Text completion: Difference between revisions

=={{header|C++}}==

{{trans|Julia}}

#include <fstream>

#include <iostream>

}

return EXIT_SUCCESS;

 

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{{Trans|Wren}}

Using '''unixdict.txt'''.

program Text_Completion;

 

end.

 

 

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{{trans|Julia}}

{{works with|Factor|0.99 2020-07-03}}

math.ranges namespaces prettyprint.config sequences splitting ;

 

dup [ similarity ] [ drop word ] [ word swap lev-dist-of ] tri

"Words at Levenshtein distance of %d (%.1f%% similarity) from %u:\n%u\n\n" printf

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<pre>

=={{header|FreeBASIC}}==

This uses '[http://wiki.puzzlers.org/pub/wordlists/unixdict.txt unixdict]' and the [https://www.rosettacode.org/wiki/Levenshtein_distance#FreeBASIC Levenshtein distance] algorithm to test for similarity.

 

Dim As String palabra = "complition"

Print

Next n

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<pre>Input word: complition

=={{header|Go}}==

{{trans|Wren}}

 

import (

fmt.Println()

}

 

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=={{header|Java}}==

[https://github.com/dwyl/english-words Github Repo Uses dependencies given].

import java.io.File;

import java.io.IOException;

}

}

;Output

<pre>

 

The "debug" statements for showing the number of words under consideration for best Levenshtein matches is retained.

include "levenshtein-distance" {search: "."}; # https://rosettacode.org/wiki/Levenshtein_distance#jq

 

 

task

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Invocation: jq -nR -f text-completion.jq unixdict.txt

=={{header|Julia}}==

See https://en.wikipedia.org/wiki/Levenshtein_distance, the number of one character edits to obtain one word from another.

 

const fname = download("https://www.mit.edu/~ecprice/wordlist.10000", "wordlist10000.txt")

levdistof(n, wrd), "\n")

end

<pre>

Words at Levenshtein distance of 1 (90% similarity) from "complition":

 

=={{header|Mathematica}}==

{word = "complition"},

Map[

SpellingCorrectionList[word]

]

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<pre>completion 90%

We use the function <code>editDistance</code> from the <code>std/editdistance</code> module to get the Levenshtein distance (computed by considering in Unicode codepoints).

 

 

let search = "complition"

echo &"Words which are {similarity:4.1f}% similar:"

echo lev[i].join(" ")

 

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=={{header|Perl}}==

Inspired by Raku Sorenson-Dice implementation (doesn't handle Unicode, but module <code>Text::Dice</code> can).

use warnings;

use feature 'say';

push @ranked, sprintf "%.3f $_", $scored{$_} for sort { $scored{$b} <=> $scored{$a} } keys %scored;

say "\n$word:\n" . join("\n", head 10, @ranked);

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<pre>complition:

=={{header|Phix}}==

uses levenshtein() from [[Levenshtein_distance#Phix]] (reproduced below for your convenience) and the standard unix_dict().

<span style="color: #008080;">function</span> <span style="color: #000000;">levenshtein</span><span style="color: #0000FF;">(</span><span style="color: #004080;">string</span> <span style="color: #000000;">a</span><span style="color: #0000FF;">,</span> <span style="color: #000000;">b</span><span style="color: #0000FF;">)</span>

<span style="color: #004080;">integer</span> <span style="color: #000000;">n</span> <span style="color: #0000FF;">=</span> <span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">a</span><span style="color: #0000FF;">),</span>

<span style="color: #0000FF;">{</span><span style="color: #000000;">n</span><span style="color: #0000FF;">,</span><span style="color: #000000;">100</span><span style="color: #0000FF;">-</span><span style="color: #7060A8;">round</span><span style="color: #0000FF;">(</span><span style="color: #000000;">100</span><span style="color: #0000FF;">*</span><span style="color: #000000;">n</span><span style="color: #0000FF;">/</span><span style="color: #7060A8;">length</span><span style="color: #0000FF;">(</span><span style="color: #000000;">word</span><span style="color: #0000FF;">)),</span><span style="color: #000000;">word</span><span style="color: #0000FF;">,</span><span style="color: #7060A8;">join_by</span><span style="color: #0000FF;">(</span><span style="color: #7060A8;">filter</span><span style="color: #0000FF;">(</span><span style="color: #000000;">words</span><span style="color: #0000FF;">,</span><span style="color: #000000;">ln</span><span style="color: #0000FF;">,</span><span style="color: #000000;">n</span><span style="color: #0000FF;">),</span><span style="color: #000000;">1</span><span style="color: #0000FF;">,</span><span style="color: #000000;">6</span><span style="color: #0000FF;">)})</span>

<span style="color: #008080;">end</span> <span style="color: #008080;">for</span>

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(matches Delphi/Go/Wren)

===Hamming distance===

{{Trans|Java}}

my @s1 = $user_word.comb;

my @listed = gather for $filename.IO.lines -> $line {

 

say "{.[0].fmt('%.2f')}% {.[1]}" for @listed;

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<pre>80.00% compaction

Using unixdict.txt from www.puzzlers.org

 

my $match = bigram $phrase;

%hash.race.map: { [(2 * ($match ∩ .value) / ($match + .value)).round(.001), .key] }

say "\n$w:";

.say for sorenson($w, %hash).grep(*.[0] >= .55).sort({-.[0],~.[1]}).head(10);

 

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No attempt was made to change (by any method) three letters or more.

parse arg what iFID . /*obtain optional arguments from the CL*/

if what==''|what=="," then what= 'complition' /*Not specified? Then use the default.*/

if @.z\==. then $= $ z; if r==1 then call recur

end /*k*/

{{out|output|text=&nbsp; when using the default inputs:}}

<pre>

</pre>

 

{{trans|Go}}

 

fn levenshtein(s string, t string) int {

println('')

}

 

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{{libheader|Wren-fmt}}

This uses 'unixdict' and the Levenshtein distance algorithm to test for similarity.

 

var levenshtein = Fn.new { |s, t|

System.print(lev[i])

System.print()

 

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