PPG数据分析命令行工具库
Project description
GHealth Tools
PPG(光电容积脉搏波)数据分析命令行工具库,支持数据转换、可视化、分类等功能。
安装
pip install ghealth-tools
或从源码安装:
git clone https://github.com/yourusername/health_tools.git
cd health_tools
pip install -e .
快速开始
# 查看帮助
ghealth_tool --help
# 查看版本
ghealth_tool --version
命令
parse - 日志解析
将原始日志文件解析为CSV格式。
# 使用解析规则文件
ghealth_tool parse -i raw.log -o output.csv -r parse/gh3220.yaml
# 使用芯片规则
ghealth_tool parse -i raw.log -o output.csv --chip gh3220
# 批量处理目录
ghealth_tool parse -i logs/ -o output/ -r parse/default.yaml -v
plot - 数据可视化
绘制PPG数据的时域/频域图。
# 绘制时域和频域图
ghealth_tool plot -i data.csv -o plots/ --type both --sample-rate 100
# 仅绘制时域图
ghealth_tool plot -i data.csv -o plots/ --type time --channels red,ir
# 指定窗口和重叠率
ghealth_tool plot -i data.csv -o plots/ --window 10 --overlap 0.75
classify - 数据分类
根据规则对数据进行分类保存。
# 使用分类规则
ghealth_tool classify -i data/ -o classified/ -r classify/default.yaml
# 生成分类报告
ghealth_tool classify -i data/ -o classified/ -r classify/default.yaml --report
# 移动文件而非复制
ghealth_tool classify -i data/ -o classified/ -r classify/default.yaml --move
convert - 格式转换
CSV格式转换(紧凑型↔展开型,芯片特定格式)。
# 使用转换规则
ghealth_tool cv -i input.csv -o output.csv -r convert/my_rule.yaml
# 合并多个文件
ghealth_tool cv -i data/ -o merged.csv -r convert/rule.yaml --merge
# 按大小分割
ghealth_tool cv -i large.csv -o split/ -r convert/rule.yaml --split 10000
# 生成规则模板
ghealth_tool convert --init-rule -c gh3220 -o my_convert_rule.yaml
factory - 产测计算
计算 SNR/CTR/Noise,支持芯片规则自动提取增益和灯电流。
# 单文件计算
ghealth_tool fac -i data.csv -c gh3036_evk
# 目录批量计算
ghealth_tool fac -i data_dir/ -c gh3036_evk -v
# 指定增益和电流
ghealth_tool fac -i data.csv -c gh3036 --gain 10 --current 25.0
# 覆盖默认时长配置
ghealth_tool fac -i data.csv -c gh3036_evk --snr-cfg "5,5,60" --ctr-cfg "1,0,2"
info - 信息查看
查看数据文件或规则文件信息。
# 查看CSV文件信息
ghealth_tool info data.csv --stats --preview 20
# 查看规则文件
ghealth_tool info rules/chip/gh3220.yaml --schema
validate - 规则验证
验证YAML规则文件格式和内容。
# 验证规则文件
ghealth_tool validate rules/chip/gh3220.yaml
# 严格模式验证
ghealth_tool validate rules/parse/gh3220.yaml --strict
规则文件
芯片规则 (rules/chip/*.yaml)
定义CSV文件的格式和产测计算参数:
version: "1.0"
chip: gh3220
csv:
info_row: 1
header_row: 2
data_start_row: 3
delimiter: ","
encoding: "utf-8"
columns:
- TimeStamp
- FRAME_ID
- CH{0-15}
factory_columns: # 产测计算列
- CH{0-15}
factory_config: # 各指标独立时长配置
sample_rate: 100
snr:
skip_head_seconds: 10
skip_tail_seconds: 10
min_duration_seconds: 90
ctr:
skip_head_seconds: 1
skip_tail_seconds: 0
min_duration_seconds: 2
noise:
skip_head_seconds: 2
skip_tail_seconds: 0
min_duration_seconds: 4
chip_info:
adc_full_scale: 8388608
adc_offset: 8388608
adc_vref: 1.8
tia_ratio: 2
解析规则 (rules/parse/*.yaml)
定义如何解析日志文件:
version: "1.0"
description: "GH3220日志解析规则"
regex: '^\[(.+?)\]\s+GH3220:\s*(\d+),(\d+),(\d+),(\d+)$'
columns:
- timestamp
- red
- ir
- green
- aux
分类规则 (rules/classify/*.yaml)
定义数据分类规则:
version: "1.0"
filename:
regex: '(\d{8})_(\w+)_(\w+)\.csv'
fields:
- date
- subject
- motion
data_columns:
- name: motion
source: filename
match:
supine: ["supine", "lie"]
sit: ["sit", "sitting"]
structure:
supine: ""
sit: ""
rules:
- target: "{motion}"
use_filename: true
转换规则 (rules/convert/*.yaml)
定义CSV格式转换,支持列映射、前值填充、频率扩展:
version: "1.0"
target_chip: gh3220
csv:
info_row: 0 # 信息所在行(0=无)
header_row: 1 # 列名所在行
data_start_row: 2 # 数据开始行
delimiter: ","
column_mapping:
time: TimeStamp
acc[0]: ACCX # [] 为字面量列名
rawdata{0-15}: CH{0-15} # {} 展开为 rawdata0->CH0, rawdata1->CH1, ...
forward_fill:
- polar_HR # 0值用前一个非0值填充
expand_repeat:
polar_HR: 25 # 每个值重复25次匹配采样率
列名展开语法
使用 {start-end} 进行范围展开,[] 保留为字面