多层权重计算逻辑实现

src/main/java/com/keymobile/indicators/model/mapper/weight/WeightIndValueMapper.java

@@ -31,4 +31,7 @@ public interface WeightIndValueMapper extends BaseMapper<WeightIndValue> {
 
     void batchDeleteByWeightIds(@Param("ids") List<Integer> ids);
 
+    WeightIndValue findByIndIdAndObjId(@Param("indId") String indId,
+                                       @Param("objId") String objId);
+
 }

src/main/java/com/keymobile/indicators/service/hytobacco/ScoreRuleService.java

@@ -8,6 +8,9 @@ import java.util.Map;
 import java.util.regex.Matcher;
 import java.util.regex.Pattern;
 
+import com.keymobile.indicators.model.entity.dataenter.TaskRuleIndicator;
+import com.keymobile.indicators.model.entity.weight.WeightIndValue;
+import com.keymobile.indicators.model.mapper.weight.WeightIndValueMapper;
 import org.apache.commons.lang.StringUtils;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
@@ -40,6 +43,10 @@ public class ScoreRuleService {
 	private DriveIndCalResultDefMapper driveIndCalResultDefMapper;
 	@Autowired
 	private ObjScoreCalResultMapper objScoreCalResultMapper;
+	@Autowired
+	private DriveIndDefService driveIndDefService;
+	@Autowired
+	private WeightIndValueMapper weightIndValueMapper;
 	
 	private static final Pattern P = Pattern.compile("(\\[[^\\]]*\\])");
 	
