{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0477d43d",
   "metadata": {},
   "source": [
    "# Estimators"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f08002bd",
   "metadata": {},
   "source": [
    "We provide here an example of scikit-dimension estimators performances on two different proteins, [villin](#villin) and [NTL9](#ntl9).\n",
    "\n",
    "The test is performed on dihedral angles and data is divided between folded and unfolded trajectories."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a13cdbc",
   "metadata": {},
   "source": [
    "## Villin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "da5834fc-63d7-4116-9183-12a5024d7410",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:24:53.662642Z",
     "iopub.status.busy": "2025-11-10T13:24:53.657725Z",
     "iopub.status.idle": "2025-11-10T13:24:55.559429Z",
     "shell.execute_reply": "2025-11-10T13:24:55.558751Z"
    },
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Settings loaded.\n"
     ]
    }
   ],
   "source": [
    "%run maintainer/sett.py #import packages and plot setup\n",
    "Path(\"../extra\").mkdir(exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "40783b1d-4f08-44de-bfd0-468992fb1577",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:24:55.561157Z",
     "iopub.status.busy": "2025-11-10T13:24:55.560760Z",
     "iopub.status.idle": "2025-11-10T13:40:23.454938Z",
     "shell.execute_reply": "2025-11-10T13:40:23.454379Z"
    },
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "states = ['u0','u1', 'u2', 'f0', 'f1', 'f2'] \n",
    "estimators = ['CorrInt', 'DANCo', 'ESS', 'FisherS','KNN', 'lPCA', 'MADA', 'MiND_ML', 'MLE', 'MOM', 'TLE', 'TwoNN']\n",
    "projection_method = 'Dihedrals'  # or 'Distances'\n",
    "projection_kwargs = {'skip': 3}\n",
    "\n",
    "for estimator, state in product(estimators, states):\n",
    "    if estimator == 'MiND_ML': \n",
    "         mean_all, mean_last= intrinsic_dimension(topology='examples/villin/2f4k.pdb', \n",
    "                                                  trajectory=f'examples/villin/2f4k_{state}.xtc', \n",
    "                                                  projection_method=projection_method, \n",
    "                                                  projection_kwargs = projection_kwargs,\n",
    "                                                  id_method='global',\n",
    "                                                  id_kwargs={'estimator': estimator, 'D': 100}, #we changed default parameters to make it work on MD\n",
    "                                                  verbose=True\n",
    "                                                  )\n",
    "    else:    \n",
    "         mean_all, mean_last= intrinsic_dimension(topology='examples/villin/2f4k.pdb', \n",
    "                                                  trajectory=f'examples/villin/2f4k_{state}.xtc', \n",
    "                                                  projection_method=projection_method, \n",
    "                                                  projection_kwargs = projection_kwargs,\n",
    "                                                  id_method='global',\n",
    "                                                  id_kwargs={'estimator': estimator}, \n",
    "                                                  verbose=False\n",
    "                                                  )\n",
    "\n",
    "    data.append({'trajectory': state,\n",
    "\t  'estimator': estimator,\n",
    "\t  'mean_all': mean_all,\n",
    "\t  'mean_last': mean_last,\n",
    "      })\n",
    "data = pd.DataFrame(data)\n",
    "data[\"folded\"] = data[\"trajectory\"].str.startswith(\"f\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe714c7e-c913-4484-9794-559000ac4374",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:40:23.461437Z",
