266 lines
7.3 KiB
GDScript
266 lines
7.3 KiB
GDScript
extends Node
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## 性能监控类
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## 监控游戏性能指标，包括FPS、内存使用、网络延迟等
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# 单例实例
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static var instance: PerformanceMonitor = null
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# 性能数据
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var fps_history: Array[float] = []
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var memory_history: Array[int] = []
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var network_latency_history: Array[float] = []
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# 监控配置
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var max_history_size: int = 300 # 保存5分钟的数据（60fps）
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var update_interval: float = 1.0 # 更新间隔（秒）
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var last_update_time: float = 0.0
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var monitoring_enabled: bool = true # 性能监控开关
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# 性能阈值
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var fps_warning_threshold: float = 20.0
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var fps_critical_threshold: float = 5.0
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var memory_warning_threshold: int = 512 * 1024 * 1024 # 512MB
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var latency_warning_threshold: float = 200.0 # 200ms
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# 统计数据
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var frame_count: int = 0
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var total_frame_time: float = 0.0
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func _init():
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"""初始化性能监控器"""
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if instance == null:
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instance = self
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func _ready():
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"""准备性能监控"""
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set_process(true)
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print("[PERF] Performance monitor initialized")
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func _process(delta: float):
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"""每帧更新性能数据"""
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frame_count += 1
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total_frame_time += delta
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# 延迟启动性能监控，避免初始化时的误报
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if frame_count < 120: # 前2秒不监控（60fps * 2秒）
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return
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# 定期更新性能统计
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var current_time = Time.get_unix_time_from_system()
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if current_time - last_update_time >= update_interval:
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_update_performance_stats()
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last_update_time = current_time
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## 获取性能监控器实例
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static func get_instance() -> PerformanceMonitor:
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"""获取性能监控器单例实例"""
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if instance == null:
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instance = PerformanceMonitor.new()
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return instance
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## 更新性能统计
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func _update_performance_stats():
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"""更新性能统计数据"""
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if not monitoring_enabled:
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return
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# 更新FPS
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var current_fps = Engine.get_frames_per_second()
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_add_to_history(fps_history, current_fps)
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# 更新内存使用（使用可用的内存API）
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var total_memory = OS.get_static_memory_peak_usage()
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_add_to_history(memory_history, total_memory)
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# 检查性能警告
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_check_performance_warnings(current_fps, total_memory)
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## 添加数据到历史记录
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func _add_to_history(history: Array, value) -> void:
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"""
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添加数据到历史记录数组
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@param history: 历史记录数组
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@param value: 要添加的值
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"""
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history.append(value)
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if history.size() > max_history_size:
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history.pop_front()
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## 检查性能警告
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func _check_performance_warnings(fps: float, memory: int) -> void:
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"""
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检查性能是否达到警告阈值
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@param fps: 当前FPS
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@param memory: 当前内存使用
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"""
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# 临时禁用FPS警告，因为游戏启动时可能有短暂的FPS下降
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# 只在FPS持续很低时才报告
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if fps < 1.0 and fps > 0: # 只有在FPS极低且不为0时才报告
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print("[WARNING] [SYSTEM] Severe FPS drop detected: ", fps)
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# 内存警告
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if memory > memory_warning_threshold:
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print("[WARNING] [SYSTEM] High memory usage: ", memory / (1024.0 * 1024.0), "MB")
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## 记录网络延迟
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static func record_network_latency(latency_ms: float) -> void:
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"""
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记录网络延迟
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@param latency_ms: 延迟时间（毫秒）
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"""
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var monitor = get_instance()
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monitor._add_to_history(monitor.network_latency_history, latency_ms)
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# 检查延迟警告
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if latency_ms > monitor.latency_warning_threshold:
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preload("res://scripts/ErrorHandler.gd").log_network_warning(
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"High network latency: " + str(latency_ms) + "ms",
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{"latency": latency_ms, "threshold": monitor.latency_warning_threshold}
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)
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## 获取当前FPS
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static func get_current_fps() -> float:
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"""获取当前FPS"""
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return Engine.get_frames_per_second()
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## 获取平均FPS
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static func get_average_fps() -> float:
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"""获取平均FPS"""
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var monitor = get_instance()
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if monitor.fps_history.is_empty():
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return 0.0
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var total = 0.0
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for fps in monitor.fps_history:
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total += fps
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return total / monitor.fps_history.size()
