https://github.com/simonster/piecewiseincreasingranges.jl

A piecewise increasing range type suitable for potentially discontinuous timestamps of sampled data
https://github.com/simonster/piecewiseincreasingranges.jl

Last synced: about 1 month ago
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A piecewise increasing range type suitable for potentially discontinuous timestamps of sampled data

• Host: GitHub
• URL: https://github.com/simonster/piecewiseincreasingranges.jl
• Owner: simonster
• License: other
• Created: 2015-04-23T00:12:02.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2020-02-19T19:02:37.000Z (almost 5 years ago)
• Last Synced: 2024-11-12T21:29:24.502Z (about 1 month ago)
• Language: Julia
• Size: 16.6 KB
• Stars: 5
• Watchers: 3
• Forks: 4
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# PiecewiseIncreasingRanges

[![Build Status](https://travis-ci.org/simonster/PiecewiseIncreasingRanges.jl.svg?branch=master)](https://travis-ci.org/simonster/PiecewiseIncreasingRanges.jl)

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PiecewiseIncreasingRanges.jl provides a PiecewiseIncreasingRange type that corresponds to a set of concatenated, monotonically increasing ranges. It implements indexing as well as `searchsortedfirst`, `searchsortedlast`, and a `findnearest` function. This type is useful for holding the potentially discontinuous timestamps corresponding to large quantities of sampled data, where creating and indexing a vector would be undesirably slow.

## Construction

You can construct a PiecewiseIncreasingRange as below:

```julia

julia> PiecewiseIncreasingRange(StepRange{Int,Int}[0:5:15, 18:2:20])

6-element PiecewiseIncreasingRanges.PiecewiseIncreasingRange{Int64,StepRange{Int64,Int64},Void}:

  0

  5

 10

 15

 18

 20

```

PiecewiseIncreasingRanges also accept an optional divisor, which is divided out of all elements:

```julia

julia> PiecewiseIncreasingRange(UnitRange{Int}[0:3, 15:16], 4)

6-element PiecewiseIncreasingRanges.PiecewiseIncreasingRange{Float64,UnitRange{Int64},Int64}:

 0.0 

 0.25

 0.5 

 0.75

 3.75

 4.0

```

## findnearest

`findnearest(rg, x, within_half_sample)` finds the index of the element of `rg` closest to `x`. If `x` is equidistant between two samples, it chooses the earlier one. If `within_half_sample` is true, `findnearest` throws a `NoNearestSampleError` if there is no sample within half of a step of `x`.