From d6f1a81f8af23e55bcb2a44909efcfbf61cd34fe Mon Sep 17 00:00:00 2001
From: zyy <zyy@email.com>
Date: Mon, 20 Oct 2025 18:53:51 +0800
Subject: [PATCH] 1
---
trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java | 323 +++++++++++++++++++++++++++--------------------------
1 files changed, 166 insertions(+), 157 deletions(-)
diff --git a/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java b/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
index 8c22ccd..9ae134f 100644
--- a/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
+++ b/trading-order-huobi/src/main/java/com.yami.trading.huobi/data/job/AbstractGetDataJob.java
@@ -17,8 +17,8 @@
import java.math.BigDecimal;
import java.math.RoundingMode;
+import java.util.ArrayList;
import java.util.List;
-import java.util.Random;
public abstract class AbstractGetDataJob implements Runnable {
@@ -45,8 +45,6 @@
public abstract String getName();
- // 在类中定义静态Random实例
- private static final Random random = new Random();
public abstract void realtimeHandle(String symbols);
@@ -61,172 +59,53 @@
AdjustmentValue delayValue = AdjustmentValueCache.getDelayValue().get(symbol);
if (delayValue != null) {
- //延时几次 缓存frequency
- Integer frequency = AdjustmentValueCache.getFrequency().get(symbol);
- if (frequency == null) { //首次计算 缓存
- frequency = (int) Arith.div(Arith.mul(delayValue.getSecond(), 1000.0D), this.interval);
- AdjustmentValueCache.getFrequency().put(symbol, frequency);
+ if (delayValue.getSecond() < 0) {
+ AdjustmentValueCache.getDelayValue().remove(symbol);
+ AdjustmentValueCache.getPreAllocatedAdjustments().remove(symbol);
+ AdjustmentValueCache.getCurrentAdjustmentIndex().remove(symbol);
+ return;
+ }
+ int frequency = (int) Arith.div(Arith.mul(delayValue.getSecond(), 1000.0D), this.interval);
+ List<BigDecimal> adjustments = AdjustmentValueCache.getPreAllocatedAdjustments().get(symbol);
+ Integer currentIndex = AdjustmentValueCache.getCurrentAdjustmentIndex().get(symbol);
+
+ // 首次执行：生成含正负值的调整序列
+ if (adjustments == null || currentIndex == null) {
+ adjustments = generateRandomAdjustments(delayValue.getValue(), frequency, decimal);
+ currentIndex = 0;
+ AdjustmentValueCache.getPreAllocatedAdjustments().put(symbol, adjustments);
+ AdjustmentValueCache.getCurrentAdjustmentIndex().put(symbol, currentIndex);
}
- if (frequency <= 1) {
+ // 分步应用调整值（确保正负交替）
+ if (currentIndex < frequency) {
+ BigDecimal currentAdjust = adjustments.get(currentIndex);
+
+ // 更新当前值（累加正负调整值）
if (currentValue == null) {
- AdjustmentValueCache.getCurrentValue().put(symbol, delayValue.getValue());
+ AdjustmentValueCache.getCurrentValue().put(symbol, currentAdjust.setScale(decimal, RoundingMode.HALF_UP));
} else {
- AdjustmentValueCache.getCurrentValue().put(symbol,
- delayValue.getValue().add(currentValue));
+ AdjustmentValueCache.getCurrentValue().put(symbol, currentValue.add(currentAdjust).setScale(decimal, RoundingMode.HALF_UP));
}
- if (!item.getAdjustmentValue().equals(AdjustmentValueCache.getCurrentValue().get(symbol))) {
