c0fe213b70
1. 修复前端图表日期排序问题: - 改进 PredictionView.vue 和 HistoryView.vue 中的图表渲染逻辑 - 确保历史数据和预测数据按照正确的日期顺序显示 2. 修复后端API处理: - 解决 optimized_kan 模型类型的路径映射问题 - 添加 JSON 序列化器处理 Pandas Timestamp 对象 - 改进预测数据与历史数据的衔接处理 3. 优化图表样式和用户体验
43 lines
1.9 KiB
Bash
43 lines
1.9 KiB
Bash
#!/bin/bash
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echo "药店销售预测系统 - 依赖库安装脚本"
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echo "=================================="
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echo ""
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echo "请选择要安装的版本:"
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echo "1. CPU版本（适用于没有NVIDIA GPU的计算机）"
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echo "2. GPU版本 - CUDA 12.8（适用于最新的NVIDIA GPU）"
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echo "3. GPU版本 - CUDA 11.8（适用于较旧的NVIDIA GPU）"
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echo ""
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read -p "请输入选项 (1/2/3): " choice
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if [ "$choice" = "1" ]; then
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echo "正在安装CPU版本依赖..."
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pip install -r requirements.txt
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elif [ "$choice" = "2" ]; then
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echo "正在安装GPU版本(CUDA 12.1)依赖..."
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echo "首先安装基础依赖..."
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pip install -r requirements-gpu.txt --no-deps
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echo "安装除PyTorch以外的其他依赖..."
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pip install numpy==2.3.0 pandas==2.3.0 matplotlib==3.10.3 scikit-learn==1.7.0 tqdm==4.67.1 openpyxl==3.1.5
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echo "从PyTorch官方源安装CUDA 12.1版本的PyTorch..."
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
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elif [ "$choice" = "3" ]; then
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echo "正在安装GPU版本(CUDA 11.8)依赖..."
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echo "首先安装基础依赖..."
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pip install -r requirements-gpu-cu118.txt --no-deps
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echo "安装除PyTorch以外的其他依赖..."
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pip install numpy==2.3.0 pandas==2.3.0 matplotlib==3.10.3 scikit-learn==1.7.0 tqdm==4.67.1 openpyxl==3.1.5
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echo "从PyTorch官方源安装CUDA 11.8版本的PyTorch..."
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
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else
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echo "无效的选项！请重新运行脚本并选择正确的选项。"
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exit 1
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fi
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echo ""
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echo "依赖库安装完成！"
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echo ""
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echo "验证PyTorch GPU支持状态..."
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python -c "import torch; print('CUDA是否可用:', torch.cuda.is_available()); print('PyTorch版本:', torch.__version__); print('GPU数量:', torch.cuda.device_count()); print('GPU名称:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else '无GPU')" |