X `expected a single-segment buffer object` problem gone

lib/xnumpy.py

@@ -19,6 +19,7 @@
 # See COPYING file for full licensing terms.
 # See https://www.nexedi.com/licensing for rationale and options.
 import numpy as np
+from numpy.lib import stride_tricks as npst
 
 
 # restructure creates view of the array interpreting its minor axis as fully covered by dtype.
@@ -52,7 +53,10 @@ import numpy as np
 # ValueError: To change to a dtype of a different size, the array must be C-contiguous
 #
 # In [6]: restructure(b, np.int64)
-# TODO
+# Out[6]: array([ 4294967296, 17179869187])
+#
+# In [7]: restructure(b, [('x', np.int32), ('y', np.int32)])
+# Out[7]: array([(0, 1), (3, 4)], dtype=[('x', '<i4'), ('y', '<i4')])
 #
 # restructure always creates view and never copies data.
 #
@@ -78,4 +82,26 @@ def restructure(arr, dtype):
     # ok to go
     shape   = arr.shape[:maxis] + arr.shape[maxis+1:]
     stridev = arr.strides[:maxis] + arr.strides[maxis+1:]
-    return np.ndarray.__new__(type(arr), shape, dtype, buffer(arr), 0, stridev)
+
+    # NOTE cannot use just np.ndarray because if arr is a slice it can give:
+    #   TypeError: expected a single-segment buffer object
+    #return np.ndarray.__new__(type(arr), shape, dtype, buffer(arr), 0, stridev)
+
+    # XXX dup from ArrayRef
+    aiface = dict(arr.__array_interface__)
+    aiface['shape']   = shape
+    aiface['strides'] = stridev
+    # type: for now we only care that itemsize is the same
+    aiface['typestr'] = '|V%d' % dtype.itemsize
+    aiface['descr']   = [('', aiface['typestr'])]
+
+    a = np.asarray(npst.DummyArray(aiface, base=arr))
+
+    # restore full dtype - it should not raise here, since itemsize is the same
+    a.dtype = dtype
+
+    # restore full array type
+    a = a.view(type=type(arr))
+
+    # we are done
+    return a