Add functionality for specifying channel names when saving to spatial…

…data Zarr (#151)

* Add ability to specify image channel names.

If provided, the channel names are saved as metadata in the Zarr. When
reading the resulting Zarr file with spatialdata, the channel names will
be read too and accessible in the corresponding spatialdata object via
the "c" field of "coords".

Channel names are also passed correctly to different image processing functions.

---------

Co-authored-by: ArneDefauw <[email protected]>

src/napari_sparrow/_tests/test_data/multi_channel_zarr/sdata.zarr/images/combine/.zattrs

@@ -0,0 +1,95 @@
+{
+ "channels_metadata": {
+ "channels": [
+ {
+ "label": 0
+ },
+ {
+ "label": 1
+ }
+ ]
+ },
+ "multiscales": [
+ {
+ "axes": [
+ {
+ "name": "c",
+ "type": "channel"
+ },
+ {
+ "name": "y",
+ "type": "space"
+ },
+ {
+ "name": "x",
+ "type": "space"
+ }
+ ],
+ "coordinateTransformations": [
+ {
+ "input": {
+ "axes": [
+ {
+ "name": "c",
+ "type": "channel"
+ },
+ {
+ "name": "y",
+ "type": "space",
+ "unit": "unit"
+ },
+ {
+ "name": "x",
+ "type": "space",
+ "unit": "unit"
+ }
+ ],
+ "name": "cyx"
+ },
+ "output": {
+ "axes": [
+ {
+ "name": "c",
+ "type": "channel"
+ },
+ {
+ "name": "y",
+ "type": "space",
+ "unit": "unit"
+ },
+ {
+ "name": "x",
+ "type": "space",
+ "unit": "unit"
+ }
+ ],
+ "name": "global"
+ },
+ "translation": [
+ 0.0,
+ 0.0,
+ 0.0
+ ],
+ "type": "translation"
+ }
+ ],
+ "datasets": [
+ {
+ "coordinateTransformations": [
+ {
+ "scale": [
+ 1.0,
+ 1.0,
+ 1.0
+ ],
+ "type": "scale"
+ }
+ ],
+ "path": "0"
+ }
+ ],
+ "name": "/images/combine",
+ "version": "0.4"
+ }
+ ]
+}

src/napari_sparrow/_tests/test_data/multi_channel_zarr/sdata.zarr/images/combine/.zgroup

@@ -0,0 +1,3 @@
+{
+ "zarr_format": 2
+}

src/napari_sparrow/_tests/test_data/multi_channel_zarr/sdata.zarr/images/combine/0/.zarray

@@ -0,0 +1,25 @@
+{
+ "chunks": [
+ 1,
+ 512,
+ 512
+ ],
+ "compressor": {
+ "blocksize": 0,
+ "clevel": 5,
+ "cname": "lz4",
+ "id": "blosc",
+ "shuffle": 1
+ },
+ "dimension_separator": "/",
+ "dtype": "<f4",
+ "fill_value": 0.0,
+ "filters": null,
+ "order": "C",
+ "shape": [
+ 2,
+ 512,
+ 512
+ ],
+ "zarr_format": 2
+}

src/napari_sparrow/_tests/test_image/test_combine.py

@@ -0,0 +1,16 @@
+from spatialdata import SpatialData
+
+from napari_sparrow.image._combine import combine
+
+def test_combine( sdata_multi_c ):
+
+ sdata_multi_c=combine( sdata_multi_c,
+ img_layer="raw_image", 
+ output_layer="combine", 
+ nuc_channels=[ 15, 14 ],
+ mem_channels=[ 0,6,11 ],
+ overwrite=True
+ )
+
+ assert "combine" in sdata_multi_c.images
+ assert isinstance(sdata_multi_c, SpatialData)

src/napari_sparrow/_tests/test_widget.py

@@ -1,11 +1,11 @@
 """This file tests the napari widgets and should be used for development purposes."""
-import unittest
+import pytest
 
 import tifffile as tiff
 from hydra.core.hydra_config import HydraConfig
 
 
-@unittest.skip
+@pytest.mark.skip
 def test_sparrow_widgets(make_napari_viewer, cfg_pipeline, caplog):
  """
  Integration test for sparrow plugin in napari
@@ -85,8 +85,7 @@ def test_sparrow_widgets(make_napari_viewer, cfg_pipeline, caplog):
  assert "Annotation metadata added" in caplog.text
 
 
-
-@unittest.skip
+@pytest.mark.skip
 def test_load_widget(make_napari_viewer, cfg_pipeline, caplog):
  """Test if the load works."""
  from napari_sparrow import utils as utils
@@ -112,7 +111,7 @@ def test_load_widget(make_napari_viewer, cfg_pipeline, caplog):
  assert f"Added {utils.LOAD}" in caplog.text
 
