Extend napari dimension slider tests to bboxes data

Author: Tushar7012

tests/fixtures/napari.py

@@ -4,7 +4,7 @@
 import pandas as pd
 import pytest
 
-from movement.io import save_poses
+from movement.io import save_bboxes, save_poses
 
 
 @pytest.fixture
@@ -129,6 +129,111 @@ def valid_poses_path_and_ds_nan_end(
     return (out_path, ds)
 
 
+@pytest.fixture
+def valid_bboxes_path_and_ds(valid_bboxes_dataset, tmp_path):
+    """Return a (path, dataset) pair representing a bboxes dataset
+    with data for 10 frames.
+
+    The fixture is derived from the ``valid_bboxes_dataset`` fixture.
+    """
+    out_path = tmp_path / "ds_bboxes.csv"
+    save_bboxes.to_via_tracks_file(valid_bboxes_dataset, out_path)
+    return (out_path, valid_bboxes_dataset)
+
+
+@pytest.fixture
+def valid_bboxes_path_and_ds_short(valid_bboxes_dataset, tmp_path):
+    """Return a (path, dataset) pair representing a bboxes dataset
+    with data for 5 frames.
+
+    The fixture is derived from the ``valid_bboxes_dataset`` fixture.
+    """
+    valid_bboxes_dataset = valid_bboxes_dataset.sel(time=slice(0, 5))
+    out_path = tmp_path / "ds_bboxes_short.csv"
+    save_bboxes.to_via_tracks_file(valid_bboxes_dataset, out_path)
+    return (out_path, valid_bboxes_dataset)
+
+
+@pytest.fixture
+def valid_bboxes_path_and_ds_with_localised_nans(
+    valid_bboxes_dataset, tmp_path
+):
+    """Return a factory of (path, dataset) pairs representing
+    valid bboxes datasets with NaN values at specific locations.
+    """
+    ds = valid_bboxes_dataset.copy(deep=True)
+
+    def _valid_bboxes_path_and_ds_with_localised_nans(
+        nan_location, filename="ds_bboxes_with_nans.csv"
+    ):
+        """Return a valid bboxes dataset and corresponding file with NaN
+        values at specific locations.
+
+        The ``nan_location`` parameter is a dictionary with keys
+        ``"time"`` and ``"individuals"`` specifying which coordinates
+        to set to NaN.
+        """
+        if nan_location["time"] == "start":
+            time_point = 0
+        elif nan_location["time"] == "middle":
+            time_point = ds.coords["time"][
+                ds.coords["time"].shape[0] // 2
+            ]
+        elif nan_location["time"] == "end":
+            time_point = ds.coords["time"][-1]
+
+        ds.position.loc[
+            {
+                "individuals": nan_location["individuals"],
+                "time": time_point,
+            }
+        ] = np.nan
+
+        out_path = tmp_path / filename
+        save_bboxes.to_via_tracks_file(ds, out_path)
+        return (out_path, ds)
+
+    return _valid_bboxes_path_and_ds_with_localised_nans
+
+
+@pytest.fixture
+def valid_bboxes_path_and_ds_nan_start(
+    valid_bboxes_path_and_ds_with_localised_nans,
+):
+    """Return a (path, dataset) pair for a bboxes dataset with NaN
+    values for one individual at the first frame.
+
+    Only one individual is set to NaN because VIA-tracks CSV format
+    drops frames where all individuals have NaN positions.
+    """
+    return valid_bboxes_path_and_ds_with_localised_nans(
+        {
+            "time": "start",
+            "individuals": ["id_0"],
+        },
+        filename="ds_bboxes_with_nan_start.csv",
+    )
+
+
+@pytest.fixture
+def valid_bboxes_path_and_ds_nan_end(
+    valid_bboxes_path_and_ds_with_localised_nans,
+):
+    """Return a (path, dataset) pair for a bboxes dataset with NaN
+    values for one individual at the last frame.
+
+    Only one individual is set to NaN because VIA-tracks CSV format
+    drops frames where all individuals have NaN positions.
+    """
+    return valid_bboxes_path_and_ds_with_localised_nans(
+        {
+            "time": "end",
+            "individuals": ["id_0"],
+        },
+        filename="ds_bboxes_with_nan_end.csv",
+    )
+
+
 @pytest.fixture
 def sample_layer_data(rng):
     """Return a dictionary of sample data for each napari layer type."""