     "iopub.status.busy": "2025-11-10T13:40:23.460903Z",
     "iopub.status.idle": "2025-11-10T13:40:24.467294Z",
     "shell.execute_reply": "2025-11-10T13:40:24.466549Z"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax =plt.subplots(figsize=(6,5))\n",
    "ax = plt.gca()\n",
    "group=data.groupby('trajectory')\n",
    "estimators = data['estimator'].unique()\n",
    "\n",
    "for i, estimator in enumerate(estimators):\n",
    "    if estimator == \"KNN\": \n",
    "        continue\n",
    "\n",
    "    color = cmap(i / (len(estimators) - 1)) \n",
    "    estimator_data = data[data['estimator'] == estimator]\n",
    "    folded_values = estimator_data[estimator_data['folded']]['mean_all'].dropna()\n",
    "    unfolded_values = estimator_data[~estimator_data['folded']]['mean_all'].dropna()\n",
    "    x_mean = folded_values.mean()\n",
    "    y_mean = unfolded_values.mean()\n",
    "    x_std = folded_values.std(ddof=1) / np.sqrt(len(folded_values))\n",
    "    y_std = unfolded_values.std(ddof=1) / np.sqrt(len(unfolded_values))\n",
    "\n",
    "    ax.errorbar(x_mean, y_mean, xerr=x_std, yerr=y_std, fmt='none', ecolor='black', elinewidth=0.8,)\n",
    "    ax.scatter(x_mean, y_mean,facecolors=color, edgecolors='black',s=60, label=estimator)\n",
    "\n",
    "ax.set_box_aspect(1)    \n",
    "min_val = data['mean_all'].min() - 0.5\n",
    "max_val = data['mean_all'].max() + 0.5\n",
    "\n",
    "plt.axline((5, 5), (12, 12), lw=0.5, color='grey', alpha=0.8)\n",
    "plt.xlabel('Folded ID')\n",
    "plt.ylabel('Unfolded ID')\n",
    "plt.legend( loc='upper right', title= 'Estimator', ncol = 2)\n",
    "\n",
    "plt.ylim(0, 50)\n",
    "plt.xlim(0, 30)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../extra/villin_estimators_fvsu_{projection_method}.pdf', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84fd38ed",
   "metadata": {},
   "source": [
    "Because of the huge gap between folded replicas, in the previous plot we omitted KNN, which is shown below instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "231acece",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:40:24.469019Z",
     "iopub.status.busy": "2025-11-10T13:40:24.468863Z",
     "iopub.status.idle": "2025-11-10T13:40:25.573752Z",
     "shell.execute_reply": "2025-11-10T13:40:25.573100Z"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "estimators = data[\"estimator\"].unique()\n",
    "states = data[\"trajectory\"].unique()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8,8))\n",
    "\n",
    "color_map = {state: colors(i % colors.N) for i, state in enumerate(states)}\n",
    "\n",
    "shift_amount = 0.05\n",
    "n_traj = len(states)\n",
    "shifts = np.linspace(-shift_amount, shift_amount, n_traj)\n",
    "shift_map = dict(zip(states, shifts))\n",
    "\n",
    "for _, row in data.iterrows():\n",
    "    est_idx = np.where(estimators == row[\"estimator\"])[0][0]\n",
    "\n",
    "    x = est_idx + shift_map[row[\"trajectory\"]]\n",
    "\n",
    "    mean_val = row[\"mean_all\"]\n",
    "    this_color = color_map[row[\"trajectory\"]]\n",
    "\n",
    "    ax.scatter(\n",
    "        x, mean_val,\n",
    "        color=this_color,\n",
    "        edgecolor=\"black\",\n",
    "        alpha=0.8,\n",
    "        s=80,\n",
    "    )\n",
    "ax.set_box_aspect(1)\n",
    "\n",
    "ax.set_xticks(range(len(estimators)))\n",
    "ax.set_xticklabels(estimators, rotation=45, ha=\"right\")\n",
    "ax.set_ylabel(\"ID\")\n",
    "ax.set_xlabel(\"Estimator\")\n",
    "\n",
    "handles = [\n",
    "    plt.Line2D([0],[0], marker='o', color='w',\n",
    "               markerfacecolor=color_map[s], markeredgecolor='black',\n",
    "               markersize=8, label=s)\n",
    "    for s in states\n",
    "]\n",
