Add vectors dataset

src/napari_clusters_plotter/__init__.py

@@ -11,6 +11,7 @@
 from ._sample_data import (
     bbbc_1_dataset,
     cells3d_curvatures,
+    granule_compression_vectors,
     skan_skeleton,
     tgmm_mini_dataset,
 )
@@ -23,4 +24,5 @@
     "tgmm_mini_dataset",
     "cells3d_curvatures",
     "skan_skeleton",
+    "granule_compression_vectors",
 ]

src/napari_clusters_plotter/_sample_data.py

@@ -204,3 +204,37 @@ def cells3d_curvatures() -> List["LayerData"]:  # noqa: F821
     )
 
     return [layer_data_nuclei, layer_data_surface]
+
+
+def granule_compression_vectors() -> List["LayerData"]:  # noqa: F821
+    import numpy as np
+    import pandas as pd
+    from napari.utils import notifications
+
+    path = Path(__file__).parent / "sample_data" / "compression_vectors"
+
+    features = pd.read_csv(path / "granular_compression_test.csv")
+    features["iterations"] = features["iterations"].astype("category")
+    features["returnStatus"] = features["returnStatus"].astype("category")
+    features["Label"] = features["Label"].astype("category")
+    features.drop(columns=["PSCC"], inplace=True)
+
+    points_4d = features[["frame", "Zpos", "Ypos", "Xpos"]].to_numpy()
+    vectors_4d = features[["frame", "Zdisp", "Ydisp", "Xdisp"]].to_numpy()
+    vectors_4d = np.stack([points_4d, vectors_4d], axis=1)
+    vectors_4d[:, 1, 0] = 0
+
+    layerdata_vectors = (
+        vectors_4d,
+        {
+            "name": "granule_compression_vectors",
+            "features": features,
+        },
+        "vectors",
+    )
+
+    notifications.show_info(
+        "Granule compression vectors dataset obtained from https://zenodo.org/records/17668709"
+    )
+
+    return [layerdata_vectors]

src/napari_clusters_plotter/_tests/test_sample_data.py

@@ -3,7 +3,13 @@
 
 @pytest.mark.parametrize(
     "sample_data_function",
-    ["bbbc1", "cells3d_curvatures", "tgmm_mini", "skan_skeleton"],
+    [
+        "bbbc1",
+        "cells3d_curvatures",
+        "tgmm_mini",
+        "skan_skeleton",
+        "granule_compression_vectors",
+    ],
 )
 def test_bbbc_1_sample_data(make_napari_viewer, sample_data_function):
 

src/napari_clusters_plotter/napari.yaml

@@ -26,6 +26,9 @@ contributions:
   - id: napari-clusters-plotter.skan_skeleton
     python_name: napari_clusters_plotter:skan_skeleton
     title: Load skan skeleton dataset
+  - id: napari-clusters-plotter.granule_compression_vectors
+    python_name: napari_clusters_plotter:granule_compression_vectors
+    title: Load granule compression vectors
 
   menus:
     napari/layers/visualize:
@@ -61,3 +64,6 @@ contributions:
   - command: napari-clusters-plotter.skan_skeleton
     key: skan_skeleton
     display_name: Skan skeleton dataset (labels and paths)
+  - command: napari-clusters-plotter.granule_compression_vectors
+    key: granule_compression_vectors
+    display_name: Granule compression vectors dataset

src/napari_clusters_plotter/sample_data/compression_vectors/data_source.txt

@@ -0,0 +1,13 @@
+The data in this folder has been made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license on Zenodo: https://zenodo.org/records/17668709
+It can be cited under the DOI: https://doi.org/10.5281/zenodo.17668708
+
+Citation:
+@dataset{ando_2025_17668709,
+  author       = {Andò, Edward},
+  title        = {M2EA05 analysis results from spam},
+  month        = nov,
+  year         = 2025,
+  publisher    = {Zenodo},
+  doi          = {10.5281/zenodo.17668709},
+  url          = {https://doi.org/10.5281/zenodo.17668709},
+}