list of assessments #85
@ -1,39 +1,39 @@
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package ru.ulstu.extractor.recommendation.controller;
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package ru.ulstu.extractor.assessment.controller;
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import org.springframework.stereotype.Controller;
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import org.springframework.ui.Model;
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import org.springframework.web.bind.annotation.GetMapping;
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import org.springframework.web.bind.annotation.RequestParam;
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import ru.ulstu.extractor.assessment.model.FilterBranchForm;
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import ru.ulstu.extractor.branch.service.BranchService;
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import ru.ulstu.extractor.recommendation.model.FilterBranchForm;
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import ru.ulstu.extractor.rule.service.FuzzyInferenceService;
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import springfox.documentation.annotations.ApiIgnore;
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import java.util.Optional;
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import static ru.ulstu.extractor.core.Route.RECOMMENDATIONS;
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import static ru.ulstu.extractor.core.Route.ASSESSMENTS;
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@Controller
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@ApiIgnore
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public class RecommendationController {
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public class AssessmentController {
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private final FuzzyInferenceService fuzzyInferenceService;
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private final BranchService branchService;
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public RecommendationController(FuzzyInferenceService fuzzyInferenceService,
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BranchService branchService) {
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public AssessmentController(FuzzyInferenceService fuzzyInferenceService,
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BranchService branchService) {
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this.fuzzyInferenceService = fuzzyInferenceService;
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this.branchService = branchService;
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}
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@GetMapping(RECOMMENDATIONS)
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public String getRecommendations(Model model, @RequestParam Optional<Integer> branchId) {
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@GetMapping(ASSESSMENTS)
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public String getAssessments(Model model, @RequestParam Optional<Integer> branchId) {
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model.addAttribute("branches", branchService.findAll());
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if (branchId.isPresent()) {
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model.addAttribute("recommendations", fuzzyInferenceService.getRecommendations(branchId.get()));
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model.addAttribute("assessments", fuzzyInferenceService.getAssessmentsByForecastTendencies(branchId.get()));
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model.addAttribute("filterBranchForm", new FilterBranchForm(branchId.get()));
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} else {
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model.addAttribute("filterBranchForm", new FilterBranchForm());
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}
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return RECOMMENDATIONS;
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return ASSESSMENTS;
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}
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}
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@ -0,0 +1,40 @@
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package ru.ulstu.extractor.assessment.model;
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import ru.ulstu.extractor.rule.model.DbRule;
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import ru.ulstu.extractor.ts.model.TimeSeriesType;
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public class Assessment {
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private final String consequent;
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private final TimeSeriesType firstAntecedent;
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private final String firstAntecedentTendency;
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private final TimeSeriesType secondAntecedent;
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private final String secondAntecedentTendency;
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public Assessment(DbRule dbRule) {
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this.consequent = dbRule.getConsequent();
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this.firstAntecedent = dbRule.getFirstAntecedent();
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this.firstAntecedentTendency = dbRule.getFirstAntecedentValue().getAntecedentValue();
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this.secondAntecedent = dbRule.getSecondAntecedent();
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this.secondAntecedentTendency = dbRule.getSecondAntecedentValue().getAntecedentValue();
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}
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public String getConsequent() {
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return consequent;
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}
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public TimeSeriesType getFirstAntecedent() {
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return firstAntecedent;
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}
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public String getFirstAntecedentTendency() {
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return firstAntecedentTendency;
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}
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public TimeSeriesType getSecondAntecedent() {
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return secondAntecedent;
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}
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public String getSecondAntecedentTendency() {
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return secondAntecedentTendency;
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}
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}
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@ -1,4 +1,4 @@
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package ru.ulstu.extractor.recommendation.model;
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package ru.ulstu.extractor.assessment.model;
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public class FilterBranchForm {
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private Integer branchId;
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@ -19,7 +19,7 @@ public class Route {
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public static final String STATISTIC = "statistic";
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public static final String LIST_RULE = "listRules";
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public static final String ADD_RULE = "addRule";
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public static final String RECOMMENDATIONS = "recommendations";
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public static final String ASSESSMENTS = "assessments";
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public static final String DELETE_RULE = "deleteRule";
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public static String getLIST_INDEXED_REPOSITORIES() {
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@ -42,7 +42,7 @@ public class Route {
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return STATISTIC;
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}
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public static String getRECOMMENDATIONS() {
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return RECOMMENDATIONS;
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public static String getASSESSMENTS() {
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return ASSESSMENTS;
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}
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}
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@ -0,0 +1,7 @@
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package ru.ulstu.extractor.rule.model;
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public class AssessmentException extends RuntimeException {
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public AssessmentException(String message) {
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super(message);
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}
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}
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@ -12,16 +12,20 @@ import com.fuzzylite.term.Triangle;
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import com.fuzzylite.variable.InputVariable;
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import com.fuzzylite.variable.OutputVariable;
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import org.springframework.stereotype.Service;
