Use one of the two predefined instances :None:None:`index_exp` or :None:None:`s_` rather than directly using :None:None:`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.
You can do all this with :None:None:`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.
If True, always returns a tuple.
A nicer way to build up index tuples for arrays.
index_exp
Predefined instance that always returns a tuple: :None:None:`index_exp = IndexExpression(maketuple=True)`.
s_
Predefined instance without tuple conversion: :None:None:`s_ = IndexExpression(maketuple=False)`.
>>> 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])See :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.routines.delete
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