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src/main/java/org/dromara/easyai/tools/Frequency.java

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+package org.dromara.easyai.tools;
+
+import java.util.List;
+
+public abstract class Frequency {//统计频数
+
+    public float average(float... m) {//计算平均值
+        int len = m.length;
+        float allNub = 0;
+        for (int i = 0; i < len; i++) {
+            allNub = allNub + m[i];
+        }
+        allNub = allNub / len;
+        return allNub;
+    }
+
+    public static float getEDist(float[] x1, float[] x2) {//返回两个等长数组之间的欧式距离
+        float[] y = new float[x1.length];
+        for (int i = 0; i < y.length; i++) {
+            y[i] = x1[i] - x2[i];
+        }
+        float sigma = 0;
+        for (int i = 0; i < y.length; i++) {
+            sigma = sigma + (float)Math.pow(y[i], 2);
+        }
+        return (float)Math.sqrt(sigma);
+    }
+
+    public float averageByList(List<Float> m) {//计算平均值
+        int len = m.size();
+        float allNub = 0;
+        for (int i = 0; i < len; i++) {
+            allNub = allNub + m.get(i);
+        }
+        allNub = ArithUtil.div(allNub, len);
+        return allNub;
+    }
+
+    public float sigma(float... m) {//求和
+        int len = m.length;
+        float allNub = 0;
+        for (int i = 0; i < len; i++) {
+            allNub = ArithUtil.add(allNub, m[i]);
+        }
+        return allNub;
+    }
+
+    public float getPointLength(float x, float y, float i, float j) {//获取两个二维坐标之间的欧式距离
+        return (float)Math.sqrt(ArithUtil.add((float)Math.pow(ArithUtil.sub(x, i), 2), (float)Math.pow(ArithUtil.sub(y, j), 2)));
+    }
+
+    public float variance(float... m) {//计算方差
+        float ave = average(m);//先计算出平均值
+        float allNub = 0;
+        for (int i = 0; i < m.length; i++) {
+            allNub = allNub + (float)Math.pow(m[i] - ave, 2);
+        }
+        return allNub / m.length;
+    }
+
+    public float varianceByAve(float[] m, float ave) {// 计算方差，依赖平均值
+        float allNub = 0;
+        for (int i = 0; i < m.length; i++) {
+            allNub = allNub + (float)Math.pow(m[i] - ave, 2);
+        }
+        return allNub / m.length;
+    }
+
+    public float sdByAvg(float[] m, float avg) {//计算标准差，带平均值
+        float var = varianceByAve(m, avg);
+        return (float)Math.sqrt(var);
+    }
+
+    public float sd(float... m) {//计算标准差
+        float var = variance(m);
+        return (float)Math.sqrt(var);
+    }
+
+    public float dcByAvg(float[] m, float ave) {//带均值算离散
+        float allNub = 0;
+        for (int i = 0; i < m.length; i++) {
+            allNub = allNub + (float)Math.pow(m[i] - ave, 2);
+        }
+        return ArithUtil.div((float)Math.sqrt(ArithUtil.div(allNub, m.length)), ave);//离散系数
+    }
+
+    public float dc(float... m) {//计算离散系数
+        float ave = average(m);//先计算出平均值
+        float dc = 0;
+        if (ave > 0) {
+            float allNub = 0;
+            for (int i = 0; i < m.length; i++) {
+                allNub = allNub + (float)Math.pow(m[i] - ave, 2);
+            }
+            dc = ArithUtil.div((float)Math.sqrt(ArithUtil.div(allNub, m.length)), ave);//离散系数
+        }
+        return dc;
+    }
+
+    public float softMax(int t, float... m) {//下标和数组
+        float my = (float)Math.exp(m[t]);
+        float all = 0.0f;
+        int allLength = m.length;
+        for (int i = 0; i < allLength; i++) {
+            all = all + (float)Math.exp(m[i]);
+        }
+        return ArithUtil.div(my, all);
+    }
+
+    public float[] getLimit(float[] m) {//获取数组中的最大值和最小值，最小值在前，最大值在后
+        float[] limit = new float[2];
+        float max = 0;
+        float min = -1;
+        int l = m.length;
+        for (int i = 0; i < l; i++) {
+            float nub = m[i];
+            if (min == -1 || nub < min) {
+                min = nub;
+            }
+            if (nub > max) {
+                max = nub;
+            }
+        }
+        limit[0] = min;
+        limit[1] = max;
+        return limit;
+    }
+}