{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6fc0ee93",
   "metadata": {},
   "source": [
    "---\n",
    "title: SeekSpace 高级分析：空间细胞类型密度分布图绘制\n",
    "author: SeekGene\n",
    "date: 2026-01-29\n",
    "tags:\n",
    "  - 空间转录组\n",
    "  - Notebooks\n",
    "  - 绘图\n",
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "420b84e4-1663-4fb7-9e80-a6c682618381",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "# SeekSpace 高级分析：空间细胞类型密度分布图绘制"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "db73d972-d261-470b-9e34-a4d4badaf5e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import gaussian_kde\n",
    "from mpl_toolkits.mplot3d import Axes3D\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e216d1cc-cfa2-4929-8da6-21b80c10a880",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## 数据加载\n",
    "先利用 R 从 rds 中保存空间坐标和注释结果"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06c37242-3522-4938-8b0d-c230142e546c",
   "metadata": {},
   "source": [
    "## 读取空间坐标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c9969a90-fec2-47cb-818e-d91b4c209194",
   "metadata": {},
   "outputs": [],
   "source": [
    "spatial_df = pd.read_csv(\"/PROJ2/FLOAT/weichendan/seekspace/SGS2401017/allsamples/00data/down_oss/ndGBM_5_2/ndGBM_5_2_barcode_centers.csv\",index_col=0,sep=',')\n",
    "spatial_df.drop(columns=['RNA_snn_res.0.8'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f7a565e-8855-4d03-9b63-7429a6bd1d7e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## 读取注释结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e01bcc33-7c3f-4a05-b4b0-578e1b7577e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#celltype_df = pd.read_csv('/PROJ2/FLOAT/weichendan/seekspace/SGS2401017/allsamples/08mistyR/ndGBM_5_2_celltype.csv', index_col=0)\n",
    "celltype_df = pd.read_csv(\"/PROJ2/FLOAT/weichendan/seekspace/SGS2401017/updata_allsamples/00data/scanpy_obs.csv\")\n",
    "celltype_df = celltype_df.drop(celltype_df.columns[0], axis=1)\n",
    "#celltype_df['new_cell_id'] = celltype_df['new_cell_id'].str.replace('_9', '')\n",
    "celltype_df['new_cell_id'] = celltype_df['new_cell_id'].str.replace(r'_\\d+$', '', regex=True)\n",
    "celltype_df = celltype_df.set_index('new_cell_id')\n",
    "celltype_df = celltype_df[celltype_df['sample_id'].str.contains(\"ndGBM_5_2\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "765b5f06-5161-4964-abe2-23b1c6a70409",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "spatial_df = spatial_df[spatial_df.index.isin(celltype_df.index)]\n",
    "spatial_df = spatial_df.reindex(celltype_df.index)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6978c231-1423-41dc-bfa9-538e3b85c9bd",
   "metadata": {},
   "source": [
    "## 合并数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9e100328-0a8b-4f61-9138-70acb5e9f80f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "merged_df = pd.merge(celltype_df, spatial_df, left_index=True, right_index=True,how=\"inner\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e505acbf-288e-459b-950f-51dbd16b9d49",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sample_id</th>\n",
       "      <th>cell_type</th>\n",
       "      <th>all_celltype</th>\n",
       "      <th>new_group</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_cell_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AGAGCCCCGATAGCTACCCTAATAACG</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Glioma</td>\n",
       "      <td>AC</td>\n",
       "      <td>GBM</td>\n",
       "      <td>27913</td>\n",
       "      <td>15055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CACCGTTATGGGAAACGTCCTATTAGG</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Fibroblast</td>\n",
