这个封装类可以独立于具体的网络传输逻辑，为任何需要减少鼠标移动数据量的应用提供灵敏度和数据量优化。

核心优化功能

1. 灵敏度调整

// 减少微小移动的数据发送
(2, 1) × 0.5 → (1, 0) // 忽略微小移动

2. 移动累积

// 累积多次小移动，批量发送
(1, 0) + (1, 1) + (0, 1) → (2, 2) // 减少3次发送为1次

3. 阈值过滤

// 忽略低于阈值的移动
(1, 0) → 忽略 // 如果阈值=2

4. 统计监控

// 实时监控优化效果
// 接收1000事件，发送300事件，过滤率70%

工作流程

// ==================== 主处理流程 ====================
函数 处理鼠标移动(原始dx, 原始dy):总事件数++// 1. 灵敏度调整阶段(调整dx, 调整dy) = 应用灵敏度乘数(原始dx, 原始dy)// 2. 阈值检查阶段如果 (调整dx和dy都小于阈值 且 不要求立即发送):如果 (启用累积模式):累积移动量(调整dx, 调整dy)  // 先存起来不发送返回 空                  // 此次不发送数据否则:返回 空                  // 直接丢弃微小移动否则:// 3. 准备发送阶段(最终dx, 最终dy) = 获取最终移动量(调整dx, 调整dy)如果 (最终dx和dy都为0):返回 空                  // 没有实际移动否则:发送事件数++返回 (最终dx, 最终dy)     // 发送优化后的数据// ==================== 灵敏度调整 ====================
函数 应用灵敏度乘数(dx, dy):如果 (灵敏度乘数 ≈ 1.0):返回 (dx, dy)               // 不做调整新dx = 四舍五入(dx × 乘数)新dy = 四舍五入(dy × 乘数)// 确保不丢失移动方向如果 (dx ≠ 0 且 新dx = 0): 新dx = 符号(dx)如果 (dy ≠ 0 且 新dy = 0): 新dy = 符号(dy)返回 (新dx, 新dy)// ==================== 移动累积 ====================
函数 累积移动量(dx, dy):累积x += dx累积y += dy// 防止累积过大（避免延迟感）累积x = 限制范围(累积x, -最大累积值, 最大累积值)累积y = 限制范围(累积y, -最大累积值, 最大累积值)// ==================== 获取最终移动量 ====================
函数 获取最终移动量(当前dx, 当前dy):最终dx = 当前dx + 累积x最终dy = 当前dy + 累积y重置累积()                      // 清空累积器返回 (最终dx, 最终dy)// ==================== 强制发送 ====================
函数 强制发送所有累积():如果 (累积x ≠ 0 或 累积y ≠ 0):移动量 = (累积x, 累积y)重置累积()返回 移动量                 // 发送所有累积的移动否则:返回 空

