From e499e2b6010ffd66bc4e135b112b092158702969 Mon Sep 17 00:00:00 2001 From: Gabriel Dinner-David <82682503+gabydd@users.noreply.github.com> Date: Fri, 4 Aug 2023 02:23:01 -0400 Subject: [PATCH] small spelling and grammar fixes (#1) --- README.md | 25 ++++++++++++------------- 1 file changed, 12 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index c4df64a..a6baa09 100644 --- a/README.md +++ b/README.md @@ -2,21 +2,21 @@ `nucleo` is a highly performant fuzzy matcher written in rust. It aims to fill the same use case as `fzf` and `skim`. Compared to `fzf` `nucleo` has a significantly faster matching algorithm. This mainly makes a difference when matching patterns with low selectivity on many items. An (unscientific) comparison is shown in the benchmark section below. -Nucleo uses the exact **same scoring system as fzf**. That means you should get the same ranking quality (or better) as you are used to from fzf. However, `nucleo` has a more faithful implementation of the Smith-Waterman algorithm which is normally used in DNA sequence alignment (see https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/gaps.pdf) with two separate matrices (instead of one like fzf). This means that `nucleo` finds the optimal match more often. For example if you match `foo` in `xf foo` `nucleo` will match `x__foo` but `fzf` will match `xf_oo` (you can increase the word length the result will stay the same).The former is the more intuitive match and has a higher score according to the ranking system that both `nucleo` and fzf. +Nucleo uses the exact **same scoring system as fzf**. That means you should get the same ranking quality (or better) as you are used to from fzf. However, `nucleo` has a more faithful implementation of the Smith-Waterman algorithm which is normally used in DNA sequence alignment (see https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/gaps.pdf) with two separate matrices (instead of one like fzf). This means that `nucleo` finds the optimal match more often. For example if you match `foo` in `xf foo` `nucleo` will match `x__foo` but `fzf` will match `xf_oo` (you can increase the word length the result will stay the same). The former is the more intuitive match and has a higher score according to the ranking system that both `nucleo` and fzf. **Compared to `skim`** (and the `fuzzy-matcher` crate) `nucleo` has an even larger performance advantage and is often around **six times faster** (see benchmarks below). Furthermore, the bonus system used by nucleo and fzf is (in my opinion)more consistent/superior. `nulceo` also handles non-ascii text much better. (`skim`s bonus system and even case insensitivity only work for ASCII). -Nucleo also handles Unicode graphemes more correctly. `Fzf` and `skim` both operate on Unicode code points (chars). That means that multi codepoint graphemes can have weird effects (match multiple times, weirdly change the score, ..). `nucleo` will always use the first codepoint of the grapheme for matching instead (and reports grapheme indices, so they can be highlighted correctly). +Nucleo also handles Unicode graphemes more correctly. `Fzf` and `skim` both operate on Unicode code points (chars). That means that multi codepoint graphemes can have weird effects (match multiple times, weirdly change the score, ...). `nucleo` will always use the first codepoint of the grapheme for matching instead (and reports grapheme indices, so they can be highlighted correctly). ## Benchmarks > WIP currently more of a demonstration than a comprehensive benchmark suit -> most notably scientific comparisons with `fzf` are missing (a pain because it can't be called as a library +> most notably scientific comparisons with `fzf` are missing (a pain because it can't be called as a library) ### Matcher micro benchmarks -Benchmark comparing the runtime of various pattterns mathec against all files in the source thee of the linux kernel. Repeat on your system with `BENCHMARK_DIR= cargo run -p benches --release` (you can specify an empty directory and the kernel is cloned automatically). +Benchmark comparing the runtime of various patterns matched against all files in the source of the linux kernel. Repeat on your system with `BENCHMARK_DIR= cargo run -p benches --release` (you can specify an empty directory and the kernel is cloned automatically). Method | Mean | Samples -----------------------|-----------|----------- @@ -51,9 +51,9 @@ For example in the following two screencasts the pattern `///.` is pasted into ` # Naming -The name `nucleo` plays at the fact that the `Smith-Waterman` algorithm (that it's based on) war originally developed for matching DNA/RNA sequences. The elements of DNA/RNA that are matched are called *nucleotides* which was shortened to `nucleo` here. +The name `nucleo` plays on the fact that the `Smith-Waterman` algorithm (that it's based on) was originally developed for matching DNA/RNA sequences. The elements of DNA/RNA that are matched are called *nucleotides* which was shortened to `nucleo` here. -The name also indicates its close relationship with the *helix* editor (sticking with the DNA theme).