Repository: BiAPoL/napari-clusters-plotter (language: python)

Issue:
add biological sample data
This adds a bunch of example image data (4MB, source txt file included, license-free) and an example usage notebook to the repo for demo purposes.


Discussion / hints:

Fix patch:
diff --git a/MANIFEST.in b/MANIFEST.in
index 0439384..9b448ea 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -2,5 +2,7 @@ include LICENSE
 include README.md
 include requirements.txt
 
+recursive-include src/napari-clusters-plotter/sample_data *
+
 recursive-exclude * __pycache__
 recursive-exclude * *.py[co]
diff --git a/notebooks/data/BBBC007_v1_images/f9620/20P1_POS0002_D_1UL.tif b/notebooks/data/BBBC007_v1_images/f9620/20P1_POS0002_D_1UL.tif
deleted file mode 100644
index fa66462..0000000
Binary files a/notebooks/data/BBBC007_v1_images/f9620/20P1_POS0002_D_1UL.tif and /dev/null differ
diff --git a/notebooks/demo_biological_data.ipynb b/notebooks/demo_biological_data.ipynb
index 0e5e74a..5f8aa19 100644
--- a/notebooks/demo_biological_data.ipynb
+++ b/notebooks/demo_biological_data.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -10,25 +10,18 @@
     "import pandas as pd\n",
     "from pathlib import Path\n",
     "import numpy as np\n",
-    "from skimage import io, measure, data\n",
+    "from skimage import io, measure\n",
     "\n",
     "import napari\n",
-    "from napari_clusters_plotter import PlotterWidget\n",
+    "import napari_clusters_plotter as ncp\n",
     "import napari_segment_blobs_and_things_with_membranes as nsbatwm"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "napari.manifest -> 'napari-vedo-bridge' could not be imported: The name field in the manifest ('napari-clusters-plotter') must match the package name ('napari-vedo-bridge')\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -41,140 +34,49 @@
     "viewer = napari.Viewer()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "root = r'./data'\n",
-    "image_files = glob.glob(r'E:\\BiAPoL\\Projects\\napari-clusters-plotter\\notebooks\\data\\**\\**\\*.tif')"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "features = [\n",
-    "    'label',\n",
-    "    'area_filled',\n",
-    "    'perimeter',\n",
-    "    'axis_major_length',\n",
-    "    'axis_minor_length',\n",
-    "    'eccentricity',\n",
-    "    'area',\n",
-    "    'intensity_mean',\n",
-    "    'intensity_max',\n",
-    "    'intensity_min',\n",
-    "    'intensity_std',\n",
-    "]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# calculate positions of images on grid\n",
-    "n_cols = np.sqrt(len(image_files))\n",
-    "n_rows = np.ceil(len(image_files) / n_cols)\n",
-    "\n",
-    "spacing = 500\n",
-    "image_layers = []\n",
-    "labels_layers = []\n",
-    "\n",
-    "for i, image_file in enumerate(image_files):\n",
-    "    row = i // n_cols\n",
-    "    col = i % n_cols\n",
-    "    image = io.imread(image_file)\n",
-    "\n",
-    "    if len(image.shape) > 2:\n",
-    "        image = image[:, :, 0]\n",
-    "\n",
-    "    # segmentation\n",
-    "    labels = np.asarray(nsbatwm.voronoi_otsu_labeling(image, spot_sigma=5))\n",
-    "\n",
-    "    # measurements\n",
-    "    features = pd.DataFrame(measure.regionprops_table(labels, intensity_image=image, properties=features))\n",
-    "\n",
-    "    image_layer = napari.layers.Image(data=image, name=Path(image_file).stem, translate=[spacing * col, spacing * row])\n",
-    "    labels_layer = napari.layers.Labels(data=labels, name=Path(image_file).stem + '_labels',\n",
-    "                                        translate=[spacing * col, spacing * row], features=features)\n",
-    "    \n",
-    "    image_layers.append(image_layer)\n",
-    "    labels_layers.append(labels_layer)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "viewer.layers.clear()\n",
-    "for layer in image_layers:\n",
-    "    viewer.add_layer(layer)\n",
-    "\n",
-    "for layer in labels_layers:\n",
+    "sample_dataset = ncp.bbbc_1_dataset()\n",
+    "for sample in sample_dataset:\n",
+    "    layer = napari.layers.Layer.create(sample[0], sample[1], sample[2])\n",
     "    viewer.add_layer(layer)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\Users\\johan\\mambaforge\\envs\\clusters-plotter\\lib\\site-packages\\napari_matplotlib\\base.py:46: FutureWarning: The `as_dict` kwarg has been deprecated since Napari 0.5.0 and will be removed in future version. You can use `get_theme(...).to_rgb_dict()`\n",
+      "c:\\Users\\johamuel\\AppData\\Local\\mambaforge\\envs\\clusters-plotter-dev\\lib\\site-packages\\napari_matplotlib\\base.py:46: FutureWarning: The `as_dict` kwarg has been deprecated since Napari 0.5.0 and will be removed in future version. You can use `get_theme(...).to_rgb_dict()`\n",
       "  get_theme(napari_viewer.theme, as_dict=False)\n",
-      "c:\\Users\\johan\\mambaforge\\envs\\clusters-plotter\\lib\\site-packages\\napari_matplotlib\\base.py:101: FutureWarning: The `as_dict` kwarg has been deprecated since Napari 0.5.0 and will be removed in future version. You can use `get_theme(...).to_rgb_dict()`\n",
+      "c:\\Users\\johamuel\\AppData\\Local\\mambaforge\\envs\\clusters-plotter-dev\\lib\\site-packages\\napari_matplotlib\\base.py:101: FutureWarning: The `as_dict` kwarg has been deprecated since Napari 0.5.0 and will be removed in future version. You can use `get_theme(...).to_rgb_dict()`\n",
       "  theme = napari.utils.theme.get_theme(self.viewer.theme, as_dict=False)\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<napari._qt.widgets.qt_viewer_dock_widget.QtViewerDockWidget at 0x1ec9acb4790>"
+       "<napari._qt.widgets.qt_viewer_dock_widget.QtViewerDockWidget at 0x12f8df50550>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "plotter_widget = PlotterWidget(viewer)\n",
+    "plotter_widget = ncp.PlotterWidget(viewer)\n",
     "viewer.window.add_dock_widget(plotter_widget, area='right')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from skimage import data, measure\n",
-    "import napari_segment_blobs_and_things_with_membranes as nsbatwm\n",
-    "import pandas as pd\n",
-    "\n",
-    "image = data.human_mitosis()\n",
-    "labels = nsbatwm.voronoi_otsu_labeling(image, spot_sigma=5)\n",
-    "measurements = pd.DataFrame(measure.regionprops_table(labels, intensity_image=image, properties=['label', 'area']))"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/src/napari_clusters_plotter/__init__.py b/src/napari_clusters_plotter/__init__.py
index f7d972c..1f42acd 100644
--- a/src/napari_clusters_plotter/__init__.py
+++ b/src/napari_clusters_plotter/__init__.py
@@ -5,9 +5,11 @@
     DimensionalityReductionWidget,
 )
 from ._new_plotter_widget import PlotterWidget
+from ._sample_data import bbbc_1_dataset
 
