#include "tensorstore/index_space/dim_expression.h"
template <int&... ExplicitArgumentBarrier>
  requires (sizeof...(Op) == 1)
auto tensorstore::DimExpression<Op...>::AddNew() const;

Adds new inert input dimensions that have no effect on the output indices.

The added dimensions have a domain of (-kInfIndex, kInfIndex), which can be reduced by chaining a call to ClosedInterval, SizedInterval, or HalfOpenInterval. The lower and upper bounds of the added dimensions are implicit. The labels of the added dimensions (if applicable) are empty.

The prior dimension selection (e.g. specified by a call to Dims on which the call to AddNew is chained) specifies the indices of the new dimensions, in the range (-input_rank - selection_rank, input_rank + selection_rank). This is unlike every other operation, for which the prior dimension selection specifies existing dimensions. The new dimension selection is equal to the prior dimension selection.

Because the prior dimension selection specifies new rather than existing dimensions, this operation cannot be chained after any other operation (but other operations may be changed after it).

For example, Dims(0, -1).AddNew() (equivalent to Dims(0, 2).AddNew()) has the following effects:

Before

After

Dimension selection

{0, 2}

{0, 2}

Input domain

[1, 5]

[-inf*, +inf*], [1, 5], [-inf*, +inf*]

Labels

{"x"}

{"", "x", ""}

Equivalent input indices

{2}

{1, 2, 8}

Equivalent input indices

{x}

{a, x, b}

where x is any index in [1, 5], a is any index, and b is any index.

Requires:

There is no prior operation in the sequence.

Requires:

The prior selected dimensions must have been specified by index, rather than by label, and must not have been specified using the AllDims() selection.