{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PLAMS working folder: /home/hellstrom/adfhome/userdoc/ScriptingExamples/gasphase-ir-spectrum-from-md/plams_workdir.002\n"
     ]
    }
   ],
   "source": [
    "import scm.plams as plams\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# this line is not required in AMS2025+\n",
    "plams.init()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Molecule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.Image.Image image mode=RGBA size=200x200>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scm.base import ChemicalSystem\n",
    "from scm.plams import view\n",
    "\n",
    "mol = ChemicalSystem.from_smiles(\"NC(CO)OCC=O\")\n",
    "view(mol, width=200, height=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Engine settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Engine GFNFF\n",
      "EndEngine\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "s = plams.Settings()\n",
    "s.input.GFNFF  # GFN-FF force field\n",
    "# s.input.MLPotential.Model = \"AIMNet2-wB97MD3\"   # new ml model in AMS2024\n",
    "\n",
    "print(plams.AMSJob(settings=s).get_input())\n",
    "\n",
    "# run in serial\n",
    "s.runscript.nproc = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Some general parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 298  # temperature in K\n",
    "max_freq = 4000  # plot spectrum up to 4000 cm^-1\n",
    "max_dt_fs = 2000  # maximum correlation in fs for dipole derivative acf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Equilibration\n",
    "\n",
    "``temperature=(500, T, T)`` means that in the first half the simulation the system is cooled from 500 K to the given temperature, and then kept constant at that temperature.\n",
    "\n",
    "The initial temperature of 500 K does some preliminary conformer search."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.02|12:04:50] JOB nvt_eq STARTED\n",
      "[11.02|12:04:50] JOB nvt_eq RUNNING\n",
      "[11.02|12:04:52] JOB nvt_eq FINISHED\n",
      "[11.02|12:04:52] JOB nvt_eq SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "eq_job = plams.AMSNVTJob(\n",
    "    settings=s,\n",
    "    name=\"nvt_eq\",\n",
    "    molecule=mol,\n",
    "    timestep=0.5,\n",
    "    nsteps=10000,\n",
    "    temperature=(500, T, T),\n",
    ")\n",
    "eq_job.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NVE production simulation\n",
    "\n",
    "The ``binlog_dipolemoment`` option stores the dipole moment at every time step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.02|12:04:52] JOB nve_single_prod STARTED\n",
      "[11.02|12:04:52] JOB nve_single_prod RUNNING\n",
      "[11.02|12:05:01] JOB nve_single_prod FINISHED\n",
      "[11.02|12:05:01] JOB nve_single_prod SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "job = plams.AMSNVEJob.restart_from(\n",
    "    eq_job,\n",
    "    name=\"nve_single_prod\",\n",
    "    nsteps=50000,\n",
    "    binlog_dipolemoment=True,\n",
    "    binlog_time=True,\n",
    "    samplingfreq=100,\n",
    "    timestep=0.5,\n",
    ")\n",
    "job.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dipole derivative autocorrelation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "times, dipole_deriv_acf = job.results.get_dipole_derivatives_acf(start_fs=0, max_dt_fs=max_dt_fs)\n",
    "plt.plot(times, dipole_deriv_acf)\n",
    "plt.xlabel(\"Time (fs)\")\n",
    "plt.ylabel(\"Dipole deriv. autocorrelation (e bohr / fs)^2\")\n",
    "plt.title(\"Raw autocorrelation function\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ideally, you should set ``max_dt_fs`` above to a large enough number so that the autocorrelation function decreases to a constant value of 0 (**and** have a long enough MD simulation to get enough statistics!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IR spectrum\n",
    "\n",
    "The IR spectrum is the Fourier transform of the above autocorrelation function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_freq, y_intens_raw = job.results.get_ir_spectrum_md(times, dipole_deriv_acf, max_freq=max_freq)\n",
    "plt.plot(x_freq, y_intens_raw)\n",
    "plt.xlabel(\"Frequency (cm^-1)\")\n",
    "plt.title(\"IR spectrum (from raw autocorrelation function)\")\n",
    "plt.xlim(500, max_freq);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There seems to be quite some \"noise\" in the IR spectrum. One reason for this is that there is still some signal (or noise?) in the autocorrelation function at dt = 2000 fs.\n",
    "\n",
    "However, it's also possible to use a tapering (window) function to make the autocorrelation function smoothly decrease to 0. This will make the resulting IR spectrum look a bit more tidy. See the next section."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tapering function for autocorrelation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def tapered_cosine(x):\n",
    "    return 0.5 * (np.cos(np.pi * x / np.max(x)) + 1)\n",
    "\n",
    "\n",
    "plt.plot(times, tapered_cosine(times))\n",
    "plt.title(\"Tapering / cutoff / window function\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now apply this function to the autocorrelation function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dipole_deriv_acf_tapered_cosine = dipole_deriv_acf * tapered_cosine(times)\n",
    "plt.plot(times, dipole_deriv_acf_tapered_cosine)\n",
    "plt.xlabel(\"Time (fs)\")\n",
    "plt.title(\"Autocorrelation cosine tapering\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And calculate the IR spectrum:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_freq, y_intens_cosine = job.results.get_ir_spectrum_md(\n",
    "    times, dipole_deriv_acf_tapered_cosine, max_freq=max_freq\n",
    ")\n",
    "plt.plot(x_freq, y_intens_cosine)\n",
    "plt.xlabel(\"Frequency (cm^-1)\")\n",
    "plt.title(\"IR spectrum (from cosine-tapered autocorrelation function)\")\n",
    "plt.xlim(500, max_freq);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we see that using the cosine-tapered autocorrelation function gives a smoother IR spectrum without affecting the intensities too much."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare to IR spectrum calculated from harmonic approximation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare to an IR spectrum calculated with a geometry optimization + frequencies job, starting from the final frame of the MD simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.02|12:05:02] JOB harmonic STARTED\n",
      "[11.02|12:05:02] JOB harmonic RUNNING\n",
      "[11.02|12:05:02] JOB harmonic FINISHED\n",
      "[11.02|12:05:02] JOB harmonic SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "ams_s = plams.Settings()\n",
    "ams_s.input.ams.Task = \"GeometryOptimization\"\n",
    "ams_s.input.ams.Properties.NormalModes = \"Yes\"\n",
    "harmonic_job = plams.AMSJob(settings=ams_s + s, name=\"harmonic\", molecule=mol)\n",
    "harmonic_job.run();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "harmonic_freq, harmonic_intens = harmonic_job.results.get_ir_spectrum(\n",
    "    broadening_type=\"lorentzian\", broadening_width=20\n",
    ")\n",
    "plt.plot(harmonic_freq, harmonic_intens)\n",
    "rescale_factor = np.sum(harmonic_intens) / np.sum(y_intens_cosine)\n",
    "plt.plot(x_freq, y_intens_cosine * rescale_factor)  # rescale\n",
    "plt.legend([\"Harmonic\", \"MD NVE\"])\n",
    "plt.title(\"IR spectrum\")\n",
    "plt.xlabel(\"Frequency (cm^-1)\")\n",
