objgraph.show_growth() doesn't notice numpy arrays (and other non-GC-tracked types)

Nobody has claimed this yet.

See this code:

``` python
import objgraph
import numpy as np
objgraph.show_growth()
j = 20
y = []
for i in range(5):
for l in range(j):
y.append(np.array([np.random.randint(500),np.random.randint(500)]))
print 'i:',i
objgraph.show_growth()
print '___'
#objgraph.show_most_common_types(limit=100)
j += 1
```

the result is:

```
function 2973 +2973
wrapper_descriptor 1584 +1584
builtin_function_or_method 873 +873
dict 867 +867
method_descriptor 823 +823
weakref 622 +622
tuple 518 +518
getset_descriptor 514 +514
list 422 +422
member_descriptor 223 +223
i: 0
wrapper_descriptor 1593 +9
getset_descriptor 518 +4
member_descriptor 226 +3
list 424 +2
weakref 624 +2
dict 869 +2
listiterator 1 +1
___
i: 1
wrapper_descriptor 1596 +3
weakref 625 +1
dict 870 +1
method_descriptor 824 +1
___
i: 2
___
i: 3
___
i: 4
___
```

for the 2,3 and 4 epoch, it shows nothing growing. But it should show that the number of numpy.array grows

Start by running the Python reproduction in the issue and inspect the objgraph.show_growth() entry point. Compare how it counts ordinary objects with how NumPy arrays and other non-GC-tracked types are handled. Done means repeated array allocations appear as growth in the reported output without breaking existing object counts.

Written by the indexing model from the issue text.