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import ru.ulstu.extractor.assessment.model.Assessment;
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import ru.ulstu.extractor.gitrepository.service.GitRepositoryService;
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import ru.ulstu.extractor.rule.model.AntecedentValue;
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import ru.ulstu.extractor.rule.model.AssessmentException;
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import ru.ulstu.extractor.rule.model.DbRule;
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import ru.ulstu.extractor.ts.model.TimeSeries;
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import ru.ulstu.extractor.ts.service.TimeSeriesService;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.stream.Collectors;
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import java.util.stream.Stream;
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@Service
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public class FuzzyInferenceService {
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@ -29,6 +33,7 @@ public class FuzzyInferenceService {
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private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then "
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+ OUTPUT_VARIABLE_NAME
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+ " is %s";
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private final static String NO_RESULT = "Нет результата";
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private final DbRuleService ruleService;
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private final AntecedentValueService antecedentValueService;
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private final GitRepositoryService gitRepositoryService;
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@ -44,10 +49,9 @@ public class FuzzyInferenceService {
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this.timeSeriesService = timeSeriesService;
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}
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public List<String> getRulesFromDb(Map<String, Double> variableValues) {
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List<DbRule> dbDbRules = ruleService.getList();
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validateVariables(variableValues, dbDbRules);
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return dbDbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
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public List<String> getRulesFromDb(List<DbRule> dbRules, Map<String, Double> variableValues) {
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validateVariables(variableValues, dbRules);
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return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
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}
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private String getFuzzyRule(DbRule dbRule) {
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@ -56,13 +60,14 @@ public class FuzzyInferenceService {
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dbRule.getFirstAntecedentValue().getAntecedentValue(),
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dbRule.getSecondAntecedent().name(),
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dbRule.getSecondAntecedentValue().getAntecedentValue(),
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dbRule.getConsequent().replaceAll(" ", "_"));
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dbRule.getId());
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}
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private RuleBlock getRuleBlock(Engine engine,
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List<DbRule> dbRules,
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Map<String, Double> variableValues,
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List<AntecedentValue> antecedentValues,
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List<String> consequentValues) {
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List<Integer> consequentValues) {
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variableValues.forEach((key, value) -> {
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InputVariable input = new InputVariable();
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input.setName(key);
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@ -86,7 +91,7 @@ public class FuzzyInferenceService {
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output.setDefaultValue(Double.NaN);
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output.setLockValueInRange(false);
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for (int i = 0; i < consequentValues.size(); i++) {
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output.addTerm(new Triangle(consequentValues.get(i).replaceAll(" ", "_"), i - 0.1, i + 2.1));
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output.addTerm(new Triangle(consequentValues.get(i).toString(), i - 0.1, i + 2.1));
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}
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engine.addOutputVariable(output);
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@ -98,7 +103,7 @@ public class FuzzyInferenceService {
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mamdani.setDisjunction(new BoundedSum());
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mamdani.setImplication(new AlgebraicProduct());
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mamdani.setActivation(new Highest());
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getRulesFromDb(variableValues).forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
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getRulesFromDb(dbRules, variableValues).forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
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return mamdani;
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}
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@ -109,15 +114,67 @@ public class FuzzyInferenceService {
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return engine;
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}
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public String getRecommendations(Integer branchId) {
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public List<Assessment> getAssessmentsByForecastTendencies(Integer branchId) {
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List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
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List<DbRule> dbRules = ruleService.getList();
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try {
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return getAssessmentsByTimeSeriesTendencies(dbRules, timeSeries);
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} catch (AssessmentException ex) {
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return new ArrayList<>();
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}
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}
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public List<Assessment> getAssessmentsByLastValues(Integer branchId) {
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List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
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List<DbRule> dbRules = ruleService.getList();
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return getAssessmentsByLastValues(dbRules, timeSeries);
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}
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private List<Assessment> getFuzzyInference(List<DbRule> dbRules, Map<String, Double> variableValues) {
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Engine engine = getFuzzyEngine();
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List<AntecedentValue> antecedentValues = antecedentValueService.getList();
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List<String> consequentValues = ruleService.getConsequentList();
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List<AntecedentValue> antecedentValues = Stream.concat(dbRules.stream().map(DbRule::getFirstAntecedentValue),
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dbRules.stream().map(DbRule::getSecondAntecedentValue)).distinct().collect(Collectors.toList());
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List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
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engine.addRuleBlock(getRuleBlock(engine, dbRules, variableValues, antecedentValues, consequentValues));
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String consequent = getConsequent(engine, variableValues);
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if (consequent.equals(NO_RESULT)) {
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return new ArrayList<>();
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}
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return dbRules
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.stream()
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.filter(r -> r.getId().equals(Integer.valueOf(consequent)))
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.map(Assessment::new)
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.collect(Collectors.toList());
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}
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private List<Assessment> getSingleAssessmentByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) throws AssessmentException {
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Map<String, Double> variableValues = new HashMap<>();
