examples/ExampleOnQueryAndPrepFitSNAP.ipynb

{
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  {
   "cell_type": "markdown",
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   "metadata": {
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   },
   "source": [
    "# [WIP] Example for using QuickFitSNAP\n",
    "Author: Stefan Bringuier\n",
    "\n",
    "### Description\n",
    "This is notebooks is a work in progress (WIP) and trys to provide a potential path forward for generating SNAP interatomic potentials quickly using existing DFT data from existing high-throughput computational materials databases (ex. Materials Project) and [FitSNAP](https://fitsnap.github.io/). \n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Warning:</b> There are no gaurantees whatsoever on the quality of the potentials fit using this approach. This is very experimental!\n",
    "</div>\n",
    "\n",
    "### First steps\n",
    "Frist need to add QuickFitSNAP modules to path."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "466f5cd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import os\n",
    "from os import getcwd\n",
    "import sys\n",
    "import glob\n",
    "module_path = os.path.abspath(os.path.join('../')) # or the path to your source code\n",
    "sys.path.insert(0, module_path);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0db22161",
   "metadata": {},
   "source": [
    "## Grabbing data from databases\n",
    "The premise of QuickFitSNAP is to grab various DFT calculation results from different high-throughput computational material science projects such as Materials Project and then fit a SNAP potential using that data. Therefore we want to have a fairly low effort approach to grabbing all possible calculations given a chemical system query.\n",
    "\n",
    "At the momement there are classes to grab Materials Project and JARVIS databasee entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1aaa79fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quickfitsnap.dataio import GetAndWriteFitData\n",
    "from quickfitsnap.matquery import MaterialsProjectQuery\n",
    "from quickfitsnap.matquery import JARVISQuery\n",
    "import getpass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80a0f424-9d01-4788-8648-7ed3ba3a8850",
   "metadata": {},
   "source": [
    "Now energy your legacy materials project API key and make sure it is correct."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9753915c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      " ········\n"
     ]
    }
   ],
   "source": [
    "apikey = getpass.getpass()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba645fc6",
   "metadata": {},
   "source": [
    "Now perform a query of a chemical system in the format \"X-Y\", \"X-Y-Z\", etc., from the materials project or NIST JARVIS databases.\n",
    "\n",
    "For now I'm going to just use the JARVIS database, and will ignore the Materials Project data since they share duplicate entries.\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Warning:</b> If you use both Materials Project and JARVIS databases you will need to delete similiar entries  using a function like below.\n",
    "</div>\n",
    "\n",
    "```python\n",
    "from copy import deepcopy\n",
    "def removeOverlapEntries(dataset1,dataset2,tasktype='DFT-SCF'):\n",
    "    dtmp1,dtmp2 = deepcopy(dataset1),deepcopy(dataset2)\n",
    "    d1_meta, _ = dtmp1\n",
    "    d2_meta,d2_urls = dtmp2\n",
    "    for d1 in d1_meta:\n",
    "        ii = 0 # Increment over url of JARVIS calculations\n",
    "        for i,j in enumerate(d2_meta.values()):\n",
    "            for jj in j:\n",
    "                if jj['task_id'] == d1 and jj['task_type'] == tasktype:\n",
    "                    j.remove(jj)\n",
    "                    del d2_urls[ii]\n",
    "                else:\n",
    "                    ii += 1       \n",
    "    #Remove entry if list is empty\n",
    "    delk = []\n",
    "    for k in d2_meta:\n",
    "        if not d2_meta[k]:\n",
    "            delk.append(k)\n",
    "    for k in delk:\n",
    "        del d2_meta[k]\n",
    "\n",
    "    return d2_meta,d2_urls\n",
    "```\n",
    "\n",