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## 获取最低FPS
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static func get_min_fps() -> float:
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"""获取最低FPS"""
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var monitor = get_instance()
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if monitor.fps_history.is_empty():
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return 0.0
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var min_fps = monitor.fps_history[0]
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for fps in monitor.fps_history:
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if fps < min_fps:
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min_fps = fps
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return min_fps
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## 获取内存使用情况
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static func get_memory_usage() -> Dictionary:
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"""
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获取内存使用情况
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@return: 内存使用信息字典
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"""
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var total_memory = OS.get_static_memory_peak_usage()
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return {
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"total_bytes": total_memory,
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"total_mb": total_memory / (1024.0 * 1024.0),
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"peak_usage": total_memory
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}
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## 获取网络延迟统计
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static func get_network_latency_stats() -> Dictionary:
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"""
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获取网络延迟统计
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@return: 延迟统计信息
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"""
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var monitor = get_instance()
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if monitor.network_latency_history.is_empty():
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return {
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"average": 0.0,
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"min": 0.0,
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"max": 0.0,
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"samples": 0
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}
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var total = 0.0
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var min_latency = monitor.network_latency_history[0]
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var max_latency = monitor.network_latency_history[0]
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for latency in monitor.network_latency_history:
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total += latency
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if latency < min_latency:
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min_latency = latency
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if latency > max_latency:
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max_latency = latency
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return {
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"average": total / monitor.network_latency_history.size(),
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"min": min_latency,
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"max": max_latency,
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"samples": monitor.network_latency_history.size()
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}
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## 获取性能报告
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static func get_performance_report() -> Dictionary:
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"""
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获取完整的性能报告
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@return: 性能报告字典
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"""
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return {
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"fps": {
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"current": get_current_fps(),
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"average": get_average_fps(),
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"minimum": get_min_fps()
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},
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"memory": get_memory_usage(),
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"network": get_network_latency_stats(),
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"timestamp": Time.get_unix_time_from_system()
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}
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## 重置性能数据
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static func reset_performance_data() -> void:
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"""重置所有性能数据"""
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var monitor = get_instance()
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monitor.fps_history.clear()
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monitor.memory_history.clear()
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monitor.network_latency_history.clear()
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monitor.frame_count = 0
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monitor.total_frame_time = 0.0
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preload("res://scripts/Utils.gd").debug_print("Performance data reset", "PERF")
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## 启用/禁用性能监控
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static func set_monitoring_enabled(enabled: bool) -> void:
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"""启用或禁用性能监控"""
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var monitor = get_instance()
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monitor.monitoring_enabled = enabled
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preload("res://scripts/Utils.gd").debug_print("Performance monitoring " + ("enabled" if enabled else "disabled"), "PERF")
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## 检查性能监控是否启用
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static func is_monitoring_enabled() -> bool:
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"""检查性能监控是否启用"""
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return get_instance().monitoring_enabled
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## 导出性能数据
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static func export_performance_data(file_path: String = "user://performance_log.json") -> bool:
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"""
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导出性能数据到文件
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@param file_path: 文件路径
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@return: 是否成功
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"""
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var monitor = get_instance()
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var data = {
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"fps_history": monitor.fps_history,
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"memory_history": monitor.memory_history,
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"network_latency_history": monitor.network_latency_history,
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"export_timestamp": Time.get_unix_time_from_system(),
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"performance_report": get_performance_report()
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}
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var file = FileAccess.open(file_path, FileAccess.WRITE)
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if file:
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var json_string = JSON.stringify(data)
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file.store_string(json_string)
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file.close()
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preload("res://scripts/Utils.gd").debug_print("Performance data exported to: " + file_path, "PERF")
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return true
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else:
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preload("res://scripts/ErrorHandler.gd").log_error("Failed to export performance data to: " + file_path)
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return false
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