计算器调整

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

@@ -66,22 +66,24 @@ public class BatchScoreCalculator {
 
                 BigDecimal minScoreValue = idx.getScoreCalculator().getMinScore();
                 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(
-                                    (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 = maxScoreValue.subtract(normalizeValue);
-                    }
-                }else {
-                    //如果不需要归一 则 直接value*权重
-                    if (idx.isScore()) {
-                        vo.setSampleValue(new BigDecimal(vo.getSampleValue().toString()).compareTo(NumConstant.ZERO_DECIMAL) == NumConstant.ZERO ? ScoreConstants.MIN_SCORE : new BigDecimal(vo.getSampleValue().toString()));
-                        normalizeValue = getFinalSampleValue(vo.getSampleValue(), threshold);
+
+                //1.如果是分数值（平均值）不需要归一 则 直接value*权重
+                //2.否则 先判断 样本值是否相等 是：反正切函数 否：归一算法
+                if (idx.isScore()) {
+                    vo.setSampleValue(new BigDecimal(vo.getSampleValue().toString()).compareTo(NumConstant.ZERO_DECIMAL) == NumConstant.ZERO ? ScoreConstants.MIN_SCORE : new BigDecimal(vo.getSampleValue().toString()));
+                    normalizeValue = getFinalSampleValue(vo.getSampleValue(), threshold);
+                } else {
+                    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(
+                                        (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 = maxScoreValue.subtract(normalizeValue);
+                        }
                     } else {
                         normalizeValue = scoreCalculator.normalize(getFinalSampleValue(vo.getSampleValue(), threshold));
                     }