diff --git a/dev/index.html b/dev/index.html index 053c4d1..7f58877 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -Home · IntervalTrees.jl
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IntervalTrees

Latest Release MIT License Stable documentation Lifecycle

Description

IntervalTrees provides the type: IntervalTree{K, V}. It implements an associative container mapping (K, K) pairs to to values of type V. K may be any ordered type, but only pairs (a, b) where a ≤ b can be stored. In other words they are associative contains that map intervals to values.

Installation

You can install the IntervalTrees package from the Julia REPL. Press ] to enter pkg mode, then enter the following command:

add IntervalTrees

If you are interested in the cutting edge of the development, please check out the master branch to try new features before release.

Testing

IntervalTrees is tested against Julia 0.7-1.X on Linux, OS X, and Windows.

Latest build status:

Unit tests Documentation codecov

Contributing

We appreciate contributions from users including reporting bugs, fixing issues, improving performance and adding new features.

Take a look at the contributing files detailed contributor and maintainer guidelines, and code of conduct.

Financial contributions

We also welcome financial contributions in full transparency on our open collective. Anyone can file an expense. If the expense makes sense for the development of the community, it will be "merged" in the ledger of our open collective by the core contributors and the person who filed the expense will be reimbursed.

Backers & Sponsors

Thank you to all our backers and sponsors!

Love our work and community? Become a backer.

backers

Does your company use BioJulia? Help keep BioJulia feature rich and healthy by sponsoring the project Your logo will show up here with a link to your website.

Questions?

If you have a question about contributing or using BioJulia software, come on over and chat to us on the Julia Slack workspace, or you can try the Bio category of the Julia discourse site.

+Home · IntervalTrees.jl
Edit on GitHub

IntervalTrees

Latest Release MIT License Stable documentation Lifecycle

Description

IntervalTrees provides the type: IntervalTree{K, V}. It implements an associative container mapping (K, K) pairs to to values of type V. K may be any ordered type, but only pairs (a, b) where a ≤ b can be stored. In other words they are associative contains that map intervals to values.

Installation

You can install the IntervalTrees package from the Julia REPL. Press ] to enter pkg mode, then enter the following command:

add IntervalTrees

If you are interested in the cutting edge of the development, please check out the master branch to try new features before release.

Testing

IntervalTrees is tested against Julia 0.7-1.X on Linux, OS X, and Windows.

Latest build status:

Unit Tests Documentation codecov

Contributing

We appreciate contributions from users including reporting bugs, fixing issues, improving performance and adding new features.

Take a look at the contributing files detailed contributor and maintainer guidelines, and code of conduct.

Financial contributions

We also welcome financial contributions in full transparency on our open collective. Anyone can file an expense. If the expense makes sense for the development of the community, it will be "merged" in the ledger of our open collective by the core contributors and the person who filed the expense will be reimbursed.

Backers & Sponsors

Thank you to all our backers and sponsors!

Love our work and community? Become a backer.

backers

Does your company use BioJulia? Help keep BioJulia feature rich and healthy by sponsoring the project Your logo will show up here with a link to your website.

Questions?

If you have a question about contributing or using BioJulia software, come on over and chat to us on the Julia Slack workspace, or you can try the Bio category of the Julia discourse site.

diff --git a/dev/man/dict/index.html b/dev/man/dict/index.html index aabbf0e..b8c26f1 100644 --- a/dev/man/dict/index.html +++ b/dev/man/dict/index.html @@ -20,4 +20,4 @@ # Delete values delete!(xs, (1,100)) - + diff --git a/dev/man/insertion/index.html b/dev/man/insertion/index.html index 44e9456..2895ae9 100644 --- a/dev/man/insertion/index.html +++ b/dev/man/insertion/index.html @@ -4,4 +4,4 @@ # construct a large array of intervals... sort!(intervals) -xs = IntervalTree{Int, Interval{Int}}(intervals) +xs = IntervalTree{Int, Interval{Int}}(intervals) diff --git a/dev/man/intersection/index.html b/dev/man/intersection/index.html index d5437c5..0a280fa 100644 --- a/dev/man/intersection/index.html +++ b/dev/man/intersection/index.html @@ -1,2 +1,2 @@ -Intersection · IntervalTrees.jl
Edit on GitHub

Intersection

The primary thing an IntervalTree offers over a Dict is the ability to efficiently find intersections. IntervalTrees supports searching and iterating over intersections between two trees or between a tree and a single interval.

intersect(t::IntervalTree, query::(Any, Any)): Return an iterator over every interval in t that intersects query.

intersect(t1::IntervalTree, t2::IntervalTree): Return an iterator over every pair of intersecting entries (interval1, interval2), where interval1 is in t1 and interval2 is in t2.

hasintersection(t::IntervalTree, position): Return true if position intersects some interval in t.