    "plt.xlim(500, max_freq);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this case, the MD simulation samples multiple conformers so there are more peaks than for the harmonic calculation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View the trajectory in AMSmovie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "!amsmovie \"{job.results.rkfpath()}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View the normal modes in AMSspectra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "!amsspectra \"{harmonic_job.results.rkfpath(file='engine')}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Appendix: Average over multiple short NVE simulations\n",
    "\n",
    "Best practice is to run multiple NVE simulations starting from different points of the NVT simulation, assuming that the NVT simulation samples the correct equilibrium distribution of structures/conformers.\n",
    "\n",
    "Let's make this more explicit with another NVT simulation, followed by multiple NVE simulations from different points of the NVT simulation. See also the \"Molecular Dynamics with Python\" tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.02|12:05:10] JOB nvt_prod STARTED\n",
      "[11.02|12:05:10] JOB nvt_prod RUNNING\n",
      "[11.02|12:05:10] nvt_prod: AMS 2025.206  RunTime: Feb11-2026 12:05:10  ShM Nodes: 1  Procs: 1\n",
      "[11.02|12:05:10] nvt_prod: Starting MD calculation:\n",
      "[11.02|12:05:10] nvt_prod: --------------------\n",
      "[11.02|12:05:10] nvt_prod: Molecular Dynamics\n",
      "[11.02|12:05:10] nvt_prod: --------------------\n",
      "[11.02|12:05:10] nvt_prod:          Step       Time    Temp.         E Pot        Pressure        Volume\n",
      "[11.02|12:05:10] nvt_prod:                     (fs)      (K)          (au)           (MPa)         (A^3)\n",
      "[11.02|12:05:10] nvt_prod:             0       0.00     230.      -2.55389            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           100      50.00     249.      -2.55488            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           200     100.00     276.      -2.55492            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           300     150.00     314.      -2.55294            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           400     200.00     357.      -2.54813            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           500     250.00     494.      -2.55200            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           600     300.00     456.      -2.54947            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           700     350.00     352.      -2.54603            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           800     400.00     327.      -2.54888            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:           900     450.00     429.      -2.56013            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1000     500.00     280.      -2.55258            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1100     550.00     253.      -2.55264            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1200     600.00     139.      -2.54530            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1300     650.00     297.      -2.55648            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1400     700.00     284.      -2.55503            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1500     750.00     379.      -2.56008            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1600     800.00     436.      -2.56089            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1700     850.00     335.      -2.54971            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1800     900.00     335.      -2.54645            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          1900     950.00     309.      -2.54408            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2000    1000.00     228.      -2.54131            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2100    1050.00     255.      -2.54837            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2200    1100.00     308.      -2.55629            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2300    1150.00     341.      -2.56162            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2400    1200.00     309.      -2.56103            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2500    1250.00     289.      -2.55971            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2600    1300.00     251.      -2.55568            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2700    1350.00     290.      -2.55535            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2800    1400.00     323.      -2.55379            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          2900    1450.00     291.      -2.54793            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3000    1500.00     286.      -2.54553            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3100    1550.00     386.      -2.55192            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3200    1600.00     339.      -2.55029            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3300    1650.00     309.      -2.55384            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3400    1700.00     252.      -2.55644            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3500    1750.00     228.      -2.55710            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3600    1800.00     230.      -2.55710            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3700    1850.00     258.      -2.55752            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3800    1900.00     264.      -2.55518            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          3900    1950.00     287.      -2.55284            n/a            0.1\n",
      "[11.02|12:05:10] nvt_prod:          4000    2000.00     379.      -2.55528            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4100    2050.00     352.      -2.55071            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4200    2100.00     400.      -2.55383            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4300    2150.00     235.      -2.54436            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4400    2200.00     246.      -2.54866            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4500    2250.00     216.      -2.55287            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4600    2300.00     266.      -2.56192            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4700    2350.00     215.      -2.55957            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4800    2400.00     253.      -2.56130            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          4900    2450.00     261.      -2.55951            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5000    2500.00     268.      -2.55639            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5100    2550.00     258.      -2.55206            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5200    2600.00     274.      -2.55070            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5300    2650.00     299.      -2.55016            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5400    2700.00     351.      -2.55235            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5500    2750.00     289.      -2.54747            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5600    2800.00     287.      -2.54682            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5700    2850.00     294.      -2.54725            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5800    2900.00     324.      -2.54969            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          5900    2950.00     311.      -2.54984            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6000    3000.00     328.      -2.55247            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6100    3050.00     315.      -2.55381            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6200    3100.00     282.      -2.55576            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6300    3150.00     253.      -2.55749            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6400    3200.00     266.      -2.56106            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6500    3250.00     302.      -2.56457            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6600    3300.00     250.      -2.56017            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6700    3350.00     299.      -2.55858            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6800    3400.00     308.      -2.55104            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          6900    3450.00     365.      -2.55185            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7000    3500.00     360.      -2.55104            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7100    3550.00     397.      -2.55550            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7200    3600.00     348.      -2.55506            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7300    3650.00     282.      -2.55271            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7400    3700.00     347.      -2.55982            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7500    3750.00     306.      -2.56196            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7600    3800.00     212.      -2.56278            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7700    3850.00     173.      -2.56130            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7800    3900.00     215.      -2.56318            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          7900    3950.00     246.      -2.56229            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8000    4000.00     247.      -2.55848            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8100    4050.00     187.      -2.55117            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8200    4100.00     221.      -2.55100            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8300    4150.00     333.      -2.55615            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8400    4200.00     352.      -2.55531            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8500    4250.00     239.      -2.54541            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8600    4300.00     280.      -2.54739            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8700    4350.00     345.      -2.55273            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8800    4400.00     241.      -2.54977            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          8900    4450.00     237.      -2.55572            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9000    4500.00     236.      -2.55847            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9100    4550.00     227.      -2.55835            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9200    4600.00     238.      -2.55760            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9300    4650.00     206.      -2.55219            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9400    4700.00     226.      -2.54946            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9500    4750.00     284.      -2.55043            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9600    4800.00     338.      -2.55312            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9700    4850.00     262.      -2.54771            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9800    4900.00     350.      -2.55449            n/a            0.1\n",
      "[11.02|12:05:11] nvt_prod:          9900    4950.00     342.      -2.55547            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10000    5000.00     242.      -2.55096            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10100    5050.00     167.      -2.54864            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10200    5100.00     217.      -2.55595            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10300    5150.00     198.      -2.56014            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10400    5200.00     200.      -2.56410            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10500    5250.00     209.      -2.56480            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10600    5300.00     184.      -2.56148            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10700    5350.00     210.      -2.56081            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10800    5400.00     239.      -2.55905            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         10900    5450.00     239.      -2.55504            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11000    5500.00     325.      -2.55764            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11100    5550.00     380.      -2.55919            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11200    5600.00     395.      -2.55892            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11300    5650.00     304.      -2.55104            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11400    5700.00     391.      -2.55548            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11500    5750.00     280.      -2.54701            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11600    5800.00     264.      -2.54853            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11700    5850.00     242.      -2.55332            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11800    5900.00     207.      -2.55537            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         11900    5950.00     227.      -2.55821            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12000    6000.00     259.      -2.56011            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12100    6050.00     218.      -2.55526            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12200    6100.00     306.      -2.55696            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12300    6150.00     254.      -2.54923            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12400    6200.00     301.      -2.55036            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12500    6250.00     257.      -2.54664            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12600    6300.00     333.      -2.55236            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12700    6350.00     290.      -2.55020            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12800    6400.00     263.      -2.55000            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         12900    6450.00     233.      -2.55002            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13000    6500.00     253.      -2.55340            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13100    6550.00     226.      -2.55199            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13200    6600.00     283.      -2.55524            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13300    6650.00     365.      -2.55936            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13400    6700.00     323.      -2.55346            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13500    6750.00     284.      -2.54664            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13600    6800.00     331.      -2.54486            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13700    6850.00     414.      -2.54779            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13800    6900.00     314.      -2.54269            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         13900    6950.00     313.      -2.55062            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14000    7000.00     343.      -2.56133            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14100    7050.00     183.      -2.55132            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14200    7100.00     241.      -2.55465            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14300    7150.00     290.      -2.55650            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14400    7200.00     277.      -2.55334            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14500    7250.00     332.      -2.55399            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14600    7300.00     400.      -2.55502            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14700    7350.00     287.      -2.54405            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14800    7400.00     419.      -2.54991            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         14900    7450.00     395.      -2.54450            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15000    7500.00     465.      -2.54722            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15100    7550.00     318.      -2.54040            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15200    7600.00     355.      -2.55093            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15300    7650.00     230.      -2.54698            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15400    7700.00     241.      -2.55010            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15500    7750.00     258.      -2.55264            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15600    7800.00     301.      -2.55614            n/a            0.1\n",
      "[11.02|12:05:12] nvt_prod:         15700    7850.00     256.      -2.55310            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         15800    7900.00     326.      -2.55766            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         15900    7950.00     258.      -2.54943            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16000    8000.00     323.      -2.54434            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16100    8050.00     323.      -2.53902            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16200    8100.00     470.      -2.54960            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16300    8150.00     359.      -2.54590            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16400    8200.00     375.      -2.55200            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16500    8250.00     279.      -2.54892            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16600    8300.00     271.      -2.55118            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16700    8350.00     305.      -2.55475            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16800    8400.00     302.      -2.55494            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         16900    8450.00     249.      -2.55091            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17000    8500.00     368.      -2.55901            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17100    8550.00     332.      -2.55605            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17200    8600.00     351.      -2.55743            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17300    8650.00     287.      -2.55278            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17400    8700.00     299.      -2.55336            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17500    8750.00     326.      -2.55430            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17600    8800.00     287.      -2.54960            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17700    8850.00     322.      -2.55056            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17800    8900.00     356.      -2.55198            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         17900    8950.00     238.      -2.54392            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18000    9000.00     235.      -2.54563            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18100    9050.00     284.      -2.55344            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18200    9100.00     204.      -2.55274            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18300    9150.00     293.      -2.56276            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18400    9200.00     165.      -2.55523            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18500    9250.00     233.      -2.55956            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18600    9300.00     243.      -2.55844            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18700    9350.00     236.      -2.55650            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18800    9400.00     214.      -2.55338            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         18900    9450.00     249.      -2.55338            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19000    9500.00     257.      -2.55122            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19100    9550.00     284.      -2.55039            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19200    9600.00     300.      -2.54899            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19300    9650.00     361.      -2.55178            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19400    9700.00     332.      -2.55054            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19500    9750.00     316.      -2.55288            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19600    9800.00     288.      -2.55729            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19700    9850.00     217.      -2.55652            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19800    9900.00     264.      -2.56095            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         19900    9950.00     231.      -2.55784            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20000   10000.00     220.      -2.55497            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20100   10050.00     325.      -2.55935            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20200   10100.00     287.      -2.55334            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20300   10150.00     261.      -2.54882            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20400   10200.00     375.      -2.55562            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20500   10250.00     345.      -2.55326            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20600   10300.00     296.      -2.55035            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20700   10350.00     341.      -2.55456            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20800   10400.00     261.      -2.55002            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         20900   10450.00     283.      -2.55259            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         21000   10500.00     268.      -2.55313            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         21100   10550.00     245.      -2.55450            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         21200   10600.00     244.      -2.55817            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         21300   10650.00     217.      -2.55879            n/a            0.1\n",