    "I'll grab data for Aluminum Phosphide, which is a widebandgap semiconductor. Keep in mind the query will grab unary and binary entries. If you don't want unary just pass the keyword argument `unary=False`.\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> I'm using the MPRester legacy API, so you'll see a warning. Eventually the the new MPRester API will be used but some query features have changed at the moment.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "380e17b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/lib/python3.8/site-packages/pymatgen/ext/matproj.py:182: UserWarning: You are using the legacy MPRester. This version of the MPRester will no longer be updated. To access the latest data with the new MPRester, obtain a new API key from https://materialsproject.org/api and consult the docs at https://docs.materialsproject.org/ for more information.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Obtaining 3D dataset 76k ...\n",
      "Reference:https://www.nature.com/articles/s41524-020-00440-1\n",
      "Other versions:https://doi.org/10.6084/m9.figshare.6815699\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40.8M/40.8M [00:03<00:00, 13.2MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading the zipfile...\n",
      "Loading completed.\n"
     ]
    }
   ],
   "source": [
    "chemsys = \"Al-P\"\n",
    "mpquery = MaterialsProjectQuery(apikey,chemsys)\n",
    "jquery = JARVISQuery(chemsys)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b491927e",
   "metadata": {},
   "source": [
    "Once queried, the calculation output file urls are available but need to be extracted from the query.\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> The Materials Query only returns the mp-id no properties, where as the JARVIS query does include properties.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "347775ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/lib/python3.8/site-packages/pymatgen/ext/matproj.py:182: UserWarning: You are using the legacy MPRester. This version of the MPRester will no longer be updated. To access the latest data with the new MPRester, obtain a new API key from https://materialsproject.org/api and consult the docs at https://docs.materialsproject.org/ for more information.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For file patterns [['vasprun*', 'OUTCAR*', 'XDATCAR*']] and task_types [['GGA Static', 'GGA Structure Optimization', 'GGA NSCF Line', 'GGA+U Deformation', 'GGA+U Structure Optimization', 'GGA Deformation', 'SCAN Structure Optimization']], \n",
      "the following ids are not found on NOMAD [['mp-1413529', 'mp-1245152', 'mp-1244953', 'mp-1444877', 'mp-1245067', 'mp-1442110', 'mp-1429878', 'mp-1393326', 'mp-1245307', 'mp-1440816', 'mp-1245129', 'mp-1443516']]. \n",
      "If you need to upload them, please contact Patrick Huck at phuck@lbl.gov\n",
      "Removing entries with no urls from meta data!.\n"
     ]
    }
   ],
   "source": [
    "mp_meta,mp_urls = mpquery.getMPCalcOutFileInfo()\n",
    "j_meta, j_urls = jquery.getJARVISCalcOutFileInfo()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73a00716",
   "metadata": {},
   "source": [
    "There is an issue whereby if the pymatgen materials project MPRester can't grab the files from NOMAD for a given mp task_id then the meta info is still present which causes the iterate counter in GetAndWriteFitData to fail. Therefore a check in the method `getMPCalcOutFileInfo` grabs any `UserWarnings` and checks to see if what the materials project ids are and then removes them from the met data dict.\n",
    "\n",
    "As metioned above, I'm not going to use the Materials Project data sets but its easy to combine meta data and url list for different data sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "81ad015f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#meta = {**mp_meta,**j_meta}\n",
    "#urls = mp_urls + j_urls\n",
    "meta = j_meta\n",
    "urls = j_urls"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9404371a",
   "metadata": {},
   "source": [
    "Now we need to actually grab the raw data. To do this I'll use the `GetAndWriteFitData` class to read download and read them. We can then use the `writefitfiles` method to output them for FitSNAP; in JSON or extXYZ format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7f7c3bae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Calc. Output Files |████████████████████████████████████████| 24/24 [100%] in 2:13.3 (0.18/s)               \n"
     ]
    }
   ],
   "source": [
    "fitdata = GetAndWriteFitData(meta=meta,urls=urls,overwrite=True,outfrmt=\"extxyz\",folderpath=\"AlP_XYZ\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a298f2b4",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> This can take a long time depending on how big the dataset is. Also it is up to you to manage where these files are finally located at based on the `folderpath`. The raw calculation files are initially downloaded to `/tmp`. This is mentioned here because you may want to resume fitting after you've queried and downloaded all the files and therefore no longer need the steps up till now.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "533d1f36",
   "metadata": {},
   "source": [
    "So now we will write the fit data files to extended XYZ format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "30ae54e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write XYZ Fit Dataset Files |████████████████████████████████████████| 24/24 [100%] in 1.1s (22.94/s)                   \n"
     ]
    }
   ],
   "source": [
    "#fitdata.folderpath=getcwd()+\"/AlP_XYZ\"\n",
    "#fitdata.outfrmt='extxyz'\n",
    "fitdata.writefitfiles()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "362f7230",
   "metadata": {},
   "source": [
    "Since we will most likely be doing other stuff in our python notebook/script related to FitSNAP, we can view the file locations (sans extension):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "87888503",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['AlP_XYZ/Al4P4_JVASP-1327_mp-1550_FD-ELAST',\n",
       " 'AlP_XYZ/AlP_JVASP-1327_mp-1550_DFT-SCF',\n",
       " 'AlP_XYZ/Al2P2_JVASP-8182_mp-8880_FD-ELAST',\n",
       " 'AlP_XYZ/Al2P2_JVASP-8182_mp-8880_DFT-SCF',\n",
       " 'AlP_XYZ/Al4P4_JVASP-30519_mp-997569_FD-ELAST',\n",
       " 'AlP_XYZ/Al4_JVASP-14615_mp-134_FD-ELAST',\n",
       " 'AlP_XYZ/Al_JVASP-14615_mp-134_DFT-SCF',\n",
       " 'AlP_XYZ/Al_JVASP-7148_mp-ase-Al_FD-ELAST',\n",
       " 'AlP_XYZ/Al_JVASP-7148_mp-ase-Al_FD-ELAST',\n",
       " 'AlP_XYZ/Al_JVASP-7148_mp-ase-Al_DFT-SCF',\n",
       " 'AlP_XYZ/Al2_JVASP-25408_mp-998860_FD-ELAST',\n",
       " 'AlP_XYZ/Al_JVASP-25408_mp-998860_DFT-SCF',\n",
       " 'AlP_XYZ/Al4_JVASP-816_mp-134_FD-ELAST',\n",
       " 'AlP_XYZ/Al_JVASP-816_mp-134_DFT-SCF',\n",
       " 'AlP_XYZ/P8_JVASP-26_mp-blackP_FD-ELAST',\n",
       " 'AlP_XYZ/P4_JVASP-26_mp-blackP_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-15781_mp-7245_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-15781_mp-7245_DFT-SCF',\n",
       " 'AlP_XYZ/P_JVASP-7544_mp-ase-P_FD-ELAST',\n",
       " 'AlP_XYZ/P_JVASP-7544_mp-ase-P_FD-ELAST',\n",
       " 'AlP_XYZ/P_JVASP-7544_mp-ase-P_DFT-SCF',\n",
       " 'AlP_XYZ/P2_JVASP-7547_mp-ase-P2_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-7547_mp-ase-P2_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-7547_mp-ase-P2_DFT-SCF',\n",
       " 'AlP_XYZ/P6_JVASP-14611_mp-130_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-14611_mp-130_DFT-SCF',\n",
       " 'AlP_XYZ/P16_JVASP-7758_mp-12883_FD-ELAST',\n",
       " 'AlP_XYZ/P16_JVASP-7758_mp-12883_FD-ELAST',\n",
       " 'AlP_XYZ/P8_JVASP-7758_mp-12883_DFT-SCF',\n",
       " 'AlP_XYZ/P8_JVASP-7758_mp-12883_DFT-SCF',\n",
       " 'AlP_XYZ/P8_JVASP-7818_mp-157_FD-ELAST',\n",
       " 'AlP_XYZ/P8_JVASP-7818_mp-157_FD-ELAST',\n",
       " 'AlP_XYZ/P4_JVASP-7818_mp-157_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-7818_mp-157_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-25267_mp-604573_DFT-SCF',\n",
       " 'AlP_XYZ/P8_JVASP-25144_mp-157_FD-ELAST',\n",
       " 'AlP_XYZ/P4_JVASP-25144_mp-157_DFT-SCF',\n",
       " 'AlP_XYZ/P6_JVASP-25047_mp-130_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-25047_mp-130_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-25326_mp-7245_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-25326_mp-7245_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-25063_mp-1014013_FD-ELAST',\n",
       " 'AlP_XYZ/P4_JVASP-25063_mp-1014013_DFT-SCF',\n",
       " 'AlP_XYZ/P4_JVASP-25311_mp-674158_FD-ELAST',\n",
       " 'AlP_XYZ/P_JVASP-25311_mp-674158_DFT-SCF',\n",
       " 'AlP_XYZ/P8_JVASP-79517_mp-1064333_FD-ELAST',\n",
       " 'AlP_XYZ/P4_JVASP-79517_mp-1064333_DFT-SCF',\n",
       " 'AlP_XYZ/P24_JVASP-25087_mp-118_FD-ELAST',\n",
       " 'AlP_XYZ/P24_JVASP-25087_mp-118_DFT-SCF',\n",
       " 'AlP_XYZ/P16_JVASP-25091_mp-12883_FD-ELAST',\n",
       " 'AlP_XYZ/P8_JVASP-25091_mp-12883_DFT-SCF',\n",
       " 'AlP_XYZ/P2_JVASP-25186_mp-53_FD-ELAST',\n",
       " 'AlP_XYZ/P2_JVASP-25186_mp-53_DFT-SCF']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fitdata.outfilelist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a552bf7",
   "metadata": {},
   "source": [
    "## Setup and run FitSNAP\n",
