Merge branch 'master' into 3-f-transform

This commit is contained in:
sam 2023-03-02 10:26:38 +04:00
commit 78c02d7dad
200 changed files with 8604 additions and 31 deletions

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@ -1,3 +1,3 @@
API http://localhost:8080/swagger-ui.html
API http://time-series.athene.tech/swagger-ui/index.html
Demo http://time-series.athene.tech/

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@ -5,9 +5,12 @@ plugins {
}
jar {
archivesBaseName='time-series-smoothing'
archivesBaseName = 'time-series-smoothing'
}
group 'ru.ulstu'
version '1.0-SNAPSHOT'
repositories {
maven {
url "https://repo.athene.tech/repository/maven-central/"
@ -17,27 +20,28 @@ repositories {
}
}
sourceCompatibility = '11'
targetCompatibility = '11'
test {
useJUnitPlatform()
}
dependencies {
ext {
versionSLF4J = '1.7.24'
versionJetty = '9.3.16.v20170120'
versionJackson = '2.9.4'
}
implementation group: 'org.springframework.boot', name: 'spring-boot-starter-web'
implementation group: 'org.springframework.boot', name: 'spring-boot-starter-jetty'
implementation group: 'org.springframework.boot', name: 'spring-boot-starter-thymeleaf'
implementation group: 'org.springframework.boot', name: 'spring-boot-starter-test'
implementation group: 'org.slf4j', name: 'slf4j-api', version: versionSLF4J
implementation group: 'nz.net.ultraq.thymeleaf', name: 'thymeleaf-layout-dialect', version: '3.1.0'
implementation group: 'nz.net.ultraq.thymeleaf', name: 'thymeleaf-layout-dialect', version: '3.0.0'
implementation group: 'org.javassist', name: 'javassist', version: '3.25.0-GA'
implementation group: 'org.eclipse.jetty', name: 'jetty-servlet', version: versionJetty
implementation group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: versionJackson
implementation group: 'com.fasterxml.jackson.core', name: 'jackson-annotations', version: versionJackson
implementation group: 'com.fasterxml.jackson.datatype', name: 'jackson-datatype-jsr310', version: versionJackson
implementation group: 'com.fasterxml.jackson.core', name: 'jackson-databind'
implementation group: 'com.fasterxml.jackson.core', name: 'jackson-annotations'
implementation group: 'com.fasterxml.jackson.datatype', name: 'jackson-datatype-jsr310'
implementation group: 'org.springdoc', name: 'springdoc-openapi-ui', version: '1.6.5'
@ -47,7 +51,8 @@ dependencies {
implementation group: 'org.webjars', name: 'font-awesome', version: '4.7.0'
implementation group: 'org.webjars', name: 'highcharts', version: '7.0.0'
testImplementation group: 'org.springframework.boot', name: 'spring-boot-starter-test'
testImplementation 'org.junit.jupiter:junit-jupiter-api:5.8.1'
testRuntimeOnly 'org.junit.jupiter:junit-jupiter-engine:5.8.1'
}

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@ -2,13 +2,16 @@ package ru.ulstu.controller;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.web.bind.annotation.ControllerAdvice;
import org.springframework.web.bind.annotation.ExceptionHandler;
import org.springframework.web.client.HttpServerErrorException;
import ru.ulstu.datamodel.exception.ForecastValidateException;
import ru.ulstu.datamodel.exception.ModelingException;
import ru.ulstu.datamodel.exception.TimeSeriesValidateException;
import ru.ulstu.datamodel.response.ErrorConstants;
import ru.ulstu.datamodel.response.ResponseExtended;
@ControllerAdvice
public class AdviceController {
private final Logger log = LoggerFactory.getLogger(AdviceController.class);
@ -30,11 +33,19 @@ public class AdviceController {
@ExceptionHandler(TimeSeriesValidateException.class)
public ResponseExtended<String> handleTimeSeriesValidateException(Throwable e) {
e.printStackTrace();
return handleException(ErrorConstants.TIME_SERIES_VALIDATE_ERROR, e.getMessage());
}
@ExceptionHandler(ForecastValidateException.class)
public ResponseExtended<String> handleForecastValidateException(Throwable e) {
e.printStackTrace();
return handleException(ErrorConstants.FORECAST_PARAMS_ERROR, e.getMessage());
}
@ExceptionHandler(ModelingException.class)
public ResponseExtended<String> handleModelingException(Throwable e) {
e.printStackTrace();
return handleException(ErrorConstants.MODELING_ERROR, e.getMessage());
}
}

