Merge pull request #84 from haesleinhuepf/sliceplot

Added interactive sliceplot

.gitignore

@@ -143,3 +143,5 @@ cython_debug/
 .DS_STORE
 deploy.bat
 *Untitled*
+
+docs/png_umap*

README.md

@@ -295,6 +295,16 @@ This functionality is inspired from the [napari-clusters-plotter](https://github
 
 ![clusterplot.gif](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/clusterplot.gif)
 
+### Sliceplot
+
+Another similar interactive plot is the `sliceplot`: In case you have a pandas DataFrame with a columns representing measurements of slices in an image stack, you can use this function to visualize the slices in a plot. 
+
+```python
+stackview.sliceplot(df, images, column_x="UMAP0", column_y="UMAP1")
+```
+
+![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/sliceplot.gif)
+
 ### Interact
 
 Exploration of the parameter space of image processing functions is available using `interact`:

docs/sliceplot.ipynb

@@ -0,0 +1,303 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9974e82c-795b-4f44-9ed0-1d539b1a71de",
+   "metadata": {},
+   "source": [
+    "# Exploring slices of stacks by plotting corresponding data\n",
+    "In this notebook we will explore a stack of images using an interactive scatterplot of measurements that were done on the individual slices of the stack. For demonstration purposes, we explore a stack of teaching slides an embedding generated using large language models."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "24a3041b-56b1-4f44-ad18-9b06c5eb62b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import stackview\n",
+    "import os\n",
+    "import numpy as np\n",
+    "from skimage.io import imread\n",
+    "import yaml\n",
+    "import requests\n",
+    "import zipfile\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e0e5c014-8e9d-47cf-a23e-668d80c9a7d7",
+   "metadata": {},
+   "source": [
+    "First, we download [the dataset](https://zenodo.org/records/14030307), which is licensed [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/) by Robert Haase."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "3ae7e89b-79cb-43a0-948d-49a7b5bfb32a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# URL of the zip file\n",
+    "url = \"https://zenodo.org/records/14030307/files/png_umap.zip?download=1\"\n",
+    "# Save the zip file locally\n",
+    "zip_path = \"png_umap.zip\"\n",
+    "\n",
+    "if not os.path.exists(zip_path):\n",
+    "    # Download the zip file\n",
+    "    response = requests.get(url)\n",
+    "    with open(zip_path, \"wb\") as f:\n",
+    "        f.write(response.content)\n",
+    "    \n",
+    "    # Extract the contents\n",
+    "    with zipfile.ZipFile(zip_path, 'r') as zip_ref:\n",
+    "        zip_ref.extractall()\n",
+    "\n",
+    "# Optionally, remove the zip file after extraction\n",
+    "#os.remove(zip_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "dd5f83a7-f774-4d3e-871a-429775be7c55",
+   "metadata": {},
+   "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>UMAP0</th>\n",
+       "      <th>UMAP1</th>\n",
+       "      <th>filename</th>\n",
+       "      <th>page_index</th>\n",
+       "      <th>png_filename</th>\n",
+       "      <th>text</th>\n",
+       "      <th>url</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2.785299</td>\n",
+       "      <td>5.125338</td>\n",
+       "      <td>12623730_14_Summary.pdf</td>\n",
+       "      <td>0</td>\n",
+       "      <td>12623730_14_Summary_0.png</td>\n",
+       "      <td>Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...</td>\n",
+       "      <td>https://zenodo.org/api/records/12623730/files/...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.759109</td>\n",
+       "      <td>5.196022</td>\n",
+       "      <td>12623730_14_Summary.pdf</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12623730_14_Summary_1.png</td>\n",
+       "      <td>Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...</td>\n",
+       "      <td>https://zenodo.org/api/records/12623730/files/...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.605859</td>\n",
+       "      <td>6.084491</td>\n",
+       "      <td>12623730_14_Summary.pdf</td>\n",
+       "      <td>2</td>\n",
+       "      <td>12623730_14_Summary_2.png</td>\n",
+       "      <td>Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...</td>\n",
+       "      <td>https://zenodo.org/api/records/12623730/files/...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.581907</td>\n",
+       "      <td>6.084695</td>\n",
+       "      <td>12623730_14_Summary.pdf</td>\n",
+       "      <td>3</td>\n",
+       "      <td>12623730_14_Summary_3.png</td>\n",
+       "      <td>Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...</td>\n",
+       "      <td>https://zenodo.org/api/records/12623730/files/...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2.163119</td>\n",
+       "      <td>7.161102</td>\n",
+       "      <td>12623730_14_Summary.pdf</td>\n",
+       "      <td>4</td>\n",
+       "      <td>12623730_14_Summary_4.png</td>\n",
+       "      <td>Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...</td>\n",
+       "      <td>https://zenodo.org/api/records/12623730/files/...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      UMAP0     UMAP1                 filename  page_index  \\\n",
