Merge remote-tracking branch 'origin/dev_screen_data' into dev_temp

5 years ago · 8e0f69e6a3
5 changed files with 156 additions and 18 deletions
--- a/epmet-module/data-report/data-report-server/src/main/java/com/epmet/datareport/service/screen/impl/PartyMemberLeadServiceImpl.java
+++ b/epmet-module/data-report/data-report-server/src/main/java/com/epmet/datareport/service/screen/impl/PartyMemberLeadServiceImpl.java
@ -77,7 +77,7 @@ public class PartyMemberLeadServiceImpl implements PartyMemberLeadService {
     * @date 2020/8/20 6:06 下午
     */
    public String getRatio(Double d){
-        BigDecimal bigDecimal = new BigDecimal(d * NumConstant.ONE_HUNDRED);
+        BigDecimal bigDecimal = new BigDecimal(d);
        return bigDecimal.setScale(NumConstant.TWO, BigDecimal.ROUND_HALF_UP).toPlainString().concat(ScreenConstant.RATIO);
    }

--- a/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/DoubleScoreCalculator.java
+++ b/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/DoubleScoreCalculator.java
@ -22,7 +22,7 @@ public class DoubleScoreCalculator extends ScoreCalculator {
        this.minScore = minScore;
        this.maxScore = maxScore;
        this.correlation = correlation;
-        this.prepare();
+        this.prepare4SourceArray();
    }

    public DoubleScoreCalculator(List<Double> sourceArray, BigDecimal minScore, BigDecimal maxScore, Correlation correlation) {
@ -30,7 +30,28 @@ public class DoubleScoreCalculator extends ScoreCalculator {
        this.minScore = minScore;
        this.maxScore = maxScore;
        this.correlation = correlation;
-        this.prepare();
+        this.prepare4SourceArray();
+    }
+
+    /**
+     * 初始化基于边界值的整数分值计算
+     * @param minSourceValue 左边界值
+     * @param maxSourceValue 右边界值
+     * @param minScore 分值区间的左边界
+     * @param maxScore 分值区间的右边界
+     * @param correlation 相关性
+     */
+    public DoubleScoreCalculator(Double minSourceValue, Double maxSourceValue, BigDecimal minScore, BigDecimal maxScore, Correlation correlation) {
+        BigDecimal minSourceValueBD = new BigDecimal(minSourceValue);
+        BigDecimal maxSourceValueBD = new BigDecimal(maxSourceValue);
+
+        this.minScore = minScore;
+        this.maxScore = maxScore;
+        this.minValue = minSourceValueBD;
+        this.maxValue = maxSourceValueBD;
+        this.correlation = correlation;
+        prepare4BoundaryValue();
+        System.out.println("最小值："+minScore+"；最大值："+maxScore);
    }

    @Override
--- a/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/IntegerScoreCalculator.java
+++ b/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/IntegerScoreCalculator.java
@ -10,9 +10,9 @@ import java.util.List;
 public class IntegerScoreCalculator extends ScoreCalculator {

    /**
-     * 初始化整数分值计算
+     * 初始化基于原数组的整数分值计算
     * ☆☆☆ 务必在该构造方法最后调用父类的prepare()方法 ☆☆☆
-     * @param sourceArray 数据所在的数组
+     * @param sourceArray 源数据完整数组
     * @param minScore 分值区间的左边界
     * @param maxScore 分值区间的右边界
     * @param correlation 相关性
@ -22,17 +22,44 @@ public class IntegerScoreCalculator extends ScoreCalculator {
        this.minScore = minScore;
        this.maxScore = maxScore;
        this.correlation = correlation;
-        this.prepare();
+        prepare4SourceArray();
        System.out.println("最小值："+minScore+"；最大值："+maxScore);
-
    }

