add check_plane_segmentation_image_mask_shape_against_ref_images

nwbinspector/checks/ophys.py

@@ -55,3 +55,15 @@ def check_excitation_lambda_in_nm(imaging_plane: ImagingPlane):
     """Check that emission lambda is in feasible range for unit nanometers."""
     if imaging_plane.excitation_lambda < MIN_LAMBDA:
         return InspectorMessage(f"excitation lambda of {imaging_plane.excitation_lambda} should be in units of nm.")
+
+
+@register_check(importance=Importance.BEST_PRACTICE_VIOLATION, neurodata_type=PlaneSegmentation)
+def check_plane_segmentation_image_mask_shape_against_ref_images(plane_segmentation: PlaneSegmentation):
+    if plane_segmentation.reference_images and "image_mask" in plane_segmentation.colnames:
+        mask_shape = plane_segmentation["image_mask"].shape[1:]
+        for ref_image in plane_segmentation.reference_images:
+            if mask_shape != ref_image.data.shape[1:]:
+                yield InspectorMessage(
+                    f"image_mask of shape {mask_shape} does not match reference image {ref_image.name} with shape"
+                    f" {ref_image.data.shape[1:]}."
+                )

tests/unit_tests/test_ophys.py

@@ -5,7 +5,14 @@
 import numpy as np
 from pynwb import NWBFile
 from pynwb.device import Device
-from pynwb.ophys import OpticalChannel, ImageSegmentation, RoiResponseSeries, ImagingPlane
+from pynwb.ophys import (
+    OpticalChannel,
+    ImageSegmentation,
+    RoiResponseSeries,
+    ImagingPlane,
+    PlaneSegmentation,
+    TwoPhotonSeries,
+)
 from hdmf.common.table import DynamicTableRegion, DynamicTable
 
 from nwbinspector import (
@@ -15,6 +22,7 @@
     check_roi_response_series_link_to_plane_segmentation,
     check_excitation_lambda_in_nm,
     check_emission_lambda_in_nm,
+    check_plane_segmentation_image_mask_shape_against_ref_images,
 )
 
 
@@ -230,3 +238,92 @@ def test_check_emission_lambda_in_nm():
 def test_pass_check_emission_lambda_in_nm():
     optical_channel = OpticalChannel(name="OpticalChannel", description="an optical channel", emission_lambda=500.0)
     assert check_emission_lambda_in_nm(optical_channel) is None
+
+
+def test_pass_check_plane_segmentation_image_mask_dims_against_imageseries():
+
+    device = Device(
+        name="Microscope", description="My two-photon microscope", manufacturer="The best microscope manufacturer"
+    )
+    optical_channel = OpticalChannel(name="OpticalChannel", description="an optical channel", emission_lambda=500.0)
+    imaging_plane = ImagingPlane(
+        name="ImagingPlane",
+        optical_channel=optical_channel,
+        imaging_rate=30.0,
+        description="a very interesting part of the brain",
+        device=device,
+        excitation_lambda=300.0,
+        indicator="GFP",
+        location="V1",
+        grid_spacing=[0.01, 0.01],
+        grid_spacing_unit="meters",
+        origin_coords=[1.0, 2.0, 3.0],
+        origin_coords_unit="meters",
+    )
+
+    two_photon_series = TwoPhotonSeries(
+        name="TwoPhotonSeries",
+        imaging_plane=imaging_plane,
+        data=np.ones((20, 10, 10)),
+        unit="n.a.",
+        rate=30.0,
+    )
+
+    plane_segmentation = PlaneSegmentation(
+        description="my plane segmentation",
+        imaging_plane=imaging_plane,
+        reference_images=two_photon_series,
+    )
+
+    plane_segmentation.add_roi(image_mask=np.ones((10, 10)))
+
+    assert check_plane_segmentation_image_mask_shape_against_ref_images(plane_segmentation) is None
+
+
+def test_fail_check_plane_segmentation_image_mask_dims_against_imageseries():
+
+    device = Device(
+        name="Microscope", description="My two-photon microscope", manufacturer="The best microscope manufacturer"
+    )
+    optical_channel = OpticalChannel(name="OpticalChannel", description="an optical channel", emission_lambda=500.0)
+    imaging_plane = ImagingPlane(
+        name="ImagingPlane",
+        optical_channel=optical_channel,
+        imaging_rate=30.0,
+        description="a very interesting part of the brain",
+        device=device,
+        excitation_lambda=300.0,
+        indicator="GFP",
+        location="V1",
+        grid_spacing=[0.01, 0.01],
+        grid_spacing_unit="meters",
+        origin_coords=[1.0, 2.0, 3.0],
+        origin_coords_unit="meters",
+    )
+
+    two_photon_series = TwoPhotonSeries(
+        name="TwoPhotonSeries",
+        imaging_plane=imaging_plane,
+        data=np.ones((20, 10, 10)),
+        unit="n.a.",
+        rate=30.0,
+    )
+
+    plane_segmentation = PlaneSegmentation(
+        description="my plane segmentation",
+        imaging_plane=imaging_plane,
+        reference_images=two_photon_series,
+    )
+
+    plane_segmentation.add_roi(image_mask=np.ones((9, 10)))
+
+    assert check_plane_segmentation_image_mask_shape_against_ref_images(plane_segmentation) == [
+        InspectorMessage(
+            message="image_mask of shape (9, 10) does not match reference image TwoPhotonSeries with shape (10, 10).",
+            importance=Importance.BEST_PRACTICE_VIOLATION,
+            check_function_name="check_plane_segmentation_image_mask_shape_against_ref_images",
+            object_type="PlaneSegmentation",
+            object_name="ImagingPlane",
+            location="/",
+        )
+    ]