    "ax.legend(handles=handles, title='Trajectory', loc='best')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../extra/villin_estimators_{projection_method}.pdf', dpi=300)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03c873fb",
   "metadata": {},
   "source": [
    "## NTL9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b2f150d0-ffda-4c4f-b8ba-2bcfe3142b15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:40:25.575340Z",
     "iopub.status.busy": "2025-11-10T13:40:25.575176Z",
     "iopub.status.idle": "2025-11-10T13:54:04.709877Z",
     "shell.execute_reply": "2025-11-10T13:54:04.709361Z"
    },
    "tags": [
     "remove-cell"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Built-in projection \"Dihedrals\" computed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "md_intrinsic_dimension.md_intrinsic_dimension - INFO - Computing global intrinsic dimension using estimator \"MiND_ML\" (last simulation section = 100 frames).\n"
     ]
    }
   ],
   "source": [
    "data2 = []\n",
    "states = ['u0','u1', 'u2', 'f0', 'f1', 'f2'] \n",
    "estimators = ['CorrInt', 'DANCo', 'ESS', 'FisherS','KNN', 'lPCA', 'MADA', 'MiND_ML', 'MLE', 'MOM', 'TLE', 'TwoNN']\n",
    "projection_method = 'Dihedrals'  # or 'Distances'\n",
    "projection_kwargs = {'skip': 3}\n",
    "\n",
    "\n",
    "for estimator, state in product(estimators, states):\n",
    "    if estimator == 'MiND_ML':\n",
    "         mean_all, mean_last = intrinsic_dimension(topology='examples/NTL9/ntl9.pdb', \n",
    "                                                   trajectory=f'examples/NTL9/ntl9_{state}.xtc', \n",
    "                                                   projection_method=projection_method, \n",
    "                                                   projection_kwargs = projection_kwargs,\n",
    "                                                   id_method='global',\n",
    "                                                   id_kwargs={'estimator': estimator, 'D': 100}, #we set non-defaults parameters to make it work with MD\n",
    "                                                   verbose=True\n",
    "                                                   )\n",
    "    else:    \n",
    "         mean_all, mean_last = intrinsic_dimension(topology='examples/NTL9/ntl9.pdb',\n",
    "                                                    trajectory=f'examples/NTL9/ntl9_{state}.xtc', \n",
    "                                                    projection_method=projection_method, \n",
    "                                                    projection_kwargs = projection_kwargs,\n",
    "                                                    id_method='global',\n",
    "                                                    id_kwargs={'estimator': estimator}, \n",
    "                                                    verbose=False\n",
    "                                                    )\n",
    "\n",
    "    data2.append({'trajectory': state,\n",
    "\t  'estimator': estimator,\n",
    "\t  'mean_all': mean_all,\n",
    "\t  'mean_last': mean_last,\n",
    "     })\n",
    "data2 = pd.DataFrame(data2)\n",
    "data2[\"folded\"] = data2[\"trajectory\"].str.startswith(\"f\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ee60f1a2-5a26-4e04-8c52-3caaef332e60",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:54:04.715260Z",
     "iopub.status.busy": "2025-11-10T13:54:04.715043Z",
     "iopub.status.idle": "2025-11-10T13:54:05.200152Z",
     "shell.execute_reply": "2025-11-10T13:54:05.199372Z"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig, ax = plt.subplots(figsize=(6,5))\n",
    "ax = plt.gca()\n",
    "group=data2.groupby('trajectory')\n",
    "estimators = data2['estimator'].unique()\n",
    "\n",
    "for i, estimator in enumerate(estimators):\n",
    "    if estimator == \"KNN\": \n",