       "      <td>Fibroblast</td>\n",
       "      <td>GBM</td>\n",
       "      <td>29920</td>\n",
       "      <td>4106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCCATTCTACGCCTTTGCTAAGTACGA</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Glioma</td>\n",
       "      <td>AC</td>\n",
       "      <td>GBM</td>\n",
       "      <td>34538</td>\n",
       "      <td>1969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAAGTCGCGACATCCGGCTAAGTACGA</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Oligodendrocyte</td>\n",
       "      <td>Oligodendrocyte</td>\n",
       "      <td>GBM</td>\n",
       "      <td>27680</td>\n",
       "      <td>10535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TACGTCCTACGAAGTGGGGACTGTGGA</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Fibroblast</td>\n",
       "      <td>Fibroblast</td>\n",
       "      <td>GBM</td>\n",
       "      <td>43135</td>\n",
       "      <td>11168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CGCGTGACGATGCAAGGAAGGCACTAT</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>GBM</td>\n",
       "      <td>33528</td>\n",
       "      <td>12544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GCCAGGTATGAGTCCGGGGACTGTGGA</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>GBM</td>\n",
       "      <td>40550</td>\n",
       "      <td>7503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TGGGTTAATGACGTCGAAAGGCACTAT</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>GBM</td>\n",
       "      <td>20952</td>\n",
       "      <td>13660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCCGGAACGAGTCAGCCCCTAATAACG</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>GBM</td>\n",
       "      <td>41631</td>\n",
       "      <td>16713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TCAGGGCGCTTTCTATCAGCGACGGAT</th>\n",
       "      <td>ndGBM_5_2</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>Endothelial_cell</td>\n",
       "      <td>GBM</td>\n",
       "      <td>34379</td>\n",
       "      <td>11688</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14055 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             sample_id         cell_type      all_celltype  \\\n",
       "new_cell_id                                                                  \n",
       "AGAGCCCCGATAGCTACCCTAATAACG  ndGBM_5_2            Glioma                AC   \n",
       "CACCGTTATGGGAAACGTCCTATTAGG  ndGBM_5_2        Fibroblast        Fibroblast   \n",
       "GCCATTCTACGCCTTTGCTAAGTACGA  ndGBM_5_2            Glioma                AC   \n",
       "TAAGTCGCGACATCCGGCTAAGTACGA  ndGBM_5_2   Oligodendrocyte   Oligodendrocyte   \n",
       "TACGTCCTACGAAGTGGGGACTGTGGA  ndGBM_5_2        Fibroblast        Fibroblast   \n",
       "...                                ...               ...               ...   \n",
       "CGCGTGACGATGCAAGGAAGGCACTAT  ndGBM_5_2  Endothelial_cell  Endothelial_cell   \n",
       "GCCAGGTATGAGTCCGGGGACTGTGGA  ndGBM_5_2  Endothelial_cell  Endothelial_cell   \n",
       "TGGGTTAATGACGTCGAAAGGCACTAT  ndGBM_5_2  Endothelial_cell  Endothelial_cell   \n",
       "CCCGGAACGAGTCAGCCCCTAATAACG  ndGBM_5_2  Endothelial_cell  Endothelial_cell   \n",
       "TCAGGGCGCTTTCTATCAGCGACGGAT  ndGBM_5_2  Endothelial_cell  Endothelial_cell   \n",
       "\n",
       "                            new_group      x      y  \n",
       "new_cell_id                                          \n",
       "AGAGCCCCGATAGCTACCCTAATAACG       GBM  27913  15055  \n",
       "CACCGTTATGGGAAACGTCCTATTAGG       GBM  29920   4106  \n",