      "[11.02|12:05:13] nvt_prod:         21400   10700.00     222.      -2.55966            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         21500   10750.00     207.      -2.55660            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         21600   10800.00     257.      -2.55493            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         21700   10850.00     354.      -2.55699            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         21800   10900.00     286.      -2.54993            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         21900   10950.00     322.      -2.55129            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22000   11000.00     387.      -2.55583            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22100   11050.00     297.      -2.55029            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22200   11100.00     233.      -2.54757            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22300   11150.00     374.      -2.56060            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22400   11200.00     267.      -2.55611            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22500   11250.00     251.      -2.55714            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22600   11300.00     260.      -2.55857            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22700   11350.00     296.      -2.56040            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22800   11400.00     232.      -2.55288            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         22900   11450.00     266.      -2.55023            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23000   11500.00     290.      -2.54720            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23100   11550.00     321.      -2.54739            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23200   11600.00     310.      -2.54715            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23300   11650.00     333.      -2.55052            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23400   11700.00     416.      -2.55824            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23500   11750.00     413.      -2.55975            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23600   11800.00     354.      -2.55713            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23700   11850.00     300.      -2.55504            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23800   11900.00     325.      -2.55842            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         23900   11950.00     324.      -2.55941            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24000   12000.00     297.      -2.55814            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24100   12050.00     230.      -2.55308            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24200   12100.00     225.      -2.55112            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24300   12150.00     313.      -2.55354            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24400   12200.00     340.      -2.55147            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24500   12250.00     309.      -2.54654            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24600   12300.00     402.      -2.55249            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24700   12350.00     374.      -2.55254            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24800   12400.00     347.      -2.55590            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         24900   12450.00     204.      -2.55141            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25000   12500.00     249.      -2.55764            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25100   12550.00     257.      -2.55848            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25200   12600.00     138.      -2.54883            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25300   12650.00     286.      -2.55755            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25400   12700.00     259.      -2.55332            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25500   12750.00     240.      -2.54969            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25600   12800.00     300.      -2.55241            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25700   12850.00     325.      -2.55363            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25800   12900.00     275.      -2.55016            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         25900   12950.00     383.      -2.55825            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26000   13000.00     347.      -2.55608            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26100   13050.00     438.      -2.56340            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26200   13100.00     335.      -2.55686            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26300   13150.00     237.      -2.55035            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26400   13200.00     226.      -2.55014            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26500   13250.00     222.      -2.55017            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26600   13300.00     235.      -2.55104            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26700   13350.00     296.      -2.55458            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26800   13400.00     366.      -2.55801            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         26900   13450.00     432.      -2.56093            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         27000   13500.00     361.      -2.55357            n/a            0.1\n",
      "[11.02|12:05:14] nvt_prod:         27100   13550.00     462.      -2.55791            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27200   13600.00     480.      -2.55636            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27300   13650.00     344.      -2.54690            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27400   13700.00     313.      -2.54970            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27500   13750.00     264.      -2.55301            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27600   13800.00     234.      -2.55444            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         27700   13850.00     278.      -2.55835            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         28100   14050.00     351.      -2.55475            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         28200   14100.00     264.      -2.54371            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         28400   14200.00     366.      -2.53986            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         28600   14300.00     307.      -2.54634            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         28700   14350.00     254.      -2.54955            n/a            0.1\n",
