Merge remote-tracking branch 'origin/dev_screen_data_2.0' into dev_temp

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/BatchScoreCalculator.java

@@ -1,7 +1,10 @@
 package com.epmet.support.normalizing.batch;
 
+import com.alibaba.fastjson.JSON;
+import com.epmet.support.normalizing.BigDecimalScoreCalculator;
 import com.epmet.support.normalizing.Correlation;
 import com.epmet.support.normalizing.ScoreCalculator;
+import com.epmet.support.normalizing.ScoreConstants;
 
 import java.math.BigDecimal;
 import java.math.RoundingMode;
@@ -59,21 +62,20 @@ public class BatchScoreCalculator {
                 String sampleId = vo.getSampleId();
                 //归一后的值
                 BigDecimal normalizeValue;// = scoreCalculator.normalize(getFinalSampleValue(vo.getSampleValue(), threshold));
-                BigDecimal maxValue = idx.getScoreCalculator().getMaxValue();
-                BigDecimal minValue = idx.getScoreCalculator().getMinValue();
+
                 BigDecimal minScoreValue = idx.getScoreCalculator().getMinScore();
-                if (maxValue.compareTo(minValue) == 0) {
+                BigDecimal maxScoreValue = idx.getScoreCalculator().getMaxScore();
+                if (idx.getScoreCalculator().getMaxValue().compareTo(idx.getScoreCalculator().getMinValue()) == 0) {
                     //*((max-min)/ (Math.PI/2))+min
                     //Math.atan(new Double(vo.getSampleValue().toString()))*
                     normalizeValue = new BigDecimal(Math.atan(new Double(getFinalSampleValue(vo.getSampleValue(), threshold).toString())))
                             .multiply(
-                                    (maxValue.subtract(minValue).divide(new BigDecimal(Math.PI / 2), 10, RoundingMode.UNNECESSARY)))
+                                    (maxScoreValue.subtract(minScoreValue).divide(new BigDecimal(Math.PI / 2), 10, RoundingMode.HALF_UP)))
                             .add(minScoreValue).setScale(6, RoundingMode.HALF_UP);
                     //
                     if (scoreCalculator.getCorrelation().getCode().equals(Correlation.NEGATIVE)) {
-                        normalizeValue = maxValue.subtract(normalizeValue);
+                        normalizeValue = maxScoreValue.subtract(normalizeValue);
                     }
-
                 }else {
                     //如果不需要归一 则 直接value*权重
                     if (idx.isScore()) {
@@ -119,4 +121,16 @@ public class BatchScoreCalculator {
                 ? bdRealValue
                 : threshold;
     }
+
+    public static void main(String[] args) {
+        List<IndexInputVO> indexInputVOS = new ArrayList<>();
+        String jsonStr = "{\"allParentIndexCode\":\"quanquxiangguan:zhilinengli\",\"indexId\":\"suoyoujiedaozlnlpjz\",\"indexValueVOs\":[{\"sampleId\":\"7b6f9a9f9f38d5f9fa7ce94a93d6eb28\",\"sampleValue\":69.830369}],\"score\":true,\"scoreCalculator\":{\"coefficient\":0,\"correlation\":\"POSITIVE\",\"maxScore\":100,\"maxValue\":69.830369,\"minScore\":60,\"minValue\":69.830369},\"threshold\":-1.0000,\"weight\":0.8000}";
+        IndexInputVO vo = JSON.parseObject(jsonStr, IndexInputVO.class);
+        BigDecimalScoreCalculator sc = new BigDecimalScoreCalculator(new BigDecimal("69.830369"), new BigDecimal("69.830369"), ScoreConstants.MIN_SCORE, ScoreConstants.MAX_SCORE, Correlation.getCorrelation(Correlation.POSITIVE.getCode()));
+        vo.setScoreCalculator(sc);
+        indexInputVOS.add(vo);
+        BatchScoreCalculator sc2 = new BatchScoreCalculator();
+        HashMap<String, CalculateResult> scoreTotalOfSampleId = sc2.getScoreTotalOfSampleId(indexInputVOS);
+        System.out.println(JSON.toJSONString(scoreTotalOfSampleId));
+    }
 }