提交短板筛选规则代码

src/main/java/com/keymobile/indicators/persistence/hyindicators/DriveIndCalResultRepository.java

@@ -35,4 +35,6 @@ public interface DriveIndCalResultRepository extends MongoRepository<DriveIndCal
 	public List<DriveIndCalResult> findByCompareObjAndDateAndIndIdIn(String compareObj,int date,List<String> indIds);
 	
 	public Optional<DriveIndCalResult> findByCompareIdAndCompareObjAndIndIdAndDate(String compareId,String compareObj,String indId,int date);
+	
+	public List<DriveIndCalResult> findByIndIdAndDateAndCompareObjIn(String indId,int date,List<String> compareObjs);
 }

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

 package com.keymobile.indicators.service.hytobacco;
 
+import java.util.ArrayList;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 import java.util.Optional;
 
 import org.slf4j.Logger;
@@ -11,8 +14,15 @@ import org.springframework.data.domain.PageRequest;
 import org.springframework.data.domain.Pageable;
 import org.springframework.stereotype.Service;
 
+import com.keymobile.indicators.model.entity.DriveIndCalResult;
+import com.keymobile.indicators.model.entity.indicators.DriveIndDef;
+import com.keymobile.indicators.model.entity.shortboard.ShortboardDriveIndRel;
+import com.keymobile.indicators.model.entity.shortboard.ShortboardItem;
 import com.keymobile.indicators.model.entity.shortboard.ShortboardRule;
+import com.keymobile.indicators.persistence.hyindicators.DriveIndCalResultRepository;
+import com.keymobile.indicators.persistence.hyindicators.ShortboardDriveIndRelRepository;
 import com.keymobile.indicators.persistence.hyindicators.ShortboardRuleRepository;
+import com.keymobile.indicators.utils.CalculateUtils;
 
 @Service
 public class ShortboardRuleService {
@@ -20,6 +30,12 @@ public class ShortboardRuleService {
 	
 	@Autowired
 	private ShortboardRuleRepository shortboardRuleRepo;
+	@Autowired
+	private ShortboardDriveIndRelRepository shortboardDriveIndRelRepo;
+	@Autowired
+	private DriveIndCalResultRepository driveIndCalResultRepo;
+	@Autowired
+	private DriveIndDefService driveIndDefService;
 	