@@ -534,9 +541,12 @@ public class ScoreRuleService {
 					}else if("2".equals(scoreRule.getCalType())){//2单个指标权重计算
 						objScoreCalResult = this.calSingleIndWeight(compareCatalog,objScoreCalResult ,scoreRule, 
 								compareObj, date, code, dateMark);
-					}else {//3:指标总得分
+					}else if ("3".equals(scoreRule.getCalType())){//3:指标总得分
 						objScoreCalResult = this.calGroupIndAverageOrSum(compareCatalog,objScoreCalResult,
 								scoreRule, compareObj, date, scoreRule.getCalType(),code,dateMark);
+					}else {//4:多层权重
+						objScoreCalResult = this.calMoreIndWeight(compareCatalog,objScoreCalResult ,scoreRule,
+								compareObj, date, code, dateMark);
 					}
 					objScoreCalResult.setCompareCatalog(compareCatalog);
 					objScoreCalResult.setCompareId(compareId);
@@ -578,7 +588,176 @@ public class ScoreRuleService {
 			logger.info("单位评分卡id："+scoreRuleId+" 不存在");
 		}
 	}
-	
+
+	/**
+	 * 多层权重计算
+	 * @param compareCatalog
+	 * @param objScoreCalResult
+	 * @param scoreRule
+	 * @param compareObj
+	 * @param date
+	 * @param code
+	 * @param dateMark
+	 * @return
+	 */
+	private ObjScoreCalResult calMoreIndWeight(String compareCatalog, ObjScoreCalResult objScoreCalResult, ScoreRule scoreRule, String compareObj, int date, String code, int dateMark) {
+		objScoreCalResult.setCompareObj(compareObj);
+		objScoreCalResult.setScoreValue("0.0");
+		objScoreCalResult.setImproveValue("0.0");
+		objScoreCalResult.setDate(date);
+		//改用添加对标单元目录过滤
+		List<DriveIndCalResultDef> calResults = driveIndCalResultDefMapper.
+				findByCompareCatalogAndCompareObjAndDate(compareCatalog,compareObj,
+						date, code, dateMark);
+		int indCount = 0;//定义用户记录纳入考核指标个数
+		// 单个指标最终的得分 = 指标分数 * 综合评价权重(改善提升权重) * 维度权重
+		List<String> improveValues = new ArrayList<>();
+		List<String> scoreValues = new ArrayList<>();
+		if(!calResults.isEmpty()) {
+			objScoreCalResult.setCompareObjDesc(calResults.get(0).getCompareObjDesc());
+			StringBuilder groupIndIds = new StringBuilder();
+			for (DriveIndCalResultDef calResult : calResults) {
+				//根据考核指标id获取考核指标
+				DriveIndDef driveIndDef = driveIndDefService.getIndById(calResult.getIndId(), true);
+				WeightIndValue weightIndValue = weightIndValueMapper.findByIndIdAndObjId(calResult.getIndId(), compareObj);
+				if(driveIndDef != null) {
+					//如果考核指标是参与单位计分的
+					if(StringUtils.isBlank(driveIndDef.getIsUnitCalScore()) || "1".equals(driveIndDef.getIsUnitCalScore())) {
+						// 判断该指标是否为多合一指标(是：1   否：0)
+						if ("1".equals(driveIndDef.getIsMoreThanOneIndicators())) {
+							indCount += 1;
+							// 判断同组内的其他指标是否已经计算
+							if (!StringUtils.contains(groupIndIds.toString(), driveIndDef.getIndId())) {
+								// 获取组内指标
+								List<TaskRuleIndicator> indicators = driveIndDef.getIndicators();
+								BigDecimal dimensionWeight = BigDecimal.ZERO;
+								if (weightIndValue.getDimensionWeight() != null) {
+									dimensionWeight = weightIndValue.getDimensionWeight().divide(new BigDecimal(100));
+								}
+								// 获取多合一指标中的最大指标值
+								Map<String, String> map = getMaxIndValue(driveIndDef, calResult, compareCatalog, compareObj, date, code, dateMark);
+								if (!StringUtils.equals("0.0", map.get("maxScore"))) {
+									BigDecimal score = new BigDecimal(map.get("maxScore"));
+									BigDecimal synthesizeWeight = BigDecimal.ZERO;
+									if (weightIndValue.getSynthesizeWeight() != null) {
+										synthesizeWeight = weightIndValue.getSynthesizeWeight().divide(new BigDecimal(100));
+									}
+									BigDecimal finalScore = score.multiply(synthesizeWeight).multiply(dimensionWeight);
+									scoreValues.add(String.valueOf(finalScore));
+								}
+								if (!StringUtils.equals("0.0", map.get("maxImproveScore"))) {
+									BigDecimal improveScore = new BigDecimal(map.get("maxImproveScore"));
+									BigDecimal improveWeight = BigDecimal.ZERO;
+									if (weightIndValue.getImproveWeight() != null) {
+										improveWeight = weightIndValue.getImproveWeight().divide(new BigDecimal(100));
+									}
+									BigDecimal finalImproveScore = improveScore.multiply(improveWeight).multiply(dimensionWeight);
+									improveValues.add(String.valueOf(finalImproveScore));
+								}
+								for (TaskRuleIndicator indicator : indicators) {
+									groupIndIds.append(indicator.getIndId());
+								}
+							}
+						}else {
+							indCount += 1;
+							BigDecimal dimensionWeight = BigDecimal.ZERO;
+							if (weightIndValue.getDimensionWeight() != null) {
+								dimensionWeight = weightIndValue.getDimensionWeight().divide(new BigDecimal(100));
+							}
+							if(!"No".equals(calResult.getImproveScore()) && StringUtils.isNotBlank(calResult.getImproveScore())) {