+Intersection · IntervalTrees.jl
Edit on GitHub

Intersection

The primary thing an IntervalTree offers over a Dict is the ability to efficiently find intersections. IntervalTrees supports searching and iterating over intersections between two trees or between a tree and a single interval.

intersect(t::IntervalTree, query::(Any, Any)): Return an iterator over every interval in t that intersects query.

intersect(t1::IntervalTree, t2::IntervalTree): Return an iterator over every pair of intersecting entries (interval1, interval2), where interval1 is in t1 and interval2 is in t2.

hasintersection(t::IntervalTree, position): Return true if position intersects some interval in t.

diff --git a/dev/man/iteration/index.html b/dev/man/iteration/index.html index 6d66365..e0cc2d2 100644 --- a/dev/man/iteration/index.html +++ b/dev/man/iteration/index.html @@ -1,4 +1,4 @@ Iterating over intervals · IntervalTrees.jl
Edit on GitHub

Iteration

As with dictionaries, key/value pairs can be iterated through efficiently.

    for x in xs
         println("Interval $(x.first), $(x.last) has value $(x.value)")
-    end

Some other iteration functions are provided:

from(t::IntervalTree, query): Return an iterator thats iterates through every key/value pair with an end position >= to query.

keys(t::IntervalTree): Return an iterator that iterates through every interval key in the tree.

values(t::IntervalTree): Return an iterator that iterates through every value in the tree.

+ end

Some other iteration functions are provided:

from(t::IntervalTree, query): Return an iterator thats iterates through every key/value pair with an end position >= to query.

keys(t::IntervalTree): Return an iterator that iterates through every interval key in the tree.

values(t::IntervalTree): Return an iterator that iterates through every value in the tree.

diff --git a/dev/man/types/index.html b/dev/man/types/index.html index 6749d6b..6fe0e1a 100644 --- a/dev/man/types/index.html +++ b/dev/man/types/index.html @@ -1,2 +1,2 @@ -Types · IntervalTrees.jl
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Intervals & IntervalTrees

IntervalTrees exports an abstract type AbstractInterval{K}, in addition to two basic concrete interval types.

IntervalTrees.AbstractInterval — Type

Types deriving from AbstractInterval{T} must have a first and last function each returning a value of type T, and first(i) <= last(i) must always be true.

source

Intervals in this package are always treated as end-inclusive, similar to the Julia Range type.

IntervalTrees

The basic data structure implemented in this package is IntervalTree{K, V}, which stores intervals of type V, that have start and end positions of type K.

IntervalMap{K, V} is a typealias for IntervalTree{K, IntervalValue{K, V}} to simplify associating data of type V with intervals.

Multiple data structures are refered to as "interval trees". What's implemented here is the data structure described in the Cormen, et al. "Algorithms" book, or what's refered to as an augmented tree in the wikipedia article. This sort of data structure is just an balanced search tree augmented with a field to keep track of the maximum interval end point in that node's subtree.

Many operations over two or more sets of intervals can be most efficiently implemented by jointly iterating over the sets in order. For example, finding all the intersecting intervals in two sets S and T can be implemented similarly to the merge function in mergesort in O(n+m) time.

Thus a general purpose data structure should be optimized for fast in-order iteration while efficiently supporting other operations like insertion, deletion, and single intersection tests. A B+-tree is nicely suited to the task. Since all the intervals and values are stored in contiguous memory in the leaf nodes, and the leaf nodes augmented with sibling pointers, in-order traversal is exceedingly efficient compared to other balanced search trees, while other operations are comparable in performance.

+Types · IntervalTrees.jl
Edit on GitHub

Intervals & IntervalTrees

IntervalTrees exports an abstract type AbstractInterval{K}, in addition to two basic concrete interval types.

IntervalTrees.AbstractInterval — Type

Types deriving from AbstractInterval{T} must have a first and last function each returning a value of type T, and first(i) <= last(i) must always be true.

source

Intervals in this package are always treated as end-inclusive, similar to the Julia Range type.

IntervalTrees

The basic data structure implemented in this package is IntervalTree{K, V}, which stores intervals of type V, that have start and end positions of type K.

IntervalMap{K, V} is a typealias for IntervalTree{K, IntervalValue{K, V}} to simplify associating data of type V with intervals.

Multiple data structures are refered to as "interval trees". What's implemented here is the data structure described in the Cormen, et al. "Algorithms" book, or what's refered to as an augmented tree in the wikipedia article. This sort of data structure is just an balanced search tree augmented with a field to keep track of the maximum interval end point in that node's subtree.

Many operations over two or more sets of intervals can be most efficiently implemented by jointly iterating over the sets in order. For example, finding all the intersecting intervals in two sets S and T can be implemented similarly to the merge function in mergesort in O(n+m) time.

Thus a general purpose data structure should be optimized for fast in-order iteration while efficiently supporting other operations like insertion, deletion, and single intersection tests. A B+-tree is nicely suited to the task. Since all the intervals and values are stored in contiguous memory in the leaf nodes, and the leaf nodes augmented with sibling pointers, in-order traversal is exceedingly efficient compared to other balanced search trees, while other operations are comparable in performance.

diff --git a/dev/search/index.html b/dev/search/index.html index eeb59d8..a055ec5 100644 --- a/dev/search/index.html +++ b/dev/search/index.html @@ -1,2 +1,2 @@ -Search · IntervalTrees.jl

Loading search...

    +Search · IntervalTrees.jl

    Loading search...

