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+package com.tzld.piaoquan.recommend.server.service.rank.strategy;
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+
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+import com.ctrip.framework.apollo.spring.annotation.ApolloJsonValue;
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+import com.google.common.reflect.TypeToken;
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+import com.tzld.piaoquan.recommend.server.common.base.RankItem;
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+import com.tzld.piaoquan.recommend.server.model.Video;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankParam;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankResult;
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+import com.tzld.piaoquan.recommend.server.service.rank.RankService;
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+import com.tzld.piaoquan.recommend.server.service.rank.extractor.ExtractorUtils;
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+import com.tzld.piaoquan.recommend.server.service.rank.extractor.RankExtractorItemTags;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorBoost;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorDensity;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorInsert;
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+import com.tzld.piaoquan.recommend.server.service.rank.processor.RankProcessorTagFilter;
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+import com.tzld.piaoquan.recommend.server.service.recall.strategy.*;
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+import com.tzld.piaoquan.recommend.server.util.CommonCollectionUtils;
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+import com.tzld.piaoquan.recommend.server.util.JSONUtils;
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+import lombok.extern.slf4j.Slf4j;
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+import org.apache.commons.collections4.CollectionUtils;
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+import org.apache.commons.lang3.RandomUtils;
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+import org.springframework.stereotype.Service;
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+
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+import java.text.SimpleDateFormat;
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+import java.util.*;
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+import java.util.stream.Collectors;
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+
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+/**
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+ * @author zhangbo
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+ * @desc 地域召回融合 流量池汤姆森
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+ */
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+@Service
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+@Slf4j
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+public class RankStrategy4ShareDeepAndWidth extends RankService {
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+ @ApolloJsonValue("${rank.score.merge.weightv645:}")
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+ private Map<String, Double> mergeWeight;
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+ @ApolloJsonValue("${RankStrategy4DensityFilterV2:}")
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+ private final Map<String, Map<String, Map<String, String>>> filterRules = new HashMap<>();
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+ final private String CLASS_NAME = this.getClass().getSimpleName();
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+
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+ public void duplicate(Set<Long> setVideo, List<Video> videos) {
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+ Iterator<Video> iterator = videos.iterator();
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+ while (iterator.hasNext()) {
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+ Video v = iterator.next();
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+ if (setVideo.contains(v.getVideoId())) {
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+ iterator.remove();
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+ } else {
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+ setVideo.add(v.getVideoId());
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+ }
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+ }
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+ }
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+
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+ @Override
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+ public List<Video> mergeAndRankRovRecall(RankParam param) {
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+ Map<String, Double> mergeWeight = this.mergeWeight != null ? this.mergeWeight : new HashMap<>(0);
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+ //-------------------融-------------------
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+ //-------------------合-------------------
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+ //-------------------逻-------------------
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+ //-------------------辑-------------------
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+
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+ List<Video> oldRovs = new ArrayList<>();
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+ oldRovs.addAll(extractAndSort(param, RegionHRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionHDupRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, Region24HRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionRelative24HRecallStrategy.PUSH_FORM));
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+ oldRovs.addAll(extractAndSort(param, RegionRelative24HDupRecallStrategy.PUSH_FORM));
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+ removeDuplicate(oldRovs);
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+ int sizeReturn = param.getSize();
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+ List<Video> v0 = oldRovs.size() <= sizeReturn