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@ -12,6 +12,7 @@ import ru.ulstu.datamodel.ts.TimeSeries;
import ru.ulstu.datamodel.ts.TimeSeriesValue;
import ru.ulstu.db.DbService;
import ru.ulstu.service.TimeSeriesService;
import ru.ulstu.statistic.StatisticService;
import java.io.IOException;
import java.lang.reflect.InvocationTargetException;
@ -27,11 +28,14 @@ import java.util.stream.Stream;
public class IndexController {
private final TimeSeriesService timeSeriesService;
private final DbService dbService;
private final StatisticService statisticService;
public IndexController(TimeSeriesService timeSeriesService,
DbService dbService) {
DbService dbService,
StatisticService statisticService) {
this.timeSeriesService = timeSeriesService;
this.dbService = dbService;
this.statisticService = statisticService;
}
@GetMapping("/")
@ -96,14 +100,14 @@ public class IndexController {
testForecastValues.addAll(testForecast.getValues().stream().map(TimeSeriesValue::getValue).collect(Collectors.toList()));
model.addAttribute("testForecast", testForecastValues.toArray());
model.addAttribute("forecastDescription", modelingResult);
model.addAttribute("statistic", statisticService.getStatistic(timeSeries));
}
private List<String> getDatesForChart(TimeSeries timeSeries, TimeSeries forecast) {
return Stream.concat(timeSeries.getValues().stream(), forecast.getValues().stream())
return Stream.concat(timeSeries.getValues().stream(), forecast.getValues().stream().skip(1))
.map(TimeSeriesValue::getDate)
.sorted()
.map(date -> date.format(DateTimeFormatter.ofLocalizedDate(FormatStyle.SHORT)))
.distinct()
.collect(Collectors.toList());
}

View File

@ -14,6 +14,7 @@ import ru.ulstu.HttpUtils;
import ru.ulstu.configuration.ApiConfiguration;
import ru.ulstu.datamodel.ForecastParams;
import ru.ulstu.datamodel.ModelingResult;
import ru.ulstu.datamodel.SmoothingParams;
import ru.ulstu.datamodel.exception.ModelingException;
import ru.ulstu.datamodel.ts.TimeSeries;
import ru.ulstu.method.Method;
@ -57,6 +58,16 @@ public class TimeSeriesController {
return result;
}
@PostMapping("getSpecificMethodSmoothed")
@Operation(description = "Получить сглаженный временной ряд выбранным методом")
public ResponseEntity<ModelingResult> getSpecificMethodSmoothedTimeSeries(@RequestBody @Valid SmoothingParams smoothingParams, HttpServletRequest request) throws ExecutionException, InterruptedException, InvocationTargetException, NoSuchMethodException, InstantiationException, IllegalAccessException, ModelingException {
LOGGER.info("User ip: " + HttpUtils.getUserIp(request));
LOGGER.info("Time series for smoothing: " + smoothingParams.getOriginalTimeSeries());
ResponseEntity<ModelingResult> result = new ResponseEntity<>(timeSeriesService.smoothTimeSeries(smoothingParams.getOriginalTimeSeries(), smoothingParams.getMethodClassName()), HttpStatus.OK);
LOGGER.info("Smoothing complete");
return result;
}
@PostMapping("getSpecificMethodForecast")
@Operation(description = "Получить прогноз временного ряда указанным методом")
public ResponseEntity<ModelingResult> getForecastTimeSeriesSpecificMethod(@RequestBody @Valid ForecastParams forecastParams, HttpServletRequest request) throws ExecutionException, InterruptedException, InvocationTargetException, NoSuchMethodException, InstantiationException, IllegalAccessException, ModelingException {
@ -74,4 +85,10 @@ public class TimeSeriesController {
public ResponseEntity<List<Method>> getAvailableMethods() {
return new ResponseEntity<>(timeSeriesService.getAvailableMethods(), HttpStatus.OK);
}
@PostMapping("getGroupedTendencies")
@Operation(description = "Получить список сгруппированных тенденций")
public ResponseEntity<List<TimeSeries>> getGroupedTendencies(@RequestBody List<TimeSeries> timeSeriesList) {
return new ResponseEntity<>(timeSeriesService.getGroupedTendencies(timeSeriesList), HttpStatus.OK);
}
}