+								BigDecimal improveScore = new BigDecimal(calResult.getImproveScore());
+								BigDecimal improveWeight = BigDecimal.ZERO;
+								if (weightIndValue.getImproveWeight() != null) {
+									improveWeight = weightIndValue.getImproveWeight().divide(new BigDecimal(100));
+								}
+								BigDecimal finalImproveScore = improveScore.multiply(improveWeight).multiply(dimensionWeight);
+								improveValues.add(String.valueOf(finalImproveScore));
+							}
+							if(!"NaN".equals(calResult.getValue()) && !"Infinite".equals(calResult.getValue()) && !"0".equals(calResult.getValue())) {
+								BigDecimal score = new BigDecimal(calResult.getScore());
+								BigDecimal synthesizeWeight = BigDecimal.ZERO;
+								if (weightIndValue.getSynthesizeWeight() != null) {
+									synthesizeWeight = weightIndValue.getSynthesizeWeight().divide(new BigDecimal(100));
+								}
+								BigDecimal finalScore = score.multiply(synthesizeWeight).multiply(dimensionWeight);
+								scoreValues.add(String.valueOf(finalScore));
+							}
+						}
+					}
+				}
+			}
+			String averageImproveValue = "0.0";
+			String improveSumValue = "0.0";
+			String scoreTmpSumValue = CalculateUtils.sumValue(scoreValues);
+			if(!improveValues.isEmpty()) {
+				improveSumValue = CalculateUtils.sumValue(improveValues);
+				averageImproveValue = improveSumValue;
+			}
+			//计算总积分
+			Double scoreSumValue = (Double.parseDouble(CalculateUtils.sumValue(scoreValues)) + Double.parseDouble(CalculateUtils.sumValue(improveValues)));
+
+			objScoreCalResult.setScoreSumValue(String.valueOf(scoreSumValue));
+			objScoreCalResult.setIndCount(indCount);
+			objScoreCalResult.setScoreValue(String.valueOf(scoreSumValue));
+			objScoreCalResult.setImproveValue(averageImproveValue);
+			objScoreCalResult.setImproveSumValue(improveSumValue);
+			objScoreCalResult.setScoreTmpSumValue(scoreTmpSumValue);
+			objScoreCalResult.setScoreTmpValue(scoreTmpSumValue);
+		}
+		return objScoreCalResult;
+	}
+
+	/**
+	 * 获取多合一指标的最大值
+	 * @param driveIndDef 指标对象
+	 * @param calResult
+	 * @param compareCatalog
+	 * @param compareObj
+	 * @param date
+	 * @param code
+	 * @param dateMark
+	 * @return 最大值集合
+	 */
+	private Map<String, String> getMaxIndValue(DriveIndDef driveIndDef, DriveIndCalResultDef calResult, String compareCatalog, String compareObj, int date, String code, int dateMark) {
+		List<TaskRuleIndicator> indicators = driveIndDef.getIndicators();
+		Map<String, String> map = new HashMap<>();
+		String maxScore = "0.0";
+		String maxImproveScore = "0.0";
+		if(!"No".equals(calResult.getImproveScore()) && StringUtils.isNotBlank(calResult.getImproveScore())) {
+			maxImproveScore = calResult.getImproveScore();
+		}
+		if(!"NaN".equals(calResult.getValue()) && !"Infinite".equals(calResult.getValue()) && !"0".equals(calResult.getValue())) {
+			maxScore = calResult.getScore();
+		}
+		for (TaskRuleIndicator indicator : indicators) {
+			// 获取组内指标的指标积分对象
+			DriveIndCalResultDef driveIndCalResultDef = driveIndCalResultDefMapper.findByCompareCatalogAndCompareObjAndIndIdAndDate(compareCatalog, compareObj,
+					indicator.getIndId(), date, code, dateMark);
+			if(!"No".equals(driveIndCalResultDef.getImproveScore()) && StringUtils.isNotBlank(driveIndCalResultDef.getImproveScore())) {
+				// 比较大小
+				BigDecimal improveScore = new BigDecimal(driveIndCalResultDef.getImproveScore());
+				// 计算两个指标改善提升分数的差值
+				double poor = improveScore.subtract(new BigDecimal(maxImproveScore)).doubleValue();
+				// 差值大于0，则说明该指标的改善提升分数更大
+				if (poor > 0) {
+					maxImproveScore = driveIndCalResultDef.getImproveScore();
+				}
+			}
+			if(!"NaN".equals(driveIndCalResultDef.getValue()) && !"Infinite".equals(driveIndCalResultDef.getValue()) && !"0".equals(driveIndCalResultDef.getValue())) {
+				// 比较大小
+				BigDecimal score = new BigDecimal(driveIndCalResultDef.getScore());
+				// 计算两个指标改善提升分数的差值
+				double poor = score.subtract(new BigDecimal(maxScore)).doubleValue();
+				if (poor > 0) {
+					maxScore = driveIndCalResultDef.getScore();
+				}
+			}
+		}
+		map.put("maxScore", maxScore);
+		map.put("maxImproveScore", maxImproveScore);
+		return map;
+	}
+
 	private ScoreRule changeJson(ScoreRule scoreRule) {
 		Gson gson = new Gson();
 		if(StringUtils.isNotBlank(scoreRule.getIndTypeWeightsJson())) {

src/main/resources/mybatis/mapping/WeightIndValueMapper.xml

@@ -34,4 +34,9 @@
         </foreach>
     </update>
 
+    <select id="findByIndIdAndObjId" resultType="com.keymobile.indicators.model.entity.weight.WeightIndValue">
+        select * from weight_ind_value
+        where ind_id = #{indId} and obj_id = #{objId} and state = 1
+    </select>
+
 </mapper>
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