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+ ? oldRovs
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+ : oldRovs.subList(0, sizeReturn);
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+ Set<Long> setVideo = new HashSet<>();
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+ this.duplicate(setVideo, v0);
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+
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+
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+ //-------------------相关性召回 融合+去重-------------------
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+ List<Video> v5 = extractAndSort(param, SimHotVideoRecallStrategy.PUSH_FORM);
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+ List<Video> v6 = extractAndSort(param, ReturnVideoRecallStrategy.PUSH_FORM);
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+ this.duplicate(setVideo, v5);
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+ this.duplicate(setVideo, v6);
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+ //-------------------分享深度、广度 融合+去重-------------------
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+ List<Video> v9 = extractAndSort(param, ShareWidthRecallStrategy.PUSH_FORM);
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+ List<Video> v10 = extractAndSort(param, ShareDeepRecallStrategy.PUSH_FORM);
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+ this.duplicate(setVideo, v9);
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+ //-------------------地域相关召回 融合+去重-------------------
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+ List<Video> v1 = extractAndSort(param, RegionRealtimeRecallStrategyV1.PUSH_FORM);
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+ this.duplicate(setVideo, v1);
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+ //-------------------节日扶持召回 融合+去重-------------------
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+ List<Video> v7 = extractAndSort(param, FestivalRecallStrategyV1.PUSH_FORM);
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+ this.duplicate(setVideo, v7);
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+ List<Video> rovRecallRank = new ArrayList<>();
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+ rovRecallRank.addAll(v0);
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+ rovRecallRank.addAll(v5.subList(0, Math.min(mergeWeight.getOrDefault("v5", 5.0).intValue(), v5.size())));
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+ rovRecallRank.addAll(v6.subList(0, Math.min(mergeWeight.getOrDefault("v6", 5.0).intValue(), v6.size())));
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+ rovRecallRank.addAll(v9.subList(0, Math.min(mergeWeight.getOrDefault("v9", 5.0).intValue(), v9.size())));
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+ rovRecallRank.addAll(v10.subList(0, Math.min(mergeWeight.getOrDefault("v10", 5.0).intValue(), v10.size())));
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+ rovRecallRank.addAll(v1.subList(0, Math.min(mergeWeight.getOrDefault("v1", 5.0).intValue(), v1.size())));
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+ rovRecallRank.addAll(v7.subList(0, Math.min(mergeWeight.getOrDefault("v7", 5.0).intValue(), v7.size())));
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+
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+ //-------------------排-------------------
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+ //-------------------序-------------------
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+ //-------------------逻-------------------
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+ //-------------------辑-------------------
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+
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+ // 1 模型分
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+ List<String> rtFeaPart = new ArrayList<>();
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+ List<RankItem> items = model(rovRecallRank, param, rtFeaPart);
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+ List<String> rtFeaPartKey = new ArrayList<>(Arrays.asList("item_rt_fea_1day_partition", "item_rt_fea_1h_partition"));
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+ List<String> rtFeaPartKeyResult = this.redisTemplate.opsForValue().multiGet(rtFeaPartKey);
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+ Calendar calendar = Calendar.getInstance();
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+ String date = new SimpleDateFormat("yyyyMMdd").format(calendar.getTime());
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+ String hour = new SimpleDateFormat("HH").format(calendar.getTime());
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+ String rtFeaPart1h = date + hour;
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+ if (rtFeaPartKeyResult != null) {
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+ if (rtFeaPartKeyResult.get(1) != null) {
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+ rtFeaPart1h = rtFeaPartKeyResult.get(1);
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+ }
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+ }
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+ // 2 统计分
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+ String cur = rtFeaPart1h;
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+ List<String> datehours = new LinkedList<>(); // 时间是倒叙的
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+ for (int i = 0; i < 24; ++i) {
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+ datehours.add(cur);
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+ cur = ExtractorUtils.subtractHours(cur, 1);
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+ }
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+ for (RankItem item : items) {
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+ Map<String, Map<String, Double>> itemRealMap = item.getItemRealTimeFeature();
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+ List<Double> views = getStaticData(itemRealMap, datehours, "view_uv_list_1h");
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+ List<Double> shares = getStaticData(itemRealMap, datehours, "share_uv_list_1h");
