numpy.s_ — NumPy v2.2 Manual (original) (raw)

numpy.s_ = <numpy.lib._index_tricks_impl.IndexExpression object>#

A nicer way to build up index tuples for arrays.

Note

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.

Parameters:

maketuplebool

If True, always returns a tuple.

See also

s_

Predefined instance without tuple conversion: s_ = IndexExpression(maketuple=False). The index_exp is another predefined instance that always returns a tuple: index_exp = IndexExpression(maketuple=True).

Notes

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.

Examples

import numpy as np 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])