attributes not pickled in subclasses of numpy.ndarrays about dill HOT 9 CLOSED

dude@hilbert>$ python numpy_new.py 
{'color': 'green'}
B2: <built-in function _reconstruct>
T2: <class '__main__.TestArray'>
F2: <function _create_type at 0x110c24140>
T1: <type 'type'>
F2: <function _load_type at 0x110c240c8>
T4: <type 'numpy.ndarray'>
D2: <dict object at 0x7fc0490132d0>
T4: <type 'staticmethod'>
F1: <function __getnewargs__ at 0x110c65cf8>
F2: <function _create_function at 0x110c241b8>
Co: <code object __getnewargs__ at 0x1102deb30, file "numpy_new.py", line 16>
F2: <function _unmarshal at 0x110c24050>
D1: <dict object at 0x7fc04841b850>
D2: <dict object at 0x7fc049009b60>
F1: <function __array_finalize__ at 0x110c65c80>
Co: <code object __array_finalize__ at 0x1102de8b0, file "numpy_new.py", line 10>
D1: <dict object at 0x7fc04841b850>
D2: <dict object at 0x7fc049008490>
T4: <type 'numpy.dtype'>
{}
B2: <built-in function _reconstruct>
T5: <class '__main__.TestArray'>
T4: <type 'numpy.dtype'>
{}
{'color': 'green'}
B2: <built-in function _reconstruct>
T2: <class '__main__.TestArray'>
F2: <function _create_type at 0x110c24140>
T1: <type 'type'>
F2: <function _load_type at 0x110c240c8>
T4: <type 'numpy.ndarray'>
D2: <dict object at 0x7fc049007d90>
T4: <type 'staticmethod'>
F1: <function __getnewargs__ at 0x110c65cf8>
F2: <function _create_function at 0x110c241b8>
Co: <code object __getnewargs__ at 0x1102deb30, file "numpy_new.py", line 16>
F2: <function _unmarshal at 0x110c24050>
D1: <dict object at 0x7fc04841b850>
D2: <dict object at 0x7fc049009b60>
F1: <function __array_finalize__ at 0x110c65c80>
Co: <code object __array_finalize__ at 0x1102de8b0, file "numpy_new.py", line 10>
D1: <dict object at 0x7fc04841b850>
D2: <dict object at 0x7fc049008490>
T4: <type 'numpy.dtype'>
{}
B2: <built-in function _reconstruct>
T5: <class '__main__.TestArray'>
T4: <type 'numpy.dtype'>
{}

import numpy as np
import dill

class TestArray2(np.ndarray):
    color = 'blue'
    pass

a3 = TestArray2([1,2,3,4,5])
a3.color = 'green'
print(a3.__dict__)
print(dill.copy(a3).__dict__)
print(dill.copy(a3, byref=True).__dict__)
dill.detect.trace(False)

{'color': 'green'}
B2: <built-in function _reconstruct>
T2: <class '__main__.TestArray2'>
F2: <function _create_type at 0x110803140>
T1: <type 'type'>
F2: <function _load_type at 0x1108030c8>
T4: <type 'numpy.ndarray'>
D2: <dict object at 0x7f99bc011870>
T4: <type 'numpy.dtype'>
{}
B2: <built-in function _reconstruct>
T5: <class '__main__.TestArray2'>
T4: <type 'numpy.dtype'>
{}

>>> b = TestArray2([1,2,3])
>>> b.color = 'red'
>>> 
>>> _b = dill.copy(b)
B2: <built-in function _reconstruct>
T4: <class 'numpy_new.TestArray2'>
T4: <type 'numpy.dtype'>
>>> _b.color
'green'
>>> _b.__dict__
{}
>>> b.__dict__
{'color': 'red'}

>>> n = np.array([1,2,3])
>>> recon, initargs, state = n.__reduce__()
>>> m = np.core.multiarray._reconstruct(*initargs)
>>> m.__setstate__(state)
>>> m
array([1, 2, 3])

>>> initargs  
(<type 'numpy.ndarray'>, (0,), 'b')

>>> t = TestArray([1,2,3], color='green')
>>> recon, initargs, state = t.__reduce__()
>>> initargs
(<class 'numpy_new.TestArray'>, (0,), 'b')
>>> d = t.__dict__.copy()
>>> m = np.core.multiarray._reconstruct(*initargs)
>>> m.__setstate__(state)
>>> m.__dict__.update(d)
>>> 
>>> m
TestArray([1, 2, 3])
>>> m.color
'green'