diff --git a/docs/source/Tutorials(Multi-sample)/Batch_QC.ipynb b/docs/source/Tutorials(Multi-sample)/Batch_QC.ipynb
index f8ac85d0..06fdda81 100644
--- a/docs/source/Tutorials(Multi-sample)/Batch_QC.ipynb
+++ b/docs/source/Tutorials(Multi-sample)/Batch_QC.ipynb
@@ -27,13 +27,20 @@
"id": "086b62ac",
"metadata": {},
"source": [
+ "This function can be run on GPU, if you want to use GPU, you need to create an environment according to the guide [Clustering_by_GPU](../Tutorials/Clustering_by_GPU.html).\n",
+ "\n",
+ "\n",
"
\n",
"\n",
"**Note**\n",
"\n",
- "**Torch** need to be installed beforehand:\n",
+ "**Torch** is the necessary dependency, we need to install it beforehand:\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",
- " pip install torch\n",
+ " GPU(CUDA12): pip install torch==2.4.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
"\n",
"
"
]
diff --git a/docs/source/Tutorials(Multi-sample)/Comparative_Analysis.ipynb b/docs/source/Tutorials(Multi-sample)/Comparative_Analysis.ipynb
index ad373394..55710d57 100644
--- a/docs/source/Tutorials(Multi-sample)/Comparative_Analysis.ipynb
+++ b/docs/source/Tutorials(Multi-sample)/Comparative_Analysis.ipynb
@@ -46,426 +46,16 @@
"outputs": [
{
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(OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n"
+ "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = 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(OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n",
+ "application/vnd.holoviews_load.v0+json": ""
},
"metadata": {},
"output_type": "display_data"
@@ -1018,7 +608,7 @@
"id": "1b1bddc1-5f06-49ed-9af2-5c605bd08ae4",
"metadata": {},
"source": [
- "From Above, we can see the increment of co-occurrence of Fibroblase with other cell types except for MC and CD-IC from WT to UMOD KI samples."
+ "From Above, we can see the increment of co-occurrence of Fibroblast with other cell types except for MC and CD-IC from WT to UMOD KI samples."
]
},
{
diff --git a/docs/source/Tutorials(Multi-sample)/MSData_Clustering.ipynb b/docs/source/Tutorials(Multi-sample)/MSData_Clustering.ipynb
index 260ee025..9473b8bf 100644
--- a/docs/source/Tutorials(Multi-sample)/MSData_Clustering.ipynb
+++ b/docs/source/Tutorials(Multi-sample)/MSData_Clustering.ipynb
@@ -330,7 +330,7 @@
" - `scope` , similar to list, means which samples used for analysis.\n",
" - `mode`, like a switch, shows that analysis is performed on single sample or multi samples, `integrate` and `isolated`. It is easy to distinguish processing modes.\n",
"\n",
- "There are two ways to set `scope` and `mode`, running `ms_data.tl.set_mode_and_scope` to set them globally or pass them as parameters into each analysis function, the latter will overwrite the former on every specific function."
+ "There are two ways to set `scope` and `mode`, running `ms_data.tl.set_scope_and_mode` to set them globally or pass them as parameters into each analysis function, the latter will overwrite the former on every specific function."
