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‎.gitignore

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*.jl.cov
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*.jl.*.cov
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*.jl.mem
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docs/build

‎README.md

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# TupleTools.jl
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[![Build Status](https://travis-ci.org/Jutho/TupleTools.jl.svg?branch=master)](https://travis-ci.org/Jutho/TupleTools.jl)
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[![License](http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat)](LICENSE.md)
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[![Coverage Status](https://coveralls.io/repos/Jutho/TupleTools.jl/badge.svg?branch=master&service=github)](https://coveralls.io/github/Jutho/TupleTools.jl?branch=master)
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[![codecov.io](http://codecov.io/github/Jutho/TupleTools.jl/coverage.svg?branch=master)](http://codecov.io/github/Jutho/TupleTools.jl?branch=master)
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[![Build Status](https://travis-ci.org/Jutho/TupleTools.jl.svg?branch=master)](https://travis-ci.org/Jutho/TupleTools.jl) [![License](http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat)](LICENSE.md) [![Coverage Status](https://coveralls.io/repos/Jutho/TupleTools.jl/badge.svg?branch=master&service=github)](https://coveralls.io/github/Jutho/TupleTools.jl?branch=master) [![codecov.io](http://codecov.io/github/Jutho/TupleTools.jl/coverage.svg?branch=master)](http://codecov.io/github/Jutho/TupleTools.jl?branch=master)
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A bunch of tools for using tuples (mostly homogeneous tuples `NTuple{N}`) as a collection and performing a number of operations with an inferrable result, typically also an `NTuple{M}` with inferrable length `M`. Type inference breaks down if some of the final or intermediate tuples exceed `MAX_TUPLETYPE_LEN`, meaning inference typically works up to output tuples of length `13` or `14`. Inference also breaks down for most methods in case of inhomogeneous tuples.
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A bunch of tools for using tuples (mostly homogeneous tuples `NTuple{N}`) as a collection and performing a number of operations with an inferrable result, typically also an `NTuple{M}` with inferrable length `M`. Type inference breaks down if some of the final or intermediate tuples exceed `MAX_TUPLETYPE_LEN`, meaning inference typically works up to output tuples of length `13` or `14`. Chosen implementations are typically faster than the corresponding functions in base for those small tuple lengths, but can be slower for larger tuples. Inference also breaks down for most functions in case of inhomogeneous tuples.
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<a id='Types-1'></a>
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Get the indices `t[i] for i in I`, again as tuple.
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<a id='TupleTools.deleteat' href='#TupleTools.deleteat'>#</a>
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**`TupleTools.deleteat`** &mdash; *Function*.
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```
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deleteat(t::Tuple, i::Int) -> ::Tuple
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deleteat(t::Tuple, I::Tuple{Vararg{Int}}) -> ::Tuple
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```
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Delete the element at location `i` in `t`; if a list `I` of indices is specified (again as a tuple), the elements of these different positions are deleted.
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<a id='TupleTools.insertat' href='#TupleTools.insertat'>#</a>
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**`TupleTools.insertat`** &mdash; *Function*.
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```
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insertat(t::Tuple, i::Int, t2::Tuple) -> ::Tuple
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```
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Insert the elements of tuple t2 at location `i` in `t`, i.e. the output tuple will look as (t[1:i-1]..., t2..., t[i+1:end]). Note that element `t[i]` is deleted. Use `setindex` for setting a single value at position `i`.
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<a id='TupleTools.vcat' href='#TupleTools.vcat'>#</a>
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**`TupleTools.vcat`** &mdash; *Function*.
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Like `vcat` for tuples, concatenates a combination of tuple arguments and non-tuple arguments into a single tuple. Only works one level deep, i.e. tuples in tuples are not expanded.
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<a id='TupleTools.deleteat' href='#TupleTools.deleteat'>#</a>
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**`TupleTools.deleteat`** &mdash; *Function*.
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<a id='TupleTools.sum' href='#TupleTools.sum'>#</a>
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**`TupleTools.sum`** &mdash; *Function*.
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```
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deleteat(t::Tuple, i::Int) -> ::Tuple
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deleteat(t::Tuple, I::Tuple{Vararg{Int}}) -> ::Tuple
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sum(t::Tuple)
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```
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Delete the element at location `i` in `t`; if a list `I` of indices is specified (again as a tuple), the elements of these different positions are deleted.
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Returns the sum of the element of a tuple, or `0` for an empty tuple.
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<a id='TupleTools.insertat' href='#TupleTools.insertat'>#</a>
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**`TupleTools.insertat`** &mdash; *Function*.
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<a id='TupleTools.prod' href='#TupleTools.prod'>#</a>
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**`TupleTools.prod`** &mdash; *Function*.
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```
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insertat(t::Tuple, i::Int, t2::Tuple) -> ::Tuple
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prod(t::Tuple)
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```
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Insert the elements of tuple t2 at location `i` in `t`, i.e. the output tuple will look as (t[1:i-1]..., t2..., t[i+1:end]). Note that element `t[i]` is deleted. See `splice` if you would also like to return `t[i]`
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Returns the product of the elements of a tuple, or `1` for an empty tuple.
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```
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TupleTools.minimum
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TupleTools.maximum
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TupleTools.findmin
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TupleTools.findmax
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TupleTools.indmin
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TupleTools.indmax
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```
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<a id='TupleTools.sort' href='#TupleTools.sort'>#</a>
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**`TupleTools.sort`** &mdash; *Function*.

‎docs/src/index.md

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and performing a number of operations with an inferrable result, typically also an `NTuple{M}`
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with inferrable length `M`. Type inference breaks down if some of the final or intermediate tuples
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exceed `MAX_TUPLETYPE_LEN`, meaning inference typically works up to output tuples of
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length `13` or `14`. Inference also breaks down for most methods in case of inhomogeneous tuples.
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length `13` or `14`. Chosen implementations are typically faster than the corresponding functions
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in base for those small tuple lengths, but can be slower for larger tuples. Inference also breaks
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down for most functions in case of inhomogeneous tuples.
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Note that none of the following functions are exported, since their name often collides with the equivalent from `Base`.
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## Types
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```@docs
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TupleTools.getindices
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TupleTools.vcat
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```
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```@docs
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TupleTools.deleteat
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TupleTools.insertat
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TupleTools.vcat
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```
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```@docs
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TupleTools.sum
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TupleTools.prod
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```
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```@docs
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TupleTools.minimum
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TupleTools.maximum
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TupleTools.findmin
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TupleTools.findmax
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TupleTools.indmin
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TupleTools.indmax
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```
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```@docs

‎src/TupleTools.jl

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"""
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indmin(t::Tuple) = findmin(t)[2]
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"""
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indmax(t::Tuple)
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Returns the index of the maximum element in a tuple. If there are multiple
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minimal elements, then the first one will be returned.
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"""
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indmax(t::Tuple) = findmax(t)[2]
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"""
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Returns the value and index of the maximum element in a tuple. If there are multiple
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"""
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indmax(t::Tuple) = findmax(t)[2]
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findmax(::Tuple{Any}) = 1
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findmax(t::Tuple) = _findmax(tail(t),2,t[1],1)
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@inline _findmax(t::Tuple{}, s, v, i) = (v, i)

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