.

lib/tests/test_xnumpy.py

@@ -20,7 +20,7 @@
 
 from numpy import ndarray, arange, dtype, int32
 from numpy.lib.stride_tricks import DummyArray
-from wendelin.lib.xnumpy import restructure
+from wendelin.lib.xnumpy import structured
 from pytest import raises
 
 # xbase returns original object from which arr was _as_strided viewed.
@@ -32,8 +32,8 @@ def xbase(arr):
     b = b.base      # -> origin
     return b
 
-# XXX text
-def test_restructure():
+# verifies xnumpy.structured()
+def test_structured():
     dtxy = dtype([('x', int32), ('y', int32)])
 
     # C order
@@ -44,14 +44,14 @@ def test_restructure():
     # 9 10 11
 
     with raises(ValueError, match="minor-axis is not C-contiguous: stride \(-4\) < 0"):
-        restructure(a[:3,:2][:,::-1], dtxy)
+        structured(a[:3,:2][:,::-1], dtxy)
     with raises(ValueError, match="minor-axis is not C-contiguous: stride \(8\) != itemsize \(4\)"):
-        restructure(a[:,::2], dtxy)
+        structured(a[:,::2], dtxy)
     with raises(ValueError, match="dtype.itemsize \(8\) != sizeof\(minor-axis\) \(12\)"):
-        restructure(a, dtxy)
+        structured(a, dtxy)
 
     b = a[:3,:2]
-    bxy = restructure(b, dtxy)
+    bxy = structured(b, dtxy)
     assert xbase(bxy) is b
     assert bxy.dtype == dtxy
     assert bxy.shape == (3,)
@@ -77,7 +77,7 @@ def test_restructure():
     # 6  7  8
     # 9 10 11
     b = a[:3,:2][::-1,:]
-    bxy = restructure(b, dtxy)
+    bxy = structured(b, dtxy)
     assert xbase(bxy) is b
     assert bxy.dtype == dtxy
     assert bxy.shape == (3,)
@@ -104,7 +104,7 @@ def test_restructure():
     # 2  6 10
     # 3  7 11
     b = a[:2,:3]
-    bxy = restructure(b, dtxy)
+    bxy = structured(b, dtxy)
     assert xbase(bxy) is b
     assert bxy.dtype == dtxy
     assert bxy.shape == (3,)
@@ -136,7 +136,7 @@ def test_restructure():
 
     a = a.view(type=MyArray)
     b = a[:3,:2]
-    bxy = restructure(b, dtxy)
+    bxy = structured(b, dtxy)
     assert xbase(bxy) is b
     assert bxy.dtype == dtxy
     assert bxy.shape == (3,)

lib/xnumpy.py

@@ -60,11 +60,12 @@ def _as_strided(arr, shape, stridev, dtype):
     # we are done
     return a
 
-# restructure creates view of the array interpreting its minor axis as fully covered by dtype.
+
+# structured creates view of the array interpreting its minor axis as fully covered by dtype.
 #
 # The minor axis of the array must be C-contiguous and be of dtype.itemsize in size.
 #
-# Restructure is similar to arr.view(dtype) + corresponding reshape, but does
+# Structured is similar to arr.view(dtype) + corresponding reshape, but does
 # not have limitations of ndarray.view(). For example:
 #
 #   In [1]: a = np.arange(3*3, dtype=np.int32).reshape((3,3))
@@ -86,7 +87,7 @@ def _as_strided(arr, shape, stridev, dtype):
 #
 #   In [6]: dtxy
 #   Out[6]: dtype([('x', '<i4'), ('y', '<i4')])
-
+#
 #   In [7]: b.view(dtxy)
 #   ---------------------------------------------------------------------------
 #   ValueError                                Traceback (most recent call last)
@@ -95,11 +96,11 @@ def _as_strided(arr, shape, stridev, dtype):
 #
 #   ValueError: To change to a dtype of a different size, the array must be C-contiguous
 #
-#   In [8]: restructure(b, dtxy)
+#   In [8]: structured(b, dtxy)
 #   Out[8]: array([(0, 1), (3, 4)], dtype=[('x', '<i4'), ('y', '<i4')])
 #
-# Restructure always creates view and never copies data.
-def restructure(arr, dtype):
+# Structured always creates view and never copies data.
+def structured(arr, dtype):
     dtype = np.dtype(dtype) # convenience
 
     atype = arr.dtype