Merge branch 'master' into 78-add-keeping-new-ts
# Conflicts: # src/main/java/ru/ulstu/extractor/ts/model/TimeSeries.javapull/79/head
commit
23a852786a
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package ru.ulstu.extractor.http;
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import ru.ulstu.extractor.ts.model.TimeSeries;
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public class SmoothingTimeSeries {
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private JsonTimeSeries originalTimeSeries;
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private String methodClassName;
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public SmoothingTimeSeries(TimeSeries timeSeries) {
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originalTimeSeries = new JsonTimeSeries(timeSeries);
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this.methodClassName = "FTransform";
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}
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public JsonTimeSeries getOriginalTimeSeries() {
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return originalTimeSeries;
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}
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public void setOriginalTimeSeries(JsonTimeSeries originalTimeSeries) {
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this.originalTimeSeries = originalTimeSeries;
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}
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public String getMethodClassName() {
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return methodClassName;
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}
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public void setMethodClassName(String methodClassName) {
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this.methodClassName = methodClassName;
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}
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}
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package ru.ulstu.extractor.recommendation.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.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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@Controller
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@ApiIgnore
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public class RecommendationController {
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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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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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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("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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}
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}
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package ru.ulstu.extractor.recommendation.model;
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public class FilterBranchForm {
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private Integer branchId;
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public FilterBranchForm() {
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}
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public FilterBranchForm(Integer branchId) {
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this.branchId = branchId;
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}
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public Integer getBranchId() {
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return branchId;
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}
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public void setBranchId(Integer branchId) {
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this.branchId = branchId;
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}
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}
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@ -1,7 +1,7 @@
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package ru.ulstu.extractor.rule.repository;
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import org.springframework.data.jpa.repository.JpaRepository;
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import ru.ulstu.extractor.rule.model.Rule;
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import ru.ulstu.extractor.rule.model.DbRule;
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public interface RuleRepository extends JpaRepository<Rule, Integer> {
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public interface RuleRepository extends JpaRepository<DbRule, Integer> {
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}
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package ru.ulstu.extractor.rule.service;
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import com.fuzzylite.Engine;
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import com.fuzzylite.activation.Highest;
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import com.fuzzylite.defuzzifier.Centroid;
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import com.fuzzylite.norm.s.BoundedSum;
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import com.fuzzylite.norm.s.Maximum;
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import com.fuzzylite.norm.t.AlgebraicProduct;
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import com.fuzzylite.rule.Rule;
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import com.fuzzylite.rule.RuleBlock;
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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.gitrepository.service.GitRepositoryService;
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import ru.ulstu.extractor.rule.model.AntecedentValue;
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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.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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@Service
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public class FuzzyInferenceService {
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private final static String OUTPUT_VARIABLE_NAME = "state";
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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 DbRuleService ruleService;
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private final AntecedentValueService antecedentValueService;
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private final GitRepositoryService gitRepositoryService;
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private final TimeSeriesService timeSeriesService;
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public FuzzyInferenceService(DbRuleService ruleService,
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AntecedentValueService antecedentValueService,
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GitRepositoryService gitRepositoryService,
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TimeSeriesService timeSeriesService) {
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this.ruleService = ruleService;
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this.antecedentValueService = antecedentValueService;
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this.gitRepositoryService = gitRepositoryService;
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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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}
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private String getFuzzyRule(DbRule dbRule) {
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return String.format(RULE_TEMPLATE,
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dbRule.getFirstAntecedent().name(),
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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());
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}
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private RuleBlock getRuleBlock(Engine engine,
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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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variableValues.forEach((key, value) -> {
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InputVariable input = new InputVariable();
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input.setName(key);
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input.setDescription("");
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input.setEnabled(true);
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input.setRange(-0.1, antecedentValues.size() + 1.1);
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input.setLockValueInRange(false);
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for (int i = 0; i < antecedentValues.size(); i++) {
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input.addTerm(new Triangle(antecedentValues.get(i).getAntecedentValue(), i - 0.1, i + 2.1));
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}
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engine.addInputVariable(input);
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});
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OutputVariable output = new OutputVariable();
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output.setName(OUTPUT_VARIABLE_NAME);
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output.setDescription("");
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output.setEnabled(true);
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output.setRange(-0.1, antecedentValues.size() + 0.1);
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output.setAggregation(new Maximum());
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output.setDefuzzifier(new Centroid(100));
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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), i - 0.1, i + 2.1));
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}
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engine.addOutputVariable(output);
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RuleBlock mamdani = new RuleBlock();
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mamdani.setName("mamdani");
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mamdani.setDescription("");
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mamdani.setEnabled(true);
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mamdani.setConjunction(new AlgebraicProduct());
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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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return mamdani;
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}
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private Engine getFuzzyEngine() {
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Engine engine = new Engine();
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engine.setName("Git rules");
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engine.setDescription("");
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return engine;
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}
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public String getRecommendations(Integer branchId) {
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List<TimeSeries> timeSeries = timeSeriesService.getByBranch(branchId);
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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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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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}
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private void validateVariables(Map<String, Double> variableValues, List<DbRule> dbDbRules) {
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for (DbRule dbRule : dbDbRules) {
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if (!variableValues.containsKey(dbRule.getFirstAntecedent().name())) {
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throw new RuntimeException(String.format("Переменной в правиле не задано значение (нет временного ряда): %s ",
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dbRule.getFirstAntecedent().name()));
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}
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if (!variableValues.containsKey(dbRule.getSecondAntecedent().name())) {
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throw new RuntimeException(String.format("Переменной в правиле не задано значение (нет временного ряда): %s ",
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dbRule.getSecondAntecedent().name()));
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}
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}
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}
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private String getConsequent(Engine engine, Map<String, Double> variableValues) {
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OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME);
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for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
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InputVariable inputVariable = engine.getInputVariable(variableValue.getKey());
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inputVariable.setValue(variableValue.getValue());
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}
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engine.process();
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if (outputVariable != null) {
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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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: outputVariable.highestMembership(outputVariable.getValue()).getSecond().getName();
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}
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}
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