FindFirstFunctions.jl

FindFirstFunctions.jl is a library for accelerated findfirst type functions.

Installation

To install FindFirstFunctions.jl, use the Julia package manager:

using Pkg
Pkg.add("FindFirstFunctions")

Available Functions

FindFirstFunctions.findfirstequal — Function

findfirstequal(x::Int64,A::DenseVector{Int64})

Finds the first value in A equal to x

source

FindFirstFunctions.bracketstrictlymontonic — Function

bracketstrictlymontonic(v, x, guess; lt=<comparison>, by=<transform>, rev=false)

Starting from an initial guess index, find indices (lo, hi) such that v[lo] ≤ x ≤ v[hi] according to the specified order, assuming that x is actually within the range of values found in v. If x is outside that range, either lo will be firstindex(v) or hi will be lastindex(v).

Note that the results will not typically satisfy lo ≤ guess ≤ hi. If x is precisely equal to a value that is not unique in the input v, there is no guarantee that (lo, hi) will encompass all indices corresponding to that value.

This algorithm is essentially an expanding binary search, which can be used as a precursor to searchsorted and related functions, which can take lo and hi as arguments. The purpose of using this function first would be to accelerate convergence in those functions by using correlated guesses for repeated calls. The best guess for the next call of this function would be the index returned by the previous call to searchsorted.

See Base.sort! for an explanation of the keyword arguments by, lt and rev.

source

FindFirstFunctions.looks_linear — Function

looks_linear(v; threshold = 1e-2)

Determine if the abscissae v are regularly distributed, taking the standard deviation of the difference between the array of abscissae with respect to the straight line linking its first and last elements, normalized by the range of v. If this standard deviation is below the given threshold, the vector looks linear (return true). Internal function - interface may change.

source

FindFirstFunctions.Guesser — Type

Guesser(v::AbstractVector; looks_linear_threshold = 1e-2)

Wrapper of the searched vector v which makes an informed guess for searchsorted*correlated by either

Exploiting that v is sufficiently evenly spaced
Using the previous outcome of searchsorted*correlated

source

FindFirstFunctions.searchsortedfirstcorrelated — Function

searchsortedfirstcorrelated(v::AbstractVector, x, guess)

An accelerated findfirst on sorted vectors using a bracketed search. Requires a guess::Union{<:Integer, Guesser} to start the search from.

source

FindFirstFunctions.searchsortedlastcorrelated — Function

searchsortedlastcorrelated(v::AbstractVector{T}, x, guess)

An accelerated findlast on sorted vectors using a bracketed search. Requires a guess::Union{<:Integer, Guesser} to start the search from.

source

FindFirstFunctions.findfirstsortedequal — Function

findfirstsortedequal(vars::DenseVector{Int64}, var::Int64)::Union{Int64,Nothing}

Note that this differs from searchsortedfirst by returning nothing when absent.

source

Contributing

Please refer to the SciML ColPrac: Contributor's Guide on Collaborative Practices for Community Packages for guidance on PRs, issues, and other matters relating to contributing to SciML.
See the SciML Style Guide for common coding practices and other style decisions.
There are a few community forums:
- The #diffeq-bridged and #sciml-bridged channels in the Julia Slack
- The #diffeq-bridged and #sciml-bridged channels in the Julia Zulip
- On the Julia Discourse forums
- See also SciML Community page

Reproducibility

The documentation of this SciML package was built using these direct dependencies,

Status `~/work/FindFirstFunctions.jl/FindFirstFunctions.jl/docs/Project.toml`
  [82cc6244] DataInterpolations v8.3.1
  [e30172f5] Documenter v1.14.1
  [64ca27bc] FindFirstFunctions v1.4.1 `~/work/FindFirstFunctions.jl/FindFirstFunctions.jl`
  [429524aa] Optim v1.13.2
  [91a5bcdd] Plots v1.40.17
  [29dad682] RegularizationTools v0.6.0
  [860ef19b] StableRNGs v1.0.3

and using this machine and Julia version.

Julia Version 1.11.6
Commit 9615af0f269 (2025-07-09 12:58 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 7763 64-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

A more complete overview of all dependencies and their versions is also provided.

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Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

You can also download the manifest file and the project file.