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@ -13,6 +13,8 @@ import ru.ulstu.configuration.ApiConfiguration;
import ru.ulstu.datamodel.ts.TimeSeries;
import ru.ulstu.service.UtilService;
import java.util.Map;
@RestController
@RequestMapping(ApiConfiguration.API_1_0)
public class UtilController {
@ -23,13 +25,13 @@ public class UtilController {
this.utilService = utilService;
}
@GetMapping("isAlive")
@GetMapping("alive")
@Operation(description = "Проверка сервиса")
public ResponseEntity<Boolean> isAlive() {
return new ResponseEntity<>(true, HttpStatus.OK);
public ResponseEntity<Map<String, Boolean>> isAlive() {
return new ResponseEntity<>(Map.of("result", true), HttpStatus.OK);
}
@GetMapping("getRandom")
@PostMapping("getRandom")
@Operation(description = "Получить временной ряд рандомной длины")
public ResponseEntity<TimeSeries> getRandomTimeSeries(@RequestParam("length") int length) {
return new ResponseEntity<>(utilService.getRandomTimeSeries(length), HttpStatus.OK);

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@ -0,0 +1,35 @@
package ru.ulstu.datamodel;
import ru.ulstu.datamodel.ts.TimeSeries;
import javax.validation.constraints.NotNull;
public class SmoothingParams {
@NotNull
private TimeSeries originalTimeSeries;
private String methodClassName;
public TimeSeries getOriginalTimeSeries() {
return originalTimeSeries;
}
public void setOriginalTimeSeries(TimeSeries originalTimeSeries) {
this.originalTimeSeries = originalTimeSeries;
}
public String getMethodClassName() {
return methodClassName;
}
public void setMethodClassName(String methodClassName) {
this.methodClassName = methodClassName;
}
@Override
public String toString() {
return "ForecastParams{" +
"originalTimeSeries=" + originalTimeSeries +
", methodClassName=" + methodClassName +
'}';
}
}

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@ -4,6 +4,7 @@ public enum ErrorConstants {
UNKNOWN(0, "Unknown error"),
TIME_SERIES_VALIDATE_ERROR(10, "Некорректный временной ряд"),
FORECAST_PARAMS_ERROR(11, "Некорректные параметры для прогнозирования"),
MODELING_ERROR(13, "Ошибка моделирования"),
HTTP_CLIENT_ERROR(66, "Http client error");
private final int code;

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@ -62,6 +62,11 @@ public abstract class Method {
return true;
}
public void validateForForecast(TimeSeries timeSeries, int countPoints) throws ModelingException {
ValidationUtils.validateTimeSeries(timeSeries);
validateForecastParams(countPoints);
}
public boolean canMakeModel(TimeSeries timeSeries, List<MethodParamValue> parameters) {
try {
ValidationUtils.validateTimeSeries(timeSeries);

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@ -11,7 +11,7 @@ import static java.lang.Math.abs;
public class Smape extends ScoreMethod {
public Smape() {
super("Smape");
super("Smape, %");
}
@Override

