nuitka package test

.gitignore

@@ -4,7 +4,9 @@ __pycache__/
 # Distribution / packaging
 build/
 dist/
+dist_nuitka/
 upperHost_stim/
+.vscode/
 #!upperHost_stim/MI_headless.py
 #!upperHost_stim/ssmvep_headless.py
 .env

nuitka_3in1_package.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Git Bash 中文 UTF-8 兼容配置（通用版，无报错）
+export LC_ALL=en_US.UTF-8
+export LANG=en_US.UTF-8
+
+echo "========================"
+echo "Nuitka 打包脚本 - 优化稳定版"
+echo "适配：PyTorch2.0.0 + CUDA11.7 + 脑电解码项目"
+echo "========================"
+
+# ===================== 自定义配置区 =====================
+PY_FILE="runDecoder.py"       # 主程序文件
+OUT_DIR="dist_nuitka"         # 输出文件夹
+MODEL_DIR="online_Models"      # 模型文件夹
+# ========================================================
+
+# 检查主文件是否存在
+if [ ! -f "${PY_FILE}" ]; then
+    echo "错误：未找到主文件 ${PY_FILE}，请检查路径！"
+    read -n 1 -s -r -p "按任意键退出"
+    exit 1
+fi
+
+echo "开始打包：${PY_FILE}"
+echo "输出目录：${OUT_DIR}"
+
+# Nuitka 核心打包命令（无错误、无冗余、全依赖）
+python -m nuitka \
+--standalone \
+--msvc=latest \
+--windows-console-mode=force \
+--module-parameter=torch-disable-jit=yes \
+--enable-plugin=no-qt \
+--include-package=numpy \
+--include-module=numpy.core._multiarray_umath \
+--include-package=scipy \
+--no-deployment-flag=self-execution \
+--include-data-dir="${MODEL_DIR}=${MODEL_DIR}" \
+--output-dir="${OUT_DIR}" \
+--remove-output \
+"${PY_FILE}"
+
+# 打包结果判断
+if [ $? -eq 0 ]; then
+    echo -e "\n========================"
+    echo "✅ 打包成功！"
+    echo "📦 产物路径：${OUT_DIR}/${PY_FILE%.py}.exe"
+    echo "========================"
+else
+    echo -e "\n❌ 打包失败！"
+fi
+
+# Git Bash 兼容的暂停
+read -n 1 -s -r -p "按任意键退出..."
+echo

requirements.txt

@@ -0,0 +1,52 @@
+Bottleneck==1.4.2
+brotlicffi==1.2.0.0
+certifi==2026.5.20
+cffi==2.0.0
+charset-normalizer==3.4.4
+contourpy==1.3.2
+cycler==0.12.1
+einops==0.8.2
+filelock==3.20.3
+fonttools==4.63.0
+gmpy2==2.2.2
+idna==3.11
+Jinja2==3.1.6
+joblib==1.5.3
+kiwisolver==1.5.0
+MarkupSafe==3.0.2
+matplotlib==3.10.9
+mkl_fft==1.3.11
+mkl_random==1.2.8
+mkl-service==2.5.2
+mpmath==1.3.0
+networkx==3.4.2
+Nuitka==4.1.1
+numexpr==2.14.1
+numpy==1.24.3
+packaging==26.0
+pandas==2.3.3
+pillow==12.2.0
+pip==26.0.1
+pycparser==3.0
+pyparsing==3.3.2
+pyserial==3.5
+PySocks==1.7.1
+python-dateutil==2.9.0.post0
+pytz==2026.1.post1
+pyzmq==27.1.0
+requests==2.33.1
+scikit-learn==1.7.1
+scipy==1.15.3
+setuptools==82.0.1
+six==1.17.0
+sympy==1.14.0
+threadpoolctl==3.5.0
+torch==2.0.0
+torchaudio==2.0.0
+torchsummary==1.5.1
+torchvision==0.15.0
+typing_extensions==4.15.0
+tzdata==2026.2
+urllib3==2.7.0
+wheel==0.46.3
+win_inet_pton==1.1.0

system_test.py

@@ -1,422 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-ZMQ 脑电数据测试工具【语法错误修复版】
-修复点：
-1. dataclass 可变列表默认值报错
-2. threading.Thread daemon 参数语法错误
-适配：Python3.10、全链路 float64、ZMQ DEALER<->ROUTER
-端口：8099(命令) / 8100(数据)
-"""
-import zmq
-import time
-import threading
-import numpy as np
-import matplotlib.pyplot as plt
-import json
-from dataclasses import dataclass, field
-from typing import Dict, List, Optional, Union, Tuple
-from matplotlib.animation import FuncAnimation
-
-# ===================== 1. 配置管理 =====================
-@dataclass(frozen=True)  # 冻结配置类
-class TestConfig:
-    # 网络配置
-    SERVER_IP: str = "127.0.0.1"
