tutorials/alanine_dipeptide/Cross_Validation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1d8375a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "MDtrajs_dir=\"./MDtrajs/\"\n",
    "Featurization_dir=\"./Featurization/\"\n",
    "GMRQ_dir=\"./GMRQ/\"\n",
    "MicroMSM_dir='./MicroMSM/'\n",
    "MacroMSM_dir='./MacroMSM/'\n",
    "\n",
    "topfile = MDtrajs_dir + \"ala2.pdb\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ad5a1e9",
   "metadata": {},
   "source": [
    "### Cross Validation of TICA parameters based on GMRQ Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3e42f573",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import KFold\n",
    "from msmbuilder.decomposition import tICA\n",
    "from msmbuilder.cluster import KMeans, KCenters, MiniBatchKMeans\n",
    "from msmbuilder.msm import MarkovStateModel\n",
    "import multiprocessing\n",
    "from joblib import Parallel, delayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9148cb26",
   "metadata": {},
   "outputs": [],
   "source": [
    "for para in ['lagtime', 'n_tics', 'n_clusters']:\n",
    "    para_dir = GMRQ_dir + para + '/'\n",
    "    if not os.path.exists(para_dir):\n",
    "        os.mkdir(para_dir)\n",
    "\n",
    "ftrajs = np.load(Featurization_dir + 'ftrajs.npy', allow_pickle=True)\n",
    "        \n",
    "def TICA_CV(lt=2, n_tics=3, n_clusters=800, trajs=ftrajs, runs=10, n_fold=5, para=None):\n",
    "    if para is None:\n",
    "        output_files_dir = GMRQ_dir\n",
    "    else:\n",
    "        output_files_dir = GMRQ_dir + para + '/'\n",
    "    \n",
    "    results = []\n",
    "    for run in range(runs):\n",
    "        cv = KFold(n_splits=n_fold, shuffle=True)\n",
    "        for train_index, test_index in cv.split(trajs):\n",
    "            \n",
    "            train_data = [trajs[i] for i in train_index]\n",
    "            test_data = [trajs[i] for i in test_index]\n",
    "            \n",
    "            tica = tICA(n_components=n_tics, lag_time=lt, kinetic_mapping=True)\n",
    "            tica.fit(train_data)\n",
    "            ttraj_train = tica.transform(train_data)\n",
    "            ttraj_test = tica.transform(test_data)\n",
    "            \n",
    "            cluster = KCenters(n_clusters=n_clusters)\n",
    "            cluster.fit(ttraj_train)\n",
    "            ctraj_train = cluster.predict(ttraj_train)\n",
    "            ctraj_test = cluster.predict(ttraj_test)\n",
    "            \n",
    "            msm = MarkovStateModel(n_timescales=3, lag_time=100, reversible_type='transpose', \n",
    "                                   verbose=False, ergodic_cutoff='off')\n",
    "            msm.fit(ctraj_train)\n",
    "            train_score = msm.score(ctraj_train)\n",
    "            test_score = msm.score(ctraj_test)\n",
    "            \n",
    "            results.append({\n",
    "                'type': 'train', 'score': train_score, \n",
    "                'lagtime': lt, 'n_tics': n_tics, 'n_clusters': n_clusters})\n",
    "            results.append({\n",
    "                'type': 'test', 'score': test_score, \n",
    "                'lagtime': lt, 'n_tics': n_tics, 'n_clusters': n_clusters})\n",
    "            \n",
    "        print('Run {} for {}lt, {}tics, {}clusters is complete'.format(run,lt,n_tics,n_clusters))\n",
    "    frame = pd.DataFrame(results)\n",
    "    frame.to_pickle(output_files_dir + \"{}lt_{}tics_{}clusters_gmrq.pickl\".format(lt,n_tics,n_clusters))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6c78999",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cross-validation for lag time\n",
    "lt_list = [1,2,4,8,16]\n",
    "Parallel(n_jobs=5)(delayed(TICA_CV)\\\n",
    "                   (lt=i, n_tics=3, n_clusters=800, para='lagtime') for i in lt_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b2ff5020",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cross-validation for number of tICs\n",
    "ntics_list = [2,3,4,5]\n",
    "Parallel(n_jobs=4)(delayed(TICA_CV)\\\n",
    "                   (lt=2, n_tics=i, n_clusters=800, para='n_tics') for i in ntics_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7af0dbb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cross-validation for number of clusters\n",
    "nc_list = [400, 600, 800, 1000, 1200]\n",
    "Parallel(n_jobs=5)(delayed(TICA_CV)\\\n",
    "                   (lt=2, n_tics=3, n_clusters=i, para=' n_clusters') for i in nc_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42f787ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# comprehensive cross-validation\n",
    "lt_list = [1,2,4,8,10,16]\n",
    "ntics_list = [2,3,4,5]\n",
    "nc_list = [400, 600, 800, 1000, 1200]\n",
    "\n",
    "for i in lt_list:\n",