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@ -16,6 +16,7 @@ import java.lang.reflect.InvocationTargetException;
import java.time.LocalDateTime;
import java.util.ArrayList;
import java.util.Comparator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.TreeMap;
@ -44,8 +45,15 @@ class MethodParamBruteForce {
TimeSeries reducedTimeSeries = new TimeSeries(timeSeries.getValues().stream().limit(timeSeries.getLength() - countPoints).collect(Collectors.toList()),
"test part of " + timeSeries.getKey());
try {
ValidationUtils.validateTimeSeries(reducedTimeSeries);
} catch (ModelingException ex) {
throw new ModelingException("Тестовая часть временного ряда не прошла валидацию: " + ex.getMessage());
}
Map<LocalDateTime, Double> tsValues = timeSeries.getValues().stream()
.collect(Collectors.toMap(TimeSeriesValue::getDate, TimeSeriesValue::getValue));
.collect(Collectors.toMap(TimeSeriesValue::getDate, TimeSeriesValue::getValue,
(oldValue, newValue) -> oldValue, LinkedHashMap::new));
for (Method method : methods) {
List<List<MethodParamValue>> availableParametersValues = getAvailableParametersValues(timeSeries, method.getAvailableParameters());
@ -74,6 +82,7 @@ class MethodParamBruteForce {
.filter(m -> m.getClass().getSimpleName().equals(methodClassName))
.findAny()
.orElseThrow(() -> new ModelingException("Неизвестный метод прогнозирования"));
method.validateForForecast(timeSeries, countPointsForecast);
return getForecastByMethods(timeSeries, List.of(method), countPointsForecast);
}
@ -88,6 +97,9 @@ class MethodParamBruteForce {
private ModelingResult getBestResultForecast(List<ModelingResult> modelingResults,
TimeSeries timeSeries,
int countPoints) throws ModelingException {
if (modelingResults.size() == 0) {
throw new ModelingException("Нет результатов моделирования");
}
ModelingResult bestResult = modelingResults.stream()
.min(Comparator.comparing(modelingResult -> modelingResult.getScore().getDoubleValue()))
.orElseThrow(() -> new ModelingException("Лучший метод не найден"));
@ -124,7 +136,8 @@ class MethodParamBruteForce {
List<ModelingResult> results2 = new CopyOnWriteArrayList<>();
Map<LocalDateTime, Double> tsValues = timeSeries.getValues().stream()
.collect(Collectors.toMap(TimeSeriesValue::getDate, TimeSeriesValue::getValue));
.collect(Collectors.toMap(TimeSeriesValue::getDate, TimeSeriesValue::getValue,
(oldValue, newValue) -> oldValue, LinkedHashMap::new));
for (Method method : methods) {
List<List<MethodParamValue>> availableParametersValues = getAvailableParametersValues(timeSeries, method.getAvailableParameters());

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@ -10,6 +10,7 @@ import ru.ulstu.method.Method;
import java.lang.reflect.InvocationTargetException;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.stream.Collectors;
@Service
@ -42,4 +43,41 @@ public class TimeSeriesService {
public List<Method> getAvailableMethods() {
return methodParamBruteForce.getAvailableMethods();
}
public List<TimeSeries> getGroupedTendencies(List<TimeSeries> timeSeriesList) {
return timeSeriesList
.stream()
.filter(ts -> ts.getValues() != null && ts.getLength() > 5)
.map(this::getGroupedTendencies)
.collect(Collectors.toList());
}
public TimeSeries getGroupedTendencies(TimeSeries timeSeries) {
try {
timeSeries = smoothTimeSeries(timeSeries, "FTransform").getTimeSeries();
} catch (Exception e) {
e.printStackTrace();
}
int i = 2;
double prevDiff = timeSeries.getNumericValue(1) -
timeSeries.getNumericValue(0);
while (i < timeSeries.getLength()) {
double diff = timeSeries.getNumericValue(i) -
timeSeries.getNumericValue(i - 1);
//если тенденция сохранилась
if (tsTendencyNotChanged(diff, prevDiff)) {
timeSeries.getValues().remove(i - 1);
} else {
i++;
}
prevDiff = diff;
}
return timeSeries;
}
private boolean tsTendencyNotChanged(double diff, double prevDiff) {
return (diff > 0 && prevDiff > 0)
|| ((diff < 0 && prevDiff < 0)
|| ((diff == 0 && prevDiff == 0)));
}
}

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@ -0,0 +1,60 @@
package ru.ulstu.statistic;
import org.springframework.stereotype.Service;
import ru.ulstu.datamodel.ts.TimeSeries;
import ru.ulstu.datamodel.ts.TimeSeriesValue;
import java.util.Optional;
import java.util.OptionalDouble;
import java.util.stream.DoubleStream;
@Service
public class StatisticService {
public Optional<Double> getAverage(TimeSeries timeSeries) {
return getOptionalValue(getDoubleStream(timeSeries).average());
}
public Optional<Double> getMin(TimeSeries timeSeries) {
return getOptionalValue(getDoubleStream(timeSeries).min());
}
public Optional<Double> getMax(TimeSeries timeSeries) {
return getOptionalValue(getDoubleStream(timeSeries).max());
}
public Optional<Double> getLength(TimeSeries timeSeries) {
return getOptionalValue(Double.valueOf(timeSeries.getLength()));
}
public Optional<Double> getDispersion(TimeSeries timeSeries) {
Optional<Double> maybeAverage = getAverage(timeSeries);
return getOptionalValue(maybeAverage.isPresent()
? timeSeries.getValues().stream().mapToDouble(v -> Math.pow(v.getValue() - maybeAverage.get(), 2)).sum() / timeSeries.getLength()
: null);
}
private DoubleStream getDoubleStream(TimeSeries timeSeries) {
return timeSeries.getValues().stream().mapToDouble(TimeSeriesValue::getValue);
}
private Optional<Double> getOptionalValue(OptionalDouble optionalDouble) {
return getOptionalValue(optionalDouble.isPresent()
? optionalDouble.getAsDouble()
: null);
}
private Optional<Double> getOptionalValue(Double value) {
value = (value == null)
? null
: ((double) Math.round(value * 100) / 100);
return Optional.ofNullable(value);
}
public TimeSeriesStatistic getStatistic(TimeSeries timeSeries) {
return new TimeSeriesStatistic(getMin(timeSeries),
getMax(timeSeries),
getAverage(timeSeries),
getLength(timeSeries),
getDispersion(timeSeries));
}
}

