Repository: spatial-image/multiscale-spatial-image (language: python)

Issue:
Datatree functionality is in Xarray
It looks like the latest version of Xarray merged Datatree functionality upstream, and [archived datatree](https://github.com/xarray-contrib/datatree). As a result SpatialData can't be imported. See [scverse/spatialdata Issue 735](https://github.com/scverse/spatialdata/issues/735#issue-2615112621) for more details.


Discussion / hints:
At some point, we then need to drop the Xarray Datatree dependency, and require the newer version of Xarray, but is that time now? Can SpatialData use and require the newer version of Xarray otherwise?

In the migration guide, it mentions:

> The most important changes made are to the data model of DataTree. Whilst previously data in different nodes was unrelated and therefore unconstrained, now trees have "internal alignment" - meaning that dimensions and indexes in child nodes must exactly align with those in their parents.

It is unclear to me whether this will hit us -- the root node does not have dimensions and indexes. The children do. The scales have different dimensions and indexes, but they are different branches of the tree.
testing this now

Fix patch:
diff --git a/.gitignore b/.gitignore
index b1bf7fa..0482653 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,6 +10,7 @@ examples/sub-I46_ses-SPIM_sample-BrocaAreaS01_stain-GAD67_chunk-00_SPIM*
 examples/dask-worker-space/
 .pixi/
 examples/Cell_Colony.zarr/
+.idea/
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
diff --git a/examples/ConvertTiffFile.ipynb b/examples/ConvertTiffFile.ipynb
index 7b5d3de..9e71bc1 100644
--- a/examples/ConvertTiffFile.ipynb
+++ b/examples/ConvertTiffFile.ipynb
@@ -10,14 +10,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "cffe4de0",
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "jupyter": {
+     "is_executing": true
+    }
+   },
    "source": [
     "import sys\n",
     "!{sys.executable} -m pip install --upgrade multiscale-spatial-image matplotlib tifffile zarr ome-types dask_image 'dask[diagnostics]'"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "code",
@@ -34,7 +38,7 @@
     "import zarr\n",
     "import ome_types\n",
     "import dask.array as da\n",
-    "import datatree\n",
+    "from xarray import open_datatree\n",
     "from numcodecs import Blosc"
    ]
   },
@@ -1296,7 +1300,7 @@
    "source": [
     "store = zarr.storage.DirectoryStore(f'{image_name}.zarr/0', dimension_separator='/')\n",
     "\n",
-    "new_multiscale = datatree.open_datatree(store, engine='zarr')\n",
+    "new_multiscale = open_datatree(store, engine='zarr')\n",
     "new_multiscale['scale2'].ds[name].isel(x=250).plot.imshow()"
    ]
   }
diff --git a/multiscale_spatial_image/multiscale_spatial_image.py b/multiscale_spatial_image/multiscale_spatial_image.py
index 1c463de..b2d3eab 100644
--- a/multiscale_spatial_image/multiscale_spatial_image.py
+++ b/multiscale_spatial_image/multiscale_spatial_image.py
@@ -1,11 +1,10 @@
 from typing import Union
 
-from datatree import DataTree
+from xarray import DataTree, register_datatree_accessor
 import numpy as np
 from collections.abc import MutableMapping
 from pathlib import Path
 from zarr.storage import BaseStore
-from datatree import register_datatree_accessor
 
 
 @register_datatree_accessor("msi")
diff --git a/multiscale_spatial_image/to_multiscale/itk_image_to_multiscale.py b/multiscale_spatial_image/to_multiscale/itk_image_to_multiscale.py
index b144084..4730643 100644
--- a/multiscale_spatial_image/to_multiscale/itk_image_to_multiscale.py
+++ b/multiscale_spatial_image/to_multiscale/itk_image_to_multiscale.py
@@ -3,7 +3,7 @@
 from spatial_image import to_spatial_image
 
 from .to_multiscale import to_multiscale, Methods
-from datatree import DataTree
+from xarray import DataTree
 
 
 def itk_image_to_multiscale(
diff --git a/multiscale_spatial_image/to_multiscale/to_multiscale.py b/multiscale_spatial_image/to_multiscale/to_multiscale.py
index 23a8c1b..bd83088 100644
--- a/multiscale_spatial_image/to_multiscale/to_multiscale.py
+++ b/multiscale_spatial_image/to_multiscale/to_multiscale.py
@@ -4,7 +4,7 @@
 from spatial_image import SpatialImage  # type: ignore
 
 
-from datatree import DataTree
+from xarray import DataTree
 
 from ._xarray import _downsample_xarray_coarsen
 from ._itk import (
@@ -184,6 +184,6 @@ def to_multiscale(
             label="mode",
         )
 