]
},
{
diff --git a/docs/source/Tutorials(Multi-sample)/ST_Gears.ipynb b/docs/source/Tutorials(Multi-sample)/ST_Gears.ipynb
index 77ef3bc5..264bedec 100644
--- a/docs/source/Tutorials(Multi-sample)/ST_Gears.ipynb
+++ b/docs/source/Tutorials(Multi-sample)/ST_Gears.ipynb
@@ -15,15 +15,28 @@
" \n",
"2. `stack_slices_pairwise_rigid` rigidly aligns sections using Procrustes Analysis.\n",
" \n",
- "3. `stack_slices_pairwise_elas_field` eliminates distorsions through Gaussian Smoothed Elastic Fields. Validity is proved mathematically.\n",
- "\n",
+ "3. `stack_slices_pairwise_elas_field` eliminates distorsions through Gaussian Smoothed Elastic Fields. Validity is proved mathematically."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "efe84931",
+ "metadata": {},
+ "source": [
"This function can be run on GPU, if you want to use GPU, you need to create an environment according to the guide [Clustering_by_GPU](../Tutorials/Clustering_by_GPU.html).\n",
"\n",
- "Before anlysing, you also need to install a necessary package: **torch**\n",
"\n",
- " CPU: pip install torch==1.10.0\n",
+ "\n",
+ "\n",
+ "**Note**\n",
+ "\n",
+ "**Torch** is the necessary dependency for using GPU, we need to install it beforehand:\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",
- " GPU: pip install torch==1.10.0+cu113 --extra-index-url https://download.pytorch.org/whl/"
+ "
"
]
},
{
diff --git a/docs/source/Tutorials(Multi-sample)/SpaSEG.ipynb b/docs/source/Tutorials(Multi-sample)/SpaSEG.ipynb
index 1221a5c7..c84d0dd6 100644
--- a/docs/source/Tutorials(Multi-sample)/SpaSEG.ipynb
+++ b/docs/source/Tutorials(Multi-sample)/SpaSEG.ipynb
@@ -22,11 +22,13 @@
"\n",
"**Note**\n",
"\n",
- "Before anlysing, you also need to install a necessary package: **torch**\n",
+ "**Torch** is the necessary dependency, we need to install it beforehand:\n",
"\n",
- " CPU: pip install torch==1.10.0\n",
+ " CPU: pip install torch==2.4.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
"\n",
- " GPU: pip install torch==1.10.0+cu113 --extra-index-url https://download.pytorch.org/whl/\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",
""
]
diff --git a/docs/source/Tutorials/CellBin_Clustering.ipynb b/docs/source/Tutorials/CellBin_Clustering.ipynb
index eae7488c..d079442b 100644
--- a/docs/source/Tutorials/CellBin_Clustering.ipynb
+++ b/docs/source/Tutorials/CellBin_Clustering.ipynb
@@ -1880,7 +1880,9 @@
"id": "28c7e577",
"metadata": {},
"source": [
- "We can visulize the detail of cells base on clustering result. If set the parameter `base_image`, it will draw the ssDNA image as background and you can set transparency of foreground by the parameter `fg_alpha`."
+ "We can visulize the detail of cells base on clustering result. If set the parameter `base_image`, it will draw the ssDNA image as background and you can set transparency of foreground by the parameter `fg_alpha`.\n",
+ "\n",
+ "we can also export this plot as SVG or PDF, more detail in [API](../content/stereo.plots.PlotCollection.cells_plotting.rst)."
]
},
{
diff --git a/docs/source/Tutorials/Cell_Segmentation.ipynb b/docs/source/Tutorials/Cell_Segmentation.ipynb
index 5cd40095..7d935755 100644
--- a/docs/source/Tutorials/Cell_Segmentation.ipynb
+++ b/docs/source/Tutorials/Cell_Segmentation.ipynb
@@ -29,22 +29,28 @@
"\n",
"Install necessary packages by running commands as below:\n",
"\n",
- "**For CPU:**\n",
+ "**CPU:**\n",
"\n",
- "> **pip install tensorflow==2.7.0** \n",
- "> **pip install torch==1.10.0** \n",
- "> **pip install torchvision==0.11.1** \n",
- "> **pip install albumentations==0.4.6** \n",
- "> **pip protobuf~=3.20.0**\n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
+ " pip install torchvision==0.19.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
"\n",
- "**For GPU:**\n",
+ "**GPU(CUDA11):**\n",
"\n",
- "> **pip install tensorflow==2.7.0** \n",
- "> **pip install torch==1.10.0+cu113 --extra-index-url https://download.pytorch.org/whl/** \n",
- "> **pip install torchvision==0.11.1+cu113 --extra-index-url https://download.pytorch.org/whl/** \n",
- "> **pip install albumentations==0.4.6** \n",
- "> **pip install onnxruntime-gpu** \n",
- "> **pip protobuf~=3.20.0** \n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cu118 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install torchvision==0.19.1+cu118 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install onnxruntime-gpu\n",
+ "\n",
+ "**GPU(CUDA12):**\n",
+ "\n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install torchvision==0.19.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install onnxruntime-gpu\n",