tests/test_unit/test_napari_plugin/test_data_loader_widget.py

@@ -567,6 +567,65 @@ def test_dimension_slider_with_nans(
     )
 
 
+@pytest.mark.parametrize(
+    "nan_time_location",
+    ["start", "middle", "end"],
+)
+def test_dimension_slider_with_nans_bboxes(
+    valid_bboxes_path_and_ds_with_localised_nans,
+    nan_time_location,
+    make_napari_viewer_proxy,
+):
+    """Test that the dimension slider is set to the total number of frames
+    when bboxes data layers with NaNs are loaded.
+
+    Only one individual is set to NaN at a given time, because the
+    VIA-tracks CSV format drops frames where all individuals have NaN
+    positions, making the round-trip lossy for all-NaN frames.
+    """
+    nan_location = {
+        "time": nan_time_location,
+        "individuals": ["id_0"],
+    }
+    file_path, ds = valid_bboxes_path_and_ds_with_localised_nans(
+        nan_location
+    )
+
+    # Define the expected frame index with the NaN value
+    if nan_location["time"] == "start":
+        expected_frame = ds.coords["time"][0]
+    elif nan_location["time"] == "middle":
+        expected_frame = ds.coords["time"][ds.coords["time"].shape[0] // 2]
+    elif nan_location["time"] == "end":
+        expected_frame = ds.coords["time"][-1]
+
+    # Load the data loader widget
+    viewer = make_napari_viewer_proxy()
+    data_loader_widget = DataLoader(viewer)
+
+    # Read sample data with a NaN at the specified location
+    data_loader_widget.file_path_edit.setText(file_path.as_posix())
+    data_loader_widget.source_software_combo.setCurrentText("VIA-tracks")
+
+    # Check the data contains nans where expected
+    assert (
+        ds.position.sel(
+            individuals=nan_location["individuals"],
+            time=expected_frame,
+        )
+        .isnull()
+        .all()
+    )
+
+    # Call the _on_load_clicked method
+    data_loader_widget._on_load_clicked()
+
+    # Check the frame slider is set to the full range of frames
+    assert viewer.dims.range[0] == RangeTuple(
+        start=0.0, stop=ds.position.shape[0] - 1, step=1.0
+    )
+
+
 @pytest.mark.parametrize(
     "list_input_data_files",
     [
@@ -614,6 +673,53 @@ def test_dimension_slider_multiple_files(
     assert max_frames == ds_long.sizes["time"]
 
 
+@pytest.mark.parametrize(
+    "list_input_data_files",
+    [
+        ["valid_bboxes_path_and_ds", "valid_bboxes_path_and_ds_short"],
+        ["valid_bboxes_path_and_ds_short", "valid_bboxes_path_and_ds"],
+    ],
+    ids=["long_first", "short_first"],
+)
+def test_dimension_slider_multiple_files_bboxes(
+    list_input_data_files, make_napari_viewer_proxy, request
+):
+    """Test that the dimension slider is set to the maximum number of frames
+    when multiple bboxes data layers are loaded.
+    """
+    # Get the datasets to load (paths and ds)
+    list_paths, list_datasets = [
+        [
+            request.getfixturevalue(file_name)[j]
+            for file_name in list_input_data_files
+        ]
+        for j in range(len(list_input_data_files))
+    ]
+
+    # Get the maximum number of frames from all datasets
+    max_frames = max(ds.sizes["time"] for ds in list_datasets)
+
+    # Load the data loader widget
+    viewer = make_napari_viewer_proxy()
+    data_loader_widget = DataLoader(viewer)
+
+    # Load each dataset in order
+    for file_path in list_paths:
+        data_loader_widget.file_path_edit.setText(file_path.as_posix())
+        data_loader_widget.source_software_combo.setCurrentText("VIA-tracks")
+        data_loader_widget._on_load_clicked()
+
+    # Check the frame slider is as expected
+    assert viewer.dims.range[0] == RangeTuple(
+        start=0.0, stop=max_frames - 1, step=1.0
+    )
+
+    # Check the maximum number of frames is the number of frames
+    # in the longest dataset
+    _, ds_long = request.getfixturevalue("valid_bboxes_path_and_ds")
+    assert max_frames == ds_long.sizes["time"]
+
+
 @pytest.mark.parametrize(
     "list_input_data_files",
     [