- item.setAdjustmentValue(AdjustmentValueCache.getCurrentValue().get(symbol));
- itemService.saveOrUpdate(item);
- }
- AdjustmentValueCache.getDelayValue().remove(symbol);
- AdjustmentValueCache.getFrequency().remove(symbol);
- } else {
- /*// 本次调整值
- BigDecimal currentValue_frequency = delayValue.getValue().divide(new BigDecimal(frequency), decimal, RoundingMode.HALF_UP);
-
- if (currentValue == null) {
- AdjustmentValueCache.getCurrentValue().put(symbol, currentValue_frequency);
- } else {
- AdjustmentValueCache.getCurrentValue().put(symbol,
- currentValue.add(currentValue_frequency));
- }
-
- delayValue.setValue(delayValue.getValue().subtract(currentValue_frequency));
+ // 更新延时值（剩余值和时间）
+ delayValue.setValue(delayValue.getValue().subtract(currentAdjust).setScale(decimal, RoundingMode.HALF_UP));
delayValue.setSecond(Arith.sub(delayValue.getSecond(), Arith.div(this.interval, 1000.0D)));
AdjustmentValueCache.getDelayValue().put(symbol, delayValue);
- if (!item.getAdjustmentValue().equals(AdjustmentValueCache.getCurrentValue().get(symbol))) {
- item.setAdjustmentValue(AdjustmentValueCache.getCurrentValue().get(symbol));
- itemService.saveOrUpdate(item);
- }*/
- //计算延时加大精度
- Integer delayDecimal = 10;
- // 保存原始总值用于计算随机分配
- BigDecimal totalValue = delayValue.getValue();
- // 计算已分配次数(从缓存中获取)
- Integer allocatedCount = AdjustmentValueCache.getAllocatedCount().get(symbol);
- if (allocatedCount == null) {
- allocatedCount = 0;
- // 首次分配时保存总值到缓存，用于后续计算
- AdjustmentValueCache.getTotalValue().put(symbol, totalValue);
- } else {
- //不是首次
- totalValue = AdjustmentValueCache.getTotalValue().get(symbol);
- }
-
- // ########## 新增：判断调整方向（正向/负向）##########
- boolean isPositiveAdjustment = totalValue.compareTo(BigDecimal.ZERO) > 0; // 正向调整（>0）
- boolean isNegativeAdjustment = totalValue.compareTo(BigDecimal.ZERO) < 0; // 负向调整（<0）
-
- BigDecimal currentValue_frequency;
- // 计算剩余分配次数
- int remainingAllocations = frequency - allocatedCount;
-
- if (remainingAllocations > 1) {
- BigDecimal average = totalValue.divide(new BigDecimal(frequency), delayDecimal, RoundingMode.HALF_UP);
- BigDecimal randomFactor;
-
- // 根据调整方向动态调整负因子概率
- double negativeProbability = isNegativeAdjustment ? 0.6 : 0.3;
- if (Math.random() <= negativeProbability) {
- // 负因子：范围 [-0.5, 0)
- double randomNeg = -0.5 + Math.random() * 0.5; // 简化计算：max - min = 0 - (-0.5) = 0.5
- randomFactor = new BigDecimal(randomNeg).setScale(delayDecimal, RoundingMode.HALF_UP);
- } else {
- // 正因子：范围 [0.3, 1.7)
- double randomPos = 0.3 + Math.random() * 1.4; // 简化计算：max - min = 1.7 - 0.3 = 1.4
- randomFactor = new BigDecimal(randomPos).setScale(delayDecimal, RoundingMode.HALF_UP);
- }
-
- currentValue_frequency = average.multiply(randomFactor).setScale(delayDecimal, RoundingMode.HALF_UP);
-
- // 核心修改1：根据调整方向动态约束累计值
- BigDecimal currentAccumulated = AdjustmentValueCache.getAccumulatedValue().getOrDefault(symbol, BigDecimal.ZERO);
