Python: What's the proper way to convert between python bool and numpy bool_?

Question

I kept getting errors with a numpy ndarray with booleans not being accepted as a mask by a pandas structure when it occured to me that I may have the 'wrong' booleans. Edit: it was not a raw numpy array but a pandas.Index.

While I was able to find a solution, the only one that worked was quite ugly:

mymask = mymask.astype(np.bool_) #ver.1 does not work, elements remain <class 'bool'>
mymask = mymask==True #ver.2, does work, elements become <class 'numpy.bool_'>
mypdstructure[mymask] 

What's the proper way to typecast the values?

Answer 1

Ok, I found the problem. My original post was not fully correct: my mask was a pandas.Index.

It seems that the pands.Index.astype is behaving unexpectedly (for me), as I get different behavior for the following:

mask = pindex.map(myfun).astype(np.bool_) # doesn't cast
mask = pindex.map(myfun).astype(np.bool_,copy=False) # doesn't cast
mask = pindex.map(myfun).values.astype(np.bool_) # does cast

Maybe it is actually a pandas bug? This result is surprising to me because I was under the impression that pandas is usually just calling the functions of the numpy arrays that it is based on. This is clearly not the case here.