    "        continue\n",
    "\n",
    "    color = cmap(i / (len(estimators) - 1)) \n",
    "    estimator_data2 = data2[data2['estimator'] == estimator]\n",
    "    folded_values = estimator_data2[estimator_data2['folded']]['mean_all'].dropna()\n",
    "    unfolded_values = estimator_data2[~estimator_data2['folded']]['mean_all'].dropna()\n",
    "    x_mean = folded_values.mean()\n",
    "    y_mean = unfolded_values.mean()\n",
    "    x_std = folded_values.std(ddof=1) / np.sqrt(len(folded_values))\n",
    "    y_std = unfolded_values.std(ddof=1) / np.sqrt(len(unfolded_values))\n",
    "\n",
    "    ax.errorbar(x_mean, y_mean, xerr=x_std, yerr=y_std, fmt='none', ecolor='black', elinewidth=0.8,)\n",
    "    ax.scatter(x_mean, y_mean,facecolors=color, edgecolors='black',s=60, label=estimator)\n",
    "\n",
    "min_val = data2['mean_all'].min() - 0.5\n",
    "max_val = data2['mean_all'].max() + 0.5\n",
    "ax.set_box_aspect(1)\n",
    "\n",
    "plt.axline((5, 5), (12, 12), lw=0.5, color='grey', alpha=0.8)\n",
    "plt.xlabel('Folded ID')\n",
    "plt.ylabel('Unfolded ID')\n",
    "plt.legend( loc='upper right', title= 'Estimator', ncol = 2)\n",
    "\n",
    "plt.ylim(0, 50)\n",
    "plt.xlim(0, 35)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../extra/ntl9_estimators_fvsu_{projection_method}.pdf', dpi=300, bbox_inches='tight')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c53ab33",
   "metadata": {},
   "source": [
    "Because of the huge gap between folded replicas, in the previous plot we omitted KNN, which is shown below instead. \n",
    "\n",
    "As the result obtained on the two proteins is similar, we suggest not to use KNN for this kind of study."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "608d5bba-21e1-4dd0-bc88-98e9b63dcc2a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-10T13:54:05.201673Z",
     "iopub.status.busy": "2025-11-10T13:54:05.201502Z",
     "iopub.status.idle": "2025-11-10T13:54:06.200107Z",
     "shell.execute_reply": "2025-11-10T13:54:06.199170Z"
    },
    "tags": [
     "remove-input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "   \n",
    "estimators = data2[\"estimator\"].unique()\n",
    "states = data2[\"trajectory\"].unique()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8,8))\n",
    "color_map = {state: colors(i % colors.N) for i, state in enumerate(states)}\n",
    "shift_amount = 0.05\n",
    "n_traj = len(states)\n",
    "shifts = np.linspace(-shift_amount, shift_amount, n_traj)\n",
    "shift_map = dict(zip(states, shifts))\n",
    "\n",
    "for _, row in data.iterrows():\n",
    "    est_idx = np.where(estimators == row[\"estimator\"])[0][0]\n",
    "    x = est_idx + shift_map[row[\"trajectory\"]]\n",
    "    mean_val = row[\"mean_all\"]\n",
    "    this_color = color_map[row[\"trajectory\"]]\n",
    "    ax.scatter(\n",
    "        x, mean_val,\n",
    "        color=this_color,\n",
    "        edgecolor=\"black\",\n",
    "        alpha=0.8,\n",
    "        s=80,\n",
    "    )\n",
    "ax.set_box_aspect(1)\n",
    "\n",
    "ax.set_xticks(range(len(estimators)))\n",
    "ax.set_xticklabels(estimators, rotation=45, ha=\"right\")\n",
    "ax.set_ylabel(\"ID\")\n",
    "ax.set_xlabel(\"Estimator\")\n",
    "\n",
    "handles = [\n",
    "    plt.Line2D([0],[0], marker='o', color='w',\n",
    "               markerfacecolor=color_map[s], markeredgecolor='black',\n",
    "               markersize=8, label=s)\n",
    "    for s in states\n",
    "]\n",
    "ax.legend(handles=handles, title='Trajectory', loc='best')\n",
    "plt.tight_layout()\n",
    "plt.savefig(f'../extra/ntl9_estimators_{projection_method}.pdf', dpi=300)\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mdintrinsicdimension",
   "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}