- BigDecimal tempAccumulated = currentAccumulated.add(currentValue_frequency);
- if (isPositiveAdjustment) {
- // 正向调整：累计值不能为负
- if (tempAccumulated.compareTo(BigDecimal.ZERO) < 0) {
- currentValue_frequency = BigDecimal.ONE.divide(new BigDecimal("10").pow(delayDecimal), delayDecimal, RoundingMode.HALF_UP);
- }
- } else if (isNegativeAdjustment) {
- // 负向调整：累计值不能小于目标值（避免过度减值）
- if (tempAccumulated.compareTo(totalValue) < 0) {
- currentValue_frequency = totalValue.subtract(currentAccumulated).divide(new BigDecimal(2), delayDecimal, RoundingMode.HALF_UP);
- }
- }
-
- //剩余的待分配值
- BigDecimal remainingValue = totalValue.subtract(currentAccumulated);
- //本次分配后剩余的待分配值
- BigDecimal tempDelayValue = remainingValue.subtract(currentValue_frequency);
-
- // 提取公共变量（剩余值的80%）
- BigDecimal remaining80Percent = remainingValue.multiply(new BigDecimal("0.8"))
- .setScale(delayDecimal, RoundingMode.HALF_UP);
-
- // 统一判断“是否需要修正剩余值”
- boolean needFixRemaining = (isPositiveAdjustment && tempDelayValue.compareTo(BigDecimal.ZERO) < 0)
- || (isNegativeAdjustment && tempDelayValue.compareTo(totalValue) > 0);
- if (needFixRemaining) {
- // 直接使用公共变量，避免重复计算
- currentValue_frequency = remaining80Percent;
- }
-
- // 直接使用公共变量作为maxAllowed，无需重复计算
- if ((isPositiveAdjustment && currentValue_frequency.compareTo(remaining80Percent) > 0)
- || (isNegativeAdjustment && currentValue_frequency.compareTo(remaining80Percent) < 0)) {
- currentValue_frequency = remaining80Percent;
- }
-
- } else {
- // 最后一次分配兜底（支持负值）
- BigDecimal accumulated = AdjustmentValueCache.getAccumulatedValue().getOrDefault(symbol, BigDecimal.ZERO);
- currentValue_frequency = totalValue.subtract(accumulated).setScale(delayDecimal, RoundingMode.HALF_UP);
-
- // 正向调整：最后一次分配值不能为负；负向调整：不能为正（无重复，无需优化）
- if (isPositiveAdjustment && currentValue_frequency.compareTo(BigDecimal.ZERO) < 0) {
- currentValue_frequency = BigDecimal.ZERO.setScale(delayDecimal, RoundingMode.HALF_UP);
- } else if (isNegativeAdjustment && currentValue_frequency.compareTo(BigDecimal.ZERO) > 0) {
- currentValue_frequency = BigDecimal.ZERO.setScale(delayDecimal, RoundingMode.HALF_UP);
- }
- }
-
-
- // 更新累计值
- BigDecimal newAccumulated = AdjustmentValueCache.getAccumulatedValue().getOrDefault(symbol, BigDecimal.ZERO)
- .add(currentValue_frequency);
- AdjustmentValueCache.getAccumulatedValue().put(symbol, newAccumulated);
- // 更新分配次数
- AdjustmentValueCache.getAllocatedCount().put(symbol, allocatedCount + 1);
-
- // 更新当前值
- if (currentValue == null) {
- AdjustmentValueCache.getCurrentValue().put(symbol, currentValue_frequency);
- } else {
- AdjustmentValueCache.getCurrentValue().put(symbol,
- currentValue.add(currentValue_frequency));
- }
-
- // 更新延迟值
- delayValue.setValue(delayValue.getValue().subtract(currentValue_frequency));
- delayValue.setSecond(Arith.sub(delayValue.getSecond(), Arith.div(this.interval, 1000.0D)));
- AdjustmentValueCache.getDelayValue().put(symbol, delayValue);
-
- // 如果是最后一次分配，清理缓存
- if (remainingAllocations <= 1) {