"\n",
""
]
@@ -56,7 +62,7 @@
"source": [
"## About tissue segmentation\n",
"\n",
- "All processes of cell segmentation will perform tissue segmentation beforehand. You could the path to tissue segmentation model file by `tissue_seg_model_path`.\n",
+ "All processes of cell segmentation will perform tissue segmentation beforehand. You can set the model path of tissue segmentation by parameter `tissue_seg_model_path`.\n",
"\n",
"Download the [Tissue Segmentation Model](http://116.6.21.110:8090/share/3ca60300-e8bd-4d67-8b68-14267e428523).\n",
"\n",
@@ -133,426 +139,16 @@
},
{
"data": {
- "application/javascript": [
- "(function(root) {\n",
- " function now() {\n",
- " return new Date();\n",
- " }\n",
- "\n",
- " var force = true;\n",
- "\n",
- " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
- " root._bokeh_onload_callbacks = [];\n",
- " root._bokeh_is_loading = undefined;\n",
- " }\n",
- "\n",
- " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
- " root._bokeh_timeout = Date.now() + 5000;\n",
- " root._bokeh_failed_load = false;\n",
- " }\n",
- "\n",
- " function run_callbacks() {\n",
- " try {\n",
- " root._bokeh_onload_callbacks.forEach(function(callback) {\n",
- " if (callback != null)\n",
- " callback();\n",
- " });\n",
- " } finally {\n",
- " delete root._bokeh_onload_callbacks\n",
- " }\n",
- " console.debug(\"Bokeh: all callbacks have finished\");\n",
- " }\n",
- "\n",
- " function load_libs(css_urls, js_urls, js_modules, callback) {\n",
- " if (css_urls == null) css_urls = [];\n",
- " if (js_urls == null) js_urls = [];\n",
- " if (js_modules == null) js_modules = [];\n",
- "\n",
- " root._bokeh_onload_callbacks.push(callback);\n",
- " if (root._bokeh_is_loading > 0) {\n",
- " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
- " return null;\n",
- " }\n",
- " if (js_urls.length === 0 && js_modules.length === 0) {\n",
- " run_callbacks();\n",
- " return null;\n",
- " }\n",
- " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
- "\n",
- " function on_load() {\n",
- " root._bokeh_is_loading--;\n",
- " if (root._bokeh_is_loading === 0) {\n",
- " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
- " run_callbacks()\n",
- " }\n",
- " }\n",
- "\n",
- " function on_error() {\n",
- " console.error(\"failed to load \" + url);\n",
- " }\n",
- "\n",
- " for (var i = 0; i < css_urls.length; i++) {\n",
- " var url = css_urls[i];\n",
- " const element = document.createElement(\"link\");\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error;\n",
- " element.rel = \"stylesheet\";\n",
- " element.type = \"text/css\";\n",
- " element.href = url;\n",
- " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
- " document.body.appendChild(element);\n",
- " }\n",
- "\n",
- " var skip = [];\n",
- " if (window.requirejs) {\n",
- " window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n",
- " require([\"gridstack\"], function(GridStack) {\n",
- "\twindow.GridStack = GridStack\n",
- "\ton_load()\n",
- " })\n",
- " require([\"notyf\"], function() {\n",
- "\ton_load()\n",
- " })\n",
- " root._bokeh_is_loading = css_urls.length + 2;\n",
- " } else {\n",
- " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n",
- " } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
- " var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n",
- " for (var i = 0; i < urls.length; i++) {\n",
- " skip.push(urls[i])\n",
- " }\n",
- " } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
- " var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
- " for (var i = 0; i < urls.length; i++) {\n",
- " skip.push(urls[i])\n",
- " }\n",
- " } for (var i = 0; i < js_urls.length; i++) {\n",
- " var url = js_urls[i];\n",
- " if (skip.indexOf(url) >= 0) {\n",
- "\tif (!window.requirejs) {\n",
- "\t on_load();\n",
- "\t}\n",
- "\tcontinue;\n",
- " }\n",
- " var element = document.createElement('script');\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error;\n",
- " element.async = false;\n",
- " element.src = url;\n",
- " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
- " document.head.appendChild(element);\n",
- " }\n",
- " for (var i = 0; i < js_modules.length; i++) {\n",
- " var url = js_modules[i];\n",
- " if (skip.indexOf(url) >= 0) {\n",
- "\tif (!window.requirejs) {\n",
- "\t on_load();\n",
- "\t}\n",
- "\tcontinue;\n",
- " }\n",
- " var element = document.createElement('script');\n",
- " element.onload = on_load;\n",
- " element.onerror = on_error;\n",
- " element.async = false;\n",
- " element.src = url;\n",
- " element.type = \"module\";\n",
- " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
