Fix Labels.data_setitem setting of view by taking dims order into a…

…ccount (#6616)

# References and relevant issues

closes #6615

# Description

In #6607, we started painting into both the data and the slice view.
(And this was already happening and broken when painting into lazy
arrays such as zarr and dask, #6112.) However, when setting the view we
need to take into account the axis ordering used when slicing (some axes
may be transposed). This manifested as an index error in #6615.

In this PR, we add an `indices_order` argument to `index_in_slice`
function and the function returns indices in the requested order, which
we can then use to set the view.

napari/layers/labels/_tests/test_labels.py

@@ -705,6 +705,15 @@ def test_data_setitem_multi_dim():
     )
 
 
+def test_data_setitiem_transposed_axes():
+    data = np.zeros((10, 100), dtype=np.uint32)
+    labels = Labels(data)
+    dims = Dims(ndim=2, ndisplay=2, order=(1, 0))
+    labels.data_setitem((np.array([9]), np.array([99])), 1)
+    labels._slice_dims(dims)
+    labels.data_setitem((np.array([9]), np.array([99])), 2)
+
+
 def test_selecting_label():
     """Test selecting label."""
     np.random.seed(0)
@@ -831,7 +840,7 @@ def test_paint_2d():
 
 
 def test_paint_2d_xarray():
-    """Test the memory usage of painting an xarray indirectly via timeout."""
+    """Test the memory usage of painting a xarray indirectly via timeout."""
     now = time.monotonic()
     data = xr.DataArray(np.zeros((3, 3, 1024, 1024), dtype=np.uint32))
 

napari/layers/labels/labels.py

@@ -1593,7 +1593,9 @@ def data_setitem(self, indices, value, refresh=True):
         self.data[indices] = value
 
         pt_not_disp = self._get_pt_not_disp()
-        displayed_indices = index_in_slice(indices, pt_not_disp)
+        displayed_indices = index_in_slice(
+            indices, pt_not_disp, self._slice.slice_input.order
+        )
         if isinstance(value, np.ndarray):
             visible_values = value[elements_in_slice(indices, pt_not_disp)]
         else:

napari/utils/_indexing.py

@@ -35,7 +35,9 @@ def elements_in_slice(
 
 
 def index_in_slice(
-    index: Tuple[npt.NDArray[np.int_], ...], position_in_axes: Dict[int, int]
+    index: Tuple[npt.NDArray[np.int_], ...],
+    position_in_axes: Dict[int, int],
+    indices_order: Tuple[int, ...],
 ) -> Tuple[npt.NDArray[np.int_], ...]:
     """Convert a NumPy fancy indexing expression from data to sliced space.
 
@@ -45,6 +47,8 @@ def index_in_slice(
         A NumPy fancy indexing expression [1]_.
     position_in_axes : dict[int, int]
         A dictionary mapping sliced (non-displayed) axes to a slice position.
+    indices_order : tuple of int
+        The order of the indices in data view.
 
     Returns
     -------
@@ -55,9 +59,9 @@ def index_in_slice(
     Examples
     --------
     >>> index = (np.arange(5), np.full(5, 1), np.arange(4, 9))
-    >>> index_in_slice(index, {0: 3})
+    >>> index_in_slice(index, {0: 3}, (0, 1, 2))
     (array([1]), array([7]))
-    >>> index_in_slice(index, {1: 1, 2: 8})
+    >>> index_in_slice(index, {1: 1, 2: 8}, (0, 1, 2))
     (array([4]),)
 
     References
@@ -66,7 +70,7 @@ def index_in_slice(
     """
     index_in_slice = elements_in_slice(index, position_in_axes)
     return tuple(
-        ix[index_in_slice]
-        for i, ix in enumerate(index)
+        index[i][index_in_slice]
+        for i in indices_order
         if i not in position_in_axes
     )