Merge pull request 'list of assessments' (#85) from 84-list-of-consequents into master

Reviewed-on: #85

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

@@ -1,39 +1,39 @@
-package ru.ulstu.extractor.recommendation.controller;
+package ru.ulstu.extractor.assessment.controller;
 
 import org.springframework.stereotype.Controller;
 import org.springframework.ui.Model;
 import org.springframework.web.bind.annotation.GetMapping;
 import org.springframework.web.bind.annotation.RequestParam;
+import ru.ulstu.extractor.assessment.model.FilterBranchForm;
 import ru.ulstu.extractor.branch.service.BranchService;
-import ru.ulstu.extractor.recommendation.model.FilterBranchForm;
 import ru.ulstu.extractor.rule.service.FuzzyInferenceService;
 import springfox.documentation.annotations.ApiIgnore;
 
 import java.util.Optional;
 
-import static ru.ulstu.extractor.core.Route.RECOMMENDATIONS;
+import static ru.ulstu.extractor.core.Route.ASSESSMENTS;
 
 @Controller
 @ApiIgnore
-public class RecommendationController {
+public class AssessmentController {
     private final FuzzyInferenceService fuzzyInferenceService;
     private final BranchService branchService;
 
-    public RecommendationController(FuzzyInferenceService fuzzyInferenceService,
-                                    BranchService branchService) {
+    public AssessmentController(FuzzyInferenceService fuzzyInferenceService,
+                                BranchService branchService) {
         this.fuzzyInferenceService = fuzzyInferenceService;
         this.branchService = branchService;
     }
 
-    @GetMapping(RECOMMENDATIONS)
-    public String getRecommendations(Model model, @RequestParam Optional<Integer> branchId) {
+    @GetMapping(ASSESSMENTS)
+    public String getAssessments(Model model, @RequestParam Optional<Integer> branchId) {
         model.addAttribute("branches", branchService.findAll());
         if (branchId.isPresent()) {
-            model.addAttribute("recommendations", fuzzyInferenceService.getRecommendations(branchId.get()));
+            model.addAttribute("assessments", fuzzyInferenceService.getAssessmentsByForecastTendencies(branchId.get()));
             model.addAttribute("filterBranchForm", new FilterBranchForm(branchId.get()));
         } else {
             model.addAttribute("filterBranchForm", new FilterBranchForm());
         }
-        return RECOMMENDATIONS;
+        return ASSESSMENTS;
     }
 }

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

@@ -0,0 +1,40 @@
+package ru.ulstu.extractor.assessment.model;
+
+import ru.ulstu.extractor.rule.model.DbRule;
+import ru.ulstu.extractor.ts.model.TimeSeriesType;
+
+public class Assessment {
+    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;
+    }
+
+    public TimeSeriesType getFirstAntecedent() {
+        return firstAntecedent;
+    }
+
+    public String getFirstAntecedentTendency() {
+        return firstAntecedentTendency;
+    }
+
+    public TimeSeriesType getSecondAntecedent() {
+        return secondAntecedent;
+    }
+
+    public String getSecondAntecedentTendency() {
+        return secondAntecedentTendency;
+    }
+}

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

@@ -1,4 +1,4 @@
-package ru.ulstu.extractor.recommendation.model;
+package ru.ulstu.extractor.assessment.model;
 
 public class FilterBranchForm {
     private Integer branchId;

src/main/java/ru/ulstu/extractor/core/Route.java

@@ -19,7 +19,7 @@ public class Route {
     public static final String STATISTIC = "statistic";
     public static final String LIST_RULE = "listRules";
     public static final String ADD_RULE = "addRule";
-    public static final String RECOMMENDATIONS = "recommendations";
+    public static final String ASSESSMENTS = "assessments";
     public static final String DELETE_RULE = "deleteRule";
 
     public static String getLIST_INDEXED_REPOSITORIES() {
@@ -42,7 +42,7 @@ public class Route {
         return STATISTIC;
     }
 