      "[11.02|12:05:15] nvt_prod:         28800   14400.00     336.      -2.55805            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         29100   14550.00     277.      -2.55509            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         30600   15300.00     379.      -2.54603            n/a            0.1\n",
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      "[11.02|12:05:15] nvt_prod:         32600   16300.00     266.      -2.55379            n/a            0.1\n",
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      "[11.02|12:05:16] nvt_prod:         34400   17200.00     317.      -2.55730            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         34500   17250.00     301.      -2.55652            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         34600   17300.00     231.      -2.55081            n/a            0.1\n",
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      "[11.02|12:05:16] nvt_prod:         34800   17400.00     241.      -2.54634            n/a            0.1\n",
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      "[11.02|12:05:16] nvt_prod:         35000   17500.00     280.      -2.54257            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35100   17550.00     386.      -2.55005            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35200   17600.00     356.      -2.55122            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35300   17650.00     270.      -2.55314            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35400   17700.00     317.      -2.56182            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35500   17750.00     255.      -2.55851            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35600   17800.00     231.      -2.55641            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35700   17850.00     277.      -2.55779            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35800   17900.00     316.      -2.55681            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         35900   17950.00     261.      -2.54859            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36000   18000.00     401.      -2.55561            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36100   18050.00     412.      -2.55510            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36200   18100.00     332.      -2.55017            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36300   18150.00     368.      -2.55379            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36400   18200.00     330.      -2.55262            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36500   18250.00     277.      -2.55037            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36600   18300.00     353.      -2.55717            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36700   18350.00     217.      -2.54935            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36800   18400.00     256.      -2.55460            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         36900   18450.00     246.      -2.55625            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37000   18500.00     218.      -2.55637            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37100   18550.00     181.      -2.55608            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37200   18600.00     169.      -2.55692            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37300   18650.00     191.      -2.55846            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37400   18700.00     241.      -2.55927            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37500   18750.00     225.      -2.55292            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37600   18800.00     401.      -2.56110            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37700   18850.00     308.      -2.55218            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37800   18900.00     366.      -2.55545            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         37900   18950.00     365.      -2.55458            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         38000   19000.00     353.      -2.55401            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         38100   19050.00     229.      -2.54774            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         38200   19100.00     226.      -2.55224            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         38300   19150.00     226.      -2.55726            n/a            0.1\n",
      "[11.02|12:05:16] nvt_prod:         38400   19200.00     212.      -2.55915            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         38500   19250.00     273.      -2.56352            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         38600   19300.00     285.      -2.56319            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         38700   19350.00     293.      -2.56179            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         38800   19400.00     333.      -2.56158            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         38900   19450.00     324.      -2.55766            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39000   19500.00     284.      -2.55251            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39100   19550.00     245.      -2.54788            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39200   19600.00     354.      -2.55465            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39300   19650.00     282.      -2.54844            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39400   19700.00     349.      -2.55255            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39500   19750.00     299.      -2.54919            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39600   19800.00     306.      -2.55150            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39700   19850.00     321.      -2.55686            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39800   19900.00     272.      -2.55794            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         39900   19950.00     175.      -2.55352            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40000   20000.00     182.      -2.55427            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40100   20050.00     217.      -2.55529            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40200   20100.00     234.      -2.55280            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40300   20150.00     296.      -2.54960            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40400   20200.00     274.      -2.54340            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40500   20250.00     350.      -2.54841            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40600   20300.00     328.      -2.54849            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40700   20350.00     345.      -2.55232            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40800   20400.00     233.      -2.54756            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         40900   20450.00     285.      -2.55430            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41000   20500.00     302.      -2.55772            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41100   20550.00     222.      -2.55370            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41200   20600.00     266.      -2.55753            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41300   20650.00     260.      -2.55619            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41400   20700.00     280.      -2.55411            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41500   20750.00     277.      -2.54645            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41600   20800.00     401.      -2.55055            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41700   20850.00     331.      -2.54486            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41800   20900.00     379.      -2.55031            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         41900   20950.00     296.      -2.54815            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42000   21000.00     292.      -2.55079            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42100   21050.00     345.      -2.55587            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42200   21100.00     257.      -2.55056            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42300   21150.00     340.      -2.55773            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42400   21200.00     240.      -2.55131            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42500   21250.00     269.      -2.55347            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42600   21300.00     227.      -2.54922            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42700   21350.00     315.      -2.55279            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42800   21400.00     358.      -2.55230            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         42900   21450.00     424.      -2.55520            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43000   21500.00     287.      -2.54621            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43100   21550.00     354.      -2.55382            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43200   21600.00     351.      -2.55888            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43300   21650.00     247.      -2.55649            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43400   21700.00     222.      -2.55699            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43500   21750.00     206.      -2.55554            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43600   21800.00     316.      -2.56223            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43700   21850.00     304.      -2.55977            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43800   21900.00     270.      -2.55595            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         43900   21950.00     285.      -2.55474            n/a            0.1\n",
      "[11.02|12:05:17] nvt_prod:         44000   22000.00     306.      -2.55329            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44100   22050.00     394.      -2.55686            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44200   22100.00     293.      -2.54758            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44300   22150.00     265.      -2.54437            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44400   22200.00     302.      -2.54633            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44500   22250.00     281.      -2.54622            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44600   22300.00     357.      -2.55597            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44700   22350.00     219.      -2.55192            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44800   22400.00     174.      -2.55147            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         44900   22450.00     237.      -2.55576            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45000   22500.00     296.      -2.55816            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45100   22550.00     257.      -2.55269            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45200   22600.00     334.      -2.55500            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45300   22650.00     286.      -2.54956            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45400   22700.00     331.      -2.55200            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45500   22750.00     260.      -2.54771            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45600   22800.00     228.      -2.54672            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45700   22850.00     280.      -2.55132            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45800   22900.00     330.      -2.55624            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         45900   22950.00     327.      -2.55798            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46000   23000.00     264.      -2.55659            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46100   23050.00     228.      -2.55768            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46200   23100.00     247.      -2.56149            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46300   23150.00     176.      -2.55706            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46400   23200.00     237.      -2.55991            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46500   23250.00     300.      -2.55871            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46600   23300.00     243.      -2.54846            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46700   23350.00     367.      -2.55398            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46800   23400.00     388.      -2.55376            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         46900   23450.00     360.      -2.55206            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47000   23500.00     408.      -2.55796            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47100   23550.00     208.      -2.54702            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47200   23600.00     298.      -2.55713            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47300   23650.00     272.      -2.55893            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47400   23700.00     220.      -2.55844            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47500   23750.00     159.      -2.55648            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47600   23800.00     240.      -2.56424            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47700   23850.00     186.      -2.56081            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47800   23900.00     203.      -2.55974            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         47900   23950.00     228.      -2.55610            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48000   24000.00     265.      -2.55394            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48100   24050.00     335.      -2.55597            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48200   24100.00     320.      -2.55281            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48300   24150.00     322.      -2.55214            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48400   24200.00     259.      -2.54696            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48500   24250.00     340.      -2.55237            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48600   24300.00     350.      -2.55412            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48700   24350.00     295.      -2.55414            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48800   24400.00     208.      -2.55205            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         48900   24450.00     282.      -2.56029            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49000   24500.00     224.      -2.55694            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49100   24550.00     286.      -2.56058            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49200   24600.00     283.      -2.55706            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49300   24650.00     310.      -2.55095            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49400   24700.00     472.      -2.55662            n/a            0.1\n",
      "[11.02|12:05:18] nvt_prod:         49500   24750.00     344.      -2.54766            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod:         49600   24800.00     281.      -2.54541            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod:         49700   24850.00     342.      -2.55339            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod:         49800   24900.00     352.      -2.55727            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod:         49900   24950.00     244.      -2.55259            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod:         50000   25000.00     252.      -2.55492            n/a            0.1\n",
      "[11.02|12:05:19] nvt_prod: MD calculation finished.\n",
      "[11.02|12:05:19] nvt_prod: NORMAL TERMINATION\n",
      "[11.02|12:05:19] JOB nvt_prod FINISHED\n",
      "[11.02|12:05:19] JOB nvt_prod SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "nvt_prod_job = plams.AMSNVTJob.restart_from(\n",
    "    eq_job,\n",
    "    name=\"nvt_prod\",\n",
    "    nsteps=50000,\n",
    "    samplingfreq=100,\n",
    "    timestep=0.5,\n",
    "    thermostat=\"NHC\",\n",
    "    tau=100,\n",
    "    temperature=T,\n",
    ")\n",
    "nvt_prod_job.run(watch=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.02|12:05:19] JOB nvespawner-nvt_prod STARTED\n",
      "[11.02|12:05:19] JOB nvespawner-nvt_prod RUNNING\n",
      "[11.02|12:05:19] JOB nvespawner-nvt_prod/nve1 STARTED\n",
      "[11.02|12:05:19] JOB nvespawner-nvt_prod/nve1 RUNNING\n",
      "[11.02|12:05:23] JOB nvespawner-nvt_prod/nve1 FINISHED\n",
      "[11.02|12:05:23] JOB nvespawner-nvt_prod/nve1 SUCCESSFUL\n",
      "[11.02|12:05:23] JOB nvespawner-nvt_prod/nve2 STARTED\n",
      "[11.02|12:05:23] JOB nvespawner-nvt_prod/nve2 RUNNING\n",
      "[11.02|12:05:27] JOB nvespawner-nvt_prod/nve2 FINISHED\n",
      "[11.02|12:05:27] JOB nvespawner-nvt_prod/nve2 SUCCESSFUL\n",
      "[11.02|12:05:27] JOB nvespawner-nvt_prod/nve3 STARTED\n",
      "[11.02|12:05:27] JOB nvespawner-nvt_prod/nve3 RUNNING\n",
      "[11.02|12:05:31] JOB nvespawner-nvt_prod/nve3 FINISHED\n",
      "[11.02|12:05:31] JOB nvespawner-nvt_prod/nve3 SUCCESSFUL\n",
      "[11.02|12:05:31] JOB nvespawner-nvt_prod/nve4 STARTED\n",
      "[11.02|12:05:31] JOB nvespawner-nvt_prod/nve4 RUNNING\n",
      "[11.02|12:05:35] JOB nvespawner-nvt_prod/nve4 FINISHED\n",
      "[11.02|12:05:35] JOB nvespawner-nvt_prod/nve4 SUCCESSFUL\n",
      "[11.02|12:05:35] JOB nvespawner-nvt_prod/nve5 STARTED\n",
      "[11.02|12:05:35] JOB nvespawner-nvt_prod/nve5 RUNNING\n",
      "[11.02|12:05:39] JOB nvespawner-nvt_prod/nve5 FINISHED\n",
      "[11.02|12:05:39] JOB nvespawner-nvt_prod/nve5 SUCCESSFUL\n",
      "[11.02|12:05:39] JOB nvespawner-nvt_prod/nve6 STARTED\n",
      "[11.02|12:05:39] JOB nvespawner-nvt_prod/nve6 RUNNING\n",
      "[11.02|12:05:43] JOB nvespawner-nvt_prod/nve6 FINISHED\n",
      "[11.02|12:05:43] JOB nvespawner-nvt_prod/nve6 SUCCESSFUL\n",
      "[11.02|12:05:43] JOB nvespawner-nvt_prod/nve7 STARTED\n",
      "[11.02|12:05:43] JOB nvespawner-nvt_prod/nve7 RUNNING\n",
      "[11.02|12:05:47] JOB nvespawner-nvt_prod/nve7 FINISHED\n",
      "[11.02|12:05:47] JOB nvespawner-nvt_prod/nve7 SUCCESSFUL\n",
      "[11.02|12:05:47] JOB nvespawner-nvt_prod/nve8 STARTED\n",
      "[11.02|12:05:47] JOB nvespawner-nvt_prod/nve8 RUNNING\n",
      "[11.02|12:05:51] JOB nvespawner-nvt_prod/nve8 FINISHED\n",
      "[11.02|12:05:51] JOB nvespawner-nvt_prod/nve8 SUCCESSFUL\n",
      "[11.02|12:05:51] JOB nvespawner-nvt_prod/nve9 STARTED\n",
      "[11.02|12:05:51] JOB nvespawner-nvt_prod/nve9 RUNNING\n",
      "[11.02|12:05:54] JOB nvespawner-nvt_prod/nve9 FINISHED\n",
      "[11.02|12:05:55] JOB nvespawner-nvt_prod/nve9 SUCCESSFUL\n",
      "[11.02|12:05:55] JOB nvespawner-nvt_prod/nve10 STARTED\n",
      "[11.02|12:05:55] JOB nvespawner-nvt_prod/nve10 RUNNING\n",
      "[11.02|12:05:58] JOB nvespawner-nvt_prod/nve10 FINISHED\n",
      "[11.02|12:05:59] JOB nvespawner-nvt_prod/nve10 SUCCESSFUL\n",
      "[11.02|12:05:59] JOB nvespawner-nvt_prod FINISHED\n",
      "[11.02|12:05:59] JOB nvespawner-nvt_prod SUCCESSFUL\n"
     ]
    }
   ],
   "source": [
    "nvespawner_job = plams.AMSNVESpawnerJob(\n",
    "    nvt_prod_job,\n",
    "    name=\"nvespawner-\" + nvt_prod_job.name,\n",
    "    n_nve=10,  # the number of NVE simulations to run\n",
    "    timestep=0.5,\n",
    "    binlog_time=True,\n",
    "    binlog_dipolemoment=True,\n",
    "    nsteps=20000,\n",
    ")\n",
    "nvespawner_job.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check that the temperature during the NVE is not too far from the requested temperature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Set temperature during NVT: 298.0 K\n",
      "Mean temperature during NVE: 289.4\n"
     ]
    }
   ],
   "source": [
    "avg_T = nvespawner_job.results.get_mean_temperature()\n",
    "\n",
    "print(f\"Set temperature during NVT: {T:.1f} K\")\n",
    "print(f\"Mean temperature during NVE: {avg_T:.1f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the average dipole derivative autocorrelation function.\n",
    "\n",
    "To calculate the IR spectrum from our custom set of averaged data, we directly call the ``power_spectrum`` function from PLAMS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_x, avg_y = nvespawner_job.results.get_dipole_derivatives_acf(start_fs=0, max_dt_fs=max_dt_fs)\n",
    "avg_y *= tapered_cosine(avg_x)\n",
    "\n",
    "x_freq_multiple, y_intens_cosine_multiple = plams.trajectories.analysis.power_spectrum(\n",
    "    times, avg_y, max_freq=max_freq\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x_freq, y_intens_cosine)\n",
    "plt.plot(x_freq_multiple, y_intens_cosine_multiple)\n",
    "plt.xlabel(\"Frequency (cm^-1)\")\n",
    "plt.title(\"IR spectrum from multiple NVE simulations\")\n",
    "plt.legend([\"single\", \"multiple\"])\n",
    "plt.xlim(500, 4000);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}