public code v1
This commit is contained in:
Francisco Jesús Martínez Mimbrera
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<?xml version="1.0" encoding="UTF-8"?>
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<classpath>
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<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.8"/>
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<classpathentry kind="con" path="org.eclipse.pde.core.requiredPlugins"/>
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<classpathentry kind="src" path="src"/>
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<classpathentry kind="output" path="bin"/>
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</classpath>
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@@ -0,0 +1,14 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd" xmlns="http://maven.apache.org/POM/4.0.0"
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xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>flintstones.group</groupId>
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<artifactId>flintstones.bundles</artifactId>
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<version>1.0.0-SNAPSHOT</version>
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</parent>
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<artifactId>flintstones.method.ahp.phase.ranking</artifactId>
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<version>1.0.0-SNAPSHOT</version>
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<packaging>eclipse-plugin</packaging>
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<name>[bundle] Ranking</name>
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</project>
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@@ -0,0 +1,45 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<projectDescription>
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<name>flintstones.method.ahp.phase.ranking</name>
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<comment></comment>
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<projects>
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</projects>
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<buildSpec>
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<buildCommand>
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<name>org.eclipse.jdt.core.javabuilder</name>
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<arguments>
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</arguments>
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</buildCommand>
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<buildCommand>
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<name>org.eclipse.pde.ManifestBuilder</name>
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<arguments>
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</arguments>
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</buildCommand>
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<buildCommand>
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<name>org.eclipse.pde.SchemaBuilder</name>
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<arguments>
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</arguments>
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</buildCommand>
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<buildCommand>
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<name>org.eclipse.m2e.core.maven2Builder</name>
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<arguments>
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</arguments>
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</buildCommand>
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</buildSpec>
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<natures>
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<nature>org.eclipse.m2e.core.maven2Nature</nature>
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<nature>org.eclipse.pde.PluginNature</nature>
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<nature>org.eclipse.jdt.core.javanature</nature>
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</natures>
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<filteredResources>
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<filter>
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<id>1779484362619</id>
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<name></name>
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<type>30</type>
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<matcher>
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<id>org.eclipse.core.resources.regexFilterMatcher</id>
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<arguments>node_modules|\.git|__CREATED_BY_JAVA_LANGUAGE_SERVER__</arguments>
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</matcher>
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</filter>
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</filteredResources>
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</projectDescription>
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+2
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eclipse.preferences.version=1
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encoding/<project>=UTF-8
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@@ -0,0 +1,7 @@
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eclipse.preferences.version=1
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org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
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org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.8
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org.eclipse.jdt.core.compiler.compliance=1.8
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org.eclipse.jdt.core.compiler.problem.assertIdentifier=error
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org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
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org.eclipse.jdt.core.compiler.source=1.8
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@@ -0,0 +1,4 @@
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activeProfiles=
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eclipse.preferences.version=1
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resolveWorkspaceProjects=true
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version=1
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@@ -0,0 +1,27 @@
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Manifest-Version: 1.0
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Bundle-ManifestVersion: 2
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Bundle-Name: Ranking
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Bundle-SymbolicName: flintstones.method.ahp.phase.ranking;singleton:=true
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Bundle-Version: 1.0.0.qualifier
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Automatic-Module-Name: flintstones.method.ahp.phase.ranking
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Bundle-RequiredExecutionEnvironment: JavaSE-11
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Require-Bundle: flintstones.operator,
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javax.inject,
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flintstones.entity.problemelement,
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flintstones.entity.valuation,
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flintstones.model.valuation.service,
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flintstones.valuation.numeric.real,
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flintstones.operator.aggregation.geometricMean,
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org.apache.commons.math3,
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org.eclipse.e4.core.contexts,
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flintstones.entity.ahp,
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flintstones.model.ahppreferences.service,
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flintstones.entity.ahppreferences,
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flintstones.model.problemelement.service,
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flintstones.entity.preferences.preferencecollection,
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org.eclipse.e4.core.di,
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flintstones.model.domain.service,
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flintstones.helper.data,
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flintstones.entity.domain,
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flintstones.entity.method.phase
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Export-Package: flintstones.method.ahp.phase.ranking
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@@ -0,0 +1,47 @@
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<p align="center">
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<img src="https://cdn.jsdelivr.net/emojione/assets/svg/1f63c.svg" width="256" height="256" alt="Snarkdown">
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<br>
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<a href="https://www.npmjs.org/package/snarkdown"><img src="https://img.shields.io/npm/v/snarkdown.svg?style=flat" alt="npm"></a> <a href="https://travis-ci.org/developit/snarkdown"><img src="https://travis-ci.org/developit/snarkdown.svg?branch=master" alt="travis"></a>
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</p>
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Snarkdown is a dead simple **1kb** [Markdown] parser.
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It's designed to be as minimal as possible, for constrained use-cases where a full Markdown parser would be inappropriate.
