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   "source": [
    "# Finding the MSD uncertainties from a VASP file\n",
    "\n",
    "Using ``kinisi`` to obtain the mean-squared displacement and uncertainty in a VASP Xdatcar type file is straightforward and involves using the `DiffusionAnalyzer` class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from kinisi.analyze import DiffusionAnalyzer\n",
    "np.random.seed(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There the `params` dictionary describes details about the simulation, and are fully documented in the [parser module](./parser.html).\n",
    "The `'specie'` is the atomic/ionic species that you want to calculate the MSD for, the `'time_step'` is the simulation timestep in your molecular dynamics, and the `'step_skip'` is the frequency which with the data was written in your simulation trajectory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "params = {'specie': 'Li',\n",
    "          'time_step': 2.0,\n",
    "          'step_skip': 50}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Therefore, for this example, we have a simulation that had a timestep of 2 femtoseconds (note the [FAQs about units](https://kinisi.readthedocs.io/en/latest/faq.html)) but we only stored the trajectory information every 50 steps and we want to investigate only the lithium motion. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "msd = DiffusionAnalyzer.from_file('example_XDATCAR.gz', parser_params=params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `DiffusionAnalyzer` will perform the bootstrapping process to obtain the displacements and uncertainties (this is detailed in the [methodology](./methodology.html). \n",
    "To find out how to determine the diffusion coefficient with `DiffusionAnalyzer` continue [here](https://kinisi.readthedocs.io/en/latest/vasp_d.html). \n",
    "\n",
    "Then the MSD (`msd`) as a function of timestep (`dt`) can be plotted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.errorbar(msd.dt, msd.msd, msd.msd_std)\n",
    "plt.ylabel('MSD/Å$^2$')\n",
    "plt.xlabel('$\\Delta t$/ps')\n",
    "plt.show()"
   ]
  }
 ],
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