Creating numpy array of custom objects gives error "SystemError: error return without exception set"

@user2357112 identified the problem: you are assigning an Element instance to a numpy array that holds integers. This is what I get when I try something similar:

>>> import numpy as np
>>> np.__version__
'1.7.1'
>>> p = np.array([1,2,3])
>>> class Foo:
...     pass
... 
>>> p[0] = Foo()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
SystemError: error return without exception set
>>> 

It is not surprising that this is not allowed. The cryptic error message, however, is almost certainly a numpy bug.

One way to fix the issue is to use an array of type object. Change this line:

    periodicTable = np.array(range(7*32)).reshape((7,32))

to this:

    periodicTable = np.empty((7,32), dtype=object)

Update

In numpy 1.10.1, the error message is still a bit cryptic:

>>> import numpy as np
>>> np.__version__
'1.10.1'    
>>> p = np.array([1, 2, 3])
>>> class Foo:
...     pass
...  
>>> p[0] = Foo()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: Foo instance has no attribute '__trunc__'

Update 2

The error message is better is later versions of numpy:

In [1]: import numpy as np

In [2]: np.__version__
Out[2]: '1.12.1'

In [3]: class Foo:
   ...:     pass
   ...: 

In [4]: p = np.array([1, 2, 3])

In [5]: p[0] = Foo()
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-739d5e5f795b> in <module>()
----> 1 p[0] = Foo()

TypeError: int() argument must be a string, a bytes-like object or a number, not 'Foo'