwZjjDGVTc5dcxGRDiIyG5gJ9PUlG/86pwC/qOr0GLtoLCLfisjHItIpwfNcIiJTRGTKkiVL0hZ/8+Zw0EFuetOmcE/JxhhTmWQsuYjIByIyK8ajW6LtVPUrVW0BtANuEJGIO3dEpCZwIxCrO9DfgD1VtQ0wEBgjIrXjPM9wVS1W1eIGDRqU5RDjOvfc8PSoUWndtTHGVAgZSy6q2lVVD4jxSGqwZlWdA6wFojpSYW+gMTBdRBYCuwPfiMguqrpRVZd5208FfgCapuuYktW7N1St6qY//xx++CHbERhjTLByqlpMRBqHLuCLyF5AM2Chfx1VnamqDVW1SFWLgMXAQar6u4g0EJGq3vZNgH2BH7N5DAANG8Lxx4fnn3022xEYY0ywgmqK3F1EFgOHAG+KyLveoo64M5JpwKtAf1Vd6m3zhL/ZchyHAzNEZDrwEu6azfLMHEVi/qqxZ55JbjQ7Y4zJF9a3GOnpWyzahg3QqFG4tdinn0LHjml9CmOMCVSivsVyqlosnxQWRnYH88wzwcVijDHZZsklg/xVY+PGwfr1wcVijDHZZMklgw45BPbe202vWgUTkmonZ4wxFZ8llwwSgT59wvMjRwYXizHGZJMllwzr08clGYD334effw42HmOMyQZLLhm2555w5JFuWtXueTHGVA6WXLLg/PPD0yNH2j0vxpj8Z8klC7p3h9peD2fz57suYYwxJp9ZcsmCmjWhV6/wvF3YN8bkO0suWeKvGhs3DtauDS4WY4zJNEsuWdKhA+y3n5tes8bGeTHG5DdLLlkiEnn28uSTwcVijDGZZskli849FwoK3PRnn8G8bQZ6NsaY/GDJJYt22QVOOik8b2cvxph8Zcklyy66KDw9ahRs3hxcLMYYkymWXLLs2GNht93c9J9/whtvBBuPMcZkgiWXLCsogPPOC89b1ZgxJh9ZcgnABReEp99+G375JbhYjDEmEyy5BKBJk3BnliUl8NRTwcZjjDHpZsklIBdfHJ5+4gnYujW4WIwxJt0suQSke3eoX99NL1oE774bbDzGGJNOllwCUr165IX9xx8PLBRjjEk7Sy4B8leNvfGGXdg3xuQPSy4BatoUunRx0yUl1izZGJM/LLkE7NJLw9N2Yd8Yky8suQTs1FPDF/Z//hneeSfYeIwx+eHuu2HixPTsa+JEt79UWHIJWPXqkV3xDxsWXCzGmPzRrh2ccUb5E8zEiW4/7dqltp0llxxwySXh6bfegoULAwvFGJMnunRxo96WJ8GEEsu4ceHrw8my5JID9tnHdWgJoGrNko0x6VGeBFOexAKWXHJGv37h6SefhI0bg4vFGJM/ypJgyptYwJJLzjjxRNhjDze9ZAm8/HKw8Rhj8kcqCSYdiQUsueSMgoLIay+PPhpcLMaY/JNMgklXYgFLLjnlootckgH4/HOYMSPYeIwx+SVRgklnYgFLLjlll13g9NPD8488Elwsxpj8FCvBpDuxgCWXnNO/f3j6uedgxYrgYjHG5Cd/grnllvQnFrDkknM6dYKWLd30unUwcmSw8Rhj8lOXLtCxIwwe7FqrpjOxQEDJRUR6ishsESkRkWJfeXsRmeY9potI9zjb3yoiv/jWPcG37AYRmS8i80Tk2GwcTzqJwBVXhOcfecT6GzPGpN9998H48VCrFjz4YPq6igkJ6sxlFnAa8EmM8mJVbQ0cBzwuIgVx9nG/qrb2Hm8BiMj+QC+ghbf9oyJSNSNHkEFnnQV167rpH3+Et98ONh5jTH4ZPx4GDXLTq1fDfvulp6sYv0CSi6rOUdV5McrXqeoWb7YQ0BR33Q14XlU3quoCYD7QvnzRZl/NmnDhheH5hx8OLhZjTH756CP4xz/cMB/gOs4dP778XcVEy7lrLiLSQURmAzOBvr5kE+1yEZkhIk+JiPc7n92An33rLPbKYj3PJSIyRUSmLFmyJG3xp0v//q6KDNwQyPO2ScXGGJOaiROhWzfYtClc9tRTrqVqOvoi88tYchGRD0RkVoxHt0TbqepXqtoCaAfcICKFMVYbBuwNtAZ+A+4LPW2sXcZ5nuGqWqyqxQ0aNEj6uLKlcWM46aTwvJ29GGPKY+JEd6vDFt/P9UsvhZNPDs+nM8FkLLmoaldVPSDGY0KS288B1gIHxFj2h6puVdUSYAThqq/FwB6+VXcHfi3fkQTnyivD0yNHwsqVwcVijKm4Qvex7LwzbNjgypo1cxf1o6UrweRUtZiINA5dwBeRvYBmwMIY6zXyzXbHNQQAeA3oJSLVRaQxsC/wdUaDzqCjjoIWLdz02rXu9NUYY1IRSizHHgtz57qyggIYPRq23z72NulIMEE1Re4uIouBQ4A3ReRdb1FHYLqITANeBfqr6lJvmyd8zZbvFpGZIjID6AIMAFDV2cA44DvgHeAyVa2wDXlF4Oqrw/MPPhh5SmuMMYmEEsuNN8KYMeHyO+6Atm0Tb1veBCOqqTbIyj/FxcU6ZcqUoMOIaf1611vysmVu/qWXIruIMcaYWEKJ5amn4LLL3DDq4JLGBx9AlSRPLRJ1DSMiU1W1ONZ2SZ+5iMj2FfGekYquRg3o2zc8P3RocLEYYyqOyZPhhRdc9VcosdStC888k3xigfAZzOTJqT1/3DMXEamCuyHxLFzLrY1AdWAJ8BYwXFX/l9rT5aZcPnMB+PVXKCqCzZvd/OTJUBzzt4IxxoSNHAkXXBCef/llOO209O2/rGcuE3HNfW8AdlHVPVS1IdAJ+BK4S0TOTl+YJuTuuyPrOHfd1d30FHL//cnva+JEtz9jTOXy/feRXUldfHF6E0tpEiWXrqo6WFVneE1+AVDV5ar6sqqeDryQ+RArn3bttr2I5r+w/8IL4dPcREJ1pe3apT9GY0zu2rQJzjzTtTIF171LKj9K0yFRcnlVRM4UkTiN1UBVN2cgpkovViuNtm3hiCPc9Nat8MADifeRifEZjDEVw003wdSpbnq77WDs2PjNjjMlUXIZAZwMLBCRF0TkVBHZLktxVXqxEsw114SXDx8Oq1bF3tYSizGV13vvwT33hOeHDIHWrbMfR9zkoqoTVLU3sBfwCtAHWOT15XV0tgKszKITzPHHQ/Pmbtnq1fDEE9tuY4nFmMrrjz/g3HPD88cdF9nTRzaV2iBNVder6guq2h04BmiDu0HRZIE/wXz8Mfzzn+FlQ4eGW5CBJRZjKrOSEjjvPJdgwHX1MmpUas2O06nUpxWRnUXkChH5HBgPvAeUcm+nSSd/gtl9d2jY0JUvXuzKwRKLMZXd/ffDO76f/c8+G/6uCELc5CIiF4vIR8A3QFNgkKo2UdXrVHVa1iI0QDjBnH02nHhiuPyee9z4DJZYjKm8Jk+GG24Izw8aBEcHfPEi0U2UI4GxwAf+psj5KNdvovSbOBF69oQ1a2DjRldWu7Yb7McSizGVz19/QZs2btRacLcefPaZayWWaWW6iVJVz1fV9wAVkbNF5BZvZ3uKSIUb3TFfdOkCL74YWY/auLElFmMqI1U3JksosdSuDc8/n53EUppkLvU8iuu9uLc3vxp4JGMRmVJ16eLutg2ZPh2+/DK4eIwxwRg50iWTkOHDoUmT4OLxSya5dFDVy4ANAKq6AsiBvFh5TZzous9u1SpcNmRIcPEYY7Lvu+/g8svD8xddFNlNVNCSSS6bvd6QFUBEGgB5fQ0ml/lbhfnHZxg/HubMCS4uY0z2rFvnvgfWr3fzzZuX3mtHtiWTXB7EDdzVUETuAD4D/i+jUZmYopsbt2gROf71gAHBxWaMyZ6rr4bZs910YaH7TqhZM9iYoiVzE+VoYBBwJ/AbcKqqvpjpwEykePexXH99ePrdd10fQsaY/DV2LIwYEZ5/6CE44IDg4omnIN4CEdlBVdcAqOpcYG6idUzmJLpB8tBDoXNnd/c+uLEbdtnFWo8Zk4/+9z+45JLwfO/ecOGFwcWTSKIzlwkicp+IHO7vGVlEmojIhd6498dlPsTKLZk772+8MTy9dSv06FG2Ma+NMblrw4bwPW4Ae+8Njz0GIsHGFU+i+1yOAj4ELgVmi8hfIrIMeA7YBeijqi9lJ8zKKdkuXbp2hfbenUebN8NRR207HowxpmIbMMDddgDuPpYXX3T3teSqhNdcVPUtVT1LVYtUtbaq1lPVQ1X1DlX9PVtBVkap9BUmEnn28tZbrk7WEowx+eH5591ZSsjQoe6u/FwWUH+ZJpGydEJ50knh+17WrnUDBUWPB2OMqXi+/z7ypukzzoC+fYOLJ1mWXHLQ5Mmpd0JZpUrk2cuDD7oBgsaNc/szxlQ869e7a6j+6ywjRuTudRa/uK3FTHAGDSrbdqefDs2awbx5rjO7Bx6AW2+1lmPGVFRXXAEzZ7rp6tXhpZdy+zqLXzLjudwrIi2yEYwpn6pV4ZZbwvNDh8LKlcHFY4wpu1Gj4Mknw/MPPRTMcMVllUy12FxguIh8JSJ9RaROpoMyZfePf7izF4BVq1yCMcZULLNmQf/+4fmzz3Z9h1Ukydyh/4SqHgacCxQBM0RkjIhYZUsOqloVbr45PG9nL8YE5+67U29Qs3q1q+Jet87N77cfDBsGkya5/VUUSV3Q9zqu3M97LAWmAwNF5PmEG5pA9OoFTZu6aTt7MSY47dql1mJT1d1x//33br5mTXedZfJkt5927TIXa7olc83lP8A84ATg/1S1raoOUdWTgRxvaV05RV97uf9+WL48uGDTilsAACAASURBVHiMqaxCw5Mnm2AeesjdHBkyYgT8+WfFHMY8mTOXWUArVb1UVb+OWmYjUuaoXr3C117++gvuvTfYeIyprJJNMP/9L/zzn+H5fv2gUaOKmVggueQyDdhPRA7yPfYWkQJVXZXpAE3ZVK0Kt90Wnn/gAfcLyBiTfaUlmD/+cP2Gbdni5ouLoVu3iptYIPlhjr8EhgMjgC+A54HvReSYDMZmyqlnz/Bd++vWwZ13BhuPMZVZvASzZYurafj1Vze/004wcKBrIVZREwskl1wWAm1UtVhV2+Kus8wCugIVqO1C5VOlCgweHJ4fNgwWLw4uHmMqu1gJ5sYbXUswcHfeX3cdXHllxU4skFxy2U9VZ4dmVPU7XLL5MXNhmXQ5+eRwj8kbN8LttwcbjzGVnT/B3HZbZPPiPn3gnnsqfmKB5JLL9yIyTEQ6e49HvbLqwOYMx2fKSSQyoTz5JMyfH1w8xhiXOO65x3XPFNKhA7zxRn4kFkguufQB5gNXAwOAH4HzcIklD16C/Ne1qxutElz9rv8mS2NM9v31FwwZEp7fcUf3oy9fEguUkly8mydHqOp9qtpdVU9V1XtVdZ2qltgQxxWDCNx1V3j++efhm2+Ci8eYykwVzjsP5noDxxcUuF40+vfPn8QCpQ8WthVoICLbpfNJRaSniMwWkRIRKfaVtxeRad5juoh0j7P9rSLyi2/dE7zyIhFZ7yt/LNb2ldHBB0N336t5/fXBxWJMZXbXXfDqq+H5GjVcbcKwYfk19lIyXe4vBD4XkdeAtaFCVf1POZ53FnAa8HiM8mJV3SIijYDpIvK6qm6JsY/7VTXWrYE/qGoF6js0e+64AyZMgJISeP99+PBDNySyMSY73n47ctylwkL3mezSxT0q8n0t0ZK55vIr8Ia3bi3fo8xUdY6qzotRvs6XSAoBLc/zmEjNm8P554fnr7vOJRpjTObNnw9nnumqxQCqVYPXXgsnklS7isl1yfSKfJuq3gbcG5r25jNCRDqIyGxgJtA3zlkLwOUiMkNEnhKRur7yxiLyrYh8LCKdEjzPJSIyRUSmLFmyJJ2HkNNuvdX9WgI3FPILLwQajjGVwpo1rlo61EN5lSru2ufRR0eul08JJpmOKw8Rke+AOd78gV5z5NK2+0BEZsV4dEu0nap+paotgHbADSJSGGO1YcDeQGvgN+A+r/w3YE9VbQMMBMaISMxx21R1uHdjaHGDBg1KO5y8sfvucNVV4fkbboANG4KLx5h8V1Li7l+ZNStc9sgjcNppsdfPlwSTTLXYUOBYYBmAqk4HDi9tI1XtqqoHxHhMSCYwVZ2Du8ZzQIxlf6jqVlUtwXVJ094r36iqoTinAj8ATZN5vsrkhhugfn03/dNPridWY0xm3HEHvPJKeH7QIOjbN/E2+ZBgkhrPRVV/jiramoFYEJHGIlLgTe8FNMM1KIher5FvtjuuIQAi0sBrPo2INAH2xd2XY3zq1Im8eeuOO2Dp0sDCMSZvTZgQOfzFaadF3t+SSEVPMMkkl59F5FBARWQ7EbkGr4qsrESku4gsBg4B3hSRd71FHXEtxKYBrwL9VXWpt80TvmbLd4vITBGZgbuRc4BXfjhupMzpwEu4azY2kkkMl1wSOaDYv/8dbDzG5JvZs13nkyFt2qR+jbMiJxhRTdwgS0TqAw/gOqoU4D3gqlD1Uz4oLi7WKVOmBB1G1k2YAKee6qYLClydcGgMGGNM2S1b5vr0+9GrN9llF/f5qlevbPubODE3mymLyFRVLY61LJnWYktV9SxV3VlVG6rq2fmUWCqzU06J7BZm4MBg4zEmH2zeDD16hBNLYSG8+27ZEwuEz2AmT05PjNlQ6k2UItIAuBgo8q+vqhdkLiyTDSJuCOS2bV3b+7feco8TTgg6MmMqrquuCnehDzB2bHhcpfII3WhZUSRzzWUCUAf4AHjT9zB5oE0buOii8PzAge6XlzEmdcOGuUfI7beHq54rm2SuuUzL9+5UKus1l5A//4R993U9tYI7m7n66mBjMqaief99OP542Oq1pe3VC8aMcTUE+apc11yAN0IdQ5r81LBhZHPJW291CccYk5y5c92w4qHEUlzsxk7K58RSmmSSy1W4BLNBRP4SkdUi8lemAzPZdcUV7uwFXNPkG24INh5jKoply9yIr6tWufnddnMtMWvWDDauoCXTWqyWqlZR1UJVre3Nx+xSxVRc220HQ4eG5596Cr78Mrh4jKkINm2C008Pj+5ao4brjHLXXYONKxck07eYiMjZInKzN7+HiLTPfGgm2044Abr5en677LLwab4xJpKquxn544/DZc8+CwcdFFxMuSSZarFHcXfSn+nNrwEeyVhEJlBDh4Z7Tf7mGxg+PNh4jMlVd94Jo0ZFzp9+enDx5JpkkksHVb0M2ACgqiuAtI5MaXJHURH861/h+RtvhEo0IoExSRk3LnLQr/PPd+MjmbBkkstmrzNIhb9vqrQhpvLYtdfC3nu76RUr3Lwxxvn8czj33PD8EUfAY49V7pZhsSSTXB7EdSLZUETuAD4D/i+jUZlAFRZGdsM/alTF6zTPmEz43//cdcmNG91806bw8suuQYyJlExrsdHAIOBO3GBcp6rqi5kOzGTf3XeHk8jxx7uO8kL69k1tULGJE93+jMkXS5e6Ri/LvJ4VGzSAt9+GnXYKNq5clex4LnNV9RFVfdgbxMvkoXbtIrv2HjoUanuNzr//Hu66K7n9hHpwbdcuM3Eak23r17uOXkNNjgsL4fXXoUmTYOPKZUklF1M5RI8d0aiRawETcued7k7kRHK1a3BjymrrVjjzTPjiCzcv4rp16dAh2LhynSUXEyE6wVx6afhDtGmT6+SyJE5zDkssJt+oul6Ox48Pl91/P3TvHlxMFYUlF7MNf4L55BN3r0uBN9jC55/Do49uu40lFpPL/NcTU3HPPfCI766+f/7TdZ9v1xNLZ8nFxORPMMuWRfY1dv318NNP4XlLLCbXRV9PTMYzz0Teu3LGGeGGLnY9sXSWXExc/gRz2GHQvLkrX7vWdXuhaonFVAypjkX/9ttwgW84xMMPd/O9etl7PVmWXExCoQ/l2WdD//7hG8Xee8/9qrPEYiqKZBPMV1+5YYpD/eq1bAnXXOM+A/ZeT54lF1Oq0IfyttvgtNPC5ffeCw8/bB82U3GUlmDmzIETT4R169z8XnvBzTe7sxZLLKmx5GKSEvpQTpoEdeu6MlV44gn315iKIl6C+eknOPro8E2S9eq5H1T9+1tiKQtLLiZpXbq4D9qKFeGyDz5w/SoZU5FEJ5glS+CYY+CXX9zy7beHwYNddZgllrKx5GKSNnEiDBvmqglq1AiXX3MN/PBDcHEZUxahBNOzJ3Ts6HqhANdP2K23uqG/LbGUnSUXkxR/q7B//xtefRWqVnXL1q2Dc86BLVuCjdGYVHXo4HqiCCWWKlXckBNDhlhiKS9LLqZUsZobH3usu5gf8sUXcMcdwcRnTFls3OgaqMyaFS474QT3vrbEUn6WXExCie5j6ds38l6AwYPhyy+zG58xZbFlC5x1Frz7brjs6KPhjTegXz9LLOlgycXElcwNksOHwwEHuOmtW90HdvXq7MVoTKq2boXzznPjsIT06QPffuuuJw4bZuMXpYMlFxNTsnfeV63qfu3VrOnmf/wRLr88OzEak6qSEtcZ6+jR4bIePeDNN8PXE1O5k9/EZ8nFbCPVLl322sudwYQ884wbvdKYXKIKV14JTz4ZLjvlFHfvlv+9nmpXMSY2Sy4mQln7CjvrLFe1EHLppaWP/WJMtqjC1VdH9nB83HHw3//Gfq9bgik/Sy7mb+XthPLhh6FZMze9caPrRmP9+vTGaEyqVGHgQHjwwXDZkUfClCmJ3+uWYMrHkov52+TJ5WuCucMObvvq1d38jz+6gZaMCYoqXHutG7I7pHNnmDEjufe6JZiys+Ri/jZoUPmbYLZqBQ88EJ4fMQKefrp8+zSmLFRd7xH33Rcu69QJZs9O7UeUJZiyseRi0u6SS6B37/B8v34wbVpw8ZjKJ3SN5T//CZd17Oh6PS7L2bklmNRZcjFpJ+Jaj+2/v5vfsAFOPz2yw0tjMqWkBK64IvIaS6dOroFJeap9LcGkJpDkIiI9RWS2iJSISLGvvL2ITPMe00Wke4J9XCEi87z93O0rv0FE5nvLjs30sZjYdtgBXnnF/QV3/eXss8MDMBmTCVu3ujNnf6uw0PDE6ejSJZRgJk8u334qBVXN+gNoDjQDJgHFvvKaQIE33Qj4MzQftX0X4AOgujff0Pu7PzAdqA40Bn4AqpYWT9u2bdVkxosvqrpKCve4/vqgIzL5atMm1d69I99vvXurbt4cdGT5C5iicb5XAzlzUdU5qjovRvk6VQ31rVsIxBuGqh9wl6pu9Lb70yvvBjyvqhtVdQEwH2if3uhNKnr0cMMhh9x1F4wdG1w8Jj9t3OjOUPzvrfPOg2efhYKCwMKq1HLumouIdBCR2cBMoK8v2fg1BTqJyFci8rGItPPKdwN+9q232CszAbrjDtfbbMiFF8I33wQXj8kva9a4e6rGjw+X9e/v7sQPDQthsi9jyUVEPhCRWTEe3RJtp6pfqWoLoB1wg4gUxlitAKgLHAxcC4wTEQEk1i7jxHeJiEwRkSlLlixJ6dhMaqpWhTFjwjdYrl/vut0IjfpnTFktXw5du8KHH4bLrrnG3dBbJed+OlcuGXv5VbWrqh4Q4zEhye3nAGuBA2IsXgy84lX7fQ2UAPW98j186+0O/Bpn/8NVtVhVixs0aJDKoZkyqFMHXnvN/QWXWE4+2f3qNKYsfv0VDj8cvvoqXHb77XD33a7FoglWTuV2EWksIgXe9F64i/4LY6w6HjjSW68psB2wFHgN6CUi1UWkMbAv8HUWQjdJaNoUXnwxXFXx7bdw5pnWgsykbu5cOOQQd0MkuGTy6KNw442WWHJFUE2Ru4vIYuAQ4E0RCQ3Z0xGYLiLTgFeB/qq61NvmCV+z5aeAJiIyC3ge6OOdxcwGxgHfAe8Al6mqfXXlkKOPduNlhLz+uuv3SeM13TB55e67y3+PyJdfuhsiFy1y8wUFrgv9fv3KH59JH1H7VFNcXKxTpkwJOoxK5brr3BdNyJAhrvsZk9/K2znqG2+47UMdohYWwquvuh6OTfaJyFRVLY61LKeqxUzlceedrplyyHXX2RgwlUF57nJ/9FHo1i2cWGrXhk8+scSSqyy5mEBUqeLuQejcOVx2wQXw1lvl3/fEiZFnRSa3pJpgSkrcWe1ll7lpgF12cXfJt2uXeFsTHEsuJjCFhTBhgutJGdwXR/fu7tdoWYWqXexLJ7clm2DWrXPr3HNPuKxZM9cRatOmmY/TlJ0lFxOoOnXg7behqMjNb9rkqjnK0ndTeevzTXaVlmB++82d2b78crjs0ENh6lTYeefsxWnKxpKLCdyuu8L777uqDnB16kce6QZ0SpYlloopXoL59lto396NFhkSOqvdfvvsx2lSZ8nF5IR99oEPPoB69dz8mjXuBrlZs0rf1hJLxRadYF54AQ47DBYvDq9z1VWul23rzqXisORickaLFvDee64VEMCqVe5+hpkz429jiSU/dOniOp088UTo1SvcIkzENc7wD1NsKgZLLianHHQQvPMO1Krl5kMJJlYVmSWW/LF8Odx/fzipgDtLGTkSrr02uLhM2VlyMTnnkEMiz2D++sslGP9Ffkss+WPaNCgu3rYZ+sCB0KdPMDGZ8rPkYnLSwQe7i/yhji5Xr3bXYCZNssSST0aNcj8mFiwIl9Wo4foIGznShhOuyCy5mJzVvr27yL/TTm5+wwbXvfqpp1piqejWrXM3zZ53nvu/gksqtWvDm2+63o1tvPqKzZKLyWnFxfDpp665MrgelFevhh9+CDYuU3bffed+OIwcGS7bc093U+348eEfDeXpKsYEz5KLyXn77+/u0A4N/qQKF18MN99svSlXJKowfLj7wRDqKh/c2ejate5myeizUUswFZclF5PzJk509zmMG+dak4Xcfjuce64bP93ktuXLXUell14a2aPxNde4C/ovvhi/mtMSTMVkycXkNP/F+9NPh48/hhNOCC9/7jn35fP778HFaBJ7911o2dLdBBnSooUbivjpp5O7fmYJpuKx5GJyVqxWYTvs4Dq7vOSS8HpffOE6qvzmm2DiNLGtXQv9+7u+4n71DTbevz/cey9cf31qDTMswVQsllxMTkrU3LigAB57DP7zn/CQtosXu3thbEyY0qVjNMiQeMMbTJoEBx4YOepogwbugn2PHnDOOWVr8WcJpuKw5GJyTjL3sYjAgAGuR+VQR4br17