以下是单独封装的鼠标灵敏度优化类：

using System;
using System.Diagnostics;/// <summary>
/// 鼠标灵敏度优化器 - 减少鼠标移动事件的数据发送量
/// </summary>
public class MouseSensitivityOptimizer
{private readonly double _sensitivityMultiplier;private int _accumulatedDx;private int _accumulatedDy;private readonly int _minMovementThreshold;private readonly int _maxAccumulation;private readonly bool _enableAccumulation;/// <summary>/// 灵敏度优化统计信息/// </summary>public class OptimizationStats{public int TotalEventsReceived { get; set; }public int TotalEventsSent { get; set; }public int EventsFiltered => TotalEventsReceived - TotalEventsSent;public double FilterRate => TotalEventsReceived > 0 ? (double)EventsFiltered / TotalEventsReceived : 0;}public OptimizationStats Stats { get; } = new OptimizationStats();/// <summary>/// 初始化鼠标灵敏度优化器/// </summary>/// <param name="sensitivityMultiplier">灵敏度乘数（0.5=减半，2.0=加倍）</param>/// <param name="minMovementThreshold">最小移动阈值（像素）</param>/// <param name="maxAccumulation">最大累积量（像素）</param>/// <param name="enableAccumulation">是否启用移动累积</param>public MouseSensitivityOptimizer(double sensitivityMultiplier = 1.0, int minMovementThreshold = 1, int maxAccumulation = 10,bool enableAccumulation = true){_sensitivityMultiplier = Math.Clamp(sensitivityMultiplier, 0.1, 10.0);_minMovementThreshold = Math.Max(1, minMovementThreshold);_maxAccumulation = Math.Max(1, maxAccumulation);_enableAccumulation = enableAccumulation;Debug.WriteLine($"MouseSensitivityOptimizer initialized: " +$"Multiplier={_sensitivityMultiplier:F2}, " +$"Threshold={_minMovementThreshold}, " +$"MaxAccumulation={_maxAccumulation}");}/// <summary>/// 从环境变量创建优化器（兼容DeskFlow设计）/// </summary>public static MouseSensitivityOptimizer FromEnvironmentVariable(string envVarName = "DESKFLOW_MOUSE_ADJUSTMENT"){double multiplier = 1.0;try{string envValue = Environment.GetEnvironmentVariable(envVarName);if (!string.IsNullOrEmpty(envValue)){if (double.TryParse(envValue, out double parsedValue)){multiplier = Math.Clamp(parsedValue, 0.1, 10.0);Debug.WriteLine($"Loaded sensitivity multiplier from {envVarName}: {multiplier:F2}");}else{Debug.WriteLine($"Invalid {envVarName} value: {envValue}");}}}catch (Exception ex){Debug.WriteLine($"Error reading environment variable {envVarName}: {ex.Message}");}return new MouseSensitivityOptimizer(multiplier);}/// <summary>/// 处理鼠标移动输入，返回优化后的移动量/// </summary>/// <param name="dx">原始X移动量</param>/// <param name="dy">原始Y移动量</param>/// <param name="sendImmediately">是否立即发送（忽略累积）</param>/// <returns>优化后的移动量，null表示应该忽略此次移动</returns>public (int dx, int dy)? ProcessMovement(int dx, int dy, bool sendImmediately = false){Stats.TotalEventsReceived++;// 1. 应用灵敏度调整(int adjustedDx, int adjustedDy) = ApplySensitivityAdjustment(dx, dy);// 2. 检查是否低于阈值if (IsBelowThreshold(adjustedDx, adjustedDy) && !sendImmediately){// 累积小幅度移动if (_enableAccumulation){AccumulateMovement(adjustedDx, adjustedDy);return null; // 暂时不发送}else{// 不启用累积时，直接忽略微小移动return null;}}// 3. 获取最终要发送的移动量（包括累积值）(int finalDx, int finalDy) = GetFinalMovement(adjustedDx, adjustedDy);if (finalDx == 0 && finalDy == 0){return null; // 没有实际移动}Stats.TotalEventsSent++;Debug.WriteLine($"Movement optimized: ({dx},{dy}) -> ({finalDx},{finalDy}) " +$"[Filtered: {Stats.FilterRate:P0}]");return (finalDx, finalDy);}/// <summary>/// 强制发送所有累积的移动量/// </summary>public (int dx, int dy)? FlushAccumulatedMovement(){if (_accumulatedDx == 0 && _accumulatedDy == 0){return null;}var movement = (_accumulatedDx, _accumulatedDy);ResetAccumulation();Stats.TotalEventsSent++;Debug.WriteLine($"Flushed accumulated movement: ({movement.dx},{movement.dy})");return movement;}/// <summary>/// 重置优化器状态（如屏幕切换时）/// </summary>public void Reset(){ResetAccumulation();Debug.WriteLine("Mouse sensitivity optimizer reset");}/// <summary>/// 应用灵敏度乘数/// </summary>private (int dx, int dy) ApplySensitivityAdjustment(int dx, int dy){if (Math.Abs(_sensitivityMultiplier - 1.0) < 0.01){return (dx, dy); // 无调整}int adjustedDx = (int)Math.Round(dx * _sensitivityMultiplier);int adjustedDy = (int)Math.Round(dy * _sensitivityMultiplier);// 确保至少保持原始方向if (dx != 0 && adjustedDx == 0) adjustedDx = Math.Sign(dx);if (dy != 0 && adjustedDy == 0) adjustedDy = Math.Sign(dy);return (adjustedDx, adjustedDy);}/// <summary>/// 检查移动量是否低于发送阈值/// </summary>private bool IsBelowThreshold(int dx, int dy){return Math.Abs(dx) < _minMovementThreshold && Math.Abs(dy) < _minMovementThreshold;}/// <summary>/// 累积移动量/// </summary>private void AccumulateMovement(int dx, int dy){_accumulatedDx += dx;_accumulatedDy += dy;// 防止累积过大_accumulatedDx = Math.Clamp(_accumulatedDx, -_maxAccumulation, _maxAccumulation);_accumulatedDy = Math.Clamp(_accumulatedDy, -_maxAccumulation, _maxAccumulation);}/// <summary>/// 获取最终要发送的移动量（包括当前和累积值）/// </summary>private (int dx, int dy) GetFinalMovement(int currentDx, int currentDy){int finalDx = currentDx + _accumulatedDx;int finalDy = currentDy + _accumulatedDy;ResetAccumulation();return (finalDx, finalDy);}/// <summary>/// 重置累积值/// </summary>private void ResetAccumulation(){_accumulatedDx = 0;_accumulatedDy = 0;}
}// 使用示例
public class MouseSensitivityExample
{private readonly MouseSensitivityOptimizer _optimizer;public MouseSensitivityExample(){// 从环境变量创建或直接配置_optimizer = MouseSensitivityOptimizer.FromEnvironmentVariable();// 或者手动配置：// _optimizer = new MouseSensitivityOptimizer(//     sensitivityMultiplier: 0.7,  // 降低30%灵敏度//     minMovementThreshold: 2,     // 2像素以下不立即发送//     maxAccumulation: 8,          // 最大累积8像素//     enableAccumulation: true// );}public void ProcessMouseMove(int dx, int dy){// 使用优化器处理移动var optimizedMovement = _optimizer.ProcessMovement(dx, dy);if (optimizedMovement.HasValue){// 发送优化后的移动数据SendMouseMove(optimizedMovement.Value.dx, optimizedMovement.Value.dy);}// 否则忽略此次移动（已累积）}public void OnScreenSwitch(){// 屏幕切换时强制发送所有累积的移动var flushedMovement = _optimizer.FlushAccumulatedMovement();if (flushedMovement.HasValue){SendMouseMove(flushedMovement.Value.dx, flushedMovement.Value.dy);}_optimizer.Reset();}private void SendMouseMove(int dx, int dy){// 实际网络发送逻辑Debug.WriteLine($"Sending mouse move: ({dx},{dy})");}public void PrintStats(){var stats = _optimizer.Stats;Debug.WriteLine($"Optimization stats: " +$"{stats.TotalEventsReceived} received, " +$"{stats.TotalEventsSent} sent, " +$"{stats.FilterRate:P0} filtered");}
}