-    public static String getRECOMMENDATIONS() {
-        return RECOMMENDATIONS;
+    public static String getASSESSMENTS() {
+        return ASSESSMENTS;
     }
 }

src/main/java/ru/ulstu/extractor/rule/model/AssessmentException.java

@@ -0,0 +1,7 @@
+package ru.ulstu.extractor.rule.model;
+
+public class AssessmentException extends RuntimeException {
+    public AssessmentException(String message) {
+        super(message);
+    }
+}

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

@@ -12,16 +12,20 @@ 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.AssessmentException;
 import ru.ulstu.extractor.rule.model.DbRule;
 import ru.ulstu.extractor.ts.model.TimeSeries;
 import ru.ulstu.extractor.ts.service.TimeSeriesService;
 
+import java.util.ArrayList;
 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 {
@@ -29,6 +33,7 @@ public class FuzzyInferenceService {
     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 final DbRuleService ruleService;
     private final AntecedentValueService antecedentValueService;
     private final GitRepositoryService gitRepositoryService;
@@ -44,10 +49,9 @@ public class FuzzyInferenceService {
         this.timeSeriesService = timeSeriesService;
     }
 
-    public List<String> getRulesFromDb(Map<String, Double> variableValues) {
-        List<DbRule> dbDbRules = ruleService.getList();
-        validateVariables(variableValues, dbDbRules);
-        return dbDbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
+    public List<String> getRulesFromDb(List<DbRule> dbRules, Map<String, Double> variableValues) {
+        validateVariables(variableValues, dbRules);
+        return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
     }
 
     private String getFuzzyRule(DbRule dbRule) {
@@ -56,13 +60,14 @@ public class FuzzyInferenceService {
                 dbRule.getFirstAntecedentValue().getAntecedentValue(),
                 dbRule.getSecondAntecedent().name(),
                 dbRule.getSecondAntecedentValue().getAntecedentValue(),
-                dbRule.getConsequent().replaceAll(" ", "_"));
+                dbRule.getId());
     }
 
     private RuleBlock getRuleBlock(Engine engine,
+                                   List<DbRule> dbRules,
                                    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 +91,7 @@ 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);
 
@@ -98,7 +103,7 @@ public class FuzzyInferenceService {
         mamdani.setDisjunction(new BoundedSum());
         mamdani.setImplication(new AlgebraicProduct());
         mamdani.setActivation(new Highest());
-        getRulesFromDb(variableValues).forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
+        getRulesFromDb(dbRules, variableValues).forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
         return mamdani;
     }
 
@@ -109,15 +114,67 @@ public class FuzzyInferenceService {
         return engine;
     }
 
-    public String getRecommendations(Integer branchId) {
+    public List<Assessment> getAssessmentsByForecastTendencies(Integer branchId) {
         List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
+        List<DbRule> dbRules = ruleService.getList();
+        try {
+            return getAssessmentsByTimeSeriesTendencies(dbRules, timeSeries);
+        } catch (AssessmentException ex) {
+            return new ArrayList<>();
+        }
+    }
+
+    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, dbRules, variableValues, antecedentValues, consequentValues));
+        String consequent = getConsequent(engine, variableValues);
+        if (consequent.equals(NO_RESULT)) {
+            return new ArrayList<>();
+        }
+        return dbRules
+                .stream()
+                .filter(r -> r.getId().equals(Integer.valueOf(consequent)))
+                .map(Assessment::new)
+                .collect(Collectors.toList());
+    }
+
+    private List<Assessment> getSingleAssessmentByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) throws AssessmentException {
+        Map<String, Double> variableValues = new HashMap<>();
+        timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(),
+                timeSeriesService.getLastTimeSeriesTendency(ts)
+                        .orElseThrow(() -> new AssessmentException(""))));
+        return getFuzzyInference(dbRules, variableValues);
+    }
+
+    private List<Assessment> getAssessmentsByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
+        return dbRules
+                .stream()
+                .flatMap(dbRule -> {
+                    Map<String, Double> variableValues = new HashMap<>();
+                    timeSeries
+                            .stream()
+                            .filter(ts -> ts.getTimeSeriesType() == dbRule.getFirstAntecedent()
+                                    || ts.getTimeSeriesType() == dbRule.getSecondAntecedent())
+                            .forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), timeSeriesService
+                                    .getLastTimeSeriesTendency(ts)
+                                    .orElseThrow(() -> new AssessmentException(""))));
+                    return getFuzzyInference(List.of(dbRule), variableValues).stream();
+                }).collect(Collectors.toList());
+    }
+
+    private List<Assessment> getAssessmentsByLastValues(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);
+        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 +201,7 @@ public class FuzzyInferenceService {
             outputVariable.defuzzify();
         }
         return (outputVariable == null || Double.isNaN(outputVariable.getValue()))
-                ? "Нет рекомендаций"
+                ? NO_RESULT
                 : outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
     }
 }