umrRdfHHmnt4nUrl16vpxjDW/w119uuOEuXSJb9HXr5vqJq127/PcoWYKpIFS10j/atm2rJjd89JFq/frub7LmzlXdc09V1x7JPVq3duUmtrK8zom2LylRfeUV1d13j/w/1KmjOnKkW66qOmRI2Z8zVgxDhqRnX6ZsgCka53s18C/2XHhYcskN5fnCW71a9aijIr/YatZUffzx8BdbLJX5y66sr3f0dgsXqp58cuRrD6qnnKL6yy/pj9vkDksullxyXnl/Sau6JHL11dt+yXXrpvr775l73nTuJ9tSjdu//rp1qv/+t2qNGpGvd4MGqmPGJE7qJj9YcrHkkvPSeQYxYoRqw4aRX3j16qmOHh37Cy/dVUQVTbLxh9b78EPVl19WLSraNpFfconq8uXZidsEz5KLJZdKZ9061csv3/bL7+STVRct2nb9dFURVVSlHUdo+cMPq3bsuO3reuCBqp9/nt2YTfAsuVhyqbTefXfbi/01a6redZfqxo2R65aniqgscu16T7zj+egj1bp1VTt33jap7LST6rBhqlu2lO+5TcVkycWSS6X211+q/ftv+8W4336qb74ZWVWWahVReZJDLl7vid7Xc8+pVq+uKhL52lWrpnrllarLlpX/OU3FZcnFkotR1U8/VW3Vatskc+SRqlOnhtdLtoooE1/m2d4+3j7r1o39WoFqz56q8+en7/lMxWXJxZKL8WzerDp0qGqtWrG/NGfOdOslqiLKxJd5LlzvKSlx101OOy12Ujn2WNWvvkrPc5n8YMnFkouJ8vvvqn37qlatuu2XaI8e7kwm+ss7kxfvs329x2/jRtd0uH372EmldWt31mdMNEsullxMHHPmqJ56auwv1SOOUL39dvclfvPNmW8Vls3rPaquauu669x9KbGO/+STVR96KD9aw5nMsORiycWUYsoUd0d5rC/ZOnXc36uvznwcmb7es2KF6vDhqp06xT5WUD3+eNUZM9L3nCZ/WXKx5GKS9M03qr17x64uA1d19MwzqqtWZS6GdF/vWb5cddQolzyrV499XPXruybaL7+cWkymcrPkYsnFpGjRItUzzti2CW7oUVjoqo0ef1x18eL0P395rveUlLgzjyFDXNVeQUHsY6haVfXEE1UHD85udZzJH4mSi7jllVtxcbFOmTIl6DBMDgl1J//cc7BsmRv7/eOP46/fogUccQR07gyHHgq77hoea6a8MfTr58ZFiddN/YYNMH06fPklfPKJeyxdGn+/bdq44aF794bvvkutC/xkhkMwlYeITFXV4pjLLLlYcjGR4n2BLlwIL7wAI0ZEjlUSy847Q3ExtGoFzZq5R5MmUL8+VElhFKVbboHBg+Gmm+Cf/4SffoIff4Q5c9xj1iz32LIl8X7atXPDRJ9+OuyzT+LjLI0lGBNiyaUUllxMSLJfnM89B337QtOmMHNm6V/uIdWqubOahg1hxx2hTh032FlBgXuoujORDRtcIpk6FWrVgpUr3bJk7bQTdO0Kxx8Pxx4LjRqV7TjjsQRjIHFyKch2MMbkqlS+MM8+G3bbza0/YYJLGh9/7KqkvvnGjR8fy+bNLmn89FPyca1YUfo6zZpB27Zw2GGuaq558/hnSOlIDP7RIC3BmFgsuRhD2b5wo79gb7/dlW/dCt9/75LMnDkwb557LFoEq1aVPcbttnP7btPGXdfZf3+XRA480J0BJWvy5PQkhNDxT55sycVsK5BqMRHpCdwKNAfaq+oUr7w9MDy0GnCrqr4aZx9XAJcDW4A3VXWQiBQBc4B53mpfqmrf0uKxarHKLZtVRGvXwi+/uEYCq1a56q71613S2LLFJaEnnoCrr3bXSerVc48GDVxV16RJdrZgckeiarFAmv7ikkozYBJQ7CuvCRR4042AP0PzUdt3AT4AqnvzDb2/RcCsVOOxpsiVVy71TJztO/SNKS8SNEVOod1K+qjqHFWdF6N8naqGLo0WAvFOq/oBd6nqRm+7PzMTqcl3magiKotUzn781XETJ5bt+YzJtECSSyIi0kFEZgMzgb6+ZOPXFOgkIl+JyMci0s63rLGIfOuVd0rwPJeIyBQRmbJkyZI0H4WpKAYNSl/1Upcubn+pKu/1HkswJhdlLLmIyAciMivGo1ui7VT1K1VtAbQDbhCRwhirFQB1gYOBa4FxIiLAb8CeqtoGGAiMEZHacZ5nuKoWq2pxgwYNynGkxpRdea73WIIxuSxjrcVUtWs5t58jImuBA4Doq+2LgVe8Or+vRaQEqK+qS4BQVdlUEfkBd5ZjV+tNzrEmwSaf5VS1mIg0FpECb3ov3EX/hTFWHQ8c6a3XFNgOWCoiDUSkqlfeBNgX+DELoRuTsly53mNMJgRyn4uIdAceAhoAb4rINFU9FugIXC8im4ESoL+qLvW2eQJ4TF2z5aeAp0RkFrAJ6KOqKiKHA/8WkS3AVtw1m+VZP0BjklCW6zPxdOliZy0mt1j3L9h9LsYYUxbWt1gpRGQJkEKHHKWqDyTolzZnWdzZZXFnV0WMO9dj3ktVY7aIsuSSASIyJV42z2UWd3ZZ3NlVEeOuiDGH5NQFfWOMMfnBkosxxpi0s+SSGcNLXyUnWdzZZXFnV0WMuyLGDNg1F2OMMRlgZy7GGGPSzpKLMcaYtLPkkgYisqOIvCQic0VkjogcIiI7icj7IvI/72/doOOMFifue7z5GSLyqojsGHScfrFi9i27RkRUROoHGWMs8eIWkStEZJ6IzBaRu4OOM1qc90hrEflSRKZ5PYu3DzpOPxFp5sUWevwlIlfn+mcyQdw5/ZmMK95AL/ZIafCzUcBF3vR2wI7A3cD1Xtn1wJCg40wy7mMID9g2JNfijhWzN70H8C7uZtj6QceZ5Gsdc9C7XHrEifs94Hiv7ARgUtBxJoi/KvA7sFdF+EzGiTunP5NxjyHoACr6A6gNLMBrHOErnwc08qYbAfOCjjWZuKPW6Q6MDjrWZGIGXgIOxHV0mlPJJcF7ZBzQNej4yhD3u8A/vOnewJigY01wDMcAn3vTOf2ZjBd3VHlOfSYTPaxarPyaAEuAkd4gZU+IyPbAzqr6G4D3t2GQQcYQL26/C4C3sx9aXDFjFpFTgF9UdXrA8cUT77VONOhdLogX99XAPSLyM3AvcEOQQZaiFzDWm871z6SfP26/XPtMxmXJpfwKgIOAYeoGKVuLO+XOdQnjFpEbgS3A6GDCiylWzLcCNwK3BBhXaeK91vEGvcsV8eLuBwxQ1T2AAcCTwYUYn4hsB5wCvBh0LKmIF3eOfibjsuRSfouBxar6lTf/Eu4D+YeINALw/v4ZUHzxxIsbEekDnAScpd65eI6IF3NjYLqILAR2B74RkV2CCTGmeHH/Peidqn6NG2YilxojxIu7D/CKV/YikFMX9H2OB75R1T+8+Vz/TIZEx53Ln8m4LLmUk6r+DvwsIs28oqOA74DXcB9CvL8TAggvrnhxi8hxwHXAKaq6LrAAY4gT8zeq2lBVi1S1CPeFeJC3bk5I8B6JOehdIEHGkCDuX4HOXtmRwP8CCC8ZvYmsWsrpz6RPRNy5/JlMxO7QTwMRaQ08gfty+BE4H5e4xwF7AouAnppjA5fFiXsyUB1Y5q32par2DSbCbcWKWVVX+JYvBIrVG2QuV8R5rdfiBr5rjRv07hpV/SiwIGOIE3cL4AFctdkG3KB+UwMLMgYRqQn8DDRR1VVeWT1y/zMZK+755PBnMh5LLsYYY9LOqsWMMcaknSUXY4wxaWfJxRhjTNpZcjHGGJN2llyMMcaknSUXY4wxaWfJxRhjTNpZcjGmEhCRh0Tkm1DnmCLSXEQe88Zq6Rd0fCb/WHIxJs95PRk3BC7F9U+Fqs7x7vI+AygOMDyTpyy5GJMEEZkkIsdGlV0tIo8m2GZN5iPb5jlreN33Vw2Vqepa3Pglk4AHfeueAnwGfOjNbycin4hIQXajNvnIkosxyRmLG2PDL96YG0G6ANfT8tZQgdenVk1gNfB3uaq+pqqHAmd585twieYfWY3Y5CVLLsYk5yXgJBGpDiAiRcCuwGciMlBEZnmPq6M3FJEiEZnlm79GRG71LZvrDcQ1S0RGi0hXEfncG+u9vbfe2SLytTe2+uP+M5MoZ7Ftb7834Qb1mg3s7+3vCBF5UEQeB97yrTve24cx5WLJxZgkqOoy4GvgOK+oF/ACbnyT84EOuEG/LhaRNinufh9cL8OtgP2AM4GOwDXAv0SkOe5s4jBVbY07+9gmAXiDTDVR1YW+siLgUC/WObgejVHVSap6papeqqqP+HYzC8i1ETFNBWTJxZjk+avGQlViHYFXVXWtqq7BDaLVKcX9LlDVmapagju7+NAbEGomUIQbR6UtMFlEpnnzTWLspz6wMqrsduDf3v7+Ti7xeNVpm0SkVorHYEwEu3BnTPLGA/8RkYOAGqr6jYgcnsR2W4j8IVcYtXyjb7rEN1+C+4wKMEpVSxurfr1/395YLKcBHUXkEW/ZzCTirY4bp8WYMrMzF2OS5J2ZTMIN8BW6kP8JcKqI1PSa/HYHPo3a9A+goYjU867ZnJTiU38I9BCRhgAispOI7BUjvhVAVREJJZghwMm+UToPpJQzF+/i/xJVysXKpwAAAMRJREFU3ZxijMZEsDMXY1IzFlf11QvAO3t5Gnc9BuAJVf3Wv4GqbhaRfwNfAQuAuak8oap+JyI3Ae+JSBVgM3AZ8FOM1d/DnamUANur6oe+/fwhItuLyE4JRmDsQuQFfmPKxEaiNCaPeI0JBqrqOWXc/hXgBlWdl97ITGVj1WLG5BHvrGligqbKcXmtzcZbYjHpYGcuxhhj0s7OXIwxxqSdJRdjjDFpZ8nFGGNM2llyMcYYk3aWXIwxxqSdJRdjjDFp9/8BMQU2g5Kn6wEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "murn.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'groups': ['structure'], 'nodes': ['energy', 'equilibrium_b_prime', 'equilibrium_bulk_modulus', 'equilibrium_energy', 'equilibrium_volume', 'error', 'id', 'volume']}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "murn['output']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x181d228e10>]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(murn['output/volume'], murn['output/energy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>status</th>\n",
       "      <th>chemicalformula</th>\n",
       "      <th>job</th>\n",