+       "0  2.785299  5.125338  12623730_14_Summary.pdf           0   \n",
+       "1  1.759109  5.196022  12623730_14_Summary.pdf           1   \n",
+       "2  1.605859  6.084491  12623730_14_Summary.pdf           2   \n",
+       "3  1.581907  6.084695  12623730_14_Summary.pdf           3   \n",
+       "4  2.163119  7.161102  12623730_14_Summary.pdf           4   \n",
+       "\n",
+       "                png_filename  \\\n",
+       "0  12623730_14_Summary_0.png   \n",
+       "1  12623730_14_Summary_1.png   \n",
+       "2  12623730_14_Summary_2.png   \n",
+       "3  12623730_14_Summary_3.png   \n",
+       "4  12623730_14_Summary_4.png   \n",
+       "\n",
+       "                                                text  \\\n",
+       "0  Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...   \n",
+       "1  Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...   \n",
+       "2  Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...   \n",
+       "3  Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...   \n",
+       "4  Robert Haase\\n@haesleinhuepf\\nBIDS Lecture 14/...   \n",
+       "\n",
+       "                                                 url  \n",
+       "0  https://zenodo.org/api/records/12623730/files/...  \n",
+       "1  https://zenodo.org/api/records/12623730/files/...  \n",
+       "2  https://zenodo.org/api/records/12623730/files/...  \n",
+       "3  https://zenodo.org/api/records/12623730/files/...  \n",
+       "4  https://zenodo.org/api/records/12623730/files/...  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Read YAML file\n",
+    "with open('png_umap/png_umap.yml', 'r') as file:\n",
+    "    loaded_dict = yaml.safe_load(file)\n",
+    "\n",
+    "\n",
+    "df = pd.DataFrame(loaded_dict)\n",
+    "\n",
+    "# Show first few rows of the loaded DataFrame\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0822cc8e-46c9-47ce-9d4b-181913dd1eb3",
+   "metadata": {},
+   "source": [
+    "We also define a helper function that loads all images mentioned in a dataframe into one big numpy array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5cf520c5-4a1b-4708-b39e-de9922cb5680",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_images(selected_rows):\n",
+    "    # Load images for selected pages\n",
+    "    images = []\n",
+    "    for _, row in selected_rows.iterrows():\n",
+    "        img_path = os.path.join('png_umap', row['png_filename'])\n",
+    "        img = imread(img_path)\n",
+    "        images.append(img)\n",
+    "\n",
+    "    if len(images) == 0:\n",
+    "        return np.zeros((2,2,2))\n",
+    "    else:\n",
+    "        return np.asarray(images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4829158d-d705-4070-ba65-a9dd64f3ebbc",
+   "metadata": {},
+   "source": [
+    "We can use the `sliceplot` function of stackview to visualize the embedding next to selected slides."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "feac021f-d0a5-4f92-b8dd-4b23c90be0bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bc68c6c84230415bb4ea64701670d2f1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(HBox(children=(VBox(children=(VBox(children=(HBox(children=(VBox(children=(ImageWidget(height=4…"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stackview.sliceplot(df, get_images(df), column_x=\"UMAP0\", column_y=\"UMAP1\", zoom_factor=1.5, zoom_spline_order=2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b871cc66-6088-42ab-9708-42858100ab52",
+   "metadata": {},
+   "source": [
+    "## Exercise\n",
+    "Explore the plot by dragging lines around islands of datapoints with the mouse. What content are these islands about?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1cc76f41-1668-45a4-82aa-61d4cb3dd783",
+   "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": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="stackview",
-    version="0.11.2",
+    version="0.12.0",
     author="Robert Haase",
     author_email="[email protected]",
     description="Interactive image stack viewing in jupyter notebooks",

stackview/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.11.2"
+__version__ = "0.12.0"
 
 from ._static_view import jupyter_displayable_output, insight
 from ._utilities import merge_rgb
@@ -21,6 +21,6 @@
 from ._scatterplot import scatterplot
 from ._grid import grid
 from ._clusterplot import clusterplot
-
+from ._sliceplot import sliceplot
 
 

stackview/_slice_viewer.py

@@ -33,8 +33,9 @@ def __init__(self,
 
         self.sliders = []
         offset = 2
-        if 3 >= image.shape[-1] >= 4: # RGB or RGBA images
+        if image.shape[-1] == 3 or image.shape[-1] == 4: # RGB or RGBA images
             offset = 3
+
         for d in range(len(image.shape) - offset):
             slider = intSlider(
                 value=slice_number[d],
@@ -60,6 +61,11 @@ def __init__(self,
         self.slice_slider = ipywidgets.VBox(self.sliders[::-1])
         self.update()
 
+    def set_image(self, image):
+        for i, s in enumerate(self.sliders):
+            s._set_value_min_max(int(image.shape[i] / 2), 0, image.shape[i] - 1)
+        self.image = image
+
     def observe(self, x):
         self.update_active = False
         for s in self.sliders: