numpy.s_ = <numpy.lib.index_tricks.IndexExpression object>
A nicer way to build up index tuples for arrays.
Use one of the two predefined instances
s_ rather than directly using
For any index combination, including slicing and axis insertion,
a[indices] is the same as
a[np.index_exp[indices]] for any array
np.index_exp[indices] can be used anywhere in Python code and returns a tuple of slice objects that can be used in the construction of complex index expressions.
index_exp = IndexExpression(maketuple=True).
s_ = IndexExpression(maketuple=False).
You can do all this with
slice() plus a few special objects, but there’s a lot to remember and this version is simpler because it uses the standard array indexing syntax.
>>> np.s_[2::2] slice(2, None, 2) >>> np.index_exp[2::2] (slice(2, None, 2),)
>>> np.array([0, 1, 2, 3, 4])[np.s_[2::2]] array([2, 4])
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