src/main/java/ru/ulstu/extractor/assessment/controller/AssessmentController.java

@@ -29,7 +29,7 @@ public class AssessmentController {
     public String getAssessments(Model model, @RequestParam Optional<Integer> branchId) {
         model.addAttribute("branches", branchService.findAll());
         if (branchId.isPresent()) {
-            model.addAttribute("assessments", fuzzyInferenceService.getAssessments(branchId.get()));
+            model.addAttribute("assessments", fuzzyInferenceService.getAssessmentsByForecastTendencies(branchId.get()));
             model.addAttribute("filterBranchForm", new FilterBranchForm(branchId.get()));
         } else {
             model.addAttribute("filterBranchForm", new FilterBranchForm());

src/main/java/ru/ulstu/extractor/assessment/model/Assessment.java

@@ -1,13 +1,22 @@
 package ru.ulstu.extractor.assessment.model;
 
+import ru.ulstu.extractor.rule.model.DbRule;
 import ru.ulstu.extractor.ts.model.TimeSeriesType;
 
 public class Assessment {
-    private String consequent;
-    private TimeSeriesType firstAntecedent;
-    private String firstAntecedentTendency;
-    private TimeSeriesType secondAntecedent;
-    private String secondAntecedentTendency;
+    private final String consequent;
+    private final TimeSeriesType firstAntecedent;
+    private final String firstAntecedentTendency;
+    private final TimeSeriesType secondAntecedent;
+    private final String secondAntecedentTendency;
+
+    public Assessment(DbRule dbRule) {
+        this.consequent = dbRule.getConsequent();
+        this.firstAntecedent = dbRule.getFirstAntecedent();
+        this.firstAntecedentTendency = dbRule.getFirstAntecedentValue().getAntecedentValue();
+        this.secondAntecedent = dbRule.getSecondAntecedent();
+        this.secondAntecedentTendency = dbRule.getSecondAntecedentValue().getAntecedentValue();
+    }
 
     public String getConsequent() {
         return consequent;

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

@@ -12,6 +12,7 @@ import com.fuzzylite.term.Triangle;
 import com.fuzzylite.variable.InputVariable;
 import com.fuzzylite.variable.OutputVariable;
 import org.springframework.stereotype.Service;
+import ru.ulstu.extractor.assessment.model.Assessment;
 import ru.ulstu.extractor.gitrepository.service.GitRepositoryService;
 import ru.ulstu.extractor.rule.model.AntecedentValue;
 import ru.ulstu.extractor.rule.model.DbRule;
@@ -22,6 +23,7 @@ import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.stream.Collectors;
+import java.util.stream.Stream;
 
 @Service
 public class FuzzyInferenceService {
@@ -56,13 +58,13 @@ public class FuzzyInferenceService {
                 dbRule.getFirstAntecedentValue().getAntecedentValue(),
                 dbRule.getSecondAntecedent().name(),
                 dbRule.getSecondAntecedentValue().getAntecedentValue(),
-                dbRule.getConsequent().replaceAll(" ", "_"));
+                dbRule.getId());
     }
 
     private RuleBlock getRuleBlock(Engine engine,
                                    Map<String, Double> variableValues,
                                    List<AntecedentValue> antecedentValues,
-                                   List<String> consequentValues) {
+                                   List<Integer> consequentValues) {
         variableValues.forEach((key, value) -> {
             InputVariable input = new InputVariable();
             input.setName(key);
@@ -86,7 +88,7 @@ public class FuzzyInferenceService {
         output.setDefaultValue(Double.NaN);
         output.setLockValueInRange(false);
         for (int i = 0; i < consequentValues.size(); i++) {
-            output.addTerm(new Triangle(consequentValues.get(i).replaceAll(" ", "_"), i - 0.1, i + 2.1));
+            output.addTerm(new Triangle(consequentValues.get(i).toString(), i - 0.1, i + 2.1));
         }
         engine.addOutputVariable(output);
 
