suffix-thumb - npm Package Compare versions

Comparing version 2.0.0 to 3.0.0

builds/suffix-thumb.min.js

@@ -1,1 +0,1 @@
-!function(r,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((r="undefined"!=typeof globalThis?globalThis:r||self).suffixThumb={})}(this,(function(r){"use strict";var n=/^.([0-9]+)/,e=function(r,n){if(e=n.rules,"[object Array]"===Object.prototype.toString.call(e))return n.rules;var e,t=r[r.length-1],o=n.rules[t]||[];return 0===o.length&&(o=n.rules[""]||o),o};function t(r,n){return function(r){if(Array.isArray(r))return r}(r)||function(r,n){var e=null==r?null:"undefined"!=typeof Symbol&&r[Symbol.iterator]||r["@@iterator"];if(null==e)return;var t,o,u=[],i=!0,f=!1;try{for(e=e.call(r);!(i=(t=e.next()).done)&&(u.push(t.value),!n||u.length!==n);i=!0);}catch(r){f=!0,o=r}finally{try{i||null==e.return||e.return()}finally{if(f)throw o}}return u}(r,n)||function(r,n){if(!r)return;if("string"==typeof r)return o(r,n);var e=Object.prototype.toString.call(r).slice(8,-1);"Object"===e&&r.constructor&&(e=r.constructor.name);if("Map"===e||"Set"===e)return Array.from(r);if("Arguments"===e||/^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(e))return o(r,n)}(r,n)||function(){throw new TypeError("Invalid attempt to destructure non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method.")}()}function o(r,n){(null==n||n>r.length)&&(n=r.length);for(var e=0,t=new Array(n);e<n;e++)t[e]=r[e];return t}var u=function(){for(var r=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",n=[],e=4;e>=0;e-=1)if(!(r.length-1<=e)){var t=r.substr(r.length-e-1,r.length-1);n.push(t)}return n},i=function(r){var n=[];return Object.keys(r).forEach((function(e){var t,o,u=(t=r[e],o=e,Object.keys(t).map((function(r){return{from:o,to:r,yes:t[r]}})).sort((function(r,n){return r.yes>n.yes?-1:r.yes<n.yes?1:0})));u[0]&&u[0].yes>1&&n.push(u[0])})),n=n.sort((function(r,n){return r.yes>n.yes?-1:r.yes<n.yes?1:0}))},f=function(r,n){var e=function(r,n){return r.map((function(r){var e=0,t=0,o={};return n.forEach((function(n){if(n[0].endsWith(r.from)){var u=new RegExp(r.from+"$");n[0].replace(u,r.to)===n[1]?e+=1:(t+=1,o[n[0]]=n[1])}})),{from:r.from,to:r.to,yes:e,no:t,percent:e/(e+t),exceptions:o}}))}(r,n);return e=(e=e.filter((function(r){return r.yes>1&&r.yes>r.no}))).sort((function(r,n){return r.yes>n.yes?-1:r.yes<n.yes?1:0}))};function c(r){return r.split("").reverse().join("")}var s=function(r){return(r=r.sort((function(r,n){return r.from.length>n.from.length?-1:r.from.length<n.from.length||(r=c(r.from))>(n=c(n.from))?1:r<n?-1:0}))).map((function(r){return[r.from,r.to,r.yes]}))},l=function(r){var n,e,t,o;return r.rules=(n=r.rules,e={},n.forEach((function(r){var n=r[0]||"",t=n[n.length-1]||"";e[t]=e[t]||[],e[t].push(r)})),e),r.exceptions=(t=r.exceptions,o={},Object.keys(t).forEach((function(r){var n=t[r],e=function(r,n){for(var e=[],t=0;t<r.length&&r[t]===n[t];t+=1)e.push(r[t]);return e.join("")}(r,n);if(e.length<2)o[r]=n;else{var u="."