- jax.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 index_exp or s_ rather than directly using IndexExpression.
For any index combination, including slicing and axis insertion,
a[indices]is the same as
a[np.index_exp[indices]]for any array a. However,
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.
maketuple (bool) – If True, always returns a tuple.
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])