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unreal/Content/Blueprints/BP_DataFlow_Spec.md
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unreal/Content/Blueprints/BP_DataFlow_Spec.md
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# BP_DataFlow 数据流向蓝图详细规格
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## 蓝图信息
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| 属性 | 值 |
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|------|-----|
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| 蓝图类型 | Actor |
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| 父类 | `Actor` |
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| 路径 | `Content/Blueprints/BP_DataFlow.uasset` |
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## 组件列表
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```
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BP_DataFlow
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├── SceneRoot (场景根)
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│ ├── SourceMarker (源点标记)
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│ │ └── StaticMesh: Sphere
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│ │ └── Material: M_DataFlow_Source
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│ ├── DestinationMarker (目标点标记)
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│ │ └── StaticMesh: Sphere
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│ │ └── Material: M_DataFlow_Destination
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│ ├── PathSpline (路径样条)
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│ │ └── SplineMeshComponent
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│ │ └── Material: M_DataFlow_Path
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│ └── FlowParticles (流向粒子)
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│ └── NiagaraComponent
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│ └── NS_DataFlow_Directional
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```
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## 变量列表
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| 变量名 | 类型 | 默认值 | 说明 |
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|--------|------|--------|------|
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| `FlowId` | String | `""` | 流向唯一标识 |
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| `SourceLocation` | GeographicPoint | - | 源位置 |
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| `DestinationLocation` | GeographicPoint | - | 目标位置 |
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| `DataRate` | Float | `1000.0` | 数据速率 (Gbps) |
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| `DataType` | EDataFlowType | `Internet` | 数据类型 |
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| `IsActive` | Boolean | `true` | 是否激活 |
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| `FlowColor` | LinearColor | (0.2, 0.6, 1.0, 1) | 流向颜色 |
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| `Duration` | Float | `3.0` | 粒子生命周期(秒) |
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## 枚举定义
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### EDataFlowType
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| 枚举值 | 说明 | 颜色 |
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|--------|------|------|
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| `Internet` | 互联网流量 | 蓝色 |
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| `Backbone` | 骨干网 | 青色 |
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| `Cloud` | 云服务 | 紫色 |
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| `AI_Training` | AI 训练数据 | 橙色 |
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| `CDN` | CDN 分发 | 绿色 |
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## 材质规格
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### M_DataFlow_Source (源点)
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| 参数 | 类型 | 默认值 | 说明 |
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|------|------|--------|------|
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| `BaseColor` | Vector3 | (0.2, 0.6, 1.0) | 蓝色 |
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| `EmissiveStrength` | Float | `10.0` | 自发光强度 |
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| `PulseSpeed` | Float | `2.0` | 脉冲速度 |
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| `Radius` | Float | `10000.0` | 脉冲半径 |
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### M_DataFlow_Destination (目标点)
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```
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与 M_DataFlow_Source 相同，但:
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├─ BaseColor: 稍暗
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└─ PulseSpeed: 稍慢
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```
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### M_DataFlow_Path (路径线)
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| 参数 | 类型 | 默认值 | 说明 |
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|------|------|--------|------|
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| `LineColor` | Vector4 | (0.2, 0.6, 1.0, 0.5) | 半透明蓝 |
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| `LineWidth` | Float | `100.0` | 线宽度 |
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| `FlowSpeed` | Float | `1.0` | 流动速度 |
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| `FlowIntensity` | Float | `0.8` | 流动强度 |
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## 粒子系统 (NS_DataFlow_Directional)
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### Niagara 参数
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| 参数 | 类型 | 默认值 | 说明 |
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|------|------|--------|------|
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| `User.Color` | LinearColor | (0.2, 0.6, 1.0, 1.0) | 粒子颜色 |
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| `User.Speed` | Float | `100.0` | 粒子速度 |
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| `User.Lifetime` | Float | `3.0` | 粒子寿命 |
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| `User.Size` | Float | `50.0` | 粒子大小 |
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| `User.Density` | Float | `1.0` | 粒子密度 |
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### 粒子行为
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```
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1. 发射器类型: 沿样条路径
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2. 发射速率: DataRate / 100 (归一化)
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3. 粒子寿命: Duration
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4. 粒子速度: 路径长度 / Duration
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5. 颜色渐变:
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├─ 起点: 高亮度
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├─ 中点: 正常亮度
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└─ 终点: 渐隐
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```
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## 函数
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### Initialize (Struct FlowData)
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```
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1. [解析] FlowData
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2. [设置] FlowId = FlowData["id"]
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3. [设置] SourceLocation = FlowData["source"]
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4. [设置] DestinationLocation = FlowData["destination"]
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5. [设置] DataRate = FlowData["data_rate"]
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6. [设置] DataType = FlowData["data_type"]
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7. [计算] PathPoints
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8. [调用] BuildPath()
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9. [调用] UpdateParticles()
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10. [调用] SetFlowColorByType()
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```
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### BuildPath
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```
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1. [计算] SourceUE = GeoUtils.LatLonToUE(SourceLocation)
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2. [计算] DestUE = GeoUtils.LatLonToUE(DestinationLocation)
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3. [设置] SourceMarker.SetRelativeLocation(SourceUE)
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4. [设置] DestinationMarker.SetRelativeLocation(DestUE)
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5. [计算] MidPoints (插值路径)
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6. [构建] SplineComponent from Source to Destination