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+ List<Double> allreturns = getStaticData(itemRealMap, datehours, "return_uv_list_1h");
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+
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+ // 全部回流的rov和ros
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+ List<Double> share2allreturn = getRateData(allreturns, shares, 0.0, 0.0);
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+ Double share2allreturnScore = calScoreWeightNoTimeDecay(share2allreturn);
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+ item.scoresMap.put("share2allreturnScore", share2allreturnScore);
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+ List<Double> view2allreturn = getRateData(allreturns, views, 0.0, 0.0);
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+ Double view2allreturnScore = calScoreWeightNoTimeDecay(view2allreturn);
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+ item.scoresMap.put("view2allreturnScore", view2allreturnScore);
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+
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+ // 全部回流
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+ Double allreturnsScore = calScoreWeightNoTimeDecay(allreturns);
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+ item.scoresMap.put("allreturnsScore", allreturnsScore);
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+
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+ Double sumShareCount = shares.stream().mapToDouble(Double::doubleValue).sum();
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+ item.scoresMap.put("sumShareCount", sumShareCount);
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+
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+
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+ }
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+ // 3 融合公式
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+ List<Video> result = new ArrayList<>();
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+ double a = mergeWeight.getOrDefault("a", 1.0);
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+ double b = mergeWeight.getOrDefault("b", 1.0);
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+
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+ double f = mergeWeight.getOrDefault("f", 0.1);
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+ double g = mergeWeight.getOrDefault("g", 1.0);
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+ for (RankItem item : items) {
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+ Map<String, String> featureMap = item.getFeatureMap();
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+ double share2allreturnScore = item.scoresMap.getOrDefault("share2allreturnScore", 0.0);
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+ double view2allreturnScore = item.scoresMap.getOrDefault("view2allreturnScore", 0.0);
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+ double score = 0.0;
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+ double allreturnsScore = item.scoresMap.getOrDefault("allreturnsScore", 0.0);
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+ if (allreturnsScore > 50) {
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+ score += (f * share2allreturnScore + g * view2allreturnScore);
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+ } else {
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+ score += (f * share2allreturnScore + g * view2allreturnScore) * 0.01;
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+ }
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+ double sumShareCount = item.scoresMap.getOrDefault("sumShareCount", 0.0);
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+ double daySharedepthMaxAvg = Double.parseDouble(featureMap.getOrDefault("i_1day_sharedepth_max_avg", "0.0"));
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+ double daySharewidthMaxAvg = Double.parseDouble(featureMap.getOrDefault("i_1day_sharewidth_max_avg", "0.0"));
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+
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+ if (sumShareCount > 30) {
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+ score += a * daySharedepthMaxAvg + b * daySharewidthMaxAvg;
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+ }
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+
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+ Video video = item.getVideo();
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+ video.setScore(score);
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+ video.setSortScore(score);
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+ video.setScoreStr(item.getScoreStr());
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+ video.setScoresMap(item.getScoresMap());
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+ result.add(video);
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+ }
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+ result.sort(Comparator.comparingDouble(o -> -o.getSortScore()));
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+ return result;
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+ }
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+
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+ public Double calScoreWeightNoTimeDecay(List<Double> data) {
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+ Double up = 0.0;
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+ Double down = 0.0;
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+ for (int i = 0; i < data.size(); ++i) {
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+ up += 1.0 * data.get(i);
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+ down += 1.0;
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+ }
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+ return down > 1E-8 ? up / down : 0.0;
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+ }
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+
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+ public List<Double> getRateData(List<Double> ups, List<Double> downs, Double up, Double down) {
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+ List<Double> data = new LinkedList<>();
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+ for (int i = 0; i < ups.size(); ++i) {
