WIP: BUG: tzyxc bin shrink crassh

Re: #157

Author: thewtex

ngff_zarr/methods/_itk.py

@@ -135,14 +135,18 @@ def _downsample_itk_bin_shrink(
     previous_dim_factors = {d: 1 for d in dims}
     spatial_dims = [dim for dim in dims if dim in _spatial_dims]
     spatial_dims = _image_dims[: len(spatial_dims)]
+    breakpoint()
     for scale_factor in scale_factors:
         dim_factors = _dim_scale_factors(dims, scale_factor, previous_dim_factors)
         previous_dim_factors = _update_previous_dim_factors(
             scale_factor, spatial_dims, previous_dim_factors
         )
         previous_image = _align_chunks(previous_image, default_chunks, dim_factors)
 
-        shrink_factors = [dim_factors[sd] for sd in spatial_dims]
+        if "t" in previous_image.dims:
+            shrink_factors = [dim_factors[sd] for sd in spatial_dims + ("t",)]
+        else:
+            shrink_factors = [dim_factors[sd] for sd in spatial_dims]
 
         block_0 = _get_block(previous_image, 0)
 

ngff_zarr/methods/_support.py

@@ -111,6 +111,11 @@ def _dim_scale_factors(dims, scale_factor, previous_dim_factors):
         result_scale_factors = {
             d: int(scale_factor[d] / previous_dim_factors[d]) for d in scale_factor
         }
+        # if a dim is not in the scale_factors, add it with a scale factor of 1
+        for d in dims:
+            if d not in result_scale_factors:
+                result_scale_factors[d] = 1
+
     return result_scale_factors
 
 def _update_previous_dim_factors(scale_factor, spatial_dims, previous_dim_factors):

test/test_to_ngff_zarr_itk.py

@@ -1,6 +1,6 @@
 import pytest
 
-from ngff_zarr import Methods, to_multiscales
+from ngff_zarr import Methods, to_multiscales, to_ngff_image
 
 from ._data import verify_against_baseline
 import platform
@@ -19,6 +19,39 @@ def test_bin_shrink_isotropic_scale_factors(input_images):
     # store_new_multiscales(dataset_name, baseline_name, multiscales)
     verify_against_baseline(dataset_name, baseline_name, multiscales)
 
+def test_bin_shrink_tzyxc():
+    import dask.array as da
+    from ngff_zarr import Axis
+    test_array = da.ones((96, 256, 256, 256, 2), chunks=(1, 128, 128, 128, 1), dtype="uint16")
+    img = to_ngff_image(
+        test_array,
+        dims=list("tzyxc"),
+        scale={
+            "t": 100_000.0,
+            "z": 0.98,
+            "y": 0.98,
+            "x": 0.98,
+            "c": 1.0,
+        },
+        axes_units={
+            "t": "millisecond",
+            "z": "micrometer",
+            "y": "micrometer",
+            "x": "micrometer",
+        },
+        name="000x_000y_000z",
+    )
+
+    multiscales = to_multiscales(
+        img,
+        scale_factors=[
+            {"z": 2, "y": 2, "x": 2},
+            {"z": 4, "y": 4, "x": 4}
+        ],
+        method=Methods.ITK_BIN_SHRINK,
+    )
+    assert len(multiscales.images) == 3
+
 
 @pytest.mark.skipif(
     platform.system() == "Linux" and platform.machine() == "aarch64",

test/test_to_ngff_zarr_itkwasm.py

@@ -106,6 +106,39 @@ def test_bin_shrink_tczyx():
     assert multiscales.images[1].data.shape[1] == 2
     assert multiscales.images[1].data.shape[2] == 16
 
+def test_bin_shrink_tzyxc():
+    import dask.array as da
+    from ngff_zarr import Axis
+    test_array = da.ones((96, 256, 256, 256, 2), chunks=(1, 128, 128, 128, 1), dtype="uint16")
+    img = to_ngff_image(
+        test_array,
+        dims=list("tzyxc"),
+        scale={
+            "t": 100_000.0,
+            "z": 0.98,
+            "y": 0.98,
+            "x": 0.98,
+            "c": 1.0,
+        },
+        axes_units={
+            "t": "millisecond",
+            "z": "micrometer",
+            "y": "micrometer",
+            "x": "micrometer",
+        },
+        name="000x_000y_000z",
+    )
+
+    multiscales = to_multiscales(
+        img,
+        scale_factors=[
+            {"z": 2, "y": 2, "x": 2},
+            {"z": 4, "y": 4, "x": 4}
+        ],
+        method=Methods.ITK_BIN_SHRINK,
+    )
+    assert len(multiscales.images) == 3
+
 
 def test_bin_shrink_isotropic_scale_factors(input_images):
     dataset_name = "cthead1"