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## Features
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- **Fast:** since it's basically one regex and a huge if statement
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- **Tiny:** it's 1kb of gzipped ES3
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- **Simple:** pass a Markdown string, get back an HTML string
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> **Note:** Tables are not yet supported. If you love impossible to read regular expressions, submit a PR!
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## Demos & Examples
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- ⚛️ [**Snarky**](https://snarky.surge.sh) - markdown editor built with Preact & Snarkdown
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- ✏️ [**Simple Markdown Editor**](http://jsfiddle.net/developit/828w6t1x/)
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## Usage
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Snarkdown exports a single function, which parses a string of Markdown and returns a String of HTML. Couldn't be simpler.
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The snarkdown module is available in [every module format](https://unpkg.com/snarkdown/dist/) you'd ever need: ES Modules, CommonJS, UMD...
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```js
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import snarkdown from 'snarkdown';
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let md = '_this_ is **easy** to `use`.';
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let html = snarkdown(md);
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console.log(html);
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// <em>this</em> is <strong>easy</strong> to <code>use</code>.
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```
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## License
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MIT
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[Markdown]: http://daringfireball.net/projects/markdown/
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@@ -0,0 +1,5 @@
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source.. = src/
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output.. = bin/
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bin.includes = META-INF/,\
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.,\
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plugin.xml
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@@ -0,0 +1,12 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<?eclipse version="3.4"?>
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<plugin>
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<extension
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point="flintstones.phasemethod.extensionpoint">
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<phase
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uid="flintstones.method.ahp.phase.ranking"
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implementation="flintstones.method.ahp.phase.ranking.AHPRankingModel">
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</phase>
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</extension>
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</plugin>
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+233
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package flintstones.method.ahp.phase.ranking;
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import java.util.Arrays;
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import javax.inject.Inject;
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import org.apache.commons.math3.linear.EigenDecomposition;
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import org.apache.commons.math3.linear.MatrixUtils;
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import org.apache.commons.math3.linear.RealMatrix;
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import org.apache.commons.math3.linear.RealVector;
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import org.eclipse.e4.core.contexts.ContextInjectionFactory;
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import org.eclipse.e4.core.contexts.IEclipseContext;
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import flintstones.entity.ahp.AHPAggregatedMatrix;
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import flintstones.entity.ahp.AHPMatrix;
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import flintstones.entity.method.phase.PhaseMethod;
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import flintstones.entity.preferences.preferencecollection.PreferenceCollection;
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import flintstones.entity.problemelement.entities.Alternative;
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import flintstones.entity.problemelement.entities.Criterion;
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import flintstones.entity.problemelement.entities.Expert;
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import flintstones.entity.problemelement.entities.ProblemElement;
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import flintstones.helper.DoubleHelper;
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import flintstones.helper.MatrixHelper;
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import flintstones.model.ahppreferences.service.IProblemPreferencesService;
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import flintstones.model.domain.service.IDomainService;
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import flintstones.model.problemelement.service.IProblemElementService;
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import flintstones.model.valuation.service.IValuationService;
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import flintstones.operator.service.IOperatorService;
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/**
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* The Class AHPRankingModel.
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*/
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public class AHPRankingModel extends PhaseMethod {
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/** The op service. */
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@Inject
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IOperatorService opService;
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/** The pref service. */
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@Inject
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IProblemPreferencesService prefService;
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/** The problem service. */
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@Inject
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IProblemElementService problemService;
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/** The valuation service. */
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@Inject
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IValuationService valuationService;
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/** The domain service. */
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@Inject
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IDomainService domainService;
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/** The context. */
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@Inject
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IEclipseContext context;
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/* (non-Javadoc)
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* @see flintstones.phasemethod.PhaseMethod#getName()
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*/
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@Override
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public String getName() {
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return "AHP Ranking";
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}
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/** The eigen vector criterion. */
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// Cache
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double[] eigenVectorCriterion;
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/** The eigen matrix alternative. */
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double[][] eigenMatrixAlternative;
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/** The final eigen vector. */
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double[] finalEigenVector;
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/** The eigen vector criterions. */
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ProblemElement[] eigenVectorCriterions;
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/** The eigen matrix alternatives. */
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ProblemElement[] eigenMatrixAlternatives;
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/**
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* Execute the model.
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*/
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public void execute() {
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eigenVectorCriterion = getCriterionEigenVector();
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eigenMatrixAlternative = getAlternativesEigenMatrix();
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finalEigenVector = new double[eigenMatrixAlternative.length];
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for (int i = 0; i < eigenMatrixAlternative.length; i++) {
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double[] sumVector = new double[eigenVectorCriterion.length];
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for (int j = 0; j < eigenVectorCriterion.length; j++) {
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double a = eigenVectorCriterion[j];
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double b = eigenMatrixAlternative[i][j];
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double r = a * b;
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sumVector[j] = r;
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}
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double sum = Arrays.stream(sumVector).sum();
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finalEigenVector[i] = sum;
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}
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}
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/**
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* Gets the criterion eigen vector.