src/main/java/ru/ulstu/extractor/ts/service/TimeSeriesService.java

@@ -115,16 +115,16 @@ public class TimeSeriesService {
         return timeSeriesRepository.getTimeSeriesByBranchId(branchId);
     }
 
-    public Double getLastTimeSeriesTendency(TimeSeries ts) {
+    public Optional<Double> getLastTimeSeriesTendency(TimeSeries ts) {
         if (ts != null && ts.getValues().size() > 5) {
             JSONObject response = httpService.post(TIME_SERIES_TENDENCY_URL, new JSONObject(new SmoothingTimeSeries(ts)));
             LOG.debug("Успешно отправлен на сервис сглаживания");
             if (response.has("response") && response.getString("response").equals("empty")) {
-                return 0.0;
+                return Optional.empty();
             }
             JSONArray jsonArray = response.getJSONObject("timeSeries").getJSONArray("values");
-            return jsonArray.getJSONObject(jsonArray.length() - 1).getDouble("value");
+            return Optional.of(jsonArray.getJSONObject(jsonArray.length() - 1).getDouble("value"));
         }
-        return 0.0;
+        return Optional.empty();
     }
 }

src/main/resources/templates/assessments.html

@@ -7,7 +7,7 @@
     <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"/>
 </head>
 <div class="container" layout:fragment="content">
-    <form action="#" th:action="${@route.RECOMMENDATIONS}" th:object="${filterBranchForm}" method="get">
+    <form action="#" th:action="${@route.ASSESSMENTS}" th:object="${filterBranchForm}" method="get">
         <div class="row">
             <div class="col-md-2 col-sm-12">
                 Репозиторий-ветка
@@ -26,17 +26,26 @@
                     ])
                     ;
                     $('#select-branch').selectpicker('refresh');
-
                 </script>
             </div>
             <input type="submit" class="btn btn-outline-success  w-100" value="Применить фильтр"/>
         </div>
-        <div th:if="*{branchId == null}">Выбрерите ветку для получения рекомендаций</div>
+        <div th:if="*{branchId == null}">Выбрерите ветку для получения оценки репозитория</div>
 
         <input type="hidden" th:field="*{branchId}">
     </form>
-    <div th:each="recommendation: ${recommendations}">
-        <div th:text="${recommendation}"></div>
+    <div th:if="${assessments != null && #lists.size(assessments) > 0}">
+        <h5>Состояние репозитория описывается следующими выражениями:</h5>
+        <div th:each="assessment: ${assessments}">
+            <span th:text="${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 th:if="${assessments != null && #lists.size(assessments) == 0}">
+        <h5>Нет результатов</h5>
     </div>
 </div>
 </html>

src/main/resources/templates/default.html

@@ -41,7 +41,7 @@
                 <a class="nav-link" href="/listRules" th:text="Правила">Link</a>
             </li>
             <li class="nav-item">
-                <a class="nav-link" href="/recommendations" th:text="Рекомендации">Link</a>
+                <a class="nav-link" href="/assessments" th:text="Рекомендации">Link</a>
             </li>
         </ul>
     </div>