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timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), timeSeriesService.getLastTimeSeriesTendency(ts)));
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engine.addRuleBlock(getRuleBlock(engine, variableValues, antecedentValues, consequentValues));
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return getConsequent(engine, variableValues);
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timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(),
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timeSeriesService.getLastTimeSeriesTendency(ts)
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.orElseThrow(() -> new AssessmentException(""))));
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return getFuzzyInference(dbRules, variableValues);
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}
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private List<Assessment> getAssessmentsByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
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return dbRules
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.stream()
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.flatMap(dbRule -> {
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Map<String, Double> variableValues = new HashMap<>();
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timeSeries
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.stream()
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.filter(ts -> ts.getTimeSeriesType() == dbRule.getFirstAntecedent()
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|| ts.getTimeSeriesType() == dbRule.getSecondAntecedent())
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.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), timeSeriesService
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.getLastTimeSeriesTendency(ts)
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.orElseThrow(() -> new AssessmentException(""))));
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return getFuzzyInference(List.of(dbRule), variableValues).stream();
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}).collect(Collectors.toList());
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}
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private List<Assessment> getAssessmentsByLastValues(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
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Map<String, Double> variableValues = new HashMap<>();
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timeSeries.forEach(ts -> variableValues.put(ts.getTimeSeriesType().name(), ts.getValues().get(ts.getValues().size() - 1).getValue()));
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return getFuzzyInference(dbRules, variableValues);
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}
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private void validateVariables(Map<String, Double> variableValues, List<DbRule> dbDbRules) {
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@ -144,7 +201,7 @@ public class FuzzyInferenceService {
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outputVariable.defuzzify();
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}
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return (outputVariable == null || Double.isNaN(outputVariable.getValue()))
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? "Нет рекомендаций"
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? NO_RESULT
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: outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
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}
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}
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@ -115,16 +115,16 @@ public class TimeSeriesService {
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return timeSeriesRepository.getTimeSeriesByBranchId(branchId);
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}
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public Double getLastTimeSeriesTendency(TimeSeries ts) {
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public Optional<Double> getLastTimeSeriesTendency(TimeSeries ts) {
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if (ts != null && ts.getValues().size() > 5) {
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JSONObject response = httpService.post(TIME_SERIES_TENDENCY_URL, new JSONObject(new SmoothingTimeSeries(ts)));
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LOG.debug("Успешно отправлен на сервис сглаживания");
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if (response.has("response") && response.getString("response").equals("empty")) {
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return 0.0;
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return Optional.empty();
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}
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JSONArray jsonArray = response.getJSONObject("timeSeries").getJSONArray("values");
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return jsonArray.getJSONObject(jsonArray.length() - 1).getDouble("value");
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return Optional.of(jsonArray.getJSONObject(jsonArray.length() - 1).getDouble("value"));
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}
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return 0.0;
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return Optional.empty();
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}
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}
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@ -7,7 +7,7 @@
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8"/>
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</head>
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<div class="container" layout:fragment="content">
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<form action="#" th:action="${@route.RECOMMENDATIONS}" th:object="${filterBranchForm}" method="get">
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<form action="#" th:action="${@route.ASSESSMENTS}" th:object="${filterBranchForm}" method="get">
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<div class="row">
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<div class="col-md-2 col-sm-12">
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Репозиторий-ветка
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@ -26,17 +26,26 @@
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])
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;
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$('#select-branch').selectpicker('refresh');
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</script>
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</div>
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<input type="submit" class="btn btn-outline-success w-100" value="Применить фильтр"/>
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</div>
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<div th:if="*{branchId == null}">Выбрерите ветку для получения рекомендаций</div>
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<div th:if="*{branchId == null}">Выбрерите ветку для получения оценки репозитория</div>
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<input type="hidden" th:field="*{branchId}">
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</form>
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<div th:each="recommendation: ${recommendations}">
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<div th:text="${recommendation}"></div>
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<div th:if="${assessments != null && #lists.size(assessments) > 0}">
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<h5>Состояние репозитория описывается следующими выражениями:</h5>
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<div th:each="assessment: ${assessments}">
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<span th:text="${assessment.consequent}"></span>
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вследствие тенденции '<span th:text="${assessment.firstAntecedentTendency}"></span>' показателя '<span
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th:text="${assessment.firstAntecedent.description}"></span>'
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и тенденции '<span th:text="${assessment.secondAntecedentTendency}"></span>' показателя '<span
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th:text="${assessment.secondAntecedent.description}"></span>';
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</div>
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</div>
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<div th:if="${assessments != null && #lists.size(assessments) == 0}">
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<h5>Нет результатов</h5>
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</div>
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</div>
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</html>
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@ -41,7 +41,7 @@
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<a class="nav-link" href="/listRules" th:text="Правила">Link</a>
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</li>
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<li class="nav-item">
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<a class="nav-link" href="/recommendations" th:text="Рекомендации">Link</a>
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<a class="nav-link" href="/assessments" th:text="Рекомендации">Link</a>
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</li>
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</ul>
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</div>
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|
Loading…
Reference in New Issue
Block a user