    "With the data set downloaded we can perform a fit and use Bayesian optimization package to adjust hyperparameters. To adjust the hyperparameters I will group the calculations into `DFT-SCF` and `FD-ELAST` which correspond to ground-state GGA calculations and Finite-difference elastic constant GGA calculations. For more specifics you'll want to look at the input files for the `JVASP`/`mp-#` entries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6084bb3b",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quickfitsnap.intface import SetupAndPerformFit\n",
    "from bayes_opt import BayesianOptimization\n",
    "from bayes_opt.logger import JSONLogger\n",
    "from bayes_opt.event import Events;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e95acab",
   "metadata": {},
   "source": [
    "## Prepare list of fitting data\n",
    "Now we we prepare the list of fitting data groups and specify any defaults we want the input script for `FitSNAP` to have.\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<b>Note:</b> The query and download will actually grab duplicate entries in the databases, if they exist. This doesn't cause an issue other than the `FitSNAP` input file `QuickFitSNAP` generates will have duplicate entries. We just remove these and no issue.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2dc658bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#Uncomment the lines below and comment the botton line if already grabbed the data\n",
    "#outfilelist = [i.split('.xyz')[0] for i in glob.glob(\"./AlP_XYZ/*\")]\n",
    "#groups = set([i.split(\"AlP_XYZ/\")[-1] for i in outfilelist]) # Remove duplicates that JARVIS returns\n",
    "groups = set([i.split(\"AlP_XYZ/\")[-1] for i in fitdata.outfilelist]) # Remove duplicates that JARVIS returns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a42eda2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "inptfilesettings = {'numtypes':2,\n",
    "                    'twojmax':[6,6],\n",
    "                    'wj':[1.0,1.0],\n",
    "                    'radelem':[0.5,0.5],\n",
    "                    'species':['Al','P'],\n",
    "                    'eshift':[0.0,0.0],\n",
    "                    'masses':[[13,13],   #This is for the ZBL pair potential, bad kwarg name\n",
    "                              [13,15],\n",
    "                              [15,15]],\n",
    "                    'metricfile':'AlP_FitSNAP_results.md',\n",
    "                    'potfitname':\"AlP_potential\"}\n",
    "qsf = SetupAndPerformFit(getcwd()+\"/AlP_XYZ\",groups,scraper='XYZ',copy_file=True,assignbycalctype=False,**inptfilesettings)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1587ce53",
   "metadata": {},
   "source": [
    "## Set default group weights for  Bayesian Opt\n",
    "\n",
    "I need to find the structures from the list that are the structures with energy convex hull at 0.0, or the stable ground state structure. The reason is that I want these structures to basically be the only ones that have a eweight value, all the other structures should just be fitted for forces and stress."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecdd7b0d",
   "metadata": {},
   "source": [
    "Here I'm specifying how to weight the different structures. This is where we need domain knowledge on how we should assign weights and ranges. the kwarg `assignbytype=True` needs to bet set for below the hyperparameter tuning. Below the code, provides the dictionary neccessary to run `QuickFitSnap` object and to set the default values for the hyperparameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "adfba23c",
   "metadata": {},
   "outputs": [],
   "source": [
    "colnames = ['eweight','fweight','vweight']\n",
    "pbounds = {}\n",
    "for f in groups:\n",
    "    for c in colnames:\n",
    "        keyn = f+'_'+c\n",
    "        if c == 'eweight':\n",
    "            if 'DFT-SCF' in f:\n",
    "                pbounds[keyn] = (1.0e2,1.0e3)\n",
    "            else:\n",
    "                pbounds[keyn] = (1.0e0,1.0e1)\n",
    "        elif c == 'fweight':\n",
    "            pbounds[keyn] = (1.0e0,5.0e2)\n",
    "        elif c == 'vweight':\n",
    "            pbounds[keyn] = (1.0e-12,1.0e-11)\n",
    "## Here specify the SNAP potential bispectrum hyperparameters (i.e. cutoff)\n",
    "## Note if you have more than 1 species you would use keys like 'twojmax_1', 'twojmax_2', etc.\n",
    "pbounds['twojmax_1'] = (4,8)\n",
    "pbounds['twojmax_2'] = (4,8)\n",
    "pbounds['wj_1'] = (0.5,1.0)\n",
    "pbounds['wj_2'] = (0.5,1.0)\n",
    "pbounds['radelem_1'] = (0.5,1.1)\n",
    "pbounds['radelem_2'] = (0.5,1.1)\n",
    "pbounds['rcutfac'] = (2.8,4.8)\n",
    "pbounds['rfac0'] = (0.9,1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cce6e4a0",