- AdjustmentValueCache.getAllocatedCount().remove(symbol);
- AdjustmentValueCache.getTotalValue().remove(symbol);
- AdjustmentValueCache.getAccumulatedValue().remove(symbol);
- AdjustmentValueCache.getFrequency().remove(symbol);
-
+ // 索引递增，完成后清理缓存
+ int nextIndex = currentIndex + 1;
+ AdjustmentValueCache.getCurrentAdjustmentIndex().put(symbol, nextIndex);
+ if (nextIndex >= frequency) {
AdjustmentValueCache.getDelayValue().remove(symbol);
+ AdjustmentValueCache.getPreAllocatedAdjustments().remove(symbol);
+ AdjustmentValueCache.getCurrentAdjustmentIndex().remove(symbol);
}
- // 保存更新
- if (!item.getAdjustmentValue().equals(AdjustmentValueCache.getCurrentValue().get(symbol))) {
- item.setAdjustmentValue(AdjustmentValueCache.getCurrentValue().get(symbol));
+ // 持久化更新
+ BigDecimal newAdjustValue = AdjustmentValueCache.getCurrentValue().get(symbol);
+ if (!item.getAdjustmentValue().equals(newAdjustValue)) {
+ item.setAdjustmentValue(newAdjustValue);
itemService.saveOrUpdate(item);
}
}
@@ -290,4 +169,134 @@
this.dataDBService.saveAsyn(realtime);
}
+
+ private List<BigDecimal> generateRandomAdjustments(BigDecimal totalValue, int count, int decimal) {
+ List<BigDecimal> adjustments = new ArrayList<>(count);
+ BigDecimal sum = BigDecimal.ZERO; // 整体累积和
+ boolean isOverallUp = totalValue.signum() > 0; // 整体大趋势
+
+ // 1. 大幅扩大基础波动幅度（比之前再提高30%+，确保单次波动更剧烈）
+ BigDecimal baseFluct = totalValue.abs().multiply(new BigDecimal(isOverallUp ? 0.25 : 0.22)) // 上涨时25%，下跌时22%
+ .max(new BigDecimal("0.001")); // 最小波动阈值提高到0.001，避免微小波动
+
+ // 2. 极大放宽累积范围（允许更大中途偏离，给子周期正负波动留空间）
+ BigDecimal minPreSum = totalValue.multiply(new BigDecimal("0.5")); // 整体最低允许50%
+ BigDecimal maxPreSum = totalValue.multiply(new BigDecimal("1.5")); // 整体最高允许150%
+
+ // 3. 几乎取消“不动”状态（概率1%，突出剧烈波动）
+ double flatProbability = 0.01;
+
+ // 4. 子周期配置：每20次为一个子周期，每个子周期随机生成正负趋势
+ int subCycleLength = 20; // 子周期长度
+ Boolean currentSubCycleUp = null; // 当前子周期的趋势（null表示未初始化）
+ BigDecimal subSum = BigDecimal.ZERO; // 当前子周期的累积和
+
+ for (int i = 0; i < count - 1; i++) {
+ // 每进入新的子周期（i为0或20的倍数），随机初始化子周期趋势（50%正，50%负）
+ if (i % subCycleLength == 0) {
+ currentSubCycleUp = Math.random() < 0.5; // 子周期趋势随机正负
+ subSum = BigDecimal.ZERO; // 重置子周期累积和
+ }
+
+ // 计算当前允许的累积总和范围（动态适配剩余步数）
+ BigDecimal remainingCount = new BigDecimal(count - 1 - i);
+ BigDecimal minCurrentSum = sum.add(minPreSum.subtract(sum).divide(remainingCount, decimal + 4, RoundingMode.HALF_UP));
+ BigDecimal maxCurrentSum = sum.add(maxPreSum.subtract(sum).divide(remainingCount, decimal + 4, RoundingMode.HALF_UP));
+
+ // 极低概率“不动”
+ boolean isFlat = Math.random() < flatProbability;
+ if (isFlat) {
+ BigDecimal adjustment = BigDecimal.ZERO.setScale(decimal, RoundingMode.HALF_UP);
+ adjustments.add(adjustment);
+ sum = sum.add(adjustment);
+ subSum = subSum.add(adjustment); // 累加子周期和
+ continue;
+ }
+
+ // 5. 动态调整涨跌概率：优先满足“子周期正负交替”，再适配整体趋势
+ double upProbability;
+ // 子周期内：若子周期趋势为正，80%概率涨；为负，80%概率跌（确保子周期总和有明确正负）
