Hackage :: [Package]

vector-sized: Size tagged vectors

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Versions [RSS] 0.1.0.0, 0.2.0.0, 0.3.0.0, 0.3.2.0, 0.3.3.0, 0.4.0.0, 0.4.0.1, 0.4.1.0, 0.5.0.0, 0.5.1.0, 0.6.1.0, 1.0.0.0, 1.0.1.0, 1.0.2.0, 1.0.3.0, 1.0.3.1, 1.0.4.0, 1.1.0.0, 1.1.1.0, 1.2.0.0, 1.2.0.1, 1.4.0.0, 1.4.1.0, 1.4.2, 1.4.3, 1.4.3.1, 1.4.4, 1.5.0, 1.6.1 (info)
Change log changelog.md
Dependencies adjunctions (>=4.3 && <4.5), base (>=4.9 && <5), binary (>=0.8.3.0), comonad (>=4 && <6), deepseq (>=1.1 && <1.5), distributive (>=0.5 && <0.7), finite-typelits (>=0.1), hashable (>=1.2.4.0), indexed-list-literals (>=0.2.0.0), primitive (>=0.5 && <0.8), vector (>=0.11 && <0.13) [details]
License BSD-3-Clause
Copyright 2016 Joe Hermaszewski
Author Joe Hermaszewski
Maintainer whats.our.vector.victor@monoid.al
Category Data
Home page https://github.com/expipiplus1/vector-sized#readme
Bug tracker https://github.com/expipiplus1/vector-sized/issues
Source repo head: git clone https://github.com/expipiplus1/vector-sized
Uploaded by jophish at 2020-12-15T08:08:23Z
Distributions Arch:1.6.1, LTSHaskell:1.6.1, NixOS:1.5.0, Stackage:1.6.1
Reverse Dependencies 28 direct, 57 indirect [details]
Downloads 25335 total (101 in the last 30 days)
Rating 2.25 (votes: 2) [estimated by Bayesian average]
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Readme for vector-sized-1.4.3.1

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vector-sized Hackage

This package exports a newtype tagging the vectors from the vector package with a type-level natural representing their size. It also exports functions from vector whose size can be determined ahead of time, appropriately retyped.

Currently, we provide size-tagged versions of the following:

We also provide mutable versions of each of the above. Additionally, we include functions for converting to and from 'unsized' vectors and lists, using CPS-style existentials.

The code in this package is based on the initial work by Ben Gamari in a PR for vulkan.

How is this different to fixed-vector?

This package is fairly similar to fixed-vector, as both libraries are designed to provide vectors of statically known length. However, the implementations used are different, with different tradeoffs. vector-sized uses a newtype wrapper around vectors from vector, and is thus able to handle vectors of arbitrary length. However, this approach requires us to carry a runtime representation of length, which is a significant memory overhead for small vectors. fixed-vector instead defines all functions as manipulations of Church-encoded product types of the form ∀r. (a → a → r) → r (for 2D vectors), allowing it to work for both arbitrary product types (like data V2 a = V2 a a) and opaque length-parameterized vectors. However, as a consequence of this implementation choice, fixed-vector cannot handle vectors whose size exceeds tens of elements.