   "metadata": {},
   "source": [
    "## Run Bayesian Opt of FitSNAP "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e86b76a2",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_29551/1353412952.py:5: DeprecationWarning: \n",
      "Passing acquisition function parameters or gaussian process parameters to maximize\n",
      "is no longer supported, and will cause an error in future releases. Instead,\n",
      "please use the \"set_gp_params\" method to set the gp params, and pass an instance\n",
      " of bayes_opt.util.UtilityFunction using the acquisition_function argument\n",
      "\n",
      "  optim.maximize(init_points=2,acq='poi',n_iter=10);\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 11957.41 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 52.13 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 17580.83 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 41.67 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 11493.93 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 32.23 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.1828 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 10411.49 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 30.74 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.3569 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 34749.46 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 31.60 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.3569 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 24185.16 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 41.94 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.3569 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 15337.62 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 31.70 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.3569 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 27374.66 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 45.99 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 11758.32 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 30.86 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.3569 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 29617.76 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 32.67 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 18551.92 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 30.60 ms on rank 0\n",
      "Using LAMMPSSNAP as FitSNAP calculator\n",
      "Al_JVASP-816_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P8_JVASP-79517_mp-1064333_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25267_mp-604573_DFT-SCF : Detected  15  fitting on  15  testing on  0\n",
      "P24_JVASP-25087_mp-118_FD-ELAST : Detected  85  fitting on  85  testing on  0\n",
      "P8_JVASP-7818_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-7818_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_FD-ELAST : Detected  21  fitting on  21  testing on  0\n",
      "AlP_JVASP-1327_mp-1550_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "P16_JVASP-7758_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "P2_JVASP-15781_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25311_mp-674158_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "Al4_JVASP-14615_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al4P4_JVASP-30519_mp-997569_FD-ELAST : Detected  25  fitting on  25  testing on  0\n",
      "Al_JVASP-14615_mp-134_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-25408_mp-998860_DFT-SCF : Detected  3  fitting on  3  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P2_JVASP-25047_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_DFT-SCF : Detected  119  fitting on  119  testing on  0\n",
      "P8_JVASP-25144_mp-157_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P16_JVASP-25091_mp-12883_FD-ELAST : Detected  31  fitting on  31  testing on  0\n",
      "Al4P4_JVASP-1327_mp-1550_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-25186_mp-53_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P2_JVASP-25326_mp-7245_DFT-SCF : Detected  19  fitting on  19  testing on  0\n",
      "Al2P2_JVASP-8182_mp-8880_DFT-SCF : Detected  11  fitting on  11  testing on  0\n",
      "P24_JVASP-25087_mp-118_DFT-SCF : Detected  192  fitting on  192  testing on  0\n",
      "P4_JVASP-79517_mp-1064333_DFT-SCF : Detected  30  fitting on  30  testing on  0\n",
      "P4_JVASP-26_mp-blackP_DFT-SCF : Detected  12  fitting on  12  testing on  0\n",
      "Al4_JVASP-816_mp-134_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P2_JVASP-7547_mp-ase-P2_DFT-SCF : Detected  5  fitting on  5  testing on  0\n",
