Merge branch 'main' into work

docs/build.sh

@@ -4,4 +4,4 @@ conda activate stereopy-doc
 
 rm -rf ./build/*
 
-make html
+make html

docs/source/Tutorials/Apply_spaTrack_to_infer_cell_transitions_across_multiple_time_points_in_spatial_transcriptomic_data_from_the_mouse_midbrain.ipynb

@@ -587,7 +587,15 @@
    "id": "e21bafc3-f64a-47b2-a07d-0d58e5388299",
    "metadata": {},
    "source": [
-    "## Visualze cell transfer by dynamic figure"
+    "## Visualze cell transfer by dynamic figure\n",
+    "\n",
+    "<div class=\"alert alert-info\">\n",
+    "\n",
+    "A necessary dependency needs to be installed:\n",
+    "    \n",
+    "    pip install nbformat\n",
+    "\n",
+    "</div>"
    ]
   },
   {
@@ -982,12 +990,25 @@
    "source": [
     "## Construct gene regulation network\n",
     "\n",
-    "Here, we use data from **E12.5** and **E14.5** as an example to construct regulatory network between TF genes and target genes inferred along the developmental trajectory between two time points.TF genes list of Mouse and Human can be download from [the link](http://116.6.21.110:8090/share/3ca60300-e8bd-4d67-8b68-14267e428523)."
+    "Here, we use data from **E12.5** and **E14.5** as an example to construct regulatory network between TF genes and target genes inferred along the developmental trajectory between two time points.TF genes list of Mouse and Human can be download from [the link](http://116.6.21.110:8090/share/3ca60300-e8bd-4d67-8b68-14267e428523).\n",
+    "\n",
+    "\n",
+    "<div class=\"alert alert-info\">\n",
+    "\n",
+    "**Torch** is the necessary dependency for this function and needs to be installed first.\n",
+    "\n",
+    "        CPU: pip install torch==2.4.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
+    "\n",
+    "        GPU(CUDA11): pip install torch==2.4.1+cu118 --extra-index-url https://download.pytorch.org/whl/\n",
+    "\n",
+    "        GPU(CUDA12): pip install torch==2.4.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
+    "\n",
+    "</div>"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "e8fd4151-9b4f-4be2-a3e8-17fe367669d5",
    "metadata": {
     "execution": {
@@ -1018,7 +1039,8 @@
     "    cell_generate_per_time=10000,\n",
     "    cell_select_per_time=50,\n",
     "    training_times=10,\n",
-    "    iter_times=30\n",
+    "    iter_times=30,\n",
+    "    use_gpu=False # set to True to use GPU\n",
     ")"
    ]
   },