WIP: страницы для правил #62

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Ghost wants to merge 132 commits from master into 61-rules-pages
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@ -1,27 +1,25 @@
package ru.ulstu.extractor.rule.service; package ru.ulstu.extractor.rule.service;
import net.sourceforge.jFuzzyLogic.defuzzifier.DefuzzifierCenterOfGravity; import com.fuzzylite.Engine;
import net.sourceforge.jFuzzyLogic.membership.MembershipFunctionTriangular; import com.fuzzylite.activation.Highest;
import net.sourceforge.jFuzzyLogic.rule.FuzzyRule; import com.fuzzylite.norm.t.AlgebraicProduct;
import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleExpression; import com.fuzzylite.rule.Rule;
import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleSet; import com.fuzzylite.rule.RuleBlock;
import net.sourceforge.jFuzzyLogic.rule.FuzzyRuleTerm; import com.fuzzylite.term.Triangle;
import net.sourceforge.jFuzzyLogic.rule.LinguisticTerm; import com.fuzzylite.variable.InputVariable;
import net.sourceforge.jFuzzyLogic.rule.Variable; import com.fuzzylite.variable.OutputVariable;
import net.sourceforge.jFuzzyLogic.ruleConnection.RuleConnectionMethodAndMin;
import net.sourceforge.jFuzzyLogic.ruleImplication.RuleImplicationMethodMin;
import org.springframework.stereotype.Service; import org.springframework.stereotype.Service;
import ru.ulstu.extractor.rule.model.AntecedentValue; import ru.ulstu.extractor.rule.model.AntecedentValue;
import ru.ulstu.extractor.rule.model.Rule; import ru.ulstu.extractor.rule.model.DbRule;
import java.util.ArrayList; import java.util.HashMap;
import java.util.Collections;
import java.util.Comparator;
import java.util.LinkedList;
import java.util.List; import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
@Service @Service
public class FuzzyInferenceService { public class FuzzyInferenceService {
private final static String RULE_TEMPLATE = "if %s is %s AND %s is %s then state is %s";
private final RuleService ruleService; private final RuleService ruleService;
private final AntecedentValueService antecedentValueService; private final AntecedentValueService antecedentValueService;
@ -31,118 +29,69 @@ public class FuzzyInferenceService {
this.antecedentValueService = antecedentValueService; this.antecedentValueService = antecedentValueService;
} }
private List<FuzzyRule> getFuzzyRulesFromDb() { public List<String> getRulesFromDb() {
List<FuzzyRule> fuzzyRules = new ArrayList<>(); List<DbRule> dbDbRules = ruleService.getList();
//List<Variable> variables = getFuzzyVariables(); return dbDbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
for (Rule dbRule : ruleService.getList()) {
FuzzyRule fuzzyRule = new FuzzyRule(String.format("Fuzzy rule %s", dbRule.getId()));
// fuzzyRule.setAntecedents(expression);
// fuzzyRule.setConsequents(new LinkedList<>(Collections.singleton(new FuzzyRuleTerm(dbRule.getConsequent(), false))));
fuzzyRules.add(fuzzyRule);
}
return fuzzyRules;
} }
private List<Variable> getFuzzyVariablesWithoutMembership() { private String getFuzzyRule(DbRule dbRule) {
List<Variable> variables = new ArrayList<>(); return String.format(RULE_TEMPLATE,
dbRule.getFirstAntecedent().name(),
dbRule.getFirstAntecedentValue().getAntecedentValue(),
dbRule.getSecondAntecedent().name(),
dbRule.getSecondAntecedentValue().getAntecedentValue(),
dbRule.getConsequent());
}
private RuleBlock getRuleBlock(Engine engine, Map<String, Double> variableValues, List<AntecedentValue> antecedentValues) {
variableValues.forEach((key, value) -> {
InputVariable input = new InputVariable();
input.setName(key);
input.setDescription("");
input.setEnabled(true);
input.setRange(0.000, 1.000);
input.setLockValueInRange(false);
for (int i = 0; i < antecedentValues.size(); i++) {
input.addTerm(new Triangle(antecedentValues.get(i).getAntecedentValue(), i, i + 2));
}
engine.addInputVariable(input);
});
RuleBlock mamdani = new RuleBlock();
mamdani.setName("mamdani");
mamdani.setDescription("");
mamdani.setEnabled(true);
mamdani.setConjunction(null);
mamdani.setDisjunction(null);
mamdani.setImplication(new AlgebraicProduct());
mamdani.setActivation(new Highest());
getRulesFromDb().forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
return mamdani;
}
private Engine getFuzzyEngine() {
Engine engine = new Engine();
engine.setName("Git rules");
engine.setDescription("");
return engine;
}
public String run() {
Engine engine = getFuzzyEngine();
List<AntecedentValue> antecedentValues = antecedentValueService.getList(); List<AntecedentValue> antecedentValues = antecedentValueService.getList();
