From time to time people keep trying to use wendelin.core with
dtype=object arrays and get segfaults without anything in logs or
whatever else.

Wendelin.core does not support it, because in case of dtype=object elements are
really pointers and data for each object is stored in separate place in RAM
with different per-object size.

As we are memory-mapping arrays this won't work. It also does not
essentially work for numpy.memmap for the same reason:

    (z4+numpy) kirr@mini:~/src/wendelin$ dd if=/dev/zero of=zero.dat bs=128 count=1
    1+0 records in
    1+0 records out
    128 bytes copied, 0.000209873 s, 610 kB/s
    (z4+numpy) kirr@mini:~/src/wendelin$ dd if=/dev/urandom of=random.dat bs=128 count=1
    1+0 records in
    1+0 records out
    128 bytes copied, 0.000225726 s, 567 kB/s
    (z4+numpy) kirr@mini:~/src/wendelin$ ipython
    ...

    In [1]: import numpy as np

    In [2]: np.memmap('zero.dat', dtype=np.object)
    Out[2]:
    memmap([None, None, None, None, None, None, None, None, None, None, None,
           None, None, None, None, None], dtype=object)

    In [3]: np.memmap('random.dat', dtype=np.object)
    Out[3]: Segmentation fault

So let's clarify this to users via explicitly raising exception when
BigArray with non-appropriate dtype is trying to be created with
descriptive explanation also logged.

/reviewed-on nexedi/wendelin.core!4