      "P_JVASP-25311_mp-674158_DFT-SCF : Detected  13  fitting on  13  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_DFT-SCF : Detected  1  fitting on  1  testing on  0\n",
      "P_JVASP-7544_mp-ase-P_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "Al_JVASP-7148_mp-ase-Al_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P4_JVASP-15781_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "Al2_JVASP-25408_mp-998860_FD-ELAST : Detected  15  fitting on  15  testing on  0\n",
      "P6_JVASP-14611_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      "P2_JVASP-14611_mp-130_DFT-SCF : Detected  26  fitting on  26  testing on  0\n",
      "P8_JVASP-7758_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P2_JVASP-25186_mp-53_DFT-SCF : Detected  10  fitting on  10  testing on  0\n",
      "P4_JVASP-25144_mp-157_DFT-SCF : Detected  25  fitting on  25  testing on  0\n",
      "P8_JVASP-26_mp-blackP_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P8_JVASP-25091_mp-12883_DFT-SCF : Detected  80  fitting on  80  testing on  0\n",
      "P4_JVASP-25063_mp-1014013_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P4_JVASP-25326_mp-7245_FD-ELAST : Detected  19  fitting on  19  testing on  0\n",
      "P6_JVASP-25047_mp-130_FD-ELAST : Detected  17  fitting on  17  testing on  0\n",
      ">>> Matrix of descriptors takes up  0.2699 % of the total memory: 8.1247 GB\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "WARNING: Configuration has no SNAP neighbors\n",
      "'decorated_process_configs' took 12297.81 ms on rank 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n",
      "/home/stefanbringuier/.python-venv/atomistics/src/fitsnap/fitsnap3lib/solvers/solver.py:169: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  rsq = 1 - ssr / np.sum(np.square(this_true - (this_true / nconfig).sum()))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'decorated_write_output' took 30.75 ms on rank 0\n"
     ]
    }
   ],
   "source": [
    "# Bayesian Optimization where runFitSNAP outputs a composite MAE as target\n",
    "logger = JSONLogger(path=\"./AlP_bayes_opt_logs.json\")\n",
    "optim = BayesianOptimization(f=qsf.runFitSNAP,pbounds=pbounds,random_state=3,verbose=2)\n",
    "optim.subscribe(Events.OPTIMIZATION_STEP, logger)\n",
    "optim.maximize(init_points=2,acq='poi',n_iter=5);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54463ae4",
   "metadata": {},
   "source": [
    "## Analyze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "427551d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.pyplot:Loaded backend module://matplotlib_inline.backend_inline version unknown.\n"
     ]
    }
   ],
   "source": [
    "from fitsnap3lib.tools.dataframe_tools import DataframeTools\n",
    "from IPython.display import Image\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "#plt.logging.getLogger('matplotlib.font_manager').disabled = True\n",
    "import logging\n",
    "mpl_logger = logging.getLogger()\n",
    "mpl_logger.setLevel(logging.WARNING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "346547e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = DataframeTools(\"FitSNAP.df\")\n",
    "df.read_dataframe();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e92248ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfe  = df.df[df.df['Row_Type']=='Energy']\n",
    "dff = df.df[df.df['Row_Type'] == 'Force']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2f3808f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Energy Parity Plot\")\n",
    "plt.xlabel(\"Prediction [eV]\")\n",
    "plt.ylabel(\"Truth [eV]\")\n",
    "plt.scatter(dfe['preds'],dfe['truths']);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "517a48ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(dff['preds'],dff['truths'])\n",
    "plt.title(\"Forces Parity Plot\")\n",
    "plt.xlabel(\"Prediction [eV/Ang.]\")\n",
    "plt.ylabel(\"Truth [eV/Ang.]\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "b0b04114",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot_agreement(\"Energy\",\"Training\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "72a63aaf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot_agreement(\"Force\",\"Training\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "atomistics",
   "language": "python",
   "name": "atomistics"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "vscode": {
   "interpreter": {
    "hash": "3b94f089b16d65659fca98573ed0673266ad84d3bbe0b11232989d6f16a6a194"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}