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   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "import warnings\n",
    "from pylj import mc, sample, util\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mc_simulation(number_of_particles, temperature, box_length, number_of_steps, sample_frequency):\n",
    "    # Creates the visualisation environment\n",
    "    %matplotlib widget\n",
    "    # Initialise the system placing the particles on a square lattice\n",
    "    system = mc.initialise(number_of_particles, temperature, box_length, 'square')\n",
    "    # This sets the sampling class as Energy, which shows the energy of the system\n",
    "    sample_system = sample.Energy(system)\n",
    "    # Compute the energy of the system\n",
    "    system.compute_energy()\n",
    "    system.old_energy = system.energies.sum()\n",
    "    # Add this energy to the energy sample array\n",
    "    system.mc_sample()\n",
    "    # Begin the monte carlo loop\n",
    "    for i in range(0, number_of_steps):\n",
    "        system.step += 1\n",
    "        # Select a random particle to remove\n",
    "        system.select_random_particle()\n",
    "        # Select a random position to replace that particle\n",
    "        system.new_random_position()\n",
    "        # Compute the new energy of the system\n",
    "        system.compute_energy()\n",
    "        system.new_energy = system.energies.sum()\n",
    "        # Assess the Metropolis condition\n",
    "        if mc.metropolis(temperature, system.old_energy, system.new_energy):\n",
    "            system.accept()\n",
    "        else:\n",
    "            system.reject()\n",
    "        # Add this energy to the energy sample array\n",
    "        system.mc_sample()\n",
    "        # At a given frequency sample the positions and plot\n",
    "        if system.step % sample_frequency == 0:\n",
    "            sample_system.update(system)\n",
    "    return system"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `mc_simulation` function takes five variables:\n",
    "- The number of particles\n",
    "- The simulation temperature (for the Metropolis condition)\n",
    "- The simulation cell vector\n",
    "- The number of steps\n",
    "- The sampling frequency (how often the image is updated)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "system = mc_simulation(100, 273.15, 45, 5000, 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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