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*
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* @return the criterion eigen vector
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*/
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private double[] getCriterionEigenVector() {
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double[] eigenVectorCriterion = new double[problemService.getAll(Criterion.Type).length];
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// NEW
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PreferenceCollection col = prefService.get(null, Expert.Type, Criterion.Type, Criterion.Type);
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AHPAggregatedMatrix aggMatrix = aggregatedMatrix(col.getEveryAHPMatrix());
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//
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double[][] resultMatrix = aggMatrix.getResultMatrix();
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eigenVectorCriterions = aggMatrix.getRow();
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RealMatrix realMatrix = MatrixUtils.createRealMatrix(resultMatrix);
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EigenDecomposition descomposition = new EigenDecomposition(realMatrix);
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// Obtenemos el autovector (sin normalizar) del autovalor que le indiquemos
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int pos = DoubleHelper.FindMaxIndex(descomposition.getRealEigenvalues());
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RealVector eigenVector = descomposition.getEigenvector(pos);
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eigenVectorCriterion = eigenVector.toArray();
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eigenVectorCriterion = DoubleHelper.Normalize(eigenVectorCriterion);
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return eigenVectorCriterion;
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}
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/**
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* Gets the alternatives eigen matrix.
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*
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* @return the alternatives eigen matrix
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*/
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private double[][] getAlternativesEigenMatrix() {
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double[][] eigenMatrixAlternativeMatrix = new double[problemService.getAll(Criterion.Type).length][problemService.getAll(Alternative.Type).length];
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PreferenceCollection col = prefService.get(Expert.Type, Criterion.Type, Alternative.Type, Alternative.Type);
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// Foreach criterion
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ProblemElement[] criterions = eigenVectorCriterions;
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for (int i = 0; i < criterions.length; i++) {
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ProblemElement c = criterions[i];
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AHPAggregatedMatrix aggMatrix = aggregatedMatrix(col.getEveryAHPMatrixOther(c));
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// AHPAggregatedMatrix aggMatrix = getAggregatedMatrix(ahpService.getAllAlternativesPreferencesFor((Criterion)c));
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double[][] resultMatrix = aggMatrix.getResultMatrix();
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eigenMatrixAlternatives = aggMatrix.getRow();
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RealMatrix realMatrix = MatrixUtils.createRealMatrix(resultMatrix);
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EigenDecomposition descomposition = new EigenDecomposition(realMatrix);
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// Obtenemos el autovector (sin normalizar) del autovalor que le indiquemos
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int pos = DoubleHelper.FindMaxIndex(descomposition.getRealEigenvalues());
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RealVector eigenVector = descomposition.getEigenvector(pos);
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double[] eigenVectorArr = eigenVector.toArray();
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eigenVectorArr = DoubleHelper.Normalize(eigenVectorArr);
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eigenMatrixAlternativeMatrix[i] = eigenVectorArr;
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}
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double[][] transposed = MatrixHelper.transpose(eigenMatrixAlternativeMatrix);
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return transposed;
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}
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/**
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* Aggregates AHPMatrix into one matrix using geometric mean.
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*
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* @param preferences the preferences
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* @return the AHP aggregated matrix
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*/
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private AHPAggregatedMatrix aggregatedMatrix(AHPMatrix[] preferences) {
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AHPAggregatedMatrix aggregatedMatrix = ContextInjectionFactory.make(AHPAggregatedMatrix.class, context);
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aggregatedMatrix.aggregate(preferences);
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return aggregatedMatrix;
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}
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/**
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* Gets the criteria priorities.
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*
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* @return the criteria priorities
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*/
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public double[] getCriteriaPriorities() {
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return eigenVectorCriterion;
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}
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/**
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* Gets the criteria priorities names.
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*
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* @return the criteria priorities names
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*/
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public String[] getCriteriaPrioritiesNames() {
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return Arrays.stream(eigenVectorCriterions).map(k -> k.getName()).sorted().toArray(String[]::new);
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}
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/**
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* Gets the alternatives priorities.
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*
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* @return the alternatives priorities
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*/
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public double[][] getAlternativesPriorities() {
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return eigenMatrixAlternative;
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}
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/**
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* Gets the alternative names.
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*
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* @return the alternative names
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*/
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public String[] getAlternativeNames() {
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return Arrays.stream(problemService.getAll(Alternative.Type)).map(k -> k.getName()).sorted().toArray(String[]::new);
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}
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/**
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* Gets the result.
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*
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* @return the result
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*/
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public double[] getResult() {
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return finalEigenVector;
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}
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}
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Reference in New Issue
Block a user