-    CMD_PORT: int = 8099
-    DATA_PORT: int = 8100
-
-    # 硬件与时序
-    SAMPLE_RATE: int = 250
-    FRAME_INTERVAL_MS: int = 20
-    SEND_INTERVAL: float = FRAME_INTERVAL_MS / 1000
-    CHANNEL_NUMS: int = 66
-    FRAME_POINTS: int = 5
-    FILTER_OUT_CHAN: int = 64
-    FILTER_FRAME_POINTS: int = 50
-
-    # 数据类型 & 字节数 (float64 8字节)
-    DATA_DTYPE: np.dtype = np.float64
-    RAW_FRAME_BYTES: int = CHANNEL_NUMS * FRAME_POINTS * 8    # 66*5*8 = 2640
-    FILTER_FRAME_BYTES: int = FILTER_OUT_CHAN * FILTER_FRAME_POINTS * 8  # 25600
-
-    # 事件通道索引
-    EVENT_CHANNEL_IDX: int = -2
-
-    # 列表类型 使用 default_factory 规避可变默认值报错
-    EVENT_TAGS: List[int] = field(default_factory=lambda: [1, 2, 99])
-    SIM_SIGNAL_FREQ: List[float] = field(default_factory=lambda: [8.0, 9.0])
-
-    # 仿真噪声
-    NOISE_STD: float = 0.25
-
-    # 可视化配置
-    PLOT_TARGET_CHAN: int = 0
-    PLOT_WINDOW_LEN: int = 400
-    PLOT_REFRESH_INTERVAL: int = 50
-
-    # 日志限流
-    FRAME_ERR_INTERVAL: float = 3.0
-
-    # ZMQ 配置
-    SEND_RETRY_MAX: int = 3
-    SEND_RETRY_SLEEP: float = 0.01
-    ZMQ_HWM: int = 1000
-
-# 初始化全局配置
-CONFIG = TestConfig()
-
-# ===================== 2. 全局状态管理 =====================
-class GlobalState:
-    def __init__(self):
-        self.run_flag: bool = True
-        self.last_frame_err_time: float = 0.0
-
-GLOBAL_STATE = GlobalState()
-
-# ===================== 3. Matplotlib 中文初始化 =====================
-def init_matplotlib():
-    # Windows 黑体，Linux/Mac 自行替换字体
-    plt.rcParams['font.sans-serif'] = ['SimHei']
-    plt.rcParams['axes.unicode_minus'] = False  # 修复负号乱码
-
-init_matplotlib()
-
-# ===================== 4. ZMQ DEALER 客户端 =====================
-class ZmqDealerClient:
-    """适配 ROUTER 的 DEALER 客户端，高频流式数据专用"""
-    def __init__(self, server_ip: str, port: int):
-        self.ctx: zmq.Context = zmq.Context()
-        self.socket: zmq.Socket = self.ctx.socket(zmq.DEALER)
-        self._configure_socket()
-        self.socket.connect(f"tcp://{server_ip}:{port}")
-
-    def _configure_socket(self):
-        """套接字参数配置"""
-        self.socket.setsockopt(zmq.RCVHWM, CONFIG.ZMQ_HWM)
-        self.socket.setsockopt(zmq.SNDHWM, CONFIG.ZMQ_HWM)
-        self.socket.setsockopt(zmq.RCVTIMEO, 0)
-        self.socket.setsockopt(zmq.SNDTIMEO, 0)
-
-    def send_json(self, data: Dict) -> bool:
-        """发送JSON命令，带重试机制"""
-        try:
-            payload = json.dumps(data, ensure_ascii=False).encode("utf-8")
-        except Exception as e:
-            print(f"[JSON序列化失败] {e}")
-            return False
-
-        for _ in range(CONFIG.SEND_RETRY_MAX):
-            try:
-                self.socket.send_multipart([b"", payload])
-                return True
-            except zmq.Again:
-                time.sleep(CONFIG.SEND_RETRY_SLEEP)
-            except Exception as e:
-                print(f"[JSON发送异常] {e}")
-                time.sleep(CONFIG.SEND_RETRY_SLEEP)
-        print(f"[JSON发送重试失败]")
-        return False
-
-    def send_bytes(self, data: bytes) -> bool:
-        """发送二进制脑电数据，带重试"""
-        for _ in range(CONFIG.SEND_RETRY_MAX):
-            try:
-                self.socket.send_multipart([b"", data])
-                return True
-            except zmq.Again:
-                time.sleep(CONFIG.SEND_RETRY_SLEEP)
-            except Exception as e:
-                print(f"[二进制发送异常] {e}")
-                time.sleep(CONFIG.SEND_RETRY_SLEEP)
-        print(f"[二进制发送重试失败]")
-        return False
-
-    def recv_json(self) -> Optional[Dict]:
-        """接收JSON命令响应（标准3帧）"""
-        try:
-            frames = self.socket.recv_multipart()
-            if len(frames) < 3:
-                self._log_frame_err(f"帧数异常: {len(frames)}")
-                return None
-            payload = frames[2].decode("utf-8")
-            return json.loads(payload)
-        except json.JSONDecodeError:
-            self._log_frame_err("JSON解析失败")
-            return None
-        except Exception as e:
-            self._log_frame_err(f"接收异常: {e}")
-            return None
-
-    def recv_bytes(self) -> Optional[bytes]:
-        """接收滤波数据，兼容3/4帧格式"""
-        try:
-            frames = self.socket.recv_multipart()
-            frame_len = len(frames)
-            if frame_len == 3:
-                payload = frames[2]
-            elif frame_len == 4:
-                payload = frames[3]
-            else:
-                self._log_frame_err(f"帧数异常: {frame_len}")
-                return None
-
-            if len(payload) != CONFIG.FILTER_FRAME_BYTES:
-                self._log_frame_err(f"字节不匹配: 期望{CONFIG.FILTER_FRAME_BYTES}, 实际{len(payload)}")
-                return None
-            return payload
-        except Exception as e:
-            self._log_frame_err(f"数据接收异常: {e}")
-            return None
-
-    def _log_frame_err(self, msg: str):
-        """日志限流，防止刷屏"""
-        now = time.time()
-        if now - GLOBAL_STATE.last_frame_err_time > CONFIG.FRAME_ERR_INTERVAL:
-            print(f"[帧异常] {msg}")
-            GLOBAL_STATE.last_frame_err_time = now
-
-    def close(self):
-        """优雅释放ZMQ资源"""
-        try:
-            self.socket.close(linger=0)
-            self.ctx.term()
-        except Exception as e:
-            print(f"[资源释放异常] {e}")
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self.close()
-
-# ===================== 5. 仿真脑电数据生成 =====================
-def generate_raw_eeg_frame(add_event: bool = False) -> np.ndarray:
-    """生成单帧float64仿真脑电数据"""
-    t = np.linspace(
-        0, CONFIG.FRAME_POINTS / CONFIG.SAMPLE_RATE,
-        CONFIG.FRAME_POINTS, endpoint=False
-    )
-    eeg_frame = np.zeros(
-        (CONFIG.CHANNEL_NUMS, CONFIG.FRAME_POINTS),
-        dtype=CONFIG.DATA_DTYPE
-    )
-
-    # 模拟脑电信号 + 高斯噪声
-    for freq in CONFIG.SIM_SIGNAL_FREQ:
-        eeg_frame[:CONFIG.FILTER_OUT_CHAN] += np.sin(2 * np.pi * freq * t)
-    eeg_frame[:CONFIG.FILTER_OUT_CHAN] += np.random.normal(
-        0, CONFIG.NOISE_STD,
-        size=(CONFIG.FILTER_OUT_CHAN, CONFIG.FRAME_POINTS)
-    )
-
-    # 事件通道处理
-    eeg_frame[CONFIG.EVENT_CHANNEL_IDX] = 0.0
-    if add_event:
-        event_pos = np.random.randint(0, CONFIG.FRAME_POINTS)
-        eeg_frame[CONFIG.EVENT_CHANNEL_IDX, event_pos] = np.random.choice(CONFIG.EVENT_TAGS)
-
-    # 预留通道置0
-    eeg_frame[-1] = 0.0
-    return eeg_frame
-
-# ===================== 6. 后台工作线程 =====================
-def start_cmd_response_thread(cmd_client: ZmqDealerClient):
-    """命令响应接收线程"""
-    print("[线程-命令接收] 已启动")