       "GCCATTCTACGCCTTTGCTAAGTACGA       GBM  34538   1969  \n",
       "TAAGTCGCGACATCCGGCTAAGTACGA       GBM  27680  10535  \n",
       "TACGTCCTACGAAGTGGGGACTGTGGA       GBM  43135  11168  \n",
       "...                               ...    ...    ...  \n",
       "CGCGTGACGATGCAAGGAAGGCACTAT       GBM  33528  12544  \n",
       "GCCAGGTATGAGTCCGGGGACTGTGGA       GBM  40550   7503  \n",
       "TGGGTTAATGACGTCGAAAGGCACTAT       GBM  20952  13660  \n",
       "CCCGGAACGAGTCAGCCCCTAATAACG       GBM  41631  16713  \n",
       "TCAGGGCGCTTTCTATCAGCGACGGAT       GBM  34379  11688  \n",
       "\n",
       "[14055 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e08289ce-b7f2-4262-b3f0-ce6aa6141541",
   "metadata": {},
   "source": [
    "## 绘制 3D 空间密度图\n",
    "以细胞类型 AC 为例，绘制其 3D 空间密度图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7a7b2b4d-3ffe-448f-baca-98b33d516deb",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure size 1500x500 with 1 Axes"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_df1 = merged_df[merged_df['all_celltype']==\"AC\"][['x', 'y']]\n",
    "\n",
    "# 计算密度分布\n",
    "xy = np.vstack([merged_df1.x, merged_df1.y])\n",
    "kde = gaussian_kde(xy, bw_method=0.2)\n",
    "xmin, xmax = merged_df1.x.min(), merged_df1.x.max()\n",
    "ymin, ymax = merged_df1.y.min(), merged_df1.y.max()\n",
    "xgrid = np.linspace(xmin, xmax, 200)\n",
    "ygrid = np.linspace(ymin, ymax, 200)\n",
    "X, Y = np.meshgrid(xgrid, ygrid)\n",
    "Z = kde(np.vstack([X.ravel(), Y.ravel()])).reshape(X.shape)\n",
    "\n",
    "# 创建画布\n",
    "fig = plt.figure(figsize=(15, 5))\n",
    "\n",
    "# ---------------------------\n",
    "# 3D密度图（关键视角设置）\n",
    "# ---------------------------\n",
    "ax3d = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "###设置长:宽:高\n",
    "ax3d.set_box_aspect([15, 5, 5])\n",
    "\n",
    "## 取消网格\n",
    "ax3d.grid(False)  \n",
    "\n",
    "# 绘制密度曲面\n",
    "surf = ax3d.plot_surface(X, Y, Z, cmap='RdYlGn_r', \n",
    "                        rstride=5, cstride=5,\n",
    "                        alpha=1, antialiased=True,\n",
    "                        edgecolor='none')\n",
    "\n",
    "# 视角参数设置（关键调整）\n",
    "ax3d.view_init(elev=25, azim=-90)  # 通过azim调整坐标轴投影方向\n",
    "#ax3d.set_proj_type('ortho')         # 正交投影消除透视变形\n",
    "\n",
    "# 坐标轴范围同步\n",
    "ax3d.set_xlim(xmin, xmax)\n",
    "ax3d.set_ylim(ymin, ymax)\n",
    "ax3d.set_zlim(0, Z.max()*1.1)\n",
    "\n",
    "# 取消坐标轴刻度\n",
    "ax3d.set_xticks([])\n",
    "ax3d.set_yticks([])\n",
    "ax3d.set_zticks([])\n",
    "\n",
    "# 取消坐标轴线\n",
    "ax3d.xaxis.line.set_color((0,0,0,0))\n",
    "ax3d.yaxis.line.set_color((0,0,0,0))\n",
    "ax3d.zaxis.line.set_color((0,0,0,0))\n",
    "\n",
    "# 取消坐标轴标签\n",
    "ax3d.set_xlabel('')\n",
    "ax3d.set_ylabel('')\n",
    "ax3d.set_zlabel('')\n",
    "\n",
    "# 隐藏冗余标签\n",
    "ax3d.set_xticklabels([])\n",
    "ax3d.set_yticklabels([])\n",
    "#ax3d.set_zlabel('Density', labelpad=15, fontsize=12)\n",
    "# 背景和三面墙变成白色\n",
    "ax3d.set_facecolor('white')\n",
    "ax3d.xaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "ax3d.yaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "ax3d.zaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "\n",
    "plt.subplots_adjust(left=0, right=1, top=1, bottom=0)\n",
    "\n",
    "#plt.savefig('output.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce789907-532e-41ba-987e-68f61d56043d",
   "metadata": {},
   "source": [
    "## 绘制 3D 空间密度图的映射图\n",
