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list of assessments #85

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romanov73 merged 6 commits from 84-list-of-consequents into master 2023-02-02 13:05:28 +04:00
Conversation 1 Commits 6 Files Changed 9 +43 -13
3 changed files with 43 additions and 13 deletions
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7
src/main/java/ru/ulstu/extractor/rule/model/AssessmentException.java Normal file
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@ -0,0 +1,7 @@
package ru.ulstu.extractor.rule.model;
public class AssessmentException extends RuntimeException {
public AssessmentException(String message) {
super(message);
}
}

39
src/main/java/ru/ulstu/extractor/rule/service/FuzzyInferenceService.java
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@ -15,6 +15,7 @@ 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;
@ -48,10 +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) {
@ -64,6 +64,7 @@ public class FuzzyInferenceService {
}
private RuleBlock getRuleBlock(Engine engine,
List<DbRule> dbRules,
Map<String, Double> variableValues,
List<AntecedentValue> antecedentValues,
List<Integer> consequentValues) {
@ -102,7 +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;
}
@ -116,7 +117,11 @@ public class FuzzyInferenceService {
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) {
@ -130,7 +135,7 @@ public class FuzzyInferenceService {
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));
engine.addRuleBlock(getRuleBlock(engine, dbRules, variableValues, antecedentValues, consequentValues));
String consequent = getConsequent(engine, variableValues);
if (consequent.equals(NO_RESULT)) {
return new ArrayList<>();
@ -142,12 +147,30 @@ public class FuzzyInferenceService {
.collect(Collectors.toList());
}
private List<Assessment> getAssessmentsByTimeSeriesTendencies(List<DbRule> dbRules, List<TimeSeries> timeSeries) {
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)));
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(), ts.getValues().get(ts.getValues().size() - 1).getValue()));

8
src/main/java/ru/ulstu/extractor/ts/service/TimeSeriesService.java
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@ -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();
}
}