Deployed 4005ec7 with MkDocs version: 1.6.0

examples/index.html

@@ -933,6 +933,7 @@
 
 <h1 id="jupyter-notebook-examples">Jupyter Notebook Examples</h1>
 <p><a href="short_notebooks/Landscape_View_Xenium/">Landscape View Xenium</a></p>
+<p><a href="short_notebooks/Mouse-Brain_Alpha-Shape-Neighborhood/">Mouse-Brain_Alpha-Shape-Neighborhood</a></p>
 
 
 

examples/index.md

@@ -1,3 +1,5 @@
 # Jupyter Notebook Examples
 
-[Landscape View Xenium](short_notebooks/Landscape_View_Xenium.ipynb)
+[Landscape View Xenium](short_notebooks/Landscape_View_Xenium.ipynb)
+
+[Mouse-Brain_Alpha-Shape-Neighborhood](short_notebooks/Mouse-Brain_Alpha-Shape-Neighborhood.ipynb)

examples/short_notebooks/Celldega-heatmap/Celldega-heatmap.ipynb

@@ -0,0 +1,235 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a9471991-9d4a-4184-911c-72fe2e93b38f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: ANYWIDGET_HMR=1\n"
+     ]
+    }
+   ],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "%env ANYWIDGET_HMR=1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "fbf77bae-4979-4020-895c-a77b78a4dbd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# macOS requirement\n",
+    "import os\n",
+    "os.environ['DYLD_LIBRARY_PATH'] = '/opt/homebrew/lib:' + os.environ.get('DYLD_LIBRARY_PATH', '')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1f498de7-d3d4-4b75-83cd-50b9b56ee705",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ipywidgets import HBox, Layout, GridBox"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2a5daa53-ff35-4f57-87d4-43afb3c8358f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import celldega as dega\n",
+    "from ipywidgets import Widget"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "630e128c-d7bf-4c76-a550-6f22fd9549af",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ">> clustergrammer2 backend version 0.18.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "from clustergrammer2 import Network, CGM2\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7026a8eb-4e20-4d36-8781-2c7dc2ff59f9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generate random matrix\n",
+    "num_rows = 10\n",
+    "num_cols = 10\n",
+    "\n",
+    "np.random.seed(seed=100)\n",
+    "mat = np.random.rand(num_rows, num_cols)\n",
+    "\n",
+    "# make row and col labels\n",
+    "rows = range(num_rows)\n",
+    "cols = range(num_cols)\n",
+    "rows = ['row-' + str(i) for i in rows]\n",
+    "cols = ['col-' + str(i) for i in cols]\n",
+    "\n",
+    "# make dataframe\n",
+    "df = pd.DataFrame(data=mat, columns=cols, index=rows)\n",
+    "df.shape\n",
+    "\n",
+    "net = Network(CGM2)\n",
+    "net.load_df(df)\n",
+    "net.cluster()\n",
+    "network = net.viz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "94df98d9-48fb-40cc-a7f6-28f3da326f8e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "base_path = 'data/visium-hd_data/Visium_HD_Mouse_Lung_Fresh_Frozen_binned_outputs/square_008um/landscape_files'\n",
+    "\n",
+    "df_sig = pd.read_parquet(base_path + '/df_sig_marker.parquet')\n",
+    "df_sig.shape\n",
+    "\n",
+    "net = Network(CGM2)\n",
+    "net.load_df(df_sig)\n",
+    "net.filter_N_top(axis='row', N_top=5000)\n",
+    "net.normalize(axis='col', norm_type='umi')\n",
+    "net.normalize(axis='row', norm_type='zscore')\n",
+    "net.cluster()\n",
+    "network = net.viz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0ebde5a0-d55d-4be0-be82-c1a51588b6ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b5d9111a52534a7f811c79fa3f5d814d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "MatrixNew(height=500, network={'row_nodes': [{'name': 'Scgb1a1', 'ini': 635, 'clust': 149, 'rank': 224, 'rankv…"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Widget.close_all()\n",
+    "mat = dega.viz.MatrixNew(network=network, width=500, height=500)\n",
+    "mat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "9f2a89a8-7c21-451f-bb4b-8341c5fd7f0f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'type': 'row_label', 'value': {'name': 'Actc1'}}"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mat.click_info"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "30df5237-af82-45f6-844d-d4f5147423d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Example: Setting width to 'auto' or a specific value\n",
+    "# mat_1.layout = Layout(width='500px')  # Adjust as needed\n",
+    "# mat_2.layout = Layout(width='500px')  # Adjust as needed\n",
+    "# widgets_side_by_side = HBox([mat_1, mat_2])\n",
+    "# display(widgets_side_by_side)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c48c1b6c-b8bf-4490-8e51-5c401726288f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "77146e56-73b0-4e3b-8367-3778c6ec26c9",
+   "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": "3.9.19"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}