+e.length+n.substr(e.length);o[r]=u}})),o),r},a=function(r){var n,e,o=function(r){var n={};return r.forEach((function(r){var e=t(r,2),o=e[0],i=e[1],f=u(o);f.push(""),f.forEach((function(r){n[r]=n[r]||{},u(i).forEach((function(e){n[r][e]=n[r][e]||0,n[r][e]+=1}))}))})),n}(r=r.filter((function(r){return r&&r[0]&&r[1]}))),c=i(o),l=f(c,r);return e={},(n=l).forEach((function(r,t){n.slice(t+1,n.length).forEach((function(n){n.from.endsWith(r.from)&&(e[n.from]=!0)}))})),function(r,n){var e={};r.forEach((function(r){Object.assign(e,r.exceptions)}));var t=n.filter((function(n){return!e.hasOwnProperty(n[0])&&!r.find((function(r){return n[0].endsWith(r.from)}))})),o=(n.length-t.length)/n.length;return{rules:s(r),exceptions:e,coverage:o,remaining:t}}(l=n=n.filter((function(r){return!1===e.hasOwnProperty(r.from)})),r)},h=function(r,n){var e,t=0;return r.rules=r.rules.map((function(r){return t+=r[2],r.slice(0,2)})),r.exceptions=r.exceptions.reduce((function(r,n){return r[n[0]]=n[1],r}),{}),r.rules=r.rules.sort((function(r,n){return r[0].length>n[0].length?-1:r[0].length<n[0].length?1:0})),r.coverage=(e=t/n,Math.round(1e3*e)/1e3),r};r.compress=l,r.convert=function(r,t){if(t.exceptions.hasOwnProperty(r))return function(r,e){var t=e.exceptions[r],o=t.match(n);if(null===o)return e.exceptions[r];var u=Number(o[1])||0;return r.substr(0,u)+t.replace(n,"")}(r,t);for(var o=e(r,t),u=0;u<o.length;u+=1){var i=o[u][0];if(r.endsWith(i)){var f=new RegExp(i+"$");return r.replace(f,o[u][1])}}return null},r.find=function(r){var n=r.length,e={},t=a(r);return e.rules=t.rules||[],e.exceptions=t.remaining.concat(Object.entries(t.exceptions)),e=h(e,n),e=l(e)},Object.defineProperty(r,"__esModule",{value:!0})}));
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?t(exports,require("efrt")):"function"==typeof define&&define.amd?define(["exports","efrt"],t):t((e="undefined"!=typeof globalThis?globalThis:e||self).suffixThumb={},e.efrt)}(this,(function(e,t){"use strict";const n=/^.([0-9]+)/,r=function(e,t){if(n=t.rules,"[object Array]"===Object.prototype.toString.call(n))return t.rules;var n;let r=e[e.length-1],o=t.rules[r]||[];return 0===o.length&&(o=t.rules[""]||o),o},o=function(e,t){if(t.exceptions.hasOwnProperty(e))return function(e,t){let r=t.exceptions[e],o=r.match(n);if(null===o)return t.exceptions[e];let s=Number(o[1])||0;return e.substr(0,s)+r.replace(n,"")}(e,t);const o=r(e,t);for(let t=0;t<o.length;t+=1){let n=o[t][0];if(e.endsWith(n)){let r=new RegExp(n+"$");return e.replace(r,o[t][1])}}return e},s=function(e=""){let t=[];for(let n=6;n>=0;n-=1){if(e.length-1<=n)continue;let r=e.length-n-1,o=e.substring(r,r+e.length-1);t.push(o)}return t},c=function(e){let t=[];return Object.keys(e).forEach((n=>{let r=function(e,t){let n=Object.keys(e).map((n=>({from:t,to:n,yes:e[n]})));return n=n.sort(((e,t)=>e.yes>t.yes?-1:e.yes<t.yes?1:0)),n}(e[n],n);r[0]&&r[0].yes>1&&t.push(r[0])})),t=t.sort(((e,t)=>e.yes>t.yes?-1:e.yes<t.yes?1:0)),t},l=function(e,t){let n=function(e,t){return e.map((e=>{let n=0,r=0,o={};return t.forEach((t=>{if(t[0].endsWith(e.from)){let s=new RegExp(e.from+"$");t[0].replace(s,e.to)===t[1]?n+=1:(r+=1,o[t[0]]=t[1])}})),{from:e.from,to:e.to,yes:n,no:r,percent:n/(n+r),exceptions:o}}))}(e,t);return n=n.filter((e=>e.yes>1&&e.yes>e.no)),n=n.sort(((e,t)=>e.yes>t.yes?