 	public String saveOrUpdate(ShortboardRule shortboardRule,String catalogId,
 			String catalogIdPath,String user) {
@@ -46,4 +62,157 @@ public class ShortboardRuleService {
 		}
 		return null;
 	}
+	
+	//根据短板规则筛选短板单位
+	public List<Map<String,String>> getObjShortboard(String compareId,int date,
+			List<String> compareObjs,List<String> driveIds){
+		List<Map<String,String>> result = new ArrayList<>();
+		for(String driveId : driveIds) {
+			//根据考核指标id获取关联的短板筛选规则id
+			List<ShortboardDriveIndRel> relations = shortboardDriveIndRelRepo.
+					findByDriveIndDefId(driveId);
+			for(ShortboardDriveIndRel rel : relations) {
+				ShortboardRule shortboardRule = this.getById(rel.getShortboardRuleId());
+				if(shortboardRule!=null) {
+					List<ShortboardItem> shortboardItems = shortboardRule.getShortboardItem();
+					for(ShortboardItem item : shortboardItems) {
+						
+					}
+				}
+			}
+		}
+		return result;
+	}
+	
+	private void selectShortboardObj(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) {
+		String type = shortboardItem.getType();
+	}
+	
+	//短板筛选规则为均值
+	private List<DriveIndCalResult> selectAverageShortboard(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) {
+		List<DriveIndCalResult> calResults = driveIndCalResultRepo.
+				findByIndIdAndDateAndCompareObjIn(driveId, date, compareObjs);
+		List<DriveIndCalResult> filterCalResults = new ArrayList<>();//用于保存符合过滤条件的指标结果
+		List<DriveIndCalResult> realCalResults = new ArrayList<>();//用于保存符合过滤条件的指标结果
+		for(DriveIndCalResult calResult : calResults) {
+			//判断规则选择是大于还是小于
+			if("0".equals(shortboardItem.getCalType())) {//大于
+				if(!"NaN".equals(calResult.getValue()) && !"0(Error)".equals(calResult.getValue())
+						&& !"0.0000".equals(calResult.getValue()) && !"0".equals(calResult.getValue())) {
+					//判断有没有实际的平均值
+					if(!"0.0".equals(calResult.getActualAverage())) {
+						if(Double.parseDouble(calResult.getValue()) > 
+							Double.parseDouble(calResult.getActualAverage())) {
+							filterCalResults.add(calResult);
+						}
+					}else {//没有比较组内平均值
+						if(Double.parseDouble(calResult.getValue()) > 
+							Double.parseDouble(calResult.getAverage())) {
+							filterCalResults.add(calResult);
+						}
+					}
+				}
+			}else {//小于
+				if(!"NaN".equals(calResult.getValue()) && !"0(Error)".equals(calResult.getValue())
+						&& !"0.0000".equals(calResult.getValue()) && !"0".equals(calResult.getValue())) {
+					//判断有没有实际的平均值
+					if(!"0.0".equals(calResult.getActualAverage())) {
+						if(Double.parseDouble(calResult.getValue()) < 
+							Double.parseDouble(calResult.getActualAverage())) {
+							filterCalResults.add(calResult);
+						}
+					}else {//没有比较组内平均值
+						if(Double.parseDouble(calResult.getValue()) < 
+							Double.parseDouble(calResult.getAverage())) {
+							filterCalResults.add(calResult);
+						}
+					}
+				}
+			}
+		}
+		//分析filterCalResults
+		for(DriveIndCalResult filterCalResult : filterCalResults) {
+			//判断是比较差还是百分比
+			if("0".equals(shortboardItem.getAnalysisType())) {//绝对值
+				//判断有没有实际的平均值
+				if(!"0.0".equals(filterCalResult.getActualAverage())) {
+					//获取差值绝对值
+					Double differ = Math.abs(Double.parseDouble(filterCalResult.getActualAverage())
+							-Double.parseDouble(filterCalResult.getValue()));
+					if(differ > Double.parseDouble(shortboardItem.getValue())) {
+						realCalResults.add(filterCalResult);
+					}
+				}else {
+					//获取差值绝对值
+					Double differ = Math.abs(Double.parseDouble(filterCalResult.getAverage())
+							-Double.parseDouble(filterCalResult.getValue()));
+					if(differ > Double.parseDouble(shortboardItem.getValue())) {
+						realCalResults.add(filterCalResult);
+					}
+				}
+			}else {//百分比
+				//判断有没有实际的平均值
+				if(!"0.0".equals(filterCalResult.getActualAverage())) {
+					Double percentage = Math.abs(Double.parseDouble(CalculateUtils.calGowth("%", 
+							filterCalResult.getValue(), filterCalResult.getActualAverage(), "1")));
+					if(percentage > Double.parseDouble(shortboardItem.getValue())) {
+						realCalResults.add(filterCalResult);
+					}
+				}else {
+					Double percentage = Math.abs(Double.parseDouble(CalculateUtils.calGowth("%", 
+							filterCalResult.getValue(), filterCalResult.getAverage(), "1")));
+					if(percentage > Double.parseDouble(shortboardItem.getValue())) {
+						realCalResults.add(filterCalResult);
+					}
+				}
+			}
+		}
+		return realCalResults;
+	}
+	
+	//短板筛选规则为最大值
+	private List<DriveIndCalResult> selectMaxShortboard(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) throws Exception{
+		List<DriveIndCalResult> calResults = driveIndCalResultRepo.
+				findByIndIdAndDateAndCompareObjIn(driveId, date, compareObjs);
+		List<DriveIndCalResult> realCalResults = new ArrayList<>();//用于保存符合过滤条件的指标结果
+		//获取排名第一的最大值
+		String maxValue = null;
+		for(DriveIndCalResult calResult : calResults) {
+			if(calResult.getRank()==1) {
+				maxValue = calResult.getValue();
+			}
+		}
+		if(maxValue!=null) {
+			for(DriveIndCalResult calResult : calResults) {
+				//判断是比较差还是百分比
+				if("0".equals(shortboardItem.getAnalysisType())) {//绝对值
+					
+				}else {//百分比
+					
+				}
+			}
+		}
+		return realCalResults;
+	}
+	
+	//短板筛选规则为最小值
+	private void selectMinShortboard(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) {
+		
+	}
+	
+	//短板筛选规则为排名
+	private void selectRankShortboard(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) {
+		
+	}
+	
+	//短板筛选规则为历史同期
+	private void selectSametimeShortboard(ShortboardItem shortboardItem,
+			List<String> compareObjs,String driveId,int date) {
+		
+	}
 }

src/main/java/com/keymobile/indicators/utils/CalculateUtils.java

@@ -214,23 +214,25 @@ public class CalculateUtils {
     }
 
 	public static void main(String[] args) {
-		Map<String,String> map = new HashMap<>();
-		map.put("1001", "1");
-		map.put("1002", "3");
-		map.put("1003", "2");
-		map.put("1004", "4");
-		map.put("1005", "8");
-		map.put("1006", "6");
-		map.put("1007", "7");
-		map.put("1008", "5");
-		CalculateUtils cal = new CalculateUtils();
-		Map<String,Integer> result = cal.rankValue(map, "1");
-		System.out.println(result);
-		
-		String formula = "([1001]+[1002])/2";
-		formula = formula.replace("[1001]", "3");
-		formula = formula.replace("[1002]", "5");
-		String result1 = AviatorEvaluator.execute(formula).toString();
-		System.out.println(result1);
+//		Map<String,String> map = new HashMap<>();
+//		map.put("1001", "1");
+//		map.put("1002", "3");
+//		map.put("1003", "2");
+//		map.put("1004", "4");
+//		map.put("1005", "8");
+//		map.put("1006", "6");
+//		map.put("1007", "7");
+//		map.put("1008", "5");
+//		CalculateUtils cal = new CalculateUtils();
+//		Map<String,Integer> result = cal.rankValue(map, "1");
+//		System.out.println(result);
+//		
+//		String formula = "([1001]+[1002])/2";
+//		formula = formula.replace("[1001]", "3");
+//		formula = formula.replace("[1002]", "5");
+//		String result1 = AviatorEvaluator.execute(formula).toString();
+//		System.out.println(result1);
+		Double b = (double) Math.abs(34-50);
+		System.out.println(b);
 	}
 }