src/main/java/ru/ulstu/fc/rule/controller/InferenceMvcController.java

@@ -8,12 +8,18 @@ import org.springframework.web.bind.annotation.RequestMapping;
 import org.springframework.web.bind.annotation.RequestMethod;
 import ru.ulstu.fc.rule.model.Antecedent;
 import ru.ulstu.fc.rule.model.InferenceForm;
+import ru.ulstu.fc.rule.service.FuzzyInferenceService;
 
 import java.util.Arrays;
 import java.util.List;
 
 @Controller
 public class InferenceMvcController {
+    private final FuzzyInferenceService fuzzyInferenceService;
+
+    public InferenceMvcController(FuzzyInferenceService fuzzyInferenceService) {
+        this.fuzzyInferenceService = fuzzyInferenceService;
+    }
 
     @GetMapping("/")
     public String initInference(Model model) {
@@ -28,7 +34,7 @@ public class InferenceMvcController {
         model.addAttribute("ageAntecedents", getAgeAntecedents());
         model.addAttribute("incomeAntecedents", getIncomeAntecedents());
         model.addAttribute("inferenceForm", inferenceForm);
-        model.addAttribute("response", "123");
+        model.addAttribute("response", fuzzyInferenceService.getFuzzyInference().get(0));
         return "index";
     }
 

src/main/java/ru/ulstu/fc/rule/service/FuzzyInferenceService.java

@@ -1,84 +1,115 @@
 package ru.ulstu.fc.rule.service;
 
 import com.fuzzylite.Engine;
+import com.fuzzylite.activation.General;
+import com.fuzzylite.defuzzifier.Centroid;
+import com.fuzzylite.norm.s.Maximum;
+import com.fuzzylite.norm.t.AlgebraicProduct;
+import com.fuzzylite.norm.t.Minimum;
+import com.fuzzylite.rule.Rule;
+import com.fuzzylite.rule.RuleBlock;
 import com.fuzzylite.term.Activated;
+import com.fuzzylite.term.Triangle;
 import com.fuzzylite.variable.InputVariable;
 import com.fuzzylite.variable.OutputVariable;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.stereotype.Service;
 
+import java.util.AbstractMap;
+import java.util.ArrayList;
+import java.util.List;
 import java.util.Map;
+import java.util.Map.Entry;
 import java.util.stream.Collectors;
 
 @Service
 public class FuzzyInferenceService {
     private final static Logger LOG = LoggerFactory.getLogger(FuzzyInferenceService.class);
-    private final static String OUTPUT_VARIABLE_NAME = "state";
+    private final static String OUTPUT_VARIABLE_NAME = "кредит";
     private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then "
             + OUTPUT_VARIABLE_NAME
             + " is %s";
     private final static String NO_RESULT = "Нет результата";
 
-//    private List<String> mapRulesToString(List<DbRule> dbRules) {
-//        return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
-//    }
+    private Map<String, List<Entry<String, Integer>>> inputFuzzyTerms = Map.of(
+            "возраст",
+            List.of(
+                    new AbstractMap.SimpleEntry("молодой", 35),
+                    new AbstractMap.SimpleEntry("средний", 60),
+                    new AbstractMap.SimpleEntry("старый", 100)),
+            "доход",
+            List.of(
+                    new AbstractMap.SimpleEntry("небольшой", 35000),
+                    new AbstractMap.SimpleEntry("средний", 100000),
+                    new AbstractMap.SimpleEntry("высокий", 500000)));
 
-//    private String getFuzzyRule(DbRule dbRule) {
-//        return format(RULE_TEMPLATE,
-//                dbRule.getFirstAntecedent().name(),
-//                dbRule.getFirstAntecedentValue().getAntecedentValue(),
-//                dbRule.getSecondAntecedent().name(),
-//                dbRule.getSecondAntecedentValue().getAntecedentValue(),
-//                dbRule.getId());
-//    }
+    private Map<String, List<Entry<String, Integer>>> outputFuzzyTerms = Map.of(
+            "кредит", List.of(new AbstractMap.SimpleEntry("небольшой", 200000),
+                    new AbstractMap.SimpleEntry("средний", 100000),
+                    new AbstractMap.SimpleEntry("большой", 1000000)));
 
-//    private RuleBlock getRuleBlock(Engine engine,
-//                                   List<DbRule> dbRules,
-//                                   Map<String, Double> variableValues,
-//                                   List<AntecedentValue> antecedentValues,
-//                                   List<Integer> consequentValues) {
-//        variableValues.forEach((key, value) -> {
-//            InputVariable input = new InputVariable();
-//            input.setName(key);
-//            input.setDescription("");
-//            input.setEnabled(true);
-//            input.setRange(-1, 1);
-//            input.setLockValueInRange(false);
-//            input.addTerm(new Triangle("спад", -1, 0));
-//            input.addTerm(new Triangle("стабильно", -0.1, 0.1));
-//            input.addTerm(new Triangle("рост", 0, 1));
-//            engine.addInputVariable(input);
-//        });
-//
-//        OutputVariable output = new OutputVariable();
-//        output.setName(OUTPUT_VARIABLE_NAME);
-//        output.setDescription("");
-//        output.setEnabled(true);
-//        output.setRange(0, consequentValues.size() + 0.1);
-//        output.setAggregation(new Maximum());
-//        output.setDefuzzifier(new Centroid(10));
-//        output.setDefaultValue(Double.NaN);
-//        output.setLockValueInRange(false);
-//        for (int i = 0; i < consequentValues.size(); i++) {
-//            output.addTerm(new Triangle(consequentValues.get(i).toString(), i, i + 1));
-//        }
-//        engine.addOutputVariable(output);
-//
-//        RuleBlock mamdani = new RuleBlock();
-//        mamdani.setName("mamdani");
-//        mamdani.setDescription("");
-//        mamdani.setEnabled(true);
-//        mamdani.setConjunction(new Minimum());
-//        //mamdani.setDisjunction(null);
-//        mamdani.setImplication(new AlgebraicProduct());
-//        mamdani.setActivation(new General());
-//        mapRulesToString(dbRules).forEach(r -> {
-//            LOG.info(r);
-//            mamdani.addRule(Rule.parse(r, engine));
-//        });
-//        return mamdani;
-//    }
+    private List<String> getDemoRules() {
+        return List.of(
+                String.format(RULE_TEMPLATE, "возраст", "молодой", "доход", "высокий", "большой"),
+                String.format(RULE_TEMPLATE, "возраст", "средний", "доход", "высокий", "средний"),
+                String.format(RULE_TEMPLATE, "возраст", "старый", "доход", "высокий", "средний")
+        );
+    }
+
+    private List<InputVariable> getInputVariables() {
+        return List.of(getInputVariable("возраст", inputFuzzyTerms.get("возраст")),
+                getInputVariable("доход", inputFuzzyTerms.get("доход")));
+    }
+
+    private InputVariable getInputVariable(String name, List<Entry<String, Integer>> terms) {
+        final InputVariable input = new InputVariable();
+        input.setName(name);
+        input.setDescription("");
+        input.setEnabled(true);
+        input.setLockValueInRange(false);
+        double prev = 0;
+        for (int i = 0; i < terms.size(); i++) {
+            Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
+            prev = term.getVertexB();
+            input.addTerm(term);
+        }
+        return input;
+    }
+
+    private <T extends Enum<T>> OutputVariable getOutputVariable(String name, List<Entry<String, Integer>> terms) {
+        final OutputVariable output = new OutputVariable();
+        output.setName(name);
+        output.setDescription("");
+        output.setEnabled(true);
+        output.setAggregation(new Maximum());
+        output.setDefuzzifier(new Centroid(10));
+        output.setDefaultValue(Double.NaN);
+        output.setLockValueInRange(false);
+        double prev = 0;
+        for (int i = 0; i < terms.size(); i++) {
+            Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
+            prev = term.getVertexB();
+            output.addTerm(term);
+        }
+        return output;
+    }
+
+    private RuleBlock getRuleBlock(Engine engine,
+                                   List<String> rules) {
+        getInputVariables().forEach(engine::addInputVariable);
+        engine.addOutputVariable(getOutputVariable("кредит", outputFuzzyTerms.get("кредит")));
+
+        RuleBlock mamdani = new RuleBlock();
+        mamdani.setName("mamdani");
+        mamdani.setDescription("");
+        mamdani.setEnabled(true);
+        mamdani.setConjunction(new Minimum());
+        mamdani.setImplication(new AlgebraicProduct());
+        mamdani.setActivation(new General());
+        rules.forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
+        return mamdani;
+    }
 
     private Engine getFuzzyEngine() {
         Engine engine = new Engine();
@@ -87,29 +118,6 @@ public class FuzzyInferenceService {
         return engine;
     }
 
-//    public List<Assessment> getFuzzyInference(List<DbRule> dbRules,
-//                                              List<AntecedentValue> antecedentValues,
-//                                              Map<String, Double> variableValues) {
-//        validateVariables(variableValues, dbRules);
-//        variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
-//        Engine engine = getFuzzyEngine();
-//        List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
-//        engine.addRuleBlock(getRuleBlock(engine, dbRules, variableValues, antecedentValues, consequentValues));
-//        Map<String, Double> consequents = getConsequent(engine, variableValues);
-//        if (consequents.containsKey(NO_RESULT)) {
-//            return new ArrayList<>();
-//        }
-//        List<Assessment> assessments = new ArrayList<>();
-//        for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
-//            for (DbRule dbRule : dbRules) {
-//                if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
-//                    assessments.add(new Assessment(dbRule, consequent.getValue()));
-//                }
-//            }
-//        }
-//        return assessments;
-//    }
-
     private Map<String, Double> getConsequent(Engine engine, Map<String, Double> variableValues) {
         OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME);
         for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
@@ -124,4 +132,25 @@ public class FuzzyInferenceService {
                 ? Map.of(NO_RESULT, 0.0)
                 : outputVariable.fuzzyOutput().getTerms().stream().collect(Collectors.toMap(t -> t.getTerm().getName(), Activated::getDegree));
     }
+
+    public List<Double> getFuzzyInference() {
+        //variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
+        Engine engine = getFuzzyEngine();
+        //List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
+        engine.addRuleBlock(getRuleBlock(engine, getDemoRules()));
+        Map<String, Double> consequents = getConsequent(engine, Map.of("возраст", 20.0, "доход", 250000.0));
+        if (consequents.containsKey(NO_RESULT)) {
+            return new ArrayList<>();
+        }
+        /*List<Assessment> assessments = new ArrayList<>();
+        for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
+            for (DbRule dbRule : dbRules) {
+                if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
+                    assessments.add(new Assessment(dbRule, consequent.getValue()));
+                }
+            }
+        }*/
+        return List.of(0.0);
+    }
+
 }