Minor fixes

Signed-off-by: Eric Kerfoot <[email protected]>

Author: ericspod

tests/inferers/test_zarr_avg_merger.py

@@ -368,6 +368,7 @@ def _get_directory_store(self, base_dir):
     def test_zarr_avg_merger_patches(self, arguments, patch_locations, expected):
         is_zarr_v3 = version_geq(get_package_version("zarr"), "3.0.0")
         codec_reg = numcodecs.registry.codec_registry
+        arguments = dict(arguments)
 
         # Handle compressor/codecs based on zarr version
         if "compressor" in arguments and is_zarr_v3:

tests/networks/layers/test_gaussian_filter.py

@@ -142,7 +142,7 @@ def test_training(self, input_args):
 
         # train
         optimizer = torch.optim.Adam(trainable.parameters(), lr=lr)
-        for s in range(1000):
+        for _ in range(1000):
             optimizer.zero_grad()
             pred = trainable(base)
             loss = torch.pow(pred - target, 2).mean()

tests/transforms/test_detect_envelope.py

@@ -52,7 +52,7 @@
 ]
 
 TEST_CASE_2D_SINE_AXIS_1 = [
-    {"axis": 2},  # set axis argument to 1
+    {"axis": 2},  # set axis argument to 2
     # Create 10 identical windowed sine waves as a 2D numpy array
     np.expand_dims(np.stack([hann_windowed_sine] * 10, axis=1), 0),
     # Expected output: absolute value of each sample of the waveform, repeated (i.e. flat envelopes)