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@ -0,0 +1,44 @@
package ru.ulstu.statistic;
import java.util.Optional;
public class TimeSeriesStatistic {
private Optional<Double> min;
private Optional<Double> max;
private Optional<Double> average;
private Optional<Double> length;
private Optional<Double> dispersion;
public TimeSeriesStatistic(Optional<Double> min,
Optional<Double> max,
Optional<Double> average,
Optional<Double> length,
Optional<Double> dispersion) {
this.min = min;
this.max = max;
this.average = average;
this.length = length;
this.dispersion = dispersion;
}
public Optional<Double> getMin() {
return min;
}
public Optional<Double> getMax() {
return max;
}
public Optional<Double> getAverage() {
return average;
}
public Optional<Double> getLength() {
return length;
}
public Optional<Double> getDispersion() {
return dispersion;
}
}

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@ -91,10 +91,8 @@
json.plotOptions = plotOptions;
$('#chart').highcharts(json);
});
</script>
<form action="#" th:action="chart" th:object="${chartForm}">
<div class="row">
<div class="col-md-12 col-sm-12 col-lg-6">
@ -109,7 +107,6 @@
<script th:inline="javascript" th:if="*{set != null}">
$('#select-set').val([[*{set.key}]]);
$('#select-set').selectpicker('refresh');
</script>
<select id="select-ts" class="selectpicker form-group" data-live-search="true"
@ -121,15 +118,51 @@
th:utext="${ts.key}">
</option>
</select>
<script th:inline="javascript" th:if="*{timeSeriesMeta != null}">
$('#select-ts').val([[*{timeSeriesMeta.key}]]);
$('#select-ts').selectpicker('refresh');
</script>
<h5 th:if="${forecastDescription != null && forecastDescription.timeSeriesMethod != null}">
Результаты моделирования:
</h5>
<div th:if="${forecastDescription != null && forecastDescription.timeSeriesMethod != null}">
<p> Метод прогнозирования: <span th:text="${forecastDescription.timeSeriesMethod}"> </span>
<p> Оценка: <span th:text="${forecastDescription.score.value}"> </span>
<p> Метод прогнозирования:
<span th:text="${forecastDescription.timeSeriesMethod}"/>
</p>
<hr/>
<p> Оценка прогноза по
<span th:text="${forecastDescription.score.scoreMethod.name}"/>:
<span th:text="${forecastDescription.score.value}"/>
</p>
<hr/>
</div>
<h5 th:if="${forecastDescription != null && forecastDescription.timeSeriesMethod != null}">
Статистические характеристики временного ряда:
</h5>
<div th:if="${forecastDescription != null && forecastDescription.timeSeriesMethod != null}">
<p> Длина:
<span th:text="${statistic.length.present ? statistic.length.get : 'Не известно'}"/>
</p>
<hr/>
<p> Минимальное значение:
<span th:text="${statistic.min.present ? statistic.min.get : 'Не известно'}"/>
</p>
<hr/>
<p> Максимальное значение:
<span th:text="${statistic.max.present ? statistic.max.get : 'Не известно'}"/>
</p>
<hr/>
<p> Среднее значение:
<span th:text="${statistic.average.present ? statistic.average.get : 'Не известно'}"/>
</p>
<hr/>
<p> Дисперсия:
<span th:text="${statistic.dispersion.present ? statistic.dispersion .get : 'Не известно'}"/>
</p>
<hr/>
</div>
</div>
<div class="col-md-12 col-sm-12 col-lg-6">

