Prep for 0.4.0-rc2 (#206)

Author: aliddell

.gitignore

@@ -45,7 +45,7 @@ pip-selfcheck.json
 # Unit test / coverage reports
 htmlcov/
 .tox/
-.coverage
+.coverage*
 .cache
 nosetests.xml
 coverage.xml

Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "acquire-imaging"
 authors = ["Nathan Clack <nclack@chanzuckerberg.com>"]
-version = "0.4.0-rc1"
+version = "0.4.0-rc2"
 edition = "2021"
 
 [lib]

acquire-common

@@ -1,5 +1,5 @@
 {
-  "acquire-driver-zarr": "0.1.12",
+  "acquire-driver-zarr": "0.1.13",
   "acquire-driver-egrabber": "0.1.5",
   "acquire-driver-hdcam": "0.1.9",
   "acquire-driver-spinnaker": "0.1.1",

drivers.json

@@ -5,15 +5,13 @@
 from typing import Optional
 
 import dotenv
-import numpy as np
 import pytest
 import s3fs
 import zarr
 from dask import array as da
 from numcodecs import blosc as blosc
 from ome_zarr.io import parse_url
 from ome_zarr.reader import Reader
-from skimage.transform import downscale_local_mean
 
 import acquire
 from acquire import Runtime, DeviceKind
@@ -420,15 +418,7 @@ def test_write_zarr_multiscale(
     data = [
         da.from_zarr(uri, component=str(i)) for i in range(len(zgroup.data))
     ]
-    assert len(data) == 3
-
-    image = data[0][0, :, :].compute()  # convert dask array to numpy array
-
-    for d in data:
-        assert (
-            np.linalg.norm(image - d[0, :, :].compute()) == 0
-        )  # validate against the same method from scikit-image
-        image = downscale_local_mean(image, (2, 2)).astype(np.uint8)
+    assert len(data) == 3  # 3 layers
 
 
 @pytest.mark.parametrize(