+    /**
+     * 初始化基于原数组的整数分值计算
+     * @param sourceList 源数据完整列表
+     * @param minScore 分值区间的左边界
+     * @param maxScore 分值区间的右边界
+     * @param correlation 相关性
+     */
    public IntegerScoreCalculator(List<Integer> sourceList, BigDecimal minScore, BigDecimal maxScore, Correlation correlation) {
        this.sourceArrary = sourceList.toArray();
        this.minScore = minScore;
        this.maxScore = maxScore;
        this.correlation = correlation;
-        this.prepare();
+        prepare4SourceArray();
+        System.out.println("最小值："+minScore+"；最大值："+maxScore);
+    }
+
+    /**
+     * 初始化基于边界值的整数分值计算
+     * @param minSourceValue 左边界值
+     * @param maxSourceValue 右边界值
+     * @param minScore 分值区间的左边界
+     * @param maxScore 分值区间的右边界
+     * @param correlation 相关性
+     */
+    public IntegerScoreCalculator(Integer minSourceValue, Integer maxSourceValue, BigDecimal minScore, BigDecimal maxScore, Correlation correlation) {
+        BigDecimal minSourceValueBD = new BigDecimal(minSourceValue);
+        BigDecimal maxSourceValueBD = new BigDecimal(maxSourceValue);
+
+        this.minScore = minScore;
+        this.maxScore = maxScore;
+        this.minValue = minSourceValueBD;
+        this.maxValue = maxSourceValueBD;
+        this.correlation = correlation;
+        prepare4BoundaryValue();
        System.out.println("最小值："+minScore+"；最大值："+maxScore);
    }

--- a/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/ScoreCalculator.java
+++ b/epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/ScoreCalculator.java
@ -1,5 +1,7 @@
 package com.epmet.support.normalizing;

+import lombok.Data;
+
 import java.math.BigDecimal;
 import java.math.MathContext;
 import java.util.Arrays;
@ -11,23 +13,40 @@ import java.util.stream.Collectors;
 * ☆☆☆ 如果需要保持传入的数组元素顺序不变，请在实现类的构造方法中将传入数组进行克隆 ☆☆☆
 * @param <T> 数据类型泛型
 */
+@Data
 public abstract class ScoreCalculator<T> {

+    /**
+     * 源数据的数组
+     */
    protected T[] sourceArrary;

+    /**
+     * 最大最小分
+     */
    protected BigDecimal minScore;
    protected BigDecimal maxScore;

+    /**
+     * 相关性
+     */
    protected Correlation correlation;

-    private BigDecimal maxValue;
-    private BigDecimal minValue;
+    /**
+     * 系数
+     */
    private BigDecimal coefficient;

    /**
-     * 计算准备
+     * 最大最小值
     */
-    protected void prepare() {
+    protected BigDecimal maxValue;
+    protected BigDecimal minValue;
+
+    /**
+     * 计算准备（基于sourceArray方式的）
+     */
+    public void prepare4SourceArray() {
        // 校验数组
        if (!validSourceArray(sourceArrary)) {
            throw new RuntimeException("入参数组错误:请设置非空数组");
@ -37,7 +56,14 @@ public abstract class ScoreCalculator<T> {
        minValue = getMinFromSourceArray();
        //计算系数
        System.out.println("最小值："+minScore+"；最大值："+maxScore);
-        coefficient = getCoefficient(minValue, maxValue);
+        coefficient = calcuteCoefficient(minValue, maxValue);
+    }
+
+    /**
+     * 计算准备（基于边界值的）
+     */
+    public void prepare4BoundaryValue() {
+        coefficient = calcuteCoefficient(minValue, maxValue);
    }

    /**
@ -50,10 +76,6 @@ public abstract class ScoreCalculator<T> {
            throw new RuntimeException("入参数组错误:请设置sourceValue");
        }