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+ if (ExtractorUtils.isDoubleEqualToZero(downs.get(i) + down)) {
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+ data.add(0.0);
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+ } else {
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+ data.add(
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+ (ups.get(i) + up) / (downs.get(i) + down)
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+ );
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+ }
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+ }
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+ return data;
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+ }
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+
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+ public List<Double> getStaticData(Map<String, Map<String, Double>> itemRealMap,
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+ List<String> datehours, String key) {
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+ List<Double> views = new LinkedList<>();
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+ Map<String, Double> tmp = itemRealMap.getOrDefault(key, new HashMap<>());
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+ for (String dh : datehours) {
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+ views.add(tmp.getOrDefault(dh, 0.0D) +
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+ (views.isEmpty() ? 0.0 : views.get(views.size() - 1))
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+ );
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+ }
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+ return views;
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+ }
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+
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+ public List<RankItem> model(List<Video> videos, RankParam param,
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+ List<String> rtFeaPart) {
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+ List<RankItem> result = new ArrayList<>();
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+ if (videos.isEmpty()) {
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+ return result;
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+ }
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+
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+ List<RankItem> rankItems = CommonCollectionUtils.toList(videos, RankItem::new);
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+ List<Long> videoIds = CommonCollectionUtils.toListDistinct(videos, Video::getVideoId);
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+
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+ // 2-2: item 实时特征处理
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+ List<String> rtFeaPartKey = new ArrayList<>(Arrays.asList("item_rt_fea_1day_partition", "item_rt_fea_1h_partition"));
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+ List<String> rtFeaPartKeyResult = this.redisTemplate.opsForValue().multiGet(rtFeaPartKey);
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+ Calendar calendar = Calendar.getInstance();
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+ String date = new SimpleDateFormat("yyyyMMdd").format(calendar.getTime());
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+ String hour = new SimpleDateFormat("HH").format(calendar.getTime());
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+ String rtFeaPart1day = date + hour;
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+ if (rtFeaPartKeyResult != null) {
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+ if (rtFeaPartKeyResult.get(0) != null) {
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+ rtFeaPart1day = rtFeaPartKeyResult.get(0);
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+ }
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+ }
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+
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+ List<String> videoRtKeys1 = videoIds.stream().map(r -> "item_rt_fea_1day_" + r)
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+ .collect(Collectors.toList());
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+ List<String> videoRtKeys2 = videoIds.stream().map(r -> "item_rt_fea_1h_" + r)
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+ .collect(Collectors.toList());
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+ videoRtKeys1.addAll(videoRtKeys2);
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+ List<String> videoRtFeatures = this.redisTemplate.opsForValue().multiGet(videoRtKeys1);
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+
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+
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+ if (videoRtFeatures != null) {
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+ int j = 0;
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+ for (RankItem item : rankItems) {
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+ String vF = videoRtFeatures.get(j);
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+ ++j;
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+ if (vF == null) {
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+ continue;
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+ }
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+ Map<String, String> vfMap = new HashMap<>();
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+ Map<String, Map<String, Double>> vfMapNew = new HashMap<>();
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+ try {
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+ vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {
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+ }, vfMap);
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+ for (Map.Entry<String, String> entry : vfMap.entrySet()) {
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+ String value = entry.getValue();
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+ if (value == null) {
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+ continue;
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+ }
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+ String[] var1 = value.split(",");