 __all__ = [
     "PlotterWidget",
     "DimensionalityReductionWidget",
     "ClusteringWidget",
+    "bbbc_1_dataset",
 ]
diff --git a/src/napari_clusters_plotter/_sample_data.py b/src/napari_clusters_plotter/_sample_data.py
new file mode 100644
index 0000000..32da011
--- /dev/null
+++ b/src/napari_clusters_plotter/_sample_data.py
@@ -0,0 +1,60 @@
+import glob
+import os
+from pathlib import Path
+from typing import List
+
+
+def bbbc_1_dataset() -> List["LayerData"]:  # noqa: F821
+    import numpy as np
+    import pandas as pd
+    from skimage import io
+
+    # get path of this file
+    path = Path(__file__).parent / "sample_data" / "BBBC007_v1_images"
+
+    tif_files = glob.glob(
+        os.path.join(str(path), "**", "*.tif"), recursive=True
+    )
+    raw_images = [f for f in tif_files if "labels" not in f]
+
+    spacing = 500
+    # calculate positions of images on grid
+    n_cols = np.sqrt(len(raw_images))
+    image_layers = []
+    labels_layers = []
+
+    for i, raw_image_filename in enumerate(raw_images):
+
+        label_filename = raw_image_filename.replace(".tif", "_labels.tif")
+        feature_filename = raw_image_filename.replace(".tif", "_features.csv")
+        image = io.imread(raw_image_filename)
+        labels = io.imread(label_filename)
+
+        row = i // n_cols
+        col = i % n_cols
+
+        features = pd.read_csv(feature_filename)
+
+        ldtuple_image = (
+            image,
+            {
+                "name": Path(raw_image_filename).stem,
+                "translate": [spacing * col, spacing * row],
+            },
+            "image",
+        )
+
+        ldtuple_labels = (
+            labels,
+            {
+                "name": Path(raw_image_filename).stem + "_labels",
+                "translate": [spacing * col, spacing * row],
+                "features": features,
+            },
+            "labels",
+        )
+
+        image_layers.append(ldtuple_image)
+        labels_layers.append(ldtuple_labels)
+
+    return image_layers + labels_layers
diff --git a/src/napari_clusters_plotter/napari.yaml b/src/napari_clusters_plotter/napari.yaml
index 56fab32..fc36743 100644
--- a/src/napari_clusters_plotter/napari.yaml
+++ b/src/napari_clusters_plotter/napari.yaml
@@ -14,6 +14,10 @@ contributions:
     python_name: napari_clusters_plotter:ClusteringWidget
     title: Clustering
 