for (AntecedentValue antecedentValue : antecedentValues) { Map<String, Double> variableValues = new HashMap<>();
variables.add(new Variable(antecedentValue.getAntecedentValue())); engine.addRuleBlock(getRuleBlock(engine, variableValues, antecedentValues));
} return getConsequent(engine, variableValues);
return variables;
} }
// private FuzzyRuleExpression getFuzzyRulesAntecedents(TimeSeriesType timeSeriesType1, TimeSeriesType timeSeriesType2) { private String getConsequent(Engine engine, Map<String, Double> variableValues) {
// return new FuzzyRuleExpression(getFuzzyRuleTerm(), getFuzzyRuleTerm(), new RuleConnectionMethodAndMin()); OutputVariable outputVariable = engine.getOutputVariable("state");
// } for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
InputVariable inputVariable = engine.getInputVariable(variableValue.getKey());
private FuzzyRuleExpression getFuzzyRuleExpression(FuzzyRuleTerm term1, FuzzyRuleTerm term2) { inputVariable.setValue(variableValue.getValue());
return new FuzzyRuleExpression(term1, term2, new RuleConnectionMethodAndMin());
} }
engine.process();
private FuzzyRuleTerm getFuzzyRuleTerm(Variable variable, String term) { return outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
return new FuzzyRuleTerm(variable, term, false);
}
public void run() {
FuzzyRule fuzzyRule1 = new FuzzyRule("rule 1");
FuzzyRule fuzzyRule2 = new FuzzyRule("rule 2");
FuzzyRule fuzzyRule3 = new FuzzyRule("rule 3");
Variable weather = new Variable("Погода");
weather.getLinguisticTerms().put("солнечно",
new LinguisticTerm("солнечно", new MembershipFunctionTriangular(0, 20, 30)));
weather.getLinguisticTerms().put("мороз",
new LinguisticTerm("мороз", new MembershipFunctionTriangular(-50, -10, 10)));
weather.setDefuzzifier(new DefuzzifierCenterOfGravity(weather));
Variable suit = new Variable("Одежда");
suit.getLinguisticTerms().put("легко одет",
new LinguisticTerm("легко одет", new MembershipFunctionTriangular(0, 5, 10)));
suit.getLinguisticTerms().put("тепло одет",
new LinguisticTerm("тепло одет", new MembershipFunctionTriangular(5, 10, 20)));
suit.setDefuzzifier(new DefuzzifierCenterOfGravity(suit));
Variable feel = new Variable("Ощущение");
feel.getLinguisticTerms().put("Холодно",
new LinguisticTerm("Холодно", new MembershipFunctionTriangular(0, 5, 10)));
feel.getLinguisticTerms().put("Жарко",
new LinguisticTerm("Жарко", new MembershipFunctionTriangular(5, 10, 20)));
feel.setDefuzzifier(new DefuzzifierCenterOfGravity(feel));
FuzzyRuleTerm weatherTerm1 = new FuzzyRuleTerm(weather, "солнечно", false);
FuzzyRuleTerm weatherTerm2 = new FuzzyRuleTerm(weather, "мороз", false);
FuzzyRuleTerm suitTerm1 = new FuzzyRuleTerm(suit, "легко одет", false);
FuzzyRuleTerm suitTerm2 = new FuzzyRuleTerm(suit, "тепло одет", false);
FuzzyRuleTerm feelCold = new FuzzyRuleTerm(feel, "Холодно", false);
FuzzyRuleTerm feelWarm = new FuzzyRuleTerm(feel, "Жарко", false);
FuzzyRuleExpression expression1 = new FuzzyRuleExpression(weatherTerm1, suitTerm2, new RuleConnectionMethodAndMin());
fuzzyRule1.setAntecedents(expression1);
fuzzyRule1.setConsequents(new LinkedList<>(Collections.singleton(feelWarm)));
FuzzyRuleExpression expression2 = new FuzzyRuleExpression(weatherTerm2, suitTerm1, new RuleConnectionMethodAndMin());
fuzzyRule2.setAntecedents(expression2);
fuzzyRule2.setConsequents(new LinkedList<>(Collections.singleton(feelCold)));
FuzzyRuleExpression expression3 = new FuzzyRuleExpression(weatherTerm1, suitTerm1, new RuleConnectionMethodAndMin());
fuzzyRule3.setAntecedents(expression3);
fuzzyRule3.setConsequents(new LinkedList<>(Collections.singleton(feelCold)));
fuzzyRule1.evaluate(new RuleImplicationMethodMin());
fuzzyRule2.evaluate(new RuleImplicationMethodMin());
//fuzzyRule3.evaluate(new RuleImplicationMethodMin());
FuzzyRuleSet set = new FuzzyRuleSet();
set.add(fuzzyRule1);
set.add(fuzzyRule2);
set.add(fuzzyRule3);
set.evaluate();
set.setVariable("Погода", 25);
set.setVariable("Одежда", 7);
// Evaluate fuzzy set
set.evaluate();
// Show output variable's chart
//set.getVariable("Ощущение").chartDefuzzifier(true);
System.out.println(set.getVariable("Ощущение").getLatestDefuzzifiedValue());
System.out.println(set);
System.out.println(set.getVariable("Ощущение"));
System.out.println(
feel.getLinguisticTerms()
.entrySet()
.stream()
.max(Comparator.comparing(e -> e.getValue()
.getMembershipFunction()
.membership(set.getVariable("Ощущение").getLatestDefuzzifiedValue())))
.get()
.getValue().getTermName()
);
set.getVariable("Ощущение").chartDefuzzifier(true);
} }
} }