Merge pull request #113 from thewtex/doc-updates

doc updates

Author: thewtex

README.md

@@ -8,19 +8,23 @@
 
 ---
 
-A lean and kind Open Microscopy Environment (OME) Next Generation File Format
-(NGFF) Zarr implementation.
+A lean and kind
+[Open Microscopy Environment (OME) Next Generation File Format (NGFF) Zarr](https://ngff.openmicroscopy.org)
+implementation.
 
 ## ✨ Features
 
 - Minimal dependencies
 - Work with arbitrary Zarr store types
 - Lazy, parallel, and web ready -- no local filesystem required
 - Process extremely large datasets
+- Conversion of most bioimaging file formats
 - Multiple downscaling methods
-- Supports Python>=3.8
-- Implements version 0.4 of the
-  [OME-Zarr NGFF specification](https://github.com/ome/ngff)
+- Supports Python>=3.9
+- Reads OME-Zarr v0.1 to v0.5 into simple Python data classes with Dask arrays
+- Optional OME-Zarr data model validation during reading
+- Writes OME-Zarr v0.4 to v0.5
+- Optional writing via [tensorstore](https://google.github.io/tensorstore/)
 
 ## Documentation
 

docs/index.md

@@ -16,10 +16,13 @@ A lean and kind
 - Work with arbitrary Zarr store types
 - Lazy, parallel, and web ready -- no local filesystem required
 - Process extremely large datasets
+- Conversion of most bioimaging file formats
 - Multiple downscaling methods
 - Supports Python>=3.9
-- Implements version 0.4 of the
-  [OME-Zarr NGFF specification](https://github.com/ome/ngff)
+- Reads OME-Zarr v0.1 to v0.5 into simple Python data classes with Dask arrays
+- Optional OME-Zarr data model validation during reading
+- Writes OME-Zarr v0.4 to v0.5
+- Optional writing via [tensorstore](https://google.github.io/tensorstore/)
 
 ```{toctree}
 :maxdepth: 2

test/test_ngff_validation.py

@@ -69,27 +69,3 @@ def test_validate_0_3():
 def test_validate_0_3_no_version():
     test_store = Path(__file__).parent / "data" / "input" / "v03" / "9528933.zarr"
     from_ngff_zarr(test_store, validate=True)
-
-
-# def test_z_y_x_valid_ngff():
-#     array = np.random.random((32, 32, 16))
-#     image = to_spatial_image(array)
-#     multiscale = to_multiscale(image, [2, 4])
-
-#     check_valid_ngff(multiscale)
-
-
-# def test_z_y_x_c_valid_ngff():
-#     array = np.random.random((32, 32, 16, 3))
-#     image = to_spatial_image(array)
-#     multiscale = to_multiscale(image, [2, 4])
-
-#     check_valid_ngff(multiscale)
-
-
-# def test_t_z_y_x_c_valid_ngff():
-#     array = np.random.random((2, 32, 32, 16, 3))
-#     image = to_spatial_image(array)
-#     multiscale = to_multiscale(image, [2, 4])
-
-#     check_valid_ngff(multiscale)