# Implementation Details +The name also indicates its close relationship with the *helix* editor (sticking with the DNA theme). # Implementation Details @@ -64,17 +64,17 @@ The name also indicates its close relationship with the *helix* editor (sticking -The fuzzy matching algorithm is based on the `Smith-Waterman` (with affine gaps) as described in https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/gaps.pdf (TODO: explain). `Nulceo` faithfully implements this algorithm and therefore has two separate matrices. However, by precomputing the next `m-matrix` row we can avoid store the p-matrix at all and instead just store the value in a variable as we iterate the row. +The fuzzy matching algorithm is based on the `Smith-Waterman` (with affine gaps) as described in https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/gaps.pdf (TODO: explain). `Nulceo` faithfully implements this algorithm and therefore has two separate matrices. However, by precomputing the next `m-matrix` row we can avoid storing the p-matrix at all and instead just store the value in a variable as we iterate the row. -Nucleo also never really stores the `m-matrix` instead we only ever store the current row (which simultaneously serves as the next row). During index calculation a full matrix is however required to barcktrack which indices were actually matched. We only store two bools here (to indicates where we came from in the matrix). +Nucleo also never really stores the `m-matrix` instead we only ever store the current row (which simultaneously serves as the next row). During index calculation a full matrix is however required to backtrack which indices were actually matched. We only store two bools here (to indicate where we came from in the matrix). -By comparison `skim` stores the full p and m matrix in that case. `Fzf` always allocates a full `mn` matrix (even during matching!). +By comparison `skim` stores the full p and m matrix in that case. `fzf` always allocates a full `mn` matrix (even during matching!). -`nucleo`s' matrix only was width `n-m+1` instead of width `n`. This comes from the observation that the `p.` char requires `p-1` chars before it and `m-p` chars after it, so there are always `p-1 + m-p = m+1` chars that can never match the current char. This works especially well with only using a single row because the first relevant char is always at the same position even tough it'rs technically further to the right. This is particularly nice because we precalculate the m-matrix row. The m-matrix is computed from diagonal elements, so the precalculated values stay in the same matrix cell. +`nucleo`s' matrix is only width `n-m+1` instead of width `n`. This comes from the observation that the `p` char requires `p-1` chars before it and `m-p` chars after it, so there are always `p-1 + m-p = m+1` chars that can never match the current char. This works especially well with only using a single row because the first relevant char is always at the same position even though it's technically further to the right. This is particularly nice because we precalculate the m-matrix row. The m-matrix is computed from diagonal elements, so the precalculated values stay in the same matrix cell. Compared to `skim` nucleo does couple simpler (but arguably even more impactful) optimizations: * *Presegment Unicode*: Unicode segmentation is somewhat slow and matcher will filter the same elements quite often so only doing it once is nice. It also prevents a very common source of bugs (mixing of char indices which we use here and utf8 indices) and makes the code a lot simpler as a result. Fzf does the same. -* *Aggressive prefiltering*: Especially for ASCII this works very well but we also do this for Unicode to a lesser extend. This ensures we reject non-matching haystacks as fast as possible. Usually most haystacks will not match when fuzzy matching large lists so having fast path for that case is a huge win. +* *Aggressive prefiltering*: Especially for ASCII this works very well, but we also do this for Unicode to a lesser extent. This ensures we reject non-matching haystacks as fast as possible. Usually most haystacks will not match when fuzzy matching large lists so having fast path for that case is a huge win. * *Special-case ASCII*: 90% of practical text is ASCII. ASCII can be stored as bytes instead of `chars`, so cache locality is improved a lot, and we can use `memchar` for superfast prefilters (even case-insensitive prefilter are possible that way) * *Fallback for very long matches*: We fall back to greedy matcher which runs in `O(N)` (and `O(1)` space complexity) to avoid the `O(mn)` blowup for large matches. This is fzfs old algorithm and yields decent (but not great) results. @@ -90,8 +90,7 @@ Compared to `skim` nucleo does couple simpler (but arguably even more impactful) - - +