-    while GLOBAL_STATE.run_flag:
-        msg = cmd_client.recv_json()
-        if msg:
-            print(f"\n【命令响应】{json.dumps(msg, ensure_ascii=False, indent=2)}")
-        time.sleep(0.01)
-    print("[线程-命令接收] 已退出")
-
-def start_raw_eeg_send_thread(data_client: ZmqDealerClient):
-    """原始脑电发送线程（20ms/帧）"""
-    print(f"[线程-原始数据发送] 20ms/帧 | 单帧{CONFIG.RAW_FRAME_BYTES}字节 | float64")
-    frame_count = 0
-    while GLOBAL_STATE.run_flag:
-        insert_event = (frame_count % 20 == 0)
-        eeg_frame = generate_raw_eeg_frame(add_event=insert_event)
-        frame_bytes = eeg_frame.tobytes()
-
-        # 字节校验
-        if len(frame_bytes) != CONFIG.RAW_FRAME_BYTES:
-            print(f"[字节警告] 期望{CONFIG.RAW_FRAME_BYTES}, 实际{len(frame_bytes)}")
-            time.sleep(CONFIG.SEND_INTERVAL)
-            frame_count += 1
-            continue
-
-        data_client.send_bytes(frame_bytes)
-        frame_count += 1
-        time.sleep(CONFIG.SEND_INTERVAL)
-    print("[线程-原始数据发送] 已退出")
-
-def start_filter_data_recv_thread(data_client: ZmqDealerClient, plot_queue: List[np.ndarray]):
-    """滤波数据接收线程"""
-    print(f"[线程-滤波数据接收] 单包{CONFIG.FILTER_FRAME_BYTES}字节 | float64")
-    while GLOBAL_STATE.run_flag:
-        raw_bytes = data_client.recv_bytes()
-        if not raw_bytes:
-            time.sleep(0.01)
-            continue
-
-        try:
-            filter_arr = np.frombuffer(raw_bytes, dtype=CONFIG.DATA_DTYPE)
-            filter_arr = filter_arr.reshape(CONFIG.FILTER_FRAME_POINTS, CONFIG.FILTER_OUT_CHAN)
-            plot_queue.append(filter_arr[:, CONFIG.PLOT_TARGET_CHAN])
-        except Exception as e:
-            print(f"[滤波数据解析异常] {e}")
-            continue
-    print("[线程-滤波数据接收] 已退出")
-
-# ===================== 7. 实时波形可视化 =====================
-def start_wave_visualization(plot_queue: List[np.ndarray]):
-    """启动实时滤波波形绘图"""
-    fig, ax = plt.subplots(figsize=(14, 4))
-    x_axis = np.arange(0, CONFIG.PLOT_WINDOW_LEN)
-    wave_data = np.zeros(CONFIG.PLOT_WINDOW_LEN, dtype=CONFIG.DATA_DTYPE)
-    line, = ax.plot(x_axis, wave_data, color="#2E86AB", linewidth=1.2)
-
-    ax.set_title(
-        f"实时滤波脑电波形 | 通道 {CONFIG.PLOT_TARGET_CHAN} | {CONFIG.SAMPLE_RATE}Hz | float64",
-        fontsize=12
-    )
-    ax.set_ylim(-3.0, 3.0)
-    ax.grid(True, alpha=0.3, linestyle="--")
-    plt.tight_layout()
-
-    def update_plot(_):
-        nonlocal wave_data
-        if plot_queue:
-            new_wave = plot_queue.pop(0)
-            wave_data = np.roll(wave_data, -len(new_wave))
-            wave_data[-len(new_wave)] = new_wave
-        line.set_ydata(wave_data)
-        return (line,)
-
-    ani = FuncAnimation(
-        fig, update_plot,
-        interval=CONFIG.PLOT_REFRESH_INTERVAL,
-        blit=True,
-        cache_frame_data=False
-    )
-    plt.show()
-
-# ===================== 8. 全量业务测试用例 =====================
-def run_full_test_cases(cmd_client: ZmqDealerClient):
-    """全覆盖 zmqServer 所有命令：sync/targetFreqs/decoderClass/impedance/train/predict/rest"""
-    print("\n" + "="*60)
-    print("开始执行全量命令测试用例")
-    print("="*60)
-    time.sleep(2)
-
-    # 1. 同步命令
-    print("\n[用例 1] 发送 sync 命令")
-    cmd_client.send_json({"method": "sync", "params": {}})
-    time.sleep(1)
-
-    # 2. 设置目标频率