-        if (!Arrays.asList(sourceArrary).contains(sourceValue)) {
-            throw new RuntimeException("请确认要计算的数组在数组中存在");
-        }
-
        if (correlation == Correlation.POSITIVE) {
            // 正相关
            BigDecimal x = coefficient.multiply(convertValue2BigDecimal(sourceValue).subtract(minValue));
@ -95,6 +117,8 @@ public abstract class ScoreCalculator<T> {
        return scores;
    }

+    //---------------------批量-------------------------
+
    /**
     * 批量归一算法，返回List
     * @param sourceValues
@ -147,7 +171,7 @@ public abstract class ScoreCalculator<T> {
     * 计算系数
     * @return
     */
-    protected BigDecimal getCoefficient(BigDecimal min, BigDecimal max) {
+    protected BigDecimal calcuteCoefficient(BigDecimal min, BigDecimal max) {
        BigDecimal fenmu = max.subtract(min);
        if (fenmu.toString().equals("0"))return new BigDecimal(0);
        BigDecimal fenzi = maxScore.subtract(minScore);
--- a/epmet-module/data-statistical/data-statistical-server/src/test/java/com/epmet/stats/test/normalizing/DemoScoreCal.java
+++ b/epmet-module/data-statistical/data-statistical-server/src/test/java/com/epmet/stats/test/normalizing/DemoScoreCal.java
@ -0,0 +1,66 @@
+package com.epmet.stats.test.normalizing;
+
+import com.epmet.support.normalizing.Correlation;
+import com.epmet.support.normalizing.DoubleScoreCalculator;
+import com.epmet.support.normalizing.IntegerScoreCalculator;
+import com.epmet.support.normalizing.ScoreCalculator;
+
+import java.math.BigDecimal;
+import java.util.Arrays;
+
+public class DemoScoreCal {
+
+    public static void main(String[] args) {
+        //demoInteger();
+        demoIntegerPartical();
+        //demoDouble();
+    }
+
+    /**
+     * 整数类型,完整源数据列表的归一算法
+     */
+    public static void demoInteger() {
+        Integer[] iArray = {4,8,1,3,2};
+        BigDecimal minScore = new BigDecimal(5);
+        BigDecimal maxScore = new BigDecimal(10);
+
+        ScoreCalculator sc = new IntegerScoreCalculator(iArray, minScore, maxScore, Correlation.NEGATIVE);
+        BigDecimal[] scores = sc.normalize(iArray);
+        Arrays.stream(scores).forEach(s -> System.out.println(s));
+    }
+
+    /**
+     * 整数类型,基于边界值的部分列表的的归一算法
+     */
+    public static void demoIntegerPartical() {
+        Integer[] iArray = {4,1,2};
+        BigDecimal minScore = new BigDecimal(5);
+        BigDecimal maxScore = new BigDecimal(10);
+
+        ScoreCalculator sc = new IntegerScoreCalculator(1, 8 ,minScore, maxScore, Correlation.NEGATIVE);
+        BigDecimal[] scores = sc.normalize(iArray);// 此处也可以直接使用list参数的重载方法，计算阶段没有任何区别，区别在于new IntegerScoreCalculator()阶段
+        Arrays.stream(scores).forEach(s -> System.out.println(s));
+    }
+
+    /**
+     * double类型归一算法
+     */
+    public static void demoDouble() {
+        Double[] iArray = {1.9,8.9,1.0,3.0,2.0};
+        BigDecimal minScore = new BigDecimal(5);
+        BigDecimal maxScore = new BigDecimal(10);
+
+        ScoreCalculator sc = new DoubleScoreCalculator(iArray, minScore, maxScore, Correlation.POSITIVE);
+        BigDecimal normalize = sc.normalize(3.0);
+        System.out.println(normalize);
+
+        /**
+         * 同一组数据内，只有被计算值变了的话，不需要重新new对象，直接重复调用即可
+         */
+        BigDecimal normalize2 = sc.normalize(2.0);
+        System.out.println(normalize2);
+    }
+
+
+
+}