-    multiscale = DataTree.from_dict(d=data_objects)
+    multiscale = DataTree.from_dict(data_objects)
 
     return multiscale
diff --git a/pixi.lock b/pixi.lock
index 1a4ac9a..2854204 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -7,11 +7,11 @@ environments:
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-  - python >=3.9,<3.10.0a0 *_cpython
-  - python_abi 3.9.* *_cp39
+  - python >=3.10,<3.11.0a0
+  - python >=3.10,<3.11.0a0 *_cpython
+  - python_abi 3.10.* *_cp310
   - zstd >=1.5.6,<1.5.7.0a0
   - zstd >=1.5.6,<1.6.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/zstandard?source=conda-forge-mapping
-  size: 319867
-  timestamp: 1718866678183
+  - pkg:pypi/zstandard?source=hash-mapping
+  size: 320810
+  timestamp: 1725305704555
 - kind: conda
   name: zstandard
   version: 0.23.0
-  build: py39h32d468b_0
+  build: py310h41d873f_1
+  build_number: 1
   subdir: osx-64
-  url: https://conda.anaconda.org/conda-forge/osx-64/zstandard-0.23.0-py39h32d468b_0.conda
-  sha256: f5b8c8f4b6260cbba8fc8f74ab6ca7d7edaaef1b108dc55accad4fdb2a5138b5
-  md5: b3234fc0ba4b2d4e173ea2f71be11de8
+  url: https://conda.anaconda.org/conda-forge/osx-64/zstandard-0.23.0-py310h41d873f_1.conda
+  sha256: 449fd094d91e509421ddbe7b707c58191473355f29373c0f3d603875b8d2b801
+  md5: cbf02a084007c683a22172094d31eac6
   depends:
   - __osx >=10.13
   - cffi >=1.11
-  - python >=3.9,<3.10.0a0
-  - python_abi 3.9.* *_cp39
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
   - zstd >=1.5.6,<1.5.7.0a0
   - zstd >=1.5.6,<1.6.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/zstandard?source=conda-forge-mapping
-  size: 400897
-  timestamp: 1721044460640
+  - pkg:pypi/zstandard?source=hash-mapping
+  size: 400765
+  timestamp: 1725305605347
 - kind: conda
   name: zstandard
   version: 0.23.0
-  build: py39h623c9ba_0
+  build: py310ha39cb0e_1
+  build_number: 1
   subdir: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/zstandard-0.23.0-py39h623c9ba_0.conda
-  sha256: ed3512de7f15accf3687cf732ab54d3ff3bc8c6463e63a4474922e5a5e0b8e97
-  md5: a19d023682384c637cb356d270c276c0
+  url: https://conda.anaconda.org/conda-forge/linux-64/zstandard-0.23.0-py310ha39cb0e_1.conda
+  sha256: fcd784735205d6c5f19dcb339f92d2eede9bc42a01ec2c384381ee1b6089d4f6
+  md5: f49de34fb99934bf49ab330b5caffd64
   depends:
   - __glibc >=2.17,<3.0.a0
   - cffi >=1.11
-  - libgcc-ng >=12
-  - python >=3.9,<3.10.0a0
-  - python_abi 3.9.* *_cp39
+  - libgcc >=13
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
   - zstd >=1.5.6,<1.5.7.0a0
   - zstd >=1.5.6,<1.6.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/zstandard?source=conda-forge-mapping
-  size: 406014
-  timestamp: 1721044148631
+  - pkg:pypi/zstandard?source=hash-mapping
+  size: 408309
+  timestamp: 1725305719512
 - kind: conda
   name: zstandard
   version: 0.23.0
-  build: py39h9bf74da_0
+  build: py310he5e10e1_1
+  build_number: 1
   subdir: win-64
-  url: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.23.0-py39h9bf74da_0.conda
-  sha256: af0c955b75aab89c24b3c1a34c323821b7e25d488d9ff31f3767bb9d583272a6
-  md5: 9658585ffb22b68adb5490e9035b93ba
+  url: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.23.0-py310he5e10e1_1.conda
+  sha256: 4e8aff4d0d42024e9f70783e51666186a681384d59fdd03fafda4b28f1fd540e
+  md5: 2a879227ccc1a10a2caddf12607ffaeb
   depends:
   - cffi >=1.11
-  - python >=3.9,<3.10.0a0
-  - python_abi 3.9.* *_cp39
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
   - ucrt >=10.0.20348.0
   - vc >=14.2,<15
   - vc14_runtime >=14.29.30139
@@ -9150,9 +9197,9 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/zstandard?source=conda-forge-mapping
-  size: 310144
-  timestamp: 1721044587416
+  - pkg:pypi/zstandard?source=hash-mapping
+  size: 311278
+  timestamp: 1725306039901
 - kind: conda
   name: zstd
   version: 1.5.6
diff --git a/pyproject.toml b/pyproject.toml
index 6356037..4901d30 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,11 +15,10 @@ classifiers = [
     'Intended Audience :: Developers',
     'Intended Audience :: Science/Research',
     'Programming Language :: Python :: 3',
-    'Programming Language :: Python :: 3.8',
-    'Programming Language :: Python :: 3.9',
     'Programming Language :: Python :: 3.10',
     'Programming Language :: Python :: 3.11',
     'Programming Language :: Python :: 3.12',
+    'Programming Language :: Python :: 3.13',
    ]
 keywords = [
     "itk",
@@ -28,18 +27,17 @@ keywords = [
     "zarr",
     "dask",
     "imaging",
-    "visualization",
+    "visualization"
 ]
 dynamic = ["version"]
 
