X xnumpy.restructure

Currently fails with:

/home/kirr/src/wendelin/wendelin.core/lib/xnumpy.py in restructure(arr, dtype)
     82     print 'stridev:', stridev
     83     #return np.ndarray.__new__(type(arr), shape, dtype, buffer(arr), 0, stridev)
---> 84     return np.ndarray(shape, dtype, buffer(arr), 0, stridev)

TypeError: expected a single-segment buffer object

lib/xnumpy.py

+# -*- coding: utf-8 -*-
+# NumPy-related utilities
+# Copyright (C) 2018  Nexedi SA and Contributors.
+#                     Kirill Smelkov <kirr@nexedi.com>
+#
+# This program is free software: you can Use, Study, Modify and Redistribute
+# it under the terms of the GNU General Public License version 3, or (at your
+# option) any later version, as published by the Free Software Foundation.
+#
+# You can also Link and Combine this program with other software covered by
+# the terms of any of the Free Software licenses or any of the Open Source
+# Initiative approved licenses and Convey the resulting work. Corresponding
+# source of such a combination shall include the source code for all other
+# software used.
+#
+# This program is distributed WITHOUT ANY WARRANTY; without even the implied
+# warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+#
+# See COPYING file for full licensing terms.
+# See https://www.nexedi.com/licensing for rationale and options.
+import numpy as np
+
+
+# restructure 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 fully covered by dtype in size.
+#
+# Restructure 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))
+#
+# In [2]: a
+# Out[2]:
+# array([[0, 1, 2],
+#        [3, 4, 5],
+#        [6, 7, 8]], dtype=int32)
+#
+# In [3]: b = a[:2,:2]
+#
+# In [4]: b
+# Out[4]:
+# array([[0, 1],
+#        [3, 4]], dtype=int32)
+#
+# In [5]: b.view(np.int64)
+# ---------------------------------------------------------------------------
+# ValueError                                Traceback (most recent call last)
+# <ipython-input-66-af98529aa150> in <module>()
+# ----> 1 b.view(np.int64)
+#
+# ValueError: To change to a dtype of a different size, the array must be C-contiguous
+#
+# In [6]: restructure(b, np.int64)
+# TODO
+#
+# restructure always creates view and never copies data.
+#
+# TODO tests
+def restructure(arr, dtype):
+    dtype = np.dtype(dtype) # convenience
+
+    atype = arr.dtype
+    # m* denotes minor *
+    maxis   = np.argmin(np.abs(arr.strides))
+    mstride = arr.strides[maxis]
+    if mstride < 0:
+        raise ValueError("minor-axis is not C-contiguous: stride (%d) < 0" % mstride)
+    if mstride != atype.itemsize:
+        raise ValueError("minor-axis is not C-contiguous: stride (%d) != itemsize (%d)" % (mstride, atype.itemsize))
+
+    # verify dtype fully covers whole minor axis
+    mnelem = arr.shape[maxis]
+    msize  = mnelem * atype.itemsize
+    if dtype.itemsize != msize:
+        raise ValueError("dtype.itemsize (%d) != sizeof(minor-axis) (%d)" % (dtype.itemsize, msize))
+
+    # 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)

t/tfault-run

-#!/bin/sh -e
+#!/bin/bash -e
 # tfault-run <tfault> <arg> <mustdie>
 # run `<tfault> <arg>` and verify that it produces correct coredump, dieing for
 #   SIGSEGV in function <mustdie>.