Style revisions

Author: Tarik Onalan

zarr/tests/test_core.py

@@ -846,7 +846,7 @@ def test_nchunks_initialized(self):
         z[:] = 42
         assert 10 == z.nchunks_initialized
 
-    def test_unstructured_array(self):
+    def test_array_dtype_shape(self):
 
         dt = "(2, 2)f4"
         # setup some data
@@ -925,7 +925,7 @@ def test_structured_array_subshapes(self):
                     assert_array_equal(a['bar'], z['bar'])
                     assert_array_equal(a['baz'], z['baz'])
                 else:
-                    # BUG(onalant): https://www.github.com/numpy/numpy/issues/11946
+                    # workaround for numpy bug https://www.github.com/numpy/numpy/issues/11946
                     assert a.tobytes() == z[...].tobytes()
 
     def test_structured_array_nested(self):
@@ -958,7 +958,7 @@ def test_structured_array_nested(self):
                     assert_array_equal(a['bar'], z['bar'])
                     assert_array_equal(a['baz'], z['baz'])
                 else:
-                    # BUG(onalant): https://www.github.com/numpy/numpy/issues/11946
+                    # workaround for numpy bug https://www.github.com/numpy/numpy/issues/11946
                     assert a.tobytes() == z[...].tobytes()
 
     def test_dtypes(self):
@@ -1645,7 +1645,7 @@ def test_astype(self):
         expected = data.astype(astype)
         assert_array_equal(expected, z2)
 
-    def test_unstructured_array(self):
+    def test_array_dtype_shape(self):
         # skip this one, cannot do delta on unstructured array
         pass
 

zarr/tests/test_meta.py

@@ -116,7 +116,7 @@ def test_encode_decode_array_2():
     assert [df.get_config()] == meta_dec['filters']
 
 
-def test_encode_decode_array_unstructured():
+def test_encode_decode_array_dtype_shape():
 
     meta = dict(
         shape=(100,),
@@ -146,12 +146,10 @@ def test_encode_decode_array_unstructured():
     # test decoding
     meta_dec = decode_array_metadata(meta_enc)
     assert ZARR_FORMAT == meta_dec['zarr_format']
-    # NOTE(onalant): https://github.com/zarr-developers/zarr/pull/296#issuecomment-417608487
-    # To maintain consistency with numpy unstructured arrays, unpack dimensions into shape.
+    # to maintain consistency with numpy unstructured arrays, unpack dimensions into shape
     assert meta['shape'] + meta['dtype'].shape == meta_dec['shape']
     assert meta['chunks'] == meta_dec['chunks']
-    # NOTE(onalant): https://github.com/zarr-developers/zarr/pull/296#issuecomment-417608487
-    # To maintain consistency with numpy unstructured arrays, unpack dtypes.
+    # to maintain consistency with numpy unstructured arrays, unpack dtypes
     assert meta['dtype'].base == meta_dec['dtype']
     assert meta['compressor'] == meta_dec['compressor']
     assert meta['order'] == meta_dec['order']
@@ -189,12 +187,10 @@ def test_encode_decode_array_structured():
     # test decoding
     meta_dec = decode_array_metadata(meta_enc)
     assert ZARR_FORMAT == meta_dec['zarr_format']
-    # NOTE(onalant): https://github.com/zarr-developers/zarr/pull/296#issuecomment-417608487
-    # To maintain consistency with numpy unstructured arrays, unpack dimensions into shape.
+    # to maintain consistency with numpy unstructured arrays, unpack dimensions into shape
     assert meta['shape'] + meta['dtype'].shape == meta_dec['shape']
     assert meta['chunks'] == meta_dec['chunks']
-    # NOTE(onalant): https://github.com/zarr-developers/zarr/pull/296#issuecomment-417608487
-    # To maintain consistency with numpy unstructured arrays, unpack dtypes.
+    # to maintain consistency with numpy unstructured arrays, unpack dimensions into shape
     assert meta['dtype'].base == meta_dec['dtype']
     assert meta['compressor'] == meta_dec['compressor']
     assert meta['order'] == meta_dec['order']