Better error checking during initialization

Beginne damit, die Backend-Initialisierung von arrayfire.backend.name() über arrayfire.Array() und den im Traceback gezeigten safe_call-Pfad nachzuverfolgen. Bestätige, wie die Geräteverfügbarkeit derzeit geprüft wird, und sorge dafür, dass der Fehlerbericht einen nützlichen Treiber- oder Gerätefehler ausgibt; überprüfe das Verhalten anhand des im Issue beschriebenen Initialisierungsszenarios.

Today I came across the following cryptic error message when trying to use arrayfire-python:

In [1]: import arrayfire
In [2]: arrayfire.backend.name()
Out[2]: 'cuda'
In [5]: arrayfire.Array()
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-5-6dffbbbc7abd> in <module>()
----> 1 arrayfire.Array()

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/array.pyc in __init__(self, src, dims, dtype, is_device)
    422             for n in range(numdims):
    423                 idims[n] = dims[n]
--> 424             self.arr = _create_empty_array(numdims, idims, to_dtype[type_char])
    425
    426     def as_type(self, ty):

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/array.pyc in _create_empty_array(numdims, idims, dtype)
     36     c_dims = dim4(idims[0], idims[1], idims[2], idims[3])
     37     safe_call(backend.get().af_create_handle(ct.pointer(out_arr),
---> 38                                              numdims, ct.pointer(c_dims), dtype.value))
     39     return out_arr
     40

/home/filipe/.local/lib/python2.7/site-packages/arrayfire-3.2.20151211-py2.7.egg/arrayfire/util.pyc in safe_call(af_error)
     73         err_len = ct.c_longlong(0)
     74         backend.get().af_get_last_error(ct.pointer(err_str), ct.pointer(err_len))
---> 75         raise RuntimeError(to_str(err_str), af_error)
     76
     77 def get_version():

RuntimeError: ('Error in /var/lib/jenkins-slave/workspace/arrayfire-linux-mkl-graphics-installer/src/api/c/data.cpp(197):\n\n\n', 998)

The error was caused by a bad driver version:

$ nvidia-smi
Failed to initialize NVML: GPU access blocked by the operating system

I think it could be useful if arrayfire would test if a device is really available, instead of just checking if it can dlopen the relevant library. For example by calling arrayfire.Array(). If that would fail a more useful error could be returned to the user.