cy5_Pack.ipynb

{
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   "execution_count": 24,
   "id": "88e5033d-e160-4274-8141-b46cbc7b9af1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import hoomd\n",
    "import flowermd\n",
    "import numpy as np\n",
    "import matplotlib as plt\n",
    "import mbuild as mb\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from flowermd.base import Molecule\n",
    "from flowermd.library import FF_from_file\n",
    "\n",
    "from flowermd.base import Pack"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "33d42c33-c6f4-4167-8356-7045da2e3913",
   "metadata": {},
   "outputs": [],
   "source": [
    "def espaloma_mol(file_path):\n",
    "    mol = mb.load(file_path)\n",
    "    for p in mol.particles():\n",
    "        p.name = f\"_{p.name}\"\n",
    "    return mol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bab8eca0-e6a6-4d6f-8ec4-0c97ecbc25c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "system_file = 'cy5.mol2'\n",
    "ff_filepath =  \"cy5.xml\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "65e94171-0b3e-4582-a96a-33a5d02900a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "esp_mol = espaloma_mol(system_file)\n",
    "cy5 = Molecule(num_mols = 2, compound = esp_mol)"
   ]
  },
  {
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   "execution_count": 28,
   "id": "9f4106d4-d3d1-4772-9e7b-1a8df523f539",
   "metadata": {},
   "outputs": [
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     "data": {
      "text/plain": [
       "<py3Dmol.view at 0x7febdf7a3dd0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cy5.molecules[0].visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "81dbda18-d513-4be4-a7ce-f9e4bc46fcad",
   "metadata": {},
   "outputs": [],
   "source": [
    "cy5_ff = FF_from_file(forcefield_files=ff_filepath)\n",
    "system=Pack(molecules=cy5,density=0.05,packing_expand_factor=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bce6b6c9-5af5-43a5-a740-b9282ed6a183",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No charged group detected, skipping electrostatics.\n"
     ]
    }
   ],
   "source": [
    "system.apply_forcefield(\n",
    "    r_cut=2.5, \n",
    "    force_field=cy5_ff, \n",
    "    auto_scale=True, \n",
    "    scale_charges=True,\n",
    "    remove_hydrogens=True, #check this\n",
    "    remove_charges=True) #check this "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2c09a48c-4316-472f-a5df-0db576a3782c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<gsd.hoomd.Frame at 0x7feaf2627810>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "system.hoomd_snapshot\n",
    "#this snapshot allows us to initialize the simulation in the next step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "46bcd5ad-633e-4818-b80d-11a28ec8c73d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing simulation state from a gsd.hoomd.Frame.\n"
     ]
    }
   ],
   "source": [
    "from flowermd.base import Simulation\n",
    "sim=Simulation.from_system(system=system, gsd_write_freq=100,log_write_freq=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ba9b40eb-3508-4dc5-8d94-5ad26afbe176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<hoomd.md.pair.pair.LJ at 0x7feae27d8b50>,\n",
       " <hoomd.md.special_pair.LJ at 0x7feaf2e750d0>,\n",
       " <hoomd.md.bond.Harmonic at 0x7feaf2fed3d0>,\n",
       " <hoomd.md.angle.Harmonic at 0x7feaf2fef050>,\n",
       " <hoomd.md.dihedral.Periodic at 0x7feaf2ddc210>,\n",
       " <hoomd.md.dihedral.Periodic at 0x7feaf2692d50>,\n",
       " <hoomd.md.dihedral.Periodic at 0x7febdf7876d0>,\n",
       " <hoomd.md.dihedral.Periodic at 0x7feaf2ffdbd0>]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hoomd_forces = system.hoomd_forcefield\n",
    "hoomd_forces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "88c4b9bf-17a8-4416-be53-be9425396ed5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'C0-C0-C2': _HOOMDDict{'t0': 2.1914687156677246, 'k': 882.8766661254487},\n",
       " 'C0-C0-N1': _HOOMDDict{'t0': 2.3564724922180176, 'k': 602.5562148446506},\n",
       " 'C2-C0-N1': _HOOMDDict{'t0': 2.233898878097534, 'k': 708.7293160261336},\n",
       " 'C0-C0-C0': _HOOMDDict{'t0': 2.2176170349121094, 'k': 700.3515285450342},\n",
       " 'C0-N1-C0': _HOOMDDict{'t0': 2.0452728271484375, 'k': 1224.1681393221738},\n",
       " 'C0-C2-C0': _HOOMDDict{'t0': 1.9567296504974365, 'k': 1154.2032283984497},\n",
       " 'C0-C2-C2': _HOOMDDict{'t0': 2.0078423023223877, 'k': 711.8165707213218},\n",
       " 'C2-C2-C2': _HOOMDDict{'t0': 1.9695239067077637, 'k': 801.2945416917091}}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "lj_force = hoomd_forces[3]\n",
    "\n",
    "dict(lj_force.params)\n",
    "#here we see the parameters of the force field t0 and k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "09e60d20-a0ef-4241-9a06-02f8c8f17aa3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.86620471e-07 2.86620471e-07 2.86620471e-07] cm\n"