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+ Map<String, Double> tmp = new HashMap<>();
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+ for (String var2 : var1) {
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+ String[] var3 = var2.split(":");
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+ tmp.put(var3[0], Double.valueOf(var3[1]));
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+ }
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+ vfMapNew.put(entry.getKey(), tmp);
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+ }
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+ } catch (Exception e) {
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+ log.error(String.format("parse video item_rt_fea_1day_ json is wrong in {} with {}", this.CLASS_NAME, e));
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+ }
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+
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+ String k1 = "sharedepth_max_avg_list_1day";
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+ String k2 = "sharewidth_max_avg_list_1day";
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+ if (vfMapNew.containsKey(k1)) {
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+ Double shareDepth = vfMapNew.get(k1).getOrDefault(rtFeaPart1day, 0.0);
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+ item.getFeatureMap().put("i_1day_sharedepth_max_avg", shareDepth + "");
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+ }
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+ if (vfMapNew.containsKey(k2)) {
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+ Double shareWidth = vfMapNew.get(k2).getOrDefault(rtFeaPart1day, 0.0);
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+ item.getFeatureMap().put("i_1day_sharewidth_max_avg", shareWidth + "");
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+ }
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+
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+ }
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+ for (RankItem item : rankItems) {
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+ String vF = videoRtFeatures.get(j);
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+ ++j;
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+ if (vF == null) {
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+ continue;
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+ }
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+ Map<String, String> vfMap = new HashMap<>();
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+ Map<String, Map<String, Double>> vfMapNew = new HashMap<>();
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+ try {
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+ vfMap = JSONUtils.fromJson(vF, new TypeToken<Map<String, String>>() {
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+ }, vfMap);
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+
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+ for (Map.Entry<String, String> entry : vfMap.entrySet()) {
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+ String value = entry.getValue();
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+ if (value == null) {
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+ continue;
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+ }
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+ String[] var1 = value.split(",");
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+ Map<String, Double> tmp = new HashMap<>();
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+ for (String var2 : var1) {
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+ String[] var3 = var2.split(":");
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+ tmp.put(var3[0], Double.valueOf(var3[1]));
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+ }
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+ vfMapNew.put(entry.getKey(), tmp);
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+ }
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+ item.setItemRealTimeFeature(vfMapNew);
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+ } catch (Exception e) {
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+ log.error(String.format("parse video item_rt_fea_1h_ json is wrong in {} with {}", this.CLASS_NAME, e));
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+ }
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+ }
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+ }
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+
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+ return rankItems;
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+ }
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+
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+ @Override
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+ public RankResult mergeAndSort(RankParam param, List<Video> rovVideos, List<Video> flowVideos) {
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+
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+ //1 兜底策略，rov池子不足时，用冷启池填补。直接返回。
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+ if (CollectionUtils.isEmpty(rovVideos)) {
|
|
|
+ if (param.getSize() < flowVideos.size()) {
|
|
|
+ return new RankResult(flowVideos.subList(0, param.getSize()));
|
|
|
+ } else {
|
|
|
+ return new RankResult(flowVideos);
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ //2 根据实验号解析阿波罗参数。
|
|
|
+ String abCode = param.getAbCode();
|
|
|
+ Map<String, Map<String, String>> rulesMap = this.filterRules.getOrDefault(abCode, new HashMap<>(0));
|
|
|
+
|
|
|
+ //3 标签读取
|
|
|
+ if (rulesMap != null && !rulesMap.isEmpty()) {
|
|
|
+ RankExtractorItemTags extractorItemTags = new RankExtractorItemTags(this.redisTemplate);
|
|
|
+ extractorItemTags.processor(rovVideos, flowVideos);
|
|
|
+ }
|
|
|
+ //6 合并结果时间卡控
|
|
|
+ if (rulesMap != null && !rulesMap.isEmpty()) {
|
|
|
+ RankProcessorTagFilter.processor(rovVideos, flowVideos, rulesMap);
|
|
|
+ }
|
|
|
+
|
|
|
+ //4 rov池提权功能
|
|
|
+ RankProcessorBoost.boostByTag(rovVideos, rulesMap);
|
|
|
+
|
|
|
+ //5 rov池强插功能
|
|
|
+ RankProcessorInsert.insertByTag(param, rovVideos, rulesMap);
|
|
|
+
|
|
|