    "以细胞类型 AC 为例，绘制其 3D 空间密度图的映射图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1282abcd-43ad-42a8-bb55-0598cb3b3b3d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure size 1500x500 with 1 Axes"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_df1 = merged_df[merged_df['all_celltype']==\"AC\"][['x', 'y']]\n",
    "\n",
    "# 计算密度分布\n",
    "xy = np.vstack([merged_df1.x, merged_df1.y])\n",
    "kde = gaussian_kde(xy, bw_method=0.2)\n",
    "xmin, xmax = merged_df1.x.min(), merged_df1.x.max()\n",
    "ymin, ymax = merged_df1.y.min(), merged_df1.y.max()\n",
    "xgrid = np.linspace(xmin, xmax, 200)\n",
    "ygrid = np.linspace(ymin, ymax, 200)\n",
    "X, Y = np.meshgrid(xgrid, ygrid)\n",
    "Z = kde(np.vstack([X.ravel(), Y.ravel()])).reshape(X.shape)\n",
    "\n",
    "# 创建画布\n",
    "fig = plt.figure(figsize=(15, 5))\n",
    "\n",
    "# ---------------------------\n",
    "# 3D密度图（关键视角设置）\n",
    "# ---------------------------\n",
    "ax3d = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "###设置长:宽:高\n",
    "ax3d.set_box_aspect([15, 5, 0.1])\n",
    "\n",
    "## 取消网格\n",
    "ax3d.grid(False)  \n",
    "\n",
    "# 绘制密度曲面\n",
    "surf = ax3d.plot_surface(X, Y, Z, cmap='RdYlGn_r', \n",
    "                        rstride=5, cstride=5,\n",
    "                        alpha=1, antialiased=True,\n",
    "                        edgecolor='none')\n",
    "\n",
    "# 视角参数设置（关键调整）\n",
    "ax3d.view_init(elev=25, azim=-90)  # 通过azim调整坐标轴投影方向\n",
    "#ax3d.set_proj_type('ortho')         # 正交投影消除透视变形\n",
    "\n",
    "# 坐标轴范围同步\n",
    "ax3d.set_xlim(xmin, xmax)\n",
    "ax3d.set_ylim(ymin, ymax)\n",
    "ax3d.set_zlim(0, Z.max()*1.1)\n",
    "\n",
    "# 取消坐标轴刻度\n",
    "ax3d.set_xticks([])\n",
    "ax3d.set_yticks([])\n",
    "ax3d.set_zticks([])\n",
    "\n",
    "# 取消坐标轴线\n",
    "ax3d.xaxis.line.set_color((0,0,0,0))\n",
    "ax3d.yaxis.line.set_color((0,0,0,0))\n",
    "ax3d.zaxis.line.set_color((0,0,0,0))\n",
    "\n",
    "# 取消坐标轴标签\n",
    "ax3d.set_xlabel('')\n",
    "ax3d.set_ylabel('')\n",
    "ax3d.set_zlabel('')\n",
    "\n",
    "# 隐藏冗余标签\n",
    "ax3d.set_xticklabels([])\n",
    "ax3d.set_yticklabels([])\n",
    "#ax3d.set_zlabel('Density', labelpad=15, fontsize=12)\n",
    "# 背景和三面墙变成白色\n",
    "ax3d.set_facecolor('white')\n",
    "ax3d.xaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "ax3d.yaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "ax3d.zaxis.set_pane_color((1.0, 1.0, 1.0, 1.0))\n",
    "\n",
    "plt.subplots_adjust(left=0, right=1, top=1, bottom=0)\n",
    "\n",
    "#plt.savefig('output.png', dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2f42fcd-cd48-4df4-9c21-1eb073d5e15f",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## 绘制 2D 密度图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "71fc14dc-85ee-4285-ac5b-39f5c27eff4e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure size 600x400 with 1 Axes"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2d, ax2d = plt.subplots(figsize=(6, 4))\n",
    "contour = ax2d.contourf(X, Y, Z, levels=20, cmap='RdYlGn_r')\n",
    "\n",
    "# 坐标轴设置\n",
    "ax2d.set(xlim=(xmin, xmax), ylim=(ymin, ymax), aspect='equal')\n",
    "\n",
    "# 取消坐标轴刻度\n",
    "ax2d.set_xticks([])\n",
    "ax2d.set_yticks([])\n",
    "\n",
    "# 取消坐标轴标签\n",
    "ax2d.set_xlabel('')\n",
    "ax2d.set_ylabel('')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e877c257-522f-49b5-839c-3c93ef1915c3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbf17b50-a4b7-4e06-90a0-04c412c14892",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cellcharter-env",
   "language": "python",
   "name": "cellcharter-env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.21"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}