       "      <th>subjob</th>\n",
       "      <th>projectpath</th>\n",
       "      <th>project</th>\n",
       "      <th>timestart</th>\n",
       "      <th>timestop</th>\n",
       "      <th>totalcputime</th>\n",
       "      <th>computer</th>\n",
       "      <th>hamilton</th>\n",
       "      <th>hamversion</th>\n",
       "      <th>parentid</th>\n",
       "      <th>masterid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>job_lammps_1</td>\n",
       "      <td>/job_lammps_1</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:45:41.117157</td>\n",
       "      <td>2019-12-10 16:45:42.227282</td>\n",
       "      <td>1.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>murn</td>\n",
       "      <td>/murn</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:45:44.863248</td>\n",
       "      <td>2019-12-10 16:46:06.707634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1#11/11</td>\n",
       "      <td>Murnaghan</td>\n",
       "      <td>0.3.0</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_9</td>\n",
       "      <td>/strain_0_9</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:46.793676</td>\n",
       "      <td>2019-12-10 16:45:47.391474</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_92</td>\n",
       "      <td>/strain_0_92</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:48.755689</td>\n",
       "      <td>2019-12-10 16:45:49.608306</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_94</td>\n",
       "      <td>/strain_0_94</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:50.988969</td>\n",
       "      <td>2019-12-10 16:45:51.454903</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_96</td>\n",
       "      <td>/strain_0_96</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:52.878985</td>\n",
       "      <td>2019-12-10 16:45:53.487162</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_98</td>\n",
       "      <td>/strain_0_98</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:54.925316</td>\n",
       "      <td>2019-12-10 16:45:55.340213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_0</td>\n",
       "      <td>/strain_1_0</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:56.551747</td>\n",
       "      <td>2019-12-10 16:45:56.977871</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_02</td>\n",
       "      <td>/strain_1_02</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:58.426541</td>\n",
       "      <td>2019-12-10 16:45:58.915650</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_04</td>\n",
       "      <td>/strain_1_04</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:00.400515</td>\n",
       "      <td>2019-12-10 16:46:01.180575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_06</td>\n",
       "      <td>/strain_1_06</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:02.470651</td>\n",
       "      <td>2019-12-10 16:46:02.930345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_08</td>\n",
       "      <td>/strain_1_08</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:04.100879</td>\n",
       "      <td>2019-12-10 16:46:04.556366</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_1</td>\n",
       "      <td>/strain_1_1</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:05.672669</td>\n",
       "      <td>2019-12-10 16:46:06.074122</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id    status chemicalformula           job         subjob  \\\n",
       "0    1  finished             Al4  job_lammps_1  /job_lammps_1   \n",
       "1    2  finished             Al4          murn          /murn   \n",
       "2    3  finished             Al4    strain_0_9    /strain_0_9   \n",
       "3    4  finished             Al4   strain_0_92   /strain_0_92   \n",
       "4    5  finished             Al4   strain_0_94   /strain_0_94   \n",
       "5    6  finished             Al4   strain_0_96   /strain_0_96   \n",
       "6    7  finished             Al4   strain_0_98   /strain_0_98   \n",
       "7    8  finished             Al4    strain_1_0    /strain_1_0   \n",
       "8    9  finished             Al4   strain_1_02   /strain_1_02   \n",
       "9   10  finished             Al4   strain_1_04   /strain_1_04   \n",
       "10  11  finished             Al4   strain_1_06   /strain_1_06   \n",
       "11  12  finished             Al4   strain_1_08   /strain_1_08   \n",
       "12  13  finished             Al4    strain_1_1    /strain_1_1   \n",
       "\n",
       "                    projectpath  \\\n",
       "0   /Users/jan/pyiron/projects/   \n",
       "1   /Users/jan/pyiron/projects/   \n",
       "2   /Users/jan/pyiron/projects/   \n",
       "3   /Users/jan/pyiron/projects/   \n",
       "4   /Users/jan/pyiron/projects/   \n",
       "5   /Users/jan/pyiron/projects/   \n",
       "6   /Users/jan/pyiron/projects/   \n",
       "7   /Users/jan/pyiron/projects/   \n",
       "8   /Users/jan/pyiron/projects/   \n",
       "9   /Users/jan/pyiron/projects/   \n",
       "10  /Users/jan/pyiron/projects/   \n",
       "11  /Users/jan/pyiron/projects/   \n",
       "12  /Users/jan/pyiron/projects/   \n",
       "\n",
       "                                                   project  \\\n",