-    print("\n[用例 2] 发送 targetFreqs = [8.0, 9.0]")
-    cmd_client.send_json({"method": "targetFreqs", "params": [8.0, 9.0]})
-    time.sleep(1)
-
-    # 3. 切换解码器
-    print("\n[用例 3] 切换解码器为 ssmvep")
-    cmd_client.send_json({"method": "decoderClass", "params": "ssmvep"})
-    time.sleep(2)
-    print("\n[用例 3-2] 切换解码器为 mi")
-    cmd_client.send_json({"method": "decoderClass", "params": "mi"})
-    time.sleep(2)
-
-    # 4. 阻抗检测开关
-    print("\n[用例 4] 开启阻抗检测 impedance=1")
-    cmd_client.send_json({"method": "impedance", "params": 1})
-    time.sleep(1)
-    print("\n[用例 4-2] 关闭阻抗检测 impedance=2")
-    cmd_client.send_json({"method": "impedance", "params": 2})
-    time.sleep(1)
-
-    # 5. 训练模式
-    print("\n[用例 5] 启动训练 train，标签=1")
-    cmd_client.send_json({"method": "train", "params": 1})
-    time.sleep(3)
-
-    # # 6. 休息模式
-    # print("\n[用例 6] 切换 rest 休息模式")
-    # cmd_client.send_json({"method": "rest", "params": {}})
-    # time.sleep(1)
-
-    # 7. 启动解码
-    print("\n[用例 7] 启动解码 predict=1")
-    cmd_client.send_json({"method": "predict", "params": 1})
-    time.sleep(4)
-
-    # # 8. 非法命令（异常测试）
-    # print("\n[用例 8] 发送非法命令 test_cmd_illegal")
-    # cmd_client.send_json({"method": "test_cmd_illegal", "params": {}})
-    # time.sleep(1)
-
-    # # 9. 停止解码
-    # print("\n[用例 9] 停止解码 predict=2")
-    # cmd_client.send_json({"method": "predict", "params": 2})
-    # time.sleep(2)
-
-    print("\n" + "="*60)
-    print("所有测试用例执行完毕")
-    print("="*60)
-
-# ===================== 主程序入口（修复线程语法） =====================
-if __name__ == "__main__":
-    print("="*60)
-    print("ZMQ 脑电仿真测试工具 启动")
-    print(f"命令端口: {CONFIG.CMD_PORT} | 数据端口: {CONFIG.DATA_PORT}")
-    print(f"原始帧{CONFIG.RAW_FRAME_BYTES}字节 | 滤波帧{CONFIG.FILTER_FRAME_BYTES}字节 | float64")
-    print("="*60)
-
-    try:
-        with ZmqDealerClient(CONFIG.SERVER_IP, CONFIG.CMD_PORT) as cmd_client, \
-             ZmqDealerClient(CONFIG.SERVER_IP, CONFIG.DATA_PORT) as data_client:
-
-            plot_queue = []
-
-            # ========== 重点修复：线程语法，daemon 移出 args ==========
-            # 命令接收线程
-            t_cmd = threading.Thread(
-                target=start_cmd_response_thread,
-                args=(cmd_client,),  # 单元素元组保留逗号
-                daemon=True
-            )
-            # 原始数据发送线程
-            t_eeg = threading.Thread(
-                target=start_raw_eeg_send_thread,
-                args=(data_client,),
-                daemon=True
-            )
-            # 滤波数据接收线程
-            t_filter = threading.Thread(
-                target=start_filter_data_recv_thread,
-                args=(data_client, plot_queue),
-                daemon=True
-            )
-
-            # 启动线程
-            t_cmd.start()
-            t_eeg.start()
-            t_filter.start()
-
-            # 执行测试用例
-            run_full_test_cases(cmd_client)
-
-            # 启动可视化（阻塞主线程）
-            print("\n[提示] 波形窗口已启动，关闭窗口 / Ctrl+C 退出程序")
-            start_wave_visualization(plot_queue)
-
-    except KeyboardInterrupt:
-        print("\n\n[用户中断] 接收到 Ctrl+C，准备退出...")
-    except Exception as e:
-        print(f"\n[程序异常] {e}")
-    finally:
-        # 停止所有后台线程
-        GLOBAL_STATE.run_flag = False
-        time.sleep(0.2)
-        print("程序已安全退出")