- " document.head.appendChild(element);\n",
- " }\n",
- " if (!js_urls.length && !js_modules.length) {\n",
- " on_load()\n",
- " }\n",
- " };\n",
- "\n",
- " function inject_raw_css(css) {\n",
- " const element = document.createElement(\"style\");\n",
- " element.appendChild(document.createTextNode(css));\n",
- " document.body.appendChild(element);\n",
- " }\n",
- "\n",
- " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n",
- " var js_modules = [];\n",
- " var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\"];\n",
- " var inline_js = [ function(Bokeh) {\n",
- " inject_raw_css(\"\\n .bk.pn-loading.arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n }\\n \");\n",
- " }, function(Bokeh) {\n",
- " Bokeh.set_log_level(\"info\");\n",
- " },\n",
- "function(Bokeh) {} // ensure no trailing comma for IE\n",
- " ];\n",
- "\n",
- " function run_inline_js() {\n",
- " if ((root.Bokeh !== undefined) || (force === true)) {\n",
- " for (var i = 0; i < inline_js.length; i++) {\n",
- " inline_js[i].call(root, root.Bokeh);\n",
- " }} else if (Date.now() < root._bokeh_timeout) {\n",
- " setTimeout(run_inline_js, 100);\n",
- " } else if (!root._bokeh_failed_load) {\n",
- " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
- " root._bokeh_failed_load = true;\n",
- " }\n",
- " }\n",
- "\n",
- " if (root._bokeh_is_loading === 0) {\n",
- " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
- " run_inline_js();\n",
- " } else {\n",
- " load_libs(css_urls, js_urls, js_modules, function() {\n",
- " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
- " run_inline_js();\n",
- " });\n",
- " }\n",
- "}(window));"
- ],
- "application/vnd.holoviews_load.v0+json": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 2;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n for (var i = 0; i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n var js_modules = [];\n var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\"];\n var inline_js = [ function(Bokeh) {\n inject_raw_css(\"\\n .bk.pn-loading.arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n }\\n \");\n }, function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, js_modules, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
+ "application/javascript": "(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, js_modules, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n if (js_modules == null) js_modules = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls.length === 0 && js_modules.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n var skip = [];\n if (window.requirejs) {\n window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'gridstack': {'exports': 'GridStack'}}});\n require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n })\n require([\"notyf\"], function() {\n\ton_load()\n })\n root._bokeh_is_loading = css_urls.length + 2;\n } else {\n root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n for (var i = 0; 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+ "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = 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+ "application/vnd.holoviews_load.v0+json": ""
},
"metadata": {},
"output_type": "display_data"
@@ -1625,12 +1221,11 @@
"\n",
"**Preparation**\n",
"\n",
- "Install necessary packages by running commands as below:\n",
+ "In addition to the **torch** mentioned at the beginning of this section, We also need to install the other three necessary packages:\n",
"\n",
- "> **pip install patchify** \n",
- "> **pip install torch** \n",
- "> **pip install fastremap** \n",
- "> **pip install roifile** \n",
+ " pip install patchify\n",
+ " pip install fastremap\n",
+ " pip install roifile\n",
"\n",
""
]
diff --git a/docs/source/Tutorials/SpaTrack.rst b/docs/source/Tutorials/SpaTrack.rst
index 8ce58c06..085692ab 100644
--- a/docs/source/Tutorials/SpaTrack.rst
+++ b/docs/source/Tutorials/SpaTrack.rst
@@ -12,7 +12,7 @@ taking into account both profile of gene expression and distance cost of cell tr
spaTrack has the potential to capture fine local details of trajectory within a single tissue section of spatial transcriptomics (ST) data,
as well as reconstruct cell dynamics across multiple tissue sections in a time series. To capture potential dynamic drivers,
spaTrack models the fate of a cell as a function of expression profile along the time points driven by transcription factors,
-which facilitates the identification of key molecular regulators that govern cellular trajectories.
+which facilitates the identification of key molecular regulators that govern cellular trajectories [`Shen `_].