       "0             2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "1             2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "2   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "3   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "4   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "5   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "6   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "7   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "8   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "9   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "10  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "11  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "12  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "\n",
       "                    timestart                   timestop  totalcputime  \\\n",
       "0  2019-12-10 16:45:41.117157 2019-12-10 16:45:42.227282           1.0   \n",
       "1  2019-12-10 16:45:44.863248 2019-12-10 16:46:06.707634          21.0   \n",
       "2  2019-12-10 16:45:46.793676 2019-12-10 16:45:47.391474           0.0   \n",
       "3  2019-12-10 16:45:48.755689 2019-12-10 16:45:49.608306           0.0   \n",
       "4  2019-12-10 16:45:50.988969 2019-12-10 16:45:51.454903           0.0   \n",
       "5  2019-12-10 16:45:52.878985 2019-12-10 16:45:53.487162           0.0   \n",
       "6  2019-12-10 16:45:54.925316 2019-12-10 16:45:55.340213           0.0   \n",
       "7  2019-12-10 16:45:56.551747 2019-12-10 16:45:56.977871           0.0   \n",
       "8  2019-12-10 16:45:58.426541 2019-12-10 16:45:58.915650           0.0   \n",
       "9  2019-12-10 16:46:00.400515 2019-12-10 16:46:01.180575           0.0   \n",
       "10 2019-12-10 16:46:02.470651 2019-12-10 16:46:02.930345           0.0   \n",
       "11 2019-12-10 16:46:04.100879 2019-12-10 16:46:04.556366           0.0   \n",
       "12 2019-12-10 16:46:05.672669 2019-12-10 16:46:06.074122           0.0   \n",
       "\n",
       "                            computer   hamilton hamversion parentid  masterid  \n",
       "0         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       NaN  \n",
       "1   pyiron@MacBook-Pro.local#1#11/11  Murnaghan      0.3.0     None       NaN  \n",
       "2         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "3         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "4         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "5         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "6         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "7         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "8         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "9         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "10        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "11        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "12        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.job_table()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data analytics "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "table = pr.create_job(pr.job_type.TableJob, 'table')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_jobs(job):\n",
    "    return 'strain' in job.job_name "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "table.filter_function = filter_jobs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.add.get_job_name\n",
    "table.add.get_energy_tot\n",
    "table.add.get_volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1000.        ,  582.70230622,  229.49990938,  381.8259667 ,\n",
       "        336.25888585,  287.50117596,  865.06486024, 1315.51010517,\n",
       "        477.09117767,  243.64736239,  341.96500837])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps['output/generic/temperature']  # temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def custom_function(job): \n",
    "    return job['output/generic/temperature'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "table.add['temperature'] = custom_function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 11/11 [00:00<00:00, 78.96it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job table was saved and received the ID: 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "table.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>job_name</th>\n",
       "      <th>job_id</th>\n",
       "      <th>energy_tot</th>\n",
       "      <th>volume</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>strain_0_9</td>\n",
       "      <td>3</td>\n",
       "      <td>-13.428526</td>\n",
       "      <td>59.787112</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>strain_0_92</td>\n",
       "      <td>4</td>\n",
       "      <td>-13.519023</td>\n",
       "      <td>61.115715</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>strain_0_94</td>\n",
       "      <td>5</td>\n",
       "      <td>-13.580416</td>\n",
       "      <td>62.444317</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>strain_0_96</td>\n",
       "      <td>6</td>\n",
       "      <td>-13.618512</td>\n",
       "      <td>63.772920</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>strain_0_98</td>\n",
       "      <td>7</td>\n",
       "      <td>-13.638014</td>\n",
       "      <td>65.101522</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>strain_1_0</td>\n",
       "      <td>8</td>\n",
       "      <td>-13.642432</td>\n",
       "      <td>66.430125</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>strain_1_02</td>\n",
       "      <td>9</td>\n",
       "      <td>-13.634209</td>\n",
       "      <td>67.758727</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>strain_1_04</td>\n",
       "      <td>10</td>\n",