+ //7 流量池按比例强插
|
|
|
+ List<Video> result = new ArrayList<>();
|
|
|
+ for (int i = 0; i < param.getTopK() && i < rovVideos.size(); i++) {
|
|
|
+ result.add(rovVideos.get(i));
|
|
|
+ }
|
|
|
+ double flowPoolP = getFlowPoolP(param);
|
|
|
+ int flowPoolIndex = 0;
|
|
|
+ int rovPoolIndex = param.getTopK();
|
|
|
+ for (int i = 0; i < param.getSize() - param.getTopK(); i++) {
|
|
|
+ double rand = RandomUtils.nextDouble(0, 1);
|
|
|
+ if (rand < flowPoolP) {
|
|
|
+ if (flowPoolIndex < flowVideos.size()) {
|
|
|
+ result.add(flowVideos.get(flowPoolIndex++));
|
|
|
+ } else {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ } else {
|
|
|
+ if (rovPoolIndex < rovVideos.size()) {
|
|
|
+ result.add(rovVideos.get(rovPoolIndex++));
|
|
|
+ } else {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (rovPoolIndex >= rovVideos.size()) {
|
|
|
+ for (int i = flowPoolIndex; i < flowVideos.size() && result.size() < param.getSize(); i++) {
|
|
|
+ result.add(flowVideos.get(i));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ if (flowPoolIndex >= flowVideos.size()) {
|
|
|
+ for (int i = rovPoolIndex; i < rovVideos.size() && result.size() < param.getSize(); i++) {
|
|
|
+ result.add(rovVideos.get(i));
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ //8 合并结果密度控制
|
|
|
+ Map<String, Integer> densityRules = new HashMap<>();
|
|
|
+ if (rulesMap != null && !rulesMap.isEmpty()) {
|
|
|
+ for (Map.Entry<String, Map<String, String>> entry : rulesMap.entrySet()) {
|
|
|
+ String key = entry.getKey();
|
|
|
+ Map<String, String> value = entry.getValue();
|
|
|
+ if (value.containsKey("density")) {
|
|
|
+ densityRules.put(key, Integer.valueOf(value.get("density")));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ Set<Long> videosSet = result.stream().map(Video::getVideoId).collect(Collectors.toSet());
|
|
|
+ List<Video> rovRecallRankNew = rovVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
|
|
|
+ List<Video> flowPoolRankNew = flowVideos.stream().filter(r -> !videosSet.contains(r.getVideoId())).collect(Collectors.toList());
|
|
|
+ List<Video> resultWithDensity = RankProcessorDensity.mergeDensityControl(result,
|
|
|
+ rovRecallRankNew, flowPoolRankNew, densityRules);
|
|
|
+
|
|
|
+ return new RankResult(resultWithDensity);
|
|
|
+ }
|
|
|
+
|
|
|
+ public static void main(String[] args) {
|
|
|
+// String up1 = "2024031012:513,2024031013:456,2024031014:449,2024031015:262,2024031016:414,2024031017:431,2024031018:643,2024031019:732,2024031020:927,2024031021:859,2024031022:866,2024031023:358,2024031100:133,2024031101:28,2024031102:22,2024031103:15,2024031104:21,2024031105:36,2024031106:157,2024031107:371,2024031108:378,2024031109:216,2024031110:269,2024031111:299,2024031112:196,2024031113:186,2024031114:85,2024031115:82";
|
|
|
+ String up1 = "2024031012:1167,2024031013:1023,2024031014:947,2024031015:664,2024031016:842,2024031017:898,2024031018:1170,2024031019:1439,2024031020:2010,2024031021:1796,2024031022:1779,2024031023:722,2024031100:226,2024031101:50,2024031102:31,2024031103:30,2024031104:38,2024031105:63,2024031106:293,2024031107:839,2024031108:1250,2024031109:858,2024031110:767,2024031111:697,2024031112:506,2024031113:534,2024031114:381,2024031115:278";
|
|
|
+ String down1 = "2024031012:2019,2024031013:1676,2024031014:1626,2024031015:1458,2024031016:1508,2024031017:1510,2024031018:1713,2024031019:1972,2024031020:2500,2024031021:2348,2024031022:2061,2024031023:1253,2024031100:659,2024031101:243,2024031102:191,2024031103:282,2024031104:246,2024031105:439,2024031106:1079,2024031107:1911,2024031108:2023,2024031109:1432,2024031110:1632,2024031111:1183,2024031112:1024,2024031113:938,2024031114:701,2024031115:541";
|
|
|
+
|
|
|
+// String up2 = "2024031012:215,2024031013:242,2024031014:166,2024031015:194,2024031016:209,2024031017:245,2024031018:320,2024031019:332,2024031020:400,2024031021:375,2024031022:636,2024031023:316,2024031100:167,2024031101:45,2024031102:22,2024031103:26,2024031104:12,2024031105:22,2024031106:24,2024031107:143,2024031108:181,2024031109:199,2024031110:194,2024031111:330,2024031112:423,2024031113:421,2024031114:497,2024031115:424";
|
|
|
+ String up2 = "2024031012:409,2024031013:464,2024031014:354,2024031015:474,2024031016:436,2024031017:636,2024031018:709,2024031019:741,2024031020:802,2024031021:904,2024031022:1112,2024031023:639,2024031100:378,2024031101:78,2024031102:47,2024031103:37,2024031104:17,2024031105:49,2024031106:103,2024031107:293,2024031108:457,2024031109:488,2024031110:558,2024031111:711,2024031112:785,2024031113:830,2024031114:974,2024031115:850";
|
|
|
+ String down2 = "2024031012:748,2024031013:886,2024031014:788,2024031015:1029,2024031016:957,2024031017:1170,2024031018:1208,2024031019:1181,2024031020:1275,2024031021:1265,2024031022:1512,2024031023:1190,2024031100:1127,2024031101:486,2024031102:289,2024031103:254,2024031104:197,2024031105:310,2024031106:344,2024031107:693,2024031108:976,2024031109:1045,2024031110:1039,2024031111:1257,2024031112:1202,2024031113:1454,2024031114:1785,2024031115:1544";
|
|
|
+
|
|
|
+ RankStrategy4RegionMergeModelV567 job = new RankStrategy4RegionMergeModelV567();
|
|
|
+ List<Double> l1 = job.getRateData(job.help(up1, "2024031115", 24), job.help(down1, "2024031115", 24), 1., 10.);
|
|
|
+ Double d1 = job.calScoreWeightNoTimeDecay(l1);
|
|
|
+
|
|
|
+ System.out.println(d1);
|
|
|
+
|
|
|
+ List<Double> l2 = job.getRateData(job.help(up2, "2024031115", 24), job.help(down2, "2024031115", 24), 1., 10.);
|
|
|
+ Double d2 = job.calScoreWeightNoTimeDecay(l2);
|
|
|
+
|
|
|
+ System.out.println(d2);
|
|
|
+
|
|
|
+ }
|
|
|
+
|
|
|
+ List<Double> help(String s, String date, Integer h) {
|
|
|
+ Map<String, Double> maps = Arrays.stream(s.split(",")).map(pair -> pair.split(":"))
|
|
|
+ .collect(Collectors.toMap(
|
|
|
+ arr -> arr[0],
|
|
|
+ arr -> Double.valueOf(arr[1])
|
|
|
+ ));
|
|
|
+ List<String> datehours = new LinkedList<>(); // 时间是倒叙的
|
|
|
+ List<Double> result = new ArrayList<>();
|
|
|
+ for (int i = 0; i < h; ++i) {
|
|
|
+ Double d = (result.isEmpty() ? 0.0 : result.get(result.size() - 1));
|
|
|
+ result.add(d + maps.getOrDefault(date, 0D));
|
|
|
+ datehours.add(date);
|
|
|
+ date = ExtractorUtils.subtractHours(date, 1);
|
|
|
+ }
|
|
|
+ return result;
|
|
|
+ }
|
|
|
+
|
|
|
+}
|
supeng