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@ -0,0 +1,44 @@
package ru.ulstu;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import ru.ulstu.datamodel.ts.TimeSeries;
import ru.ulstu.datamodel.ts.TimeSeriesValue;
import ru.ulstu.statistic.StatisticService;
import java.time.LocalDateTime;
public class StatisticServiceTest {
private TimeSeries getTimeSeries() {
TimeSeries ts = new TimeSeries();
for (int i = 0; i < 11; i++) {
ts.addValue(new TimeSeriesValue(LocalDateTime.now(), (double) i));
}
return TimeSeriesUtils.fillDates(ts);
}
@Test
public void testAverage() {
Assertions.assertEquals(new StatisticService().getAverage(getTimeSeries())
.orElseThrow(() -> new RuntimeException("Average test failed")), 5.0);
}
@Test
public void testMin() {
Assertions.assertEquals(new StatisticService().getMin(getTimeSeries())
.orElseThrow(() -> new RuntimeException("Min test failed")), 0.0);
}
@Test
public void testMax() {
Assertions.assertEquals(new StatisticService().getMax(getTimeSeries())
.orElseThrow(() -> new RuntimeException("Max test failed")), 10.0);
}
@Test
public void testLength() {
Assertions.assertEquals(new StatisticService().getLength(getTimeSeries())
.orElseThrow(() -> new RuntimeException("Length test failed")), 11.0);
}
}

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@ -0,0 +1 @@
{"key":"Random time series","size":1000,"hasDateTime":true}

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@ -0,0 +1,2 @@
2018-12-21T16:00:00;1.0
2018-12-29T09:00:00;1.0
1 2018-12-21T16:00:00 1.0
2 2018-12-29T09:00:00 1.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_02 Alexandra Временной ряд авторов","size":2,"hasDateTime":true}

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@ -0,0 +1,2 @@
2018-12-21T16:00:00;2.0
2018-12-29T09:00:00;1.0
1 2018-12-21T16:00:00 2.0
2 2018-12-29T09:00:00 1.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_02 Временной ряд коммитов","size":2,"hasDateTime":true}

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@ -0,0 +1,2 @@
2018-12-21T16:00:00;0.0
2018-12-29T09:00:00;0.0
1 2018-12-21T16:00:00 0.0
2 2018-12-29T09:00:00 0.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_02 Временной ряд сущностей","size":2,"hasDateTime":true}

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@ -0,0 +1,3 @@
2018-12-21T16:00:00;1.0
2018-12-29T09:00:00;1.0
2018-12-29T12:00:00;1.0
1 2018-12-21T16:00:00 1.0
2 2018-12-29T09:00:00 1.0
3 2018-12-29T12:00:00 1.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_03 Alexandra Временной ряд авторов","size":3,"hasDateTime":true}

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@ -0,0 +1,3 @@
2018-12-21T16:00:00;2.0
2018-12-29T09:00:00;1.0
2018-12-29T12:00:00;1.0
1 2018-12-21T16:00:00 2.0
2 2018-12-29T09:00:00 1.0
3 2018-12-29T12:00:00 1.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_03 Временной ряд коммитов","size":3,"hasDateTime":true}

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@ -0,0 +1,3 @@
2018-12-21T16:00:00;0.0
2018-12-29T09:00:00;0.0
2018-12-29T12:00:00;0.0
1 2018-12-21T16:00:00 0.0
2 2018-12-29T09:00:00 0.0
3 2018-12-29T12:00:00 0.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._CSharp.git Lab_03 Временной ряд сущностей","size":3,"hasDateTime":true}

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@ -0,0 +1,2 @@
2018-12-21T16:00:00;1.0
2018-12-21T17:00:00;1.0
1 2018-12-21T16:00:00 1.0
2 2018-12-21T17:00:00 1.0

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@ -0,0 +1 @@
{"key":"PIbd-21_Barmina_A.V._Java Lab_01 Временной ряд коммитов","size":2,"hasDateTime":true}

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@ -0,0 +1,3 @@
2018-12-21T16:00:00;1.0
2018-12-21T17:00:00;1.0
2019-01-27T08:00:00;1.0
1 2018-12-21T16:00:00 1.0
2 2018-12-21T17:00:00 1.0
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