-requires-python = ">=3.8"
+requires-python = ">=3.10"
 dependencies = [
     "numpy",
     "dask",
     "python-dateutil",
     "spatial_image>=0.2.1",
-    "xarray",
-    "xarray-datatree>=0.0.5",
+    "xarray>=2024.10.0",
     "zarr",
 ]
 
@@ -71,7 +69,7 @@ dask-image = [
 imagej = [
   "pyimagej",
 ]
-notebooks = ["matplotlib>=3.9.1,<4", "ome-types>=0.5.1.post1,<0.6", "tqdm>=4.66.4,<5"]
+notebooks = ["matplotlib>=3.9.2,<4", "ome-types>=0.5.1.post1,<0.6", "tqdm>=4.66.4,<5"]
 
 [tool.black]
 line-length = 88
@@ -99,13 +97,13 @@ lint = { features = ["lint"], no-default-feature = true, solve-group = "default"
 test = { cmd = "pytest", description = "Run the test suite" }
 
 [tool.pixi.feature.test.dependencies]
-python = "3.9.*"
+python = "3.10.*"
 
 [tool.pixi.feature.notebooks.dependencies]
 openjdk = "8.*"
 maven = ">=3.9.8,<3.10"
 jupyterlab = ">=4.2.4,<4.3"
-python = "3.9.*"
+python = "3.10.*"
 
 [tool.pixi.feature.notebooks.tasks]
 init-imagej = { cmd = "python3 -c \"import imagej; ij = imagej.init('2.15.0'); print(ij.getVersion())\"", description = "Initialize the python imagej installation" }
@@ -113,7 +111,7 @@ test-notebooks = { cmd = "pytest --nbmake --nbmake-timeout=3000 examples/Convert
 dev-notebooks = { cmd = "jupyter lab examples", description = "Start Jupyter Lab" }
 
 [tool.pixi.feature.data.dependencies]
-python = ">=3.9.19,<4"
+python = ">=3.10.0,<4"
 pooch = ">=1.8.2,<2"
 
 [tool.pixi.feature.data.tasks]


Test patch:
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 17714cd..b68fb59 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -9,7 +9,7 @@ jobs:
       max-parallel: 5
       matrix:
         os: [ubuntu-22.04, windows-2022, macos-12, macos-14]
-        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - uses: actions/checkout@v4
diff --git a/test/_data.py b/test/_data.py
index 97ed434..8859203 100644
--- a/test/_data.py
+++ b/test/_data.py
@@ -4,7 +4,6 @@
 import pooch
 from zarr.storage import DirectoryStore
 import xarray as xr
-from datatree import open_datatree
 
 test_data_ipfs_cid = "bafybeiaskr5fxg6rbcwlxl6ibzqhubdleacenrpbnymc6oblwoi7ceqzta"
 test_data_sha256 = "507dd779cba007c46ea68a5fe8865cabd5d8a7e00816470faae9195d1f1c3cd1"
@@ -58,7 +57,7 @@ def verify_against_baseline(dataset_name, baseline_name, multiscale):
         test_data_dir / f"baseline/{dataset_name}/{baseline_name}",
         dimension_separator="/",
     )
-    dt = open_datatree(store, engine="zarr", mode="r")
+    dt = xr.open_datatree(store, engine="zarr", mode="r")
     xr.testing.assert_equal(dt.ds, multiscale.ds)
     for scale in multiscale.children:
         xr.testing.assert_equal(dt[scale].ds, multiscale[scale].ds)
diff --git a/test/test_ngff_validation.py b/test/test_ngff_validation.py
index 98b56d7..0bc3e4c 100644
--- a/test/test_ngff_validation.py
+++ b/test/test_ngff_validation.py
@@ -5,7 +5,7 @@
 from referencing import Registry, Resource
 from jsonschema import Draft202012Validator
 
-from datatree import DataTree
+from xarray import DataTree
 
 from multiscale_spatial_image import to_multiscale, MultiscaleSpatialImage
 from spatial_image import to_spatial_image