Evn though the kernel not generally releasing mmap_sem on IO caused by
pagefault.

* master:
  lib.xnumpy.structured: New utility to create structured view of an array
  bigarray: Factor-out our custom numpy.lib.stride_tricks.as_strided-alike into lib/xnumpy.py

Structured creates view of the array interpreting its minor axis as fully covered by a dtype.

It 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]: dtxy = np.dtype([('x', np.int32), ('y', np.int32)])

  In [6]: dtxy
  Out[6]: dtype([('x', '<i4'), ('y', '<i4')])

  In [7]: b.view(dtxy)
  ---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  <ipython-input-66-af98529aa150> in <module>()
  ----> 1 b.view(dtxy)

  ValueError: To change to a dtype of a different size, the array must be C-contiguous

  In [8]: structured(b, dtxy)
  Out[8]: array([(0, 1), (3, 4)], dtype=[('x', '<i4'), ('y', '<i4')])

Structured always creates view and never copies data.

Here is original context where separately playing with .shape and .dtype
was not enough, since it was creating array copy and OOM'ing the machine:

klaus/wendelin@cbe4938b

We are going to use this code in another place, so move this out to
dommon place as a preparatory step first.

On a related note: Since ArrayRef is generic and quite independent from
BigArray (it only supports it, but equally it supports just other - e.g.
plain arrays), the proper place for it might be also to be lib/xnumpy.py .
We might get to this topic a bit later.

* nxd/master:
  bigarray: RAMArray
  bigarray/tests: Factor out a way to spcify on which BigFile/BigFileH an array is tested into fixture parameter

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

The kernel sends SIGSTOP to interrupt tracee, but the signal will be
processed only when the process returns from kernel space, e.g. here

	https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/tree/arch/x86/entry/common.c?id=v4.19-rc8-151-g23469de647c4#n160

This way the tracer won't receive obligatory information that tracee
stopped (via wait...) and even though ptrace(ATTACH) succeeds, all other
ptrace commands will fail:

	https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/tree/kernel/ptrace.c?id=v4.19-rc8-151-g23469de647c4#n1140
	https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/tree/kernel/ptrace.c?id=v4.19-rc8-151-g23469de647c4#n207

My original idea was to use ptrace to run code in process to change it's
memory mappings, while the triggering process is under pagefault/read
to wcfs, and the above shows it won't work - trying to ptrace the
client from under wcfs will just block forever (the kernel will be
waiting for read operation to finish for ptrace, and read will be first
waiting on ptrace stopping to complete = deadlock)