-1:e.yes<t.yes?1:0)),n};function u(e){return e.split("").reverse().join("")}const i=function(e,t){let n={};return e.forEach((e=>{Object.assign(n,e.exceptions)})),e=function(e){return(e=e.sort(((e,t)=>e.from.length>t.from.length?-1:e.from.length<t.from.length||(e=u(e.from))>(t=u(t.from))?1:e<t?-1:0))).map((e=>[e.from,e.to]))}(e),t.filter((t=>!n.hasOwnProperty(t[0])&&!e.find((e=>t[0].endsWith(e.from))))).forEach((e=>{n[e[0]]=e[1]})),{rules:e,exceptions:n}},f=function(e){const t=function(e){const t={};return e.forEach((e=>{let[n,r]=e,o=s(n);o.push(""),o.forEach((e=>{t[e]=t[e]||{},s(r).forEach((n=>{t[e][n]=t[e][n]||0,t[e][n]+=1}))}))})),t}(e=e.filter((e=>e&&e[0]&&e[1])));let n=c(t),r=l(n,e);return r=function(e){let t={};return e.forEach(((n,r)=>{e.slice(r+1,e.length).forEach((e=>{e.from.endsWith(n.from)&&0===e.no&&(t[e.from]=!0)}))})),e=e.filter((e=>!1===t.hasOwnProperty(e.from)))}(r),i(r,e)},p=function(e){return e.exceptions=function(e){let t={},{rules:n,exceptions:r}=e;return Object.keys(r).forEach((e=>{let o=n.find((t=>e.endsWith(t[0])));o?e.replace(o[0],o[1])!==r[e]&&(t[e]=r[e]):t[e]=r[e]})),t}(e),e},h=function(e){let t={};return e.forEach((e=>{let n=e[0]||"",r=n[n.length-1]||"";t[r]=t[r]||[],t[r].push(e)})),t},a=function(e){return e=e.sort(((e,t)=>e[0].length>t[0].length?-1:e[0].length<t[0].length?1:0))},g=function(e,t,n){return e=p(e),!1!==n.inverse&&(e=function(e,t){let n=Object.assign({},e);n.rules=h(e.rules);let r=E(n);return t.forEach((t=>{let[n,s]=t;o(s,r)!==n&&(e.exceptions[t[0]]=t[1])})),e}(e,t)),e},y=function(e,t={}){let n={},r={};return e=e.filter((e=>void 0!==n[e[0]]?(t.verbose&&(console.warn("Duplicate left side:"),console.log("  1.",[e[0],n[e[0]]]),console.log("  2.",e)),!1):void 0!==r[e[1]]?(t.verbose&&(console.warn("Duplicate right side:"),console.log("  1.",[r[e[1]],e[1]]),console.log("  2.",e)),!1===t.inverse):(n[e[0]]=e[1],r[e[1]]=e[0],!0)))},m=function(e){let t={};return Object.keys(e).forEach((n=>{let r=e[n],o=((e,t)=>{let n=[];for(let r=0;r<e.length&&e[r]===t[r];r+=1)n.push(e[r]);return n.join("")})(n,r);if(o.length<2)return void(t[n]=r);let s="."+o.length+r.substr(o.length);t[n]=s})),t},b=function(e){return e=(e=>e.reduce(((e,t)=>(e[t[0]]=t[1],e)),{}))(e=function(e){let t=[];return Object.keys(e).forEach((n=>{t=t.concat(e[n])})),t}(e)),e=m(e),e=t.pack(e)},d=/^.([0-9]+)/,x=function(e){return Object.keys(e).forEach((t=>{let n=e[t],r=n.match(d);if(null!==r){let o=Number(r[1])||0,s=t.substring(0,o)+n.replace(d,"");e[t]=s}})),e},E=function(e){let t=[];var n;return Object.keys(e.rules).forEach((n=>{t=t.concat(e.rules[n].map((e=>[e[1],e[0]])))})),t=a(t),{rules:h(t),exceptions:(n=e.exceptions,Object.entries(n).reduce(((e,t)=>(e[t[1]]=t[0],e)),{}))}};e.compress=function(e={}){return e.rules=b(e.rules),e.exceptions=m(e.exceptions),e.exceptions=t.pack(e.exceptions),e},e.convert=o,e.learn=function(e,t={}){e=y(e,t);let n=f(e);return n=g(n,e,t),n.rules=h(n.rules),n},e.reverse=E,e.uncompress=function(e={}){var n;return"string"==typeof e.exceptions&&(e.exceptions=t.unpack(e.exceptions),e.exceptions=x(e.exceptions)),"string"==typeof e.rules&&(e.rules=(n=e.rules,n=t.unpack(n),n=x(n),n=Object.entries(n),n=a(n),h(n))),e},e.validate=y,Object.defineProperty(e,"__esModule",{value:!0})}));

