{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8a36c37f",
   "metadata": {},
   "source": [
    "# Read and Save file"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "aefac773",
   "metadata": {},
   "source": [
    "### mdapy can read/save file very efficiently. Including Dump, Data and Dump.gz formats.\n",
    "### The performance of mdapy is around **2-7 times** higher than ovito."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "05b4c287",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Taichi] version 1.7.1, llvm 15.0.1, commit 0f143b2f, win, python 3.10.14\n",
      "[Taichi] Starting on arch=x64\n"
     ]
    }
   ],
   "source": [
    "import mdapy as mp\n",
    "from time import time\n",
    "import matplotlib.pyplot as plt\n",
    "mp.init()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4a8e5849",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.11.3'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mp.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8c1789bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 10, 4)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ovito\n",
    "ovito.version"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "5214ca65",
   "metadata": {},
   "source": [
    "### Prepare a Data, Dump, Dump.gz files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dc55b45e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def prepare():\n",
    "    FCC = mp.LatticeMaker(3.615, 'FCC', 100, 100, 100)\n",
    "    FCC.compute()\n",
    "    print(f'Atom number is {FCC.N}.')\n",
    "    print('Saving to mdapy.data.')\n",
    "    FCC.write_data(output_name='mdapy.data')\n",
    "    print('Saving to mdapy.dump')\n",
    "    FCC.write_dump(output_name='mdapy.dump')\n",
    "    print('Saving to mdapy.dump.gz')\n",
    "    FCC.write_dump(output_name='mdapy.dump.gz', compress=True)\n",
    "    return FCC.N"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8c2c7d5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Atom number is 4000000.\n",
      "Saving to mdapy.data.\n",
      "Saving to mdapy.dump\n",
      "Saving to mdapy.dump.gz\n"
     ]
    }
   ],
   "source": [
    "N = prepare()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "50a32b32",
   "metadata": {},
   "source": [
    "### Read a dump file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5d9fefd3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.09702905019124348 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = mp.System('mdapy.dump')\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fced2811-1577-4787-82c3-09c5e641bff0",
   "metadata": {},
   "source": [
    "### Read a dump file in OVITO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "67336cc9-ae9f-4021-9303-b7aba3cac4f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4411790370941162 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = ovito.io.import_file('mdapy.dump')\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "55d40173-2595-425b-87e6-3e76bb8f1b11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Read dump with 4000000 atoms.')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Read dump with {N} atoms.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03199644-7c11-405f-b380-b3556429c3a6",
   "metadata": {},
   "source": [
    "### Read a data file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "af0ef438-5312-40ed-8a8b-81438c255e83",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.31187836329142254 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = mp.System('mdapy.data')\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36631d25-4ff4-4435-a5ad-6e6ce5478914",
   "metadata": {},
   "source": [
    "### Read a data file in ovito"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b50b19cb-1442-41ad-acd4-dbe2d132d8d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.358816146850586 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = ovito.io.import_file('mdapy.data')\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b1577185-8834-447c-9f67-e84a568eab01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Read data with 4000000 atoms.')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Read data with {N} atoms.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b31bc994-4f3e-4873-9fc6-a6255933419e",
   "metadata": {},
   "source": [
    "### Read a dump.gz file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cff160a7-1629-4b13-90b3-3f35e30a5a97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.32890017827351886 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = mp.System('mdapy.dump.gz')\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "073b18bf-bdb7-4530-8362-062473da8772",
   "metadata": {},
   "source": [
    "### Read a dump.gz file in ovito"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a1b23f1c-5c94-4915-963f-0f780cf2d56d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6621599197387695 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    _ = ovito.io.import_file('mdapy.dump.gz')\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c83f499f-9d41-4c5d-bc4a-cf09d68eebce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Read dump.gz with 4000000 atoms.')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Read dump.gz with {N} atoms.')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "20cfdcfd",
   "metadata": {},
   "source": [
    "### Save a dump file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f1d536b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.12828675905863443 s\n"
     ]
    }
   ],
   "source": [
    "system = mp.System('mdapy.dump')\n",
    "start = time()\n",
    "for _ in range(3):\n",
    "    system.write_dump()\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "89ccd665",
   "metadata": {},
   "source": [
    "### Save a dump file in OVITO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a93bad8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.302753448486328 s\n"
     ]
    }
   ],
   "source": [
    "pipeline = ovito.io.import_file('mdapy.dump')\n",
    "start = time()\n",
    "for _ in range(3):\n",
    "    ovito.io.export_file(pipeline, 'ovito.dump', format='lammps/dump', columns=[\"Particle Identifier\", \"Particle Type\", \"Position.X\", \"Position.Y\", \"Position.Z\"])\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4f27f00a-2f39-4a40-8383-2896a3fe0334",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Save dump with 4000000 atoms.')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Save dump with {N} atoms.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a315194c-5792-492f-a56d-6965359d902a",
   "metadata": {},
   "source": [
    "### Save a data file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6bbf0826-9e75-4e59-801b-af37eab4735f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.12710205713907877 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    system.write_data()\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94bb287a-a7be-4c67-b616-cd390cf0aee8",
   "metadata": {},
   "source": [
    "### Save a data file in ovito"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fd9b65c1-1954-4da9-b79f-7c18655637f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.2113478978474936 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    ovito.io.export_file(pipeline, 'ovito.data', format='lammps/data', atom_style='atomic')\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "036cdaac-bb09-4a23-b76d-55efb7980f0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Save data with 4000000 atoms.')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Save data with {N} atoms.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c52f3418-361a-4b68-b65c-81cd32abe51b",
   "metadata": {},
   "source": [
    "### Save a dump.gz file in mdapy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "164ce6d8-a564-4e5d-825d-8ff6431b0f5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7059536774953207 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    system.write_dump(compress=True)\n",
    "end = time()\n",
    "mdapy_time = (end - start)/3\n",
    "print(mdapy_time, 's')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fc1b674-a7b7-41c4-aa3a-cbd961f26a2e",
   "metadata": {},
   "source": [
    "### Save a dump.gz file in ovito"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2879c174-8703-4665-86f0-46132203212b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.8013707002003985 s\n"
     ]
    }
   ],
   "source": [
    "start = time()\n",
    "for _ in range(3):\n",
    "    ovito.io.export_file(pipeline, 'ovito.dump.gz', format='lammps/dump', columns=[\"Particle Identifier\", \"Particle Type\", \"Position.X\", \"Position.Y\", \"Position.Z\"])\n",
    "end = time()\n",
    "ovito_time = (end - start)/3\n",
    "print(ovito_time, 's')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "96958cbb-e9c7-4cca-bb8f-e4e11ebdc488",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Save dump.gz with 4000000 atoms.')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1181.1x708.661 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = mp.set_figure(figsize=(10, 6), use_pltset=True)\n",
    "plt.bar([0, 1], [mdapy_time, ovito_time])\n",
    "plt.xticks([0, 1], ['mdapy', 'ovito'])\n",
    "plt.ylabel('Time (s)')\n",
    "plt.title(f'Save dump.gz with {N} atoms.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d999929d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clear the output\n",
    "import os\n",
    "from glob import glob\n",
    "file_list = glob('*dump*') + glob(\"*.data\")\n",
    "for file in file_list:\n",
    "    try:\n",
    "        os.remove(file)\n",
    "    except Exception:\n",
    "        pass"
   ]
  }
 ],
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