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7. [设置] SplineMeshComponent.Start/End
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```
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### UpdateParticles
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```
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1. [计算] ParticleSpeed = PathLength / Duration
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2. [获取] NiagaraComponent
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3. [设置] User.Speed = ParticleSpeed
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4. [计算] EmissionRate = DataRate / 10
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5. [设置] User.EmissionRate = EmissionRate
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6. [调用] NiagaraComponent.Activate()
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```
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### SetFlowColorByType
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```
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1. [分支] DataType
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├─ "internet": [设置] FlowColor = (0.2, 0.6, 1.0, 1) 蓝色
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├─ "backbone": [设置] FlowColor = (0.0, 1.0, 1.0, 1) 青色
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├─ "cloud": [设置] FlowColor = (0.6, 0.2, 1.0, 1) 紫色
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├─ "ai_training": [设置] FlowColor = (1.0, 0.5, 0.0, 1) 橙色
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├─ "cdn": [设置] FlowColor = (0.2, 1.0, 0.4, 1) 绿色
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└─ [默认]: [设置] FlowColor = (0.5, 0.5, 0.5, 1) 灰色
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2. [设置] Material.LineColor = FlowColor
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3. [设置] NiagaraComponent.User.Color = FlowColor
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```
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## 数据格式
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### 输入数据结构
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```json
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{
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"id": "flow_1",
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"source": {
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"latitude": 37.7749,
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"longitude": -122.4194,
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"name": "San Francisco"
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},
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"destination": {
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"latitude": 1.3521,
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"longitude": 103.8198,
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"name": "Singapore"
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},
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"data_rate": 5000.0,
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"data_type": "internet",
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"status": "active"
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}
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```
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## 视觉效果规格
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### 粒子外观
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| 数据类型 | 粒子形状 | 颜色 | 尾迹 |
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|----------|----------|------|------|
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| Internet | 圆形光点 | 蓝色 | 短 |
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| Backbone | 方形光块 | 青色 | 中 |
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| Cloud | 菱形 | 紫色 | 长 |
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| AI_Training | 三角形 | 橙色 | 短 |
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| CDN | 六边形 | 绿色 | 无 |
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### 带宽可视化
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| 带宽范围 | 粒子密度 | 粒子大小 | 速度 |
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|----------|----------|----------|------|
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| > 10 Tbps | 高 | 大 | 快 |
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| 1-10 Tbps | 中 | 中 | 中 |
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| < 1 Tbps | 低 | 小 | 慢 |
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## 交互效果
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### 悬停效果
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```
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1. [高亮] 路径线
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└─ LineWidth: 200 → 300
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2. [显示] Tooltip
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└─ 显示: 源、目标、数据速率、类型
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3. [暂停] 粒子 (可选)
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```
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### 点击效果
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```
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1. [聚焦] 相机到流向中心
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2. [显示] 详细信息面板
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3. [播放] Sound Effect
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```
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## 性能优化
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### 视距设置
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```
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├─ 显示距离: 50000 km
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├─ 粒子剔除距离: 20000 km
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└─ 简化粒子距离: 10000 km
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```
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### 批处理
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```
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├─ 多个相近流向合并显示
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├─ 远距离流向使用简化的粒子
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└─ 禁用低优先级流向的粒子
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```
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## 使用场景
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### 场景 1: 全球互联网流量
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```
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DataType: Internet
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├─ Source: 主要互联网交换中心
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├─ Destination: 其他地区
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└─ Visual: 蓝色粒子流
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```
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### 场景 2: AI 训练数据传输
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```
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DataType: AI_Training
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├─ Source: GPU 集群
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├─ Destination: 数据中心
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└─ Visual: 橙色高速粒子
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```
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### 场景 3: CDN 内容分发
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```
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DataType: CDN
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├─ Source: 源站
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├─ Destination: 边缘节点
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└─ Visual: 绿色扩散粒子
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```
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## 后端数据映射
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### API 响应格式
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```json
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{
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"type": "data_flow",
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"data": [
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{
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"id": "flow_1",
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"source": {"latitude": 37.77, "longitude": -122.41},
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"destination": {"latitude": 1.35, "longitude": 103.81},
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"data_rate": 5000.0,
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"data_type": "internet"
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}
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]
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}
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```
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