       "      <td>-13.614879</td>\n",
       "      <td>69.087330</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>strain_1_06</td>\n",
       "      <td>11</td>\n",
       "      <td>-13.585168</td>\n",
       "      <td>70.415932</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>strain_1_08</td>\n",
       "      <td>12</td>\n",
       "      <td>-13.545276</td>\n",
       "      <td>71.744535</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>strain_1_1</td>\n",
       "      <td>13</td>\n",
       "      <td>-13.495408</td>\n",
       "      <td>73.073137</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       job_name  job_id  energy_tot     volume  temperature\n",
       "0    strain_0_9       3  -13.428526  59.787112            0\n",
       "1   strain_0_92       4  -13.519023  61.115715            0\n",
       "2   strain_0_94       5  -13.580416  62.444317            0\n",
       "3   strain_0_96       6  -13.618512  63.772920            0\n",
       "4   strain_0_98       7  -13.638014  65.101522            0\n",
       "5    strain_1_0       8  -13.642432  66.430125            0\n",
       "6   strain_1_02       9  -13.634209  67.758727            0\n",
       "7   strain_1_04      10  -13.614879  69.087330            0\n",
       "8   strain_1_06      11  -13.585168  70.415932            0\n",
       "9   strain_1_08      12  -13.545276  71.744535            0\n",
       "10   strain_1_1      13  -13.495408  73.073137            0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.get_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x116e41710>]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(table.get_dataframe()['volume'], table.get_dataframe()['energy_tot'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# interactive jobs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'modal'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.server.run_mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_lammps.server.run_mode.non_modal  # run in background "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive = pr.create_job(pr.job_type.Lammps, 'lammps_interactive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.structure = structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.potential = 'Al_Mg_Mendelev_eam'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.server.run_mode.interactive = True "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job lammps_interactive was saved and received the ID: 15\n"
     ]
    }
   ],
   "source": [
    "job_interactive.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>status</th>\n",
       "      <th>chemicalformula</th>\n",
       "      <th>job</th>\n",
       "      <th>subjob</th>\n",
       "      <th>projectpath</th>\n",
       "      <th>project</th>\n",
       "      <th>timestart</th>\n",
       "      <th>timestop</th>\n",
       "      <th>totalcputime</th>\n",
       "      <th>computer</th>\n",
       "      <th>hamilton</th>\n",
       "      <th>hamversion</th>\n",
       "      <th>parentid</th>\n",
       "      <th>masterid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>job_lammps_1</td>\n",
       "      <td>/job_lammps_1</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:45:41.117157</td>\n",
       "      <td>2019-12-10 16:45:42.227282</td>\n",
       "      <td>1.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>murn</td>\n",
       "      <td>/murn</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:45:44.863248</td>\n",
       "      <td>2019-12-10 16:46:06.707634</td>\n",
       "      <td>21.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1#11/11</td>\n",
       "      <td>Murnaghan</td>\n",
       "      <td>0.3.0</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_9</td>\n",
       "      <td>/strain_0_9</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:46.793676</td>\n",
       "      <td>2019-12-10 16:45:47.391474</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_92</td>\n",
       "      <td>/strain_0_92</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:48.755689</td>\n",
       "      <td>2019-12-10 16:45:49.608306</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_94</td>\n",
       "      <td>/strain_0_94</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:50.988969</td>\n",
       "      <td>2019-12-10 16:45:51.454903</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_96</td>\n",
       "      <td>/strain_0_96</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:52.878985</td>\n",
       "      <td>2019-12-10 16:45:53.487162</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_0_98</td>\n",
       "      <td>/strain_0_98</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:54.925316</td>\n",
       "      <td>2019-12-10 16:45:55.340213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_0</td>\n",
       "      <td>/strain_1_0</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:56.551747</td>\n",
       "      <td>2019-12-10 16:45:56.977871</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_02</td>\n",
       "      <td>/strain_1_02</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:45:58.426541</td>\n",
       "      <td>2019-12-10 16:45:58.915650</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_04</td>\n",
       "      <td>/strain_1_04</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:00.400515</td>\n",
       "      <td>2019-12-10 16:46:01.180575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_06</td>\n",