    "    for j in ntics_list:\n",
    "        for k in nc_list:\n",
    "            TICA_CV(lt=i, n_tics=j, n_clusters=k)\n",
    "            \n",
    "# If enough resources:\n",
    "# Parallel(n_jobs=10)(delayed(TICA_CV)(lt=i, n_tics=j, n_clusters=k, trajs=oasis_trajs) for i, j, k in product(lt_list, ntics_list, nc_list))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12dfeeb7",
   "metadata": {},
   "source": [
    "### Plot the cross-validation results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a87e0e17",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "def load_pickles(file_dir):\n",
    "    pickle_files = glob.glob(file_dir)\n",
    "    data_list = []\n",
    "    for file in pickle_files:\n",
    "        with open(file, \"rb\") as f:\n",
    "            data = pickle.load(f)\n",
    "            data_list.append(data)\n",
    "    return data_list\n",
    "\n",
    "delta_t = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0fc1879c",
   "metadata": {},
   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 1800x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the results of sequential cross-validation\n",
    "plt.rcParams['font.size'] = 30\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 6), sharey=True,\n",
    "                         gridspec_kw={'width_ratios': [6, 4, 5]})\n",
    "\n",
    "pal = {'train': '#67a9cf', 'test': '#ed5736'}\n",
    "para = ['lagtime', 'n_tics', 'n_clusters']\n",
    "\n",
    "for i in range(len(para)):\n",
    "    file_dir = GMRQ_dir + para[i] + '/'\n",
    "    data = load_pickles(file_dir + '*.pickl')\n",
    "    df = pd.concat(data, axis=0)\n",
    "    df['lagtime'] = df['lagtime'] * delta_t\n",
    "    sns.boxplot(data=df, x=para[i], y='score', hue='type', \n",
    "                orient=\"v\", notch=False, \n",
    "                palette=pal, linewidth=3, width=0.7, \n",
    "                sym=\".\", showfliers=False, ax=axes[i])\n",
    "    axes[i].set_ylabel(\"\")   \n",
    "    axes[i].set_ylim(3.2, 3.6)\n",
    "    axes[i].legend([], frameon=False)\n",
    "    axes[i].tick_params(axis='both', direction='in', width=2, length=8)\n",
    "    for spine in axes[i].spines.values():\n",
    "        spine.set_linewidth(3)\n",
    "        \n",
    "axes[0].set_xlabel(\"lagtime (ps)\")\n",
    "axes[1].set_xlabel(\"Number of tICs\")\n",
    "axes[2].set_xlabel(\"Number of clusters\")\n",
    "fig.text(0.07, 0.5, \"GMRQ Score\", ha='center', va='center', rotation=90)\n",
    "\n",
    "plt.subplots_adjust(wspace=0.05)\n",
    "plt.savefig('./png/gmrq_tica_sequential.png', dpi=1000, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1a24de9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3200x2000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "file_dirs = ['./GMRQ/1lt_*.pickl', './GMRQ/2lt_*.pickl', './GMRQ/4lt_*.pickl',\n",
    "            './GMRQ/8lt_*.pickl', './GMRQ/10lt_*.pickl', './GMRQ/16lt_*.pickl']\n",
    "df_list = []\n",
    "\n",
    "for i in range(3):\n",
    "    df = pd.concat(load_pickles(file_dirs[2*i]) + load_pickles(file_dirs[2*i+1]), axis=0)\n",
    "    df['lagtime'] = df['lagtime'] * delta_t\n",
    "    df_sorted = df.sort_values(by=['lagtime','n_tics','n_clusters'])\n",
    "    df_sorted = df_sorted.reset_index(drop=True)\n",
    "    df_sorted['Model'] = df_sorted.apply(lambda row: f\"({row['lagtime']}, {row['n_tics']}, {row['n_clusters']})\", axis=1)\n",
    "    df_list.append(df_sorted)\n",
    "\n",
    "plt.rcParams['font.size'] = 30\n",
    "fig, axes = plt.subplots(3, 1, figsize=(32,20))\n",
    "\n",
    "pal = {'train': '#67a9cf', 'test': '#ed5736'}\n",
    "\n",
    "for i in range(len(axes)):\n",
    "    sns.boxplot(data=df_list[i], x='Model', y='score', hue='type', \n",
    "                orient=\"v\", notch=False, \n",
    "                palette=pal, linewidth=3, width=0.7, \n",
    "                sym=\".\", showfliers=False, ax=axes[i])\n",
    "    axes[i].axhline(y=3.45, color='grey', linewidth=3, zorder=0)\n",
    "    axes[i].set_ylabel(\"GMRQ Scores\")   \n",
    "    axes[i].set_yticks([3.3, 3.4, 3.45, 3.5])   \n",
    "    axes[i].set_yticklabels([3.3, 3.4, 3.45, 3.5])  \n",
    "    axes[i].set_xlabel(\"\")\n",
    "    axes[i].set_ylim(3.3, 3.5)\n",
    "    axes[i].legend([], frameon=False)\n",
    "    axes[i].tick_params(axis='both', direction='in', width=2, length=8)\n",
    "    axes[i].set_xticklabels(axes[i].get_xticklabels(), rotation=90)\n",
    "\n",
    "    for spine in axes[i].spines.values():\n",
    "        spine.set_linewidth(3)\n",
    "        \n",
    "plt.subplots_adjust(hspace=1)\n",
    "# plt.savefig('./png/gmrq_tica_comprehensive.png', dpi=1000, bbox_inches='tight')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}