Highlighted features
---------------------
diff --git a/docs/source/Tutorials/Tissue_Segmentation.ipynb b/docs/source/Tutorials/Tissue_Segmentation.ipynb
index 23362db5..7f207baf 100644
--- a/docs/source/Tutorials/Tissue_Segmentation.ipynb
+++ b/docs/source/Tutorials/Tissue_Segmentation.ipynb
@@ -40,22 +40,28 @@
"\n",
"Install necessary packages by running commands as below:\n",
"\n",
- "**For CPU:**\n",
+ "**CPU:**\n",
"\n",
- "> **pip install tensorflow==2.7.0** \n",
- "> **pip install torch==1.10.0** \n",
- "> **pip install torchvision==0.11.1** \n",
- "> **pip install albumentations==0.4.6** \n",
- "> **pip protobuf~=3.20.0**\n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
+ " pip install torchvision==0.19.1+cpu --extra-index-url https://download.pytorch.org/whl\n",
"\n",
- "**For GPU:**\n",
+ "**GPU(CUDA11):**\n",
"\n",
- "> **pip install tensorflow==2.7.0** \n",
- "> **pip install torch==1.10.0+cu113 --extra-index-url https://download.pytorch.org/whl/** \n",
- "> **pip install torchvision==0.11.1+cu113 --extra-index-url https://download.pytorch.org/whl/** \n",
- "> **pip install albumentations==0.4.6** \n",
- "> **pip install onnxruntime-gpu** \n",
- "> **pip protobuf~=3.20.0**\n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cu118 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install torchvision==0.19.1+cu118 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install onnxruntime-gpu\n",
+ "\n",
+ "**GPU(CUDA12):**\n",
+ "\n",
+ " pip install tensorflow==2.12.0\n",
+ " pip install albumentations==1.3.1\n",
+ " pip install torch==2.4.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install torchvision==0.19.1+cu124 --extra-index-url https://download.pytorch.org/whl/\n",
+ " pip install onnxruntime-gpu\n",
"\n",
""
]
@@ -68,7 +74,7 @@
"source": [
"## Tissue segmentation from .TIFF image\n",
"\n",
- "We now support 4 staining types of **.TIFF** image: **ssDNA**, **DAPI**, **HE** and **mIF** and have two models to process these four types images:\n",
+ "We now support 4 staining types of **.TIFF** image: **ssDNA**, **DAPI**, **HE** and **mIF**, and have two models to process these four types images:\n",
"\n",
" 1. tissueseg_bcdu_H&E_20240201_tf.onnx: be used for staining type HE.\n",
"\n",
diff --git a/docs/source/content/07_References.rst b/docs/source/content/07_References.rst
index 06223f82..ff42926c 100644
--- a/docs/source/content/07_References.rst
+++ b/docs/source/content/07_References.rst
@@ -81,3 +81,7 @@ References
.. [Bai23]
Yong Bai, Xiangyu Guo, Keyin Liu, Bingjie Zheng, Yingyue Wang, Qiuhong Luo, Jianhua Yin, Liang Wu, Yuxiang Li, Yong Zhang, Ao Chen, Xun Xu, Xin Jin,
*Efficient reliability analysis of spatially resolved transcriptomics at varying resolutions using SpaSEG*, bioRxiv.
+
+.. [Shen23]
+ Xunan Shen, Ke Huang, Lulu Zuo, Zhongfei Ye, Zeyu Li, Qichao Yu, Xuanxuan Zou, Xiaoyu Wei, Ping Xu, Xin Jin, Xun Xu, Liang Wu, Hongmei Zhu, Pengfei Qin,
+ *Inferring cell trajectories of spatial transcriptomics via optimal transport analysis*, bioRxiv.
diff --git a/stereo/core/st_pipeline.py b/stereo/core/st_pipeline.py
index e589b351..ff6b0fd0 100644
--- a/stereo/core/st_pipeline.py
+++ b/stereo/core/st_pipeline.py
@@ -794,6 +794,8 @@ def highly_variable_genes(
n_bins
number of bins for binning the mean gene expression. Normalization is done with respect to
each bin. If just a single gene falls into a bin, the normalized dispersion is artificially set to 1.
+ layer
+ the key of layer to be used instead of the data.exp_matrix.
res_key
the key for getting the result from `self.result`.
@@ -868,6 +870,7 @@ def pca(self,
:param hvg_res_key: the key of highly variable genes to get targeted result,`use_highly_genes=True` is a necessary prerequisite.
:param random_state: change to use different initial states for the optimization, fixed value to fixed result.
:param dtype: numpy data type string to which to convert the result.
+ :param layer: the key of layer to be used instead of the data.exp_matrix.
:param res_key: the key for storage of PCA result.