       "      <td>/strain_1_06</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:02.470651</td>\n",
       "      <td>2019-12-10 16:46:02.930345</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_08</td>\n",
       "      <td>/strain_1_08</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:04.100879</td>\n",
       "      <td>2019-12-10 16:46:04.556366</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>finished</td>\n",
       "      <td>Al4</td>\n",
       "      <td>strain_1_1</td>\n",
       "      <td>/strain_1_1</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/</td>\n",
       "      <td>2019-12-10 16:46:05.672669</td>\n",
       "      <td>2019-12-10 16:46:06.074122</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>finished</td>\n",
       "      <td>None</td>\n",
       "      <td>table</td>\n",
       "      <td>/table</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:46:07.886290</td>\n",
       "      <td>2019-12-10 16:46:08.090257</td>\n",
       "      <td>0.0</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>TableJob</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>running</td>\n",
       "      <td>Al4</td>\n",
       "      <td>lammps_interactive</td>\n",
       "      <td>/lammps_interactive</td>\n",
       "      <td>/Users/jan/pyiron/projects/</td>\n",
       "      <td>2019/2019-12-11-lanl-tutorial/demonstration/</td>\n",
       "      <td>2019-12-10 16:46:08.593883</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pyiron@MacBook-Pro.local#1</td>\n",
       "      <td>Lammps</td>\n",
       "      <td>0.1</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id    status chemicalformula                 job               subjob  \\\n",
       "0    1  finished             Al4        job_lammps_1        /job_lammps_1   \n",
       "1    2  finished             Al4                murn                /murn   \n",
       "2    3  finished             Al4          strain_0_9          /strain_0_9   \n",
       "3    4  finished             Al4         strain_0_92         /strain_0_92   \n",
       "4    5  finished             Al4         strain_0_94         /strain_0_94   \n",
       "5    6  finished             Al4         strain_0_96         /strain_0_96   \n",
       "6    7  finished             Al4         strain_0_98         /strain_0_98   \n",
       "7    8  finished             Al4          strain_1_0          /strain_1_0   \n",
       "8    9  finished             Al4         strain_1_02         /strain_1_02   \n",
       "9   10  finished             Al4         strain_1_04         /strain_1_04   \n",
       "10  11  finished             Al4         strain_1_06         /strain_1_06   \n",
       "11  12  finished             Al4         strain_1_08         /strain_1_08   \n",
       "12  13  finished             Al4          strain_1_1          /strain_1_1   \n",
       "13  14  finished            None               table               /table   \n",
       "14  15   running             Al4  lammps_interactive  /lammps_interactive   \n",
       "\n",
       "                    projectpath  \\\n",
       "0   /Users/jan/pyiron/projects/   \n",
       "1   /Users/jan/pyiron/projects/   \n",
       "2   /Users/jan/pyiron/projects/   \n",
       "3   /Users/jan/pyiron/projects/   \n",
       "4   /Users/jan/pyiron/projects/   \n",
       "5   /Users/jan/pyiron/projects/   \n",
       "6   /Users/jan/pyiron/projects/   \n",
       "7   /Users/jan/pyiron/projects/   \n",
       "8   /Users/jan/pyiron/projects/   \n",
       "9   /Users/jan/pyiron/projects/   \n",
       "10  /Users/jan/pyiron/projects/   \n",
       "11  /Users/jan/pyiron/projects/   \n",
       "12  /Users/jan/pyiron/projects/   \n",
       "13  /Users/jan/pyiron/projects/   \n",
       "14  /Users/jan/pyiron/projects/   \n",
       "\n",
       "                                                   project  \\\n",
       "0             2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "1             2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "2   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "3   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "4   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "5   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "6   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "7   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "8   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "9   2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "10  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "11  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "12  2019/2019-12-11-lanl-tutorial/demonstration/murn_hdf5/   \n",
       "13            2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "14            2019/2019-12-11-lanl-tutorial/demonstration/   \n",
       "\n",
       "                    timestart                   timestop  totalcputime  \\\n",
       "0  2019-12-10 16:45:41.117157 2019-12-10 16:45:42.227282           1.0   \n",
       "1  2019-12-10 16:45:44.863248 2019-12-10 16:46:06.707634          21.0   \n",
       "2  2019-12-10 16:45:46.793676 2019-12-10 16:45:47.391474           0.0   \n",
       "3  2019-12-10 16:45:48.755689 2019-12-10 16:45:49.608306           0.0   \n",
       "4  2019-12-10 16:45:50.988969 2019-12-10 16:45:51.454903           0.0   \n",
       "5  2019-12-10 16:45:52.878985 2019-12-10 16:45:53.487162           0.0   \n",