     ]
    }
   ],
   "source": [
    "from flowermd.utils import get_target_box_mass_density\n",
    "\n",
    "target_box = get_target_box_mass_density(density=system.density, mass=system.mass.to(\"g\"))\n",
    "print(target_box)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5c082dcd-c0f5-485c-976a-7966c1cf935d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unyt_quantity(5.0000008e-05, 'g/cm**3')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.density.to(\"g/cm**3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0842aa53-8dba-4818-82d1-31f2d72eded5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 100 of 1000; TPS: 258.13; ETA: 0.1 minutes\n",
      "Step 200 of 1000; TPS: 493.05; ETA: 0.0 minutes\n",
      "Step 300 of 1000; TPS: 724.19; ETA: 0.0 minutes\n",
      "Step 400 of 1000; TPS: 940.77; ETA: 0.0 minutes\n",
      "Step 500 of 1000; TPS: 1149.07; ETA: 0.0 minutes\n",
      "Step 600 of 1000; TPS: 1336.26; ETA: 0.0 minutes\n",
      "Step 700 of 1000; TPS: 1533.42; ETA: 0.0 minutes\n",
      "Step 800 of 1000; TPS: 1725.1; ETA: 0.0 minutes\n",
      "Step 900 of 1000; TPS: 1910.85; ETA: 0.0 minutes\n",
      "Step 1000 of 1000; TPS: 2086.46; ETA: 0.0 minutes\n"
     ]
    }
   ],
   "source": [
    "sim.run_update_volume(n_steps=1000, period=1, kT=1, tau_kt=1, final_box_lengths= target_box)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1ac6473f-c1c2-404e-9c6c-46c5f7f59532",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "unyt_quantity(0.05, 'g/cm**3')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.density.to(\"g/cm**3\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "62e47d69-2208-45d6-a22d-b5a93b4c1b0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import hoomd\n",
    "for writer in sim.operations.writers:\n",
    "    if isinstance(writer, hoomd.write.GSD):\n",
    "        writer.flush()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4e357829-d7d6-4f97-a6a3-115ce76cf62b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<fresnel.util.ImageArray at 0x7feafb203dd0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from cmeutils.visualize import FresnelGSD\n",
    "\n",
    "sim_visualizer = FresnelGSD(gsd_file=\"trajectory.gsd\", frame=0, view_axis=(1, 1, 1))\n",
    "sim_visualizer.view()\n",
    "                         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "abb4d66e-b458-4e7a-a798-efbaeeb4b13d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<fresnel.util.ImageArray at 0x7feaf2a7df10>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_visualizer.frame = -1\n",
    "sim_visualizer.view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "14bad4fb-0576-4fbd-86f5-287b2c757d8c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 99 of 2000; TPS: 8898.08; ETA: 0.0 minutes\n",
      "Step 199 of 2000; TPS: 8600.2; ETA: 0.0 minutes\n",
      "Step 299 of 2000; TPS: 7923.89; ETA: 0.0 minutes\n",
      "Step 399 of 2000; TPS: 8436.94; ETA: 0.0 minutes\n",
      "Step 499 of 2000; TPS: 8906.9; ETA: 0.0 minutes\n",
      "Step 599 of 2000; TPS: 9497.38; ETA: 0.0 minutes\n",
      "Step 699 of 2000; TPS: 9663.1; ETA: 0.0 minutes\n",
      "Step 799 of 2000; TPS: 10036.05; ETA: 0.0 minutes\n",
      "Step 899 of 2000; TPS: 10213.24; ETA: 0.0 minutes\n",
      "Step 999 of 2000; TPS: 10482.58; ETA: 0.0 minutes\n",
      "Step 1099 of 2000; TPS: 10712.65; ETA: 0.0 minutes\n",
      "Step 1199 of 2000; TPS: 10939.58; ETA: 0.0 minutes\n",
      "Step 1299 of 2000; TPS: 11079.65; ETA: 0.0 minutes\n",
      "Step 1399 of 2000; TPS: 11249.06; ETA: 0.0 minutes\n",
      "Step 1499 of 2000; TPS: 11376.4; ETA: 0.0 minutes\n",
      "Step 1599 of 2000; TPS: 11477.67; ETA: 0.0 minutes\n",
      "Step 1699 of 2000; TPS: 11539.85; ETA: 0.0 minutes\n",
      "Step 1799 of 2000; TPS: 11564.89; ETA: 0.0 minutes\n",
      "Step 1899 of 2000; TPS: 11587.39; ETA: 0.0 minutes\n",
      "Step 1999 of 2000; TPS: 11614.93; ETA: 0.0 minutes\n"
     ]
    }
   ],
   "source": [
    "sim.run_NVT(n_steps=2000, kT=0.5, tau_kt=0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f281d977-e4f6-4fbf-a19e-f0b5ba6ece91",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "for writer in sim.operations.writers:\n",
    "    if isinstance(writer, hoomd.write.GSD):\n",
    "        writer.flush()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "abbaec1f-151a-495a-b6a0-460732cd2b78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<fresnel.util.ImageArray at 0x7feaf2631250>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "sim_visualizer.frame=-1\n",
    "sim_visualizer.view()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b676e20c-189d-4f75-be55-a6dc1eec0fb9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b896fb70-47de-4060-8005-356cdb7c194a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}