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Press ] to enter pkg mode, then enter the following command:","category":"page"},{"location":"","page":"Home","title":"Home","text":"add IntervalTrees","category":"page"},{"location":"","page":"Home","title":"Home","text":"If you are interested in the cutting edge of the development, please check out the master branch to try new features before release.","category":"page"},{"location":"#Testing","page":"Home","title":"Testing","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"IntervalTrees is tested against Julia 0.7-1.X on Linux, OS X, and Windows.","category":"page"},{"location":"","page":"Home","title":"Home","text":"Latest build status:","category":"page"},{"location":"","page":"Home","title":"Home","text":"(Image: Unit Tests) (Image: Documentation) (Image: codecov)","category":"page"},{"location":"#Contributing","page":"Home","title":"Contributing","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"We appreciate contributions from users including reporting bugs, fixing issues, improving performance and adding new features.","category":"page"},{"location":"","page":"Home","title":"Home","text":"Take a look at the contributing files detailed contributor and maintainer guidelines, and code of conduct.","category":"page"},{"location":"#Financial-contributions","page":"Home","title":"Financial contributions","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"We also welcome financial contributions in full transparency on our open collective. Anyone can file an expense. If the expense makes sense for the development of the community, it will be \"merged\" in the ledger of our open collective by the core contributors and the person who filed the expense will be reimbursed.","category":"page"},{"location":"#Backers-and-Sponsors","page":"Home","title":"Backers & Sponsors","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"Thank you to all our backers and sponsors!","category":"page"},{"location":"","page":"Home","title":"Home","text":"Love our work and community? Become a backer.","category":"page"},{"location":"","page":"Home","title":"Home","text":"(Image: backers)","category":"page"},{"location":"","page":"Home","title":"Home","text":"Does your company use BioJulia? Help keep BioJulia feature rich and healthy by sponsoring the project Your logo will show up here with a link to your website.","category":"page"},{"location":"","page":"Home","title":"Home","text":"(Image: ) (Image: ) (Image: ) (Image: ) (Image: ) (Image: ) (Image: ) (Image: ) (Image: ) (Image: )","category":"page"},{"location":"#Questions?","page":"Home","title":"Questions?","text":"","category":"section"},{"location":"","page":"Home","title":"Home","text":"If you have a question about contributing or using BioJulia software, come on over and chat to us on the Julia Slack workspace, or you can try the Bio category of the Julia discourse site.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"CurrentModule = IntervalTrees","category":"page"},{"location":"man/types/#Intervals-and-IntervalTrees","page":"Types","title":"Intervals & IntervalTrees","text":"","category":"section"},{"location":"man/types/","page":"Types","title":"Types","text":"IntervalTrees exports an abstract type AbstractInterval{K}, in addition to two basic concrete interval types.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"AbstractInterval\nInterval\nIntervalValue","category":"page"},{"location":"man/types/#IntervalTrees.AbstractInterval","page":"Types","title":"IntervalTrees.AbstractInterval","text":"Types deriving from AbstractInterval{T} must have a first and last function each returning a value of type T, and first(i) <= last(i) must always be true.\n\n\n\n\n\n","category":"type"},{"location":"man/types/#IntervalTrees.Interval","page":"Types","title":"IntervalTrees.Interval","text":"A basic interval.\n\n\n\n\n\n","category":"type"},{"location":"man/types/#IntervalTrees.IntervalValue","page":"Types","title":"IntervalTrees.IntervalValue","text":"An interval with some associated data.\n\n\n\n\n\n","category":"type"},{"location":"man/types/","page":"Types","title":"Types","text":"Intervals in this package are always treated as end-inclusive, similar to the Julia Range type.","category":"page"},{"location":"man/types/#IntervalTrees","page":"Types","title":"IntervalTrees","text":"","category":"section"},{"location":"man/types/","page":"Types","title":"Types","text":"The basic data structure implemented in this package is IntervalTree{K, V}, which stores intervals of type V, that have start and end positions of type K.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"IntervalMap{K, V} is a typealias for IntervalTree{K, IntervalValue{K, V}} to simplify associating data of type V with intervals.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"Multiple data structures are refered to as \"interval trees\". What's implemented here is the data structure described in the Cormen, et al. \"Algorithms\" book, or what's refered to as an augmented tree in the wikipedia article. This sort of data structure is just an balanced search tree augmented with a field to keep track of the maximum interval end point in that node's subtree.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"Many operations over two or more sets of intervals can be most efficiently implemented by jointly iterating over the sets in order. For example, finding all the intersecting intervals in two sets S and T can be implemented similarly to the merge function in mergesort in O(n+m) time.","category":"page"},{"location":"man/types/","page":"Types","title":"Types","text":"Thus a general purpose data structure should be optimized for fast in-order iteration while efficiently supporting other operations like insertion, deletion, and single intersection tests. A B+-tree is nicely suited to the task. Since all the intervals and values are stored in contiguous memory in the leaf nodes, and the leaf nodes augmented with sibling pointers, in-order traversal is exceedingly efficient compared to other balanced search trees, while other operations are comparable in performance.","category":"page"}] }