       "6  2019-12-10 16:45:54.925316 2019-12-10 16:45:55.340213           0.0   \n",
       "7  2019-12-10 16:45:56.551747 2019-12-10 16:45:56.977871           0.0   \n",
       "8  2019-12-10 16:45:58.426541 2019-12-10 16:45:58.915650           0.0   \n",
       "9  2019-12-10 16:46:00.400515 2019-12-10 16:46:01.180575           0.0   \n",
       "10 2019-12-10 16:46:02.470651 2019-12-10 16:46:02.930345           0.0   \n",
       "11 2019-12-10 16:46:04.100879 2019-12-10 16:46:04.556366           0.0   \n",
       "12 2019-12-10 16:46:05.672669 2019-12-10 16:46:06.074122           0.0   \n",
       "13 2019-12-10 16:46:07.886290 2019-12-10 16:46:08.090257           0.0   \n",
       "14 2019-12-10 16:46:08.593883                        NaT           NaN   \n",
       "\n",
       "                            computer   hamilton hamversion parentid  masterid  \n",
       "0         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       NaN  \n",
       "1   pyiron@MacBook-Pro.local#1#11/11  Murnaghan      0.3.0     None       NaN  \n",
       "2         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "3         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "4         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "5         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "6         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "7         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "8         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "9         pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "10        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "11        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "12        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       2.0  \n",
       "13        pyiron@MacBook-Pro.local#1   TableJob        0.1     None       NaN  \n",
       "14        pyiron@MacBook-Pro.local#1     Lammps        0.1     None       NaN  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr.job_table()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[-1.21430643e-17, -8.67361738e-18,  1.38777878e-17],\n",
       "        [ 4.02455846e-16, -1.73472348e-17,  3.46944695e-17],\n",
       "        [ 4.57966998e-16, -3.12250226e-17,  1.04083409e-17],\n",
       "        [-8.50881865e-16,  2.77555756e-17,  1.04083409e-17]]])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_interactive.output.forces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "structure_displace = structure.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [2.02500000e+00, 2.02500000e+00, 0.00000000e+00],\n",
       "       [2.02500000e+00, 1.23995488e-16, 2.02500000e+00],\n",
       "       [2.47990977e-16, 2.02500000e+00, 2.02500000e+00]])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "structure_displace.positions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "structure_displace.positions[0] = [0.1, 0.1, 0.1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.structure = structure_displace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[-1.21430643e-17, -8.67361738e-18,  1.38777878e-17],\n",
       "        [ 4.02455846e-16, -1.73472348e-17,  3.46944695e-17],\n",
       "        [ 4.57966998e-16, -3.12250226e-17,  1.04083409e-17],\n",
       "        [-8.50881865e-16,  2.77555756e-17,  1.04083409e-17]],\n",
       "\n",
       "       [[-4.55030844e-01, -4.55030844e-01, -4.55030844e-01],\n",
       "        [ 2.35038075e-01,  2.35038075e-01, -1.50453048e-02],\n",
       "        [ 2.35038075e-01, -1.50453048e-02,  2.35038075e-01],\n",
       "        [-1.50453048e-02,  2.35038075e-01,  2.35038075e-01]]])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job_interactive.output.forces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_interactive.interactive_close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_inter_mini = pr.create_job(pr.job_type.Lammps, 'lammps_int_template')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_inter_mini.structure = structure_displace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_inter_mini.potential = 'Al_Mg_Mendelev_eam'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "job_inter_mini.server.run_mode.interactive = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "mini = pr.create_job(pr.job_type.ScipyMinimizer, 'mini')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "mini.ref_job = job_inter_mini"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The job mini was saved and received the ID: 16\n",
      "The job lammps_int_template was saved and received the ID: 17\n"
     ]
    }
   ],
   "source": [
    "mini.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-13.57796067,  -9.43921041, -13.62207552, -13.63559813,\n",
       "       -13.54439975, -13.64239149, -13.64071651, -13.64243195,\n",
       "       -13.64243082, -13.642432  , -13.64243181, -13.64243201])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mini.ref_job.output.energy_tot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x116e62c18>]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(mini.ref_job.output.energy_tot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GUI "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "63b88c79209b4a3c8e633e1a90b894b0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HBox(children=(VBox(children=(Select(description='Groups:', options=('.', '..'), value='.'), Se…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pr.gui()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}