:return: Computation result of principal component analysis is stored in `self.result` where the result key is `'pca'`.
@@ -1253,7 +1256,7 @@ def find_marker_genes(self,
:param case_groups: case group, default all clusters.
:param control_groups: control group, default the rest of groups.
:param corr_method: p-value correction method, only available for `t_test` and `wilcoxon_test`.
- :param use_raw: whether to use raw express matrix for analysis, default True.
+ :param use_raw: whether to use raw express matrix for analysis, default True, it will be ignored if `layer` is not None.
:param use_highly_genes: whether to use only the expression of hypervariable genes as input, default True.
:param hvg_res_key: the key of highly variable genes to get corresponding result.
:param res_key: the key for storing result of marker genes.
@@ -1263,6 +1266,7 @@ def find_marker_genes(self,
larger or equal to 1, less or equal to 50.
:param ascending: default to False.
:param n_jobs: the number of parallel jobs to run. default to 4.
+ :param layer: the key of layer to be used instead of the data.exp_matrix, `use_raw` is ignored if it is not None.
:return: The result of marker genes is stored in `self.result` where the key is `'marker_genes'`.
"""
from ..tools.find_markers import FindMarker
diff --git a/stereo/io/reader.py b/stereo/io/reader.py
index 48b1da7e..73607654 100644
--- a/stereo/io/reader.py
+++ b/stereo/io/reader.py
@@ -70,11 +70,13 @@ def read_gem(
if set it to True, the coordinate of each bin will be the center of the bin,
otherwise, the coordinate of each bin will be the left-top corner of the bin.
gene_name_index
- In a v0.1 gem file, the column geneID is the gene name actually, but in a v0.2,
- geneID just a ID for genes and there is an additional column called geneName where is the gene name,
- When the version of gem file is v0.2, set `gene_name_index` to True to set column geneName as index, otherwise,
- set column geneID, if a v0.1 gem file, `gene_name_index` will be ignored and column geneID is set as index.
-
+ In a **v0.1** gem file, the column **geneID** actually is the **gene name**, but in **v0.2**,
+ **geneID** is just the **ID** for genes and there is an additional column called **geneName** which is the **gene name**,
+ When being **v0.2**, setting `gene_name_index` to True means setting column **geneName** as index,
+ otherwise, setting column **geneID** as index and the column **geneName** is stored in `data.real_gene_names`,
+ if **v0.1**, `gene_name_index` will be ignored and the column **geneID** will be set as index,
+ regardless of **v0.1** or **v0.2**, the column set as index is stored in `data.gene_names`,
+ the index mentioned here is the index of `data.genes`.
Returns
-------------
An object of StereoExpData.
@@ -1181,9 +1183,13 @@ def read_gef(
region
restrict data to the region condition, like [minX, maxX, minY, maxY].
gene_name_index
- `True` to set gene name as index if the version of gef file is 4 or greater,
- otherwise to set gene id, if the version is 3 or less, `gene_name_index` would
- be forced to `True` because there is no gene id in this case.
+ In a gef file whose version is 3 or lower, there is only a column called **geneName** which is the **gene name**,
+ but in the version higher than 3, additional column called **geneID** is added, which is the **ID** for genes,
+ When being higher version, setting `gene_name_index` to True means setting column **geneName** as index,
+ otherwise, setting column **geneID** as index and the column **geneName** is stored in `data.real_gene_names`,
+ if lower version, `gene_name_index` will be ignored and the column **geneID** will be set as index,
+ regardless of lower or higher version, the column set as index is stored in `data.gene_names`,
+ the index mentioned here is the index of `data.genes`.
num_threads
the number of threads to read the data, only available when `bin_type` is `'bins'`.
-1 means to use all the cores of the machine.
diff --git a/stereo/plots/plot_collection.py b/stereo/plots/plot_collection.py
index 9ff164c8..2bc6f00b 100644
--- a/stereo/plots/plot_collection.py
+++ b/stereo/plots/plot_collection.py
@@ -1402,7 +1402,7 @@ def cells_plotting(
:param horizontal_offset_additional: the additional offset between each slice on horizontal direction while reorganizing coordinates.
:param vertical_offset_additional: the additional offset between each slice on vertical direction while reorganizing coordinates.
- :return the figure object if `show` is set to False, otherwise, show the figure directly.
+ :return: the figure object if `show` is set to False, otherwise, show the figure directly.
.. note::