 
-@unittest.skip
+@pytest.mark.skip
 def test_clean_widget(make_napari_viewer, cfg_pipeline, caplog):
  """Tests if the clean widget works."""
 

src/napari_sparrow/image/_apply.py

@@ -190,7 +190,8 @@ def adjust_depth(depth, chunksize, depth_dim):
  crd = _substract_translation_crd(se, crd)
 
  for ch, _fn_kwargs in zip(channel, _fn_kwargs_channel):
- arr = se.isel(c=ch).data
+ channel_idx = list(se.c.data).index(ch)
+ arr = se.isel(c=channel_idx).data
  if len(arr.shape) != 2:
  raise ValueError(
  f"Array is of dimension {arr.shape}, currently only 2D images are supported."
@@ -218,6 +219,7 @@ def adjust_depth(depth, chunksize, depth_dim):
  chunks=arr.chunksize,
  transformation=translation,
  scale_factors=scale_factors,
+ c_coords=channel,
  overwrite=overwrite,
  )
 

src/napari_sparrow/image/_combine.py

@@ -25,14 +25,14 @@ def combine(
  sdata: SpatialData,
  img_layer: Optional[str] = None,
  output_layer: Optional[str] = None,
- nuc_channels: Optional[int | Iterable[int]] = None,
- mem_channels: Optional[int | Iterable[int]] = None,
+ nuc_channels: Optional[int | str | Iterable[int | str]] = None,
+ mem_channels: Optional[int | str | Iterable[int | str]] = None,
  crd: Optional[Tuple[int, int, int, int]] = None,
  scale_factors: Optional[ScaleFactors_t] = None,
  overwrite: bool = False,
 ) -> SpatialData:
  """
- Combines specific channels within an image layer of a SpatialData object. 
+ Combines specific channels within an image layer of a SpatialData object.
  When given, nuc_channels are aggregated together, as are mem_channels.
 
  Parameters
@@ -43,9 +43,9 @@ def combine(
  The image layer in `sdata` to process. If not provided, the last image layer in `sdata` is used.
  output_layer : Optional[str]
  The name of the output layer where results will be stored. This must be specified.
- nuc_channels : Optional[int | Iterable[int]], default=None
+ nuc_channels : Optional[int | str | Iterable[int | str ]], default=None
  Specifies which channel(s) to consider as nuclear channels.
- mem_channels : Optional[int | Iterable[int]], default=None
+ mem_channels : Optional[int | str | Iterable[int | str ]], default=None
  Specifies which channel(s) to consider as membrane channels.
  crd : Optional[Tuple[int, int, int, int]], default=None
  The coordinates specifying the region of the image to be processed. Defines the bounds (x_min, x_max, y_min, y_max).
@@ -108,14 +108,25 @@ def _process_channels(
  if isinstance(channels, Iterable) and not isinstance(channels, str)
  else [channels]
  )
- arr = se.isel(c=channels).data
+
+ all_channels = list(se.c.data)
+ ch_indices = [
+ all_channels.index(_ch) for _ch in channels if _ch in all_channels
+ ]
+
+ if len(ch_indices) == 0:
+ raise ValueError(
+ f"No matching channels between provided channels '{channels}' and channels in '{img_layer}': '{all_channels}'."
+ )
+
+ arr = se.isel(c=ch_indices).data
  if len(arr.shape) != 3:
  raise ValueError(
  f"Array is of dimension {arr.shape}, currently only 2D images are supported."
  )
  if crd is not None:
- arr = arr[:,crd[2] : crd[3], crd[0] : crd[1]]
- arr=arr.rechunk( arr.chunksize )
+ arr = arr[:, crd[2] : crd[3], crd[0] : crd[1]]
+ arr = arr.rechunk(arr.chunksize)
  arr = arr.sum(axis=0)
  arr = arr[None, ...]
  return arr

src/napari_sparrow/image/_image.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import Optional, Tuple, Union
+from typing import List, Optional, Tuple, Union
 
 import numpy as np
 import xarray as xr
@@ -212,6 +212,7 @@ def _add_image_layer(
  chunks: Optional[str | tuple[int, int, int] | int] = None,
  transformation: Union[BaseTransformation, dict[str, BaseTransformation]] = None,
  scale_factors: Optional[ScaleFactors_t] = None,
+ c_coords: Optional[List[str]] = None,
  overwrite: bool = False,
 ):
  manager = ImageLayerManager()
@@ -222,6 +223,7 @@ def _add_image_layer(
  chunks=chunks,
  transformation=transformation,
  scale_factors=scale_factors,
+ c_coords=c_coords,
  overwrite=overwrite,
  )