package.json

 {
   "name": "suffix-thumb",
   "description": "learn transformations between two sets of words",
-  "version": "2.0.0",
+  "version": "3.0.0",
   "author": "Spencer Kelly <[e-mail]> (http://spencermounta.in)",
@@ -16,7 +16,10 @@ "main": "./builds/suffix-thumb.mjs",
     },
-    "./find": {
-      "import": "./src/find/index.js"
+    "./learn": {
+      "import": "./src/learn/index.js"
     },
     "./convert": {
       "import": "./src/convert/index.js"
+    },
+    "./uncompress": {
+      "import": "./src/uncompress/index.js"
     }
@@ -49,18 +52,13 @@ },
   "devDependencies": {
-    "@babel/core": "7.15.0",
-    "@babel/preset-env": "7.15.0",
-    "@rollup/plugin-commonjs": "20.0.0",
-    "@rollup/plugin-json": "4.1.0",
-    "@rollup/plugin-node-resolve": "13.0.4",
+    "@rollup/plugin-commonjs": "21.0.1",
+    "@rollup/plugin-node-resolve": "13.1.1",
     "amble": "1.3.0",
-    "efrt": "2.3.2",
-    "eslint": "7.32.0",
-    "rollup": "2.56.3",
-    "rollup-plugin-babel": "4.4.0",
+    "efrt": "^2.3.2",
+    "rollup": "2.62.0",
     "rollup-plugin-filesize-check": "0.0.1",
     "rollup-plugin-terser": "7.0.2",
     "tap-dancer": "0.3.4",
-    "tape": "5.3.1"
+    "tape": "5.4.0"
   },
   "license": "MIT"
 }

README.md

@@ -20,3 +20,5 @@ <div align="center">
   
-   <hr/>
+  <!-- spacer -->
+  <img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
   
@@ -29,10 +31,14 @@ </div>
 
-The assumption is that a word's _suffix_ is the most changeable part of a word.
+The assumption is that a word's _suffix_ is the most-changed part of a word.
 
-![carbon(1)](https://user-images.githubusercontent.com/399657/79898840-e7e66780-83d9-11ea-9ff3-099bf39cf892.png)
+<!-- ![carbon(1)](https://user-images.githubusercontent.com/399657/79898840-e7e66780-83d9-11ea-9ff3-099bf39cf892.png) -->
 