+ if (currentSubCycleUp) {
+ upProbability = 0.8;
+ } else {
+ upProbability = 0.2;
+ }
+ // 二次修正：若子周期累积和已偏离目标（如子周期应为正但当前为负），进一步提高对应概率
+ if (currentSubCycleUp && subSum.compareTo(BigDecimal.ZERO) < 0) {
+ upProbability = Math.min(0.98, upProbability + 0.2); // 子周期需正但当前负，大幅提高涨概率
+ } else if (!currentSubCycleUp && subSum.compareTo(BigDecimal.ZERO) > 0) {
+ upProbability = Math.max(0.02, upProbability - 0.2); // 子周期需负但当前正，大幅提高跌概率
+ }
+ // 三次修正：确保整体累积和不偏离太远（弱于子周期优先级）
+ if (sum.compareTo(minPreSum) < 0) {
+ upProbability = Math.min(0.98, upProbability + 0.1);
+ } else if (sum.compareTo(maxPreSum) > 0) {
+ upProbability = Math.max(0.02, upProbability - 0.1);
+ }
+ boolean isCurrentUp = Math.random() < upProbability;
+
+ // 6. 生成超大随机幅度（0.6~1.2倍baseFluct，跳过中小幅度，直接用大波动）
+ double randomRate = 0.6 + Math.random() * 0.6; // 范围：0.6~1.2（确保单次波动至少是baseFluct的60%）
+ BigDecimal fluct = baseFluct.multiply(new BigDecimal(randomRate))
+ .setScale(decimal + 4, RoundingMode.HALF_UP);
+
+ // 7. 生成当前调整值（允许接近上限的剧烈波动）
+ BigDecimal adjustment;
+ if (isCurrentUp) {
+ adjustment = fluct.setScale(decimal, RoundingMode.HALF_UP);
+ // 超上限时仅截断到上限（不额外缩小，保留大涨幅）
+ if (sum.add(adjustment).compareTo(maxCurrentSum) > 0) {
+ adjustment = maxCurrentSum.subtract(sum).setScale(decimal, RoundingMode.HALF_UP);
+ }
+ } else {
+ adjustment = fluct.negate().setScale(decimal, RoundingMode.HALF_UP);
+ // 低于下限时仅截断到下限（保留大跌幅）
+ if (sum.add(adjustment).compareTo(minCurrentSum) < 0) {
+ adjustment = minCurrentSum.subtract(sum).setScale(decimal, RoundingMode.HALF_UP);
+ }
+ }
+
+ adjustments.add(adjustment);
+ sum = sum.add(adjustment);
+ subSum = subSum.add(adjustment); // 累加子周期和
+ }
+
+ // 8. 最后一个值：允许极大补平幅度（不超过baseFluct的8倍，适配剧烈波动后的差额）
+ BigDecimal lastAdjustment = totalValue.subtract(sum)
+ .setScale(decimal, RoundingMode.HALF_UP);
+ BigDecimal maxLastAdjust = baseFluct.multiply(new BigDecimal(8)); // 从5倍提高到8倍
+ if (lastAdjustment.abs().compareTo(maxLastAdjust) > 0) {
+ lastAdjustment = maxLastAdjust.multiply(lastAdjustment.signum() == 1 ? BigDecimal.ONE : BigDecimal.ONE.negate());
+ // 微调前一个值分担差额（确保总和准确）
+ BigDecimal prevAdjust = adjustments.get(adjustments.size() - 1);
+ adjustments.set(adjustments.size() - 1, prevAdjust.add(totalValue.subtract(sum).subtract(lastAdjustment)));
+ }
+ adjustments.add(lastAdjustment);
+
+ return adjustments;
+ }
+
+ public static void main(String[] args) {
+ AbstractGetDataJob abstractGetDataJob = new CryptosGetDataJob();
+ List<BigDecimal> list = abstractGetDataJob.generateRandomAdjustments(new BigDecimal(0.002), 300, 8);
+ BigDecimal sum = BigDecimal.ZERO;
+ int num = 0;
+ int dmt = 1;
+ BigDecimal numd = BigDecimal.ZERO;
+ for (int i = 0; i < list.size(); i++) {
+ sum = sum.add(list.get(i));
+ System.out.println((i+1) + "~ " + list.get(i));
+ System.out.println(sum);
+
+ numd = numd.add(list.get(i));
+ num++;
+ if (num == 20) {
+ System.out.println(dmt+"ddd" + numd);
+ dmt++;
+ num=0;
+ numd=BigDecimal.ZERO;
+ }
+ }
+ }
+
}
--
Gitblit v1.9.3