+  - id: napari-clusters-plotter.bbbc_sample_data
+    python_name: napari_clusters_plotter:bbbc_1_dataset
+    title: Load bbbc sample data
+
   menus:
     napari/layers/visualize:
       - submenu: features_submenu
@@ -35,3 +39,8 @@ contributions:
   submenus:
     - id : features_submenu
       label: Features
+
+  sample_data:
+  - command: napari-clusters-plotter.bbbc_sample_data
+    key: bbbc1
+    display_name: BBBC 1 dataset & segmentations
diff --git a/notebooks/data/BBBC007_v1_images/A9/A9 p10d.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d.tif
similarity index 100%
rename from notebooks/data/BBBC007_v1_images/A9/A9 p10d.tif
rename to src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d.tif
diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d_features.csv b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d_features.csv
new file mode 100644
index 0000000..d3f1ca8
--- /dev/null
+++ b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d_features.csv
@@ -0,0 +1,108 @@
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d_labels_labels.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p10d_labels_labels.tif
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diff --git a/notebooks/data/BBBC007_v1_images/A9/A9 p5d.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p5d.tif
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p5d_features.csv b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p5d_features.csv
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p5d_labels_labels.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p5d_labels_labels.tif
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diff --git a/notebooks/data/BBBC007_v1_images/A9/A9 p7d.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p7d.tif
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p7d_features.csv b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p7d_features.csv
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diff --git a/notebooks/data/BBBC007_v1_images/A9/A9 p9d.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p9d.tif
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p9d_features.csv b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/A9/A9 p9d_features.csv
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diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/f9620/20P1_POS0011_D_1UL_labels.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/f9620/20P1_POS0011_D_1UL_labels.tif
new file mode 100644
index 0000000..6a72499
Binary files /dev/null and b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/f9620/20P1_POS0011_D_1UL_labels.tif differ
diff --git a/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/f9620/20P1_POS0011_D_1UL_labels_labels.tif b/src/napari_clusters_plotter/sample_data/BBBC007_v1_images/f9620/20P1_POS0011_D_1UL_labels_labels.tif
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Test patch:
diff --git a/src/napari_clusters_plotter/_tests/test_sample_data.py b/src/napari_clusters_plotter/_tests/test_sample_data.py
new file mode 100644
index 0000000..f7c7e1e
--- /dev/null
+++ b/src/napari_clusters_plotter/_tests/test_sample_data.py
@@ -0,0 +1,13 @@
+def test_sample_data(make_napari_viewer):
+    from napari.layers import Layer
+
+    import napari_clusters_plotter as ncp
+
+    viewer = make_napari_viewer()
+
+    sample_dataset = ncp.bbbc_1_dataset()
+    for sample in sample_dataset:
+        layer = Layer.create(sample[0], sample[1], sample[2])
+        viewer.add_layer(layer)
+
+    assert len(viewer.layers) == len(sample_dataset)