+### Learn → Convert
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
 ```js
-import { find, convert } from 'suffix-thumb'
+import { learn, convert } from 'suffix-thumb'
 
-const pairs = [
+let pairs = [
   ['walk', 'walked'],
@@ -42,10 +48,9 @@ ['talk', 'talked'],
 ]
-let model = find(pairs)
+let model = learn(pairs)
 /* {
   rules: { k: [ [ 'alk', 'alked' ] ] },
   exceptions: { go: 'went' },
-  coverage: 0.667
 }*/
 
-const pairs = [
+let pairs = [
   ['aail', 'aael'],
@@ -57,7 +62,6 @@ ['bbil', 'bbel'],
 ]
-let model = find(pairs)
+let model = learn(pairs)
 /* {
   rules: { o: [ [ 'foo', 'bar' ] ], l: [ [ 'il', 'el' ] ] },
   exceptions: {},
-  coverage: 1
 }
@@ -69,17 +73,105 @@ */
 ```
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
 
+### Reverse
+the model also works transforming the words the other way:
+```js
+import { learn, reverse, convert } from 'suffix-thumb'
+
+let pairs = [
+  ['walk', 'walked'],
+  ['talk', 'talked'],
+  ['go', 'went'],
+]
+let model = learn(pairs)
+let rev = reverse(model)
+let out = convert('walked', rev)
+// 'walk'
+```
+by default, the model ensures all two-way transformation - if you only require 1-way, you can do:
+```js
+learn(pairs, {inverse: false})
+```
+you can expect the model to be 5% smaller or so - not much.
+
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
+### Compress
+by default, the model is small, but remains human-readable (and human-editable).
+We can compress it further, turning it into a snowball inscrutible characters:
+
+```js
+import { learn, compress, uncompress, convert } from 'suffix-thumb'
+
+let pairs = [
+  ['walk', 'walked'],
+  ['talk', 'talked'],
+  ['go', 'went'],
+]
+let model = learn(pairs)
+// shrink it
+model = compress(shrink)
+// {rules:'LSKs3H2-LNL.S3DH'}
+// pop it back
+model = uncompress(model)
+let out = convert('walk', model)
+// 'walked'
+
+```
+The models must be uncompressed before they are used, or reversed.
+
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
+### Validation
+sometimes you can accidentally send in an impossible set of transformations. This library quietly ignores duplicates, by default.
+You can use `{verbose:true}` to log warnings about this, or validate your input manually:
+```js
+import { validate } from 'suffix-thumb'
+let pairs = [
+  ['left', 'right'],
+  ['left', 'right-two'],
+  ['ok', 'right'],
+]
+pairs = validate(pairs) //remove dupes (on both sides)
+```
+
+If you are just doing one-way transformation, and not reverse, you may want to allow duplicates on the right side:
+```js
+let pairs = [
+  ['left', 'right'],
+  ['ok', 'right'],
+]
+let model = learn(pairs, {inverse: false})
+let out = convert('ok', model)
+// 'right'
+```
+
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
 ## How it works
 
-For each word-pair, it generates all **n-suffixes** of the left, and **n-suffixes** of the right.
+For each word-pair, it generates all **n-suffixes** of the left-side, and **n-suffixes** of the right-side.
 
-any pattern between the two sets of words begins to pop out.
+any good correlations between the two suffix pairs begins to pop out. Exceptions to these rules are remembered. It then exhaustively reduces any redundancies in these rules.
 
-it reduces any redundancies in this list.
+There are some compromises, magic-numbers, and opinionated decisions - in-order to allow productive, but imperfect rules.
 
-it then runs the patters on the dataset, to get a score, and any exceptions.
+* The library is meant optimize for file-size of the model
+* compression is slow, uncompression is fast
+* it should always return a perfect result
 
-There may be wordlists with no helpful patterns.
+The library drops case-information - and numbers and some characters[1](https://github.com/spencermountain/efrt) will not compress properly.
 
-Ideally, you should be able to take a list of word-pairs, create a model for them, and then delete the 2nd half of the word pairs.
+There may be wordlists with few helpful patterns. Conjugation datasets in English and French tend to get ~85% filesize compression.
 
+<!-- spacer -->
+<img height="50px" src="https://user-images.githubusercontent.com/399657/68221862-17ceb980-ffb8-11e9-87d4-7b30b6488f16.png"/>
+
+### See also
+* [efrt](https://github.com/spencermountain/efrt) - trie-based JSON compression
+
 MIT

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