NumPy chained comparison with two predicates

In NumPy, I can generate a boolean array like this:

>>> arr = np.array([1, 2, 1, 2, 3, 6, 9])
>>> arr > 2
array([False, False, False, False,  True,  True,  True], dtype=bool)

How can we chain comparisons together? For example:

>>> 6 > arr > 2
array([False, False, False, False,  True,  False,  False], dtype=bool)

Attempting to do so results in the error message

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

AFAIK the closest you can get is to use &, |, and ^:

>>> arr = np.array([1, 2, 1, 2, 3, 6, 9])
>>> (2 < arr) & (arr < 6)
array([False, False, False, False,  True, False, False], dtype=bool)
>>> (2 < arr) | (arr < 6)
array([ True,  True,  True,  True,  True,  True,  True], dtype=bool)
>>> (2 < arr) ^ (arr < 6)
array([ True,  True,  True,  True, False,  True,  True], dtype=bool)

I don't think you'll be able to get a < b < c-style chaining to work.

You can use the numpy logical operators to do something similar.

>>> arr = np.array([1, 2, 1, 2, 3, 6, 9])
>>> arr > 2
array([False, False, False, False,  True,  True,  True], dtype=bool)
>>>np.logical_and(arr>2,arr<6)
Out[5]: array([False, False, False, False,  True, False, False], dtype=bool)