@@ -109,15 +111,42 @@ public class FuzzyInferenceService {
         return engine;
     }
 
-    public String getAssessments(Integer branchId) {
+    public List<Assessment> getAssessmentsByForecastTendencies(Integer branchId) {
         List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
+        List<DbRule> dbRules = ruleService.getList();
+        return getAssessmentsByTimeSeriesTendencies(dbRules, timeSeries);
+    }
+
+    public List<Assessment> getAssessmentsByLastValues(Integer branchId) {
+        List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
+        List<DbRule> dbRules = ruleService.getList();
+        return getAssessmentsByLastValues(dbRules, timeSeries);
+    }
+
+    private List<Assessment> getFuzzyInference(List<DbRule> dbRules, Map<String, Double> variableValues) {
         Engine engine = getFuzzyEngine();
-        List<AntecedentValue> antecedentValues = antecedentValueService.getList();
-        List<String> consequentValues = ruleService.getConsequentList();
+        List<AntecedentValue> antecedentValues = Stream.concat(dbRules.stream().map(DbRule::getFirstAntecedentValue),
+                dbRules.stream().map(DbRule::getSecondAntecedentValue)).distinct().collect(Collectors.toList());
+        List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
+        engine.addRuleBlock(getRuleBlock(engine, variableValues, antecedentValues, consequentValues));
+        String consequent = getConsequent(engine, variableValues);
+        return dbRules
+                .stream()
+                .filter(r -> r.getId().equals(Integer.valueOf(consequent)))
+                .map(Assessment::new)
+                .collect(Collectors.toList());
+    }
+
+    private List<Assessment> getAssessmentsByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
         Map<String, Double> variableValues = new HashMap<>();
         timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), timeSeriesService.getLastTimeSeriesTendency(ts)));
-        engine.addRuleBlock(getRuleBlock(engine, variableValues, antecedentValues, consequentValues));
-        return getConsequent(engine, variableValues);
+        return getFuzzyInference(dbRules, variableValues);
+    }
+
+    private List<Assessment> getAssessmentsByLastValues(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
+        Map<String, Double> variableValues = new HashMap<>();
+        timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), ts.getValues().get(ts.getValues().size() - 1).getValue()));
+        return getFuzzyInference(dbRules, variableValues);
     }
 
     private void validateVariables(Map<String, Double> variableValues, List<DbRule> dbDbRules) {
@@ -144,7 +173,7 @@ public class FuzzyInferenceService {
             outputVariable.defuzzify();
         }
         return (outputVariable == null || Double.isNaN(outputVariable.getValue()))
-                ? "Нет рекомендаций"
+                ? "Нет результата"
                 : outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
     }
 }

src/main/resources/templates/assessments.html

@@ -35,18 +35,13 @@
         <input type="hidden" th:field="*{branchId}">
     </form>
     <div th:if="${assessments  != null}">
-        <h3>Состояние репозитория описывается следующими выражениями:</h3>
+        <h5>Состояние репозитория описывается следующими выражениями:</h5>
         <div th:each="assessment: ${assessments}">
-            <div th:text="${assessment.consequent}"></div>
-            вследствие тенденции
-            <div th:text="${assessment.firstAntecedentTendency}"></div>
-            показателя
-            <div th:text="${assessment.firstAntecedent}"></div>
-            и тенденции
-            <div th:text="${assessment.secondAntecedentTendency}"></div>
-            показателя
-            <div th:text="${assessment.secondAntecedent}"></div>
-            и
+            <span th:text="${assessment.consequent}"></span>
+            вследствие тенденции '<span th:text="${assessment.firstAntecedentTendency}"></span>' показателя '<span
+                th:text="${assessment.firstAntecedent.description}"></span>'
+            и тенденции '<span th:text="${assessment.secondAntecedentTendency}"></span>' показателя '<span
+                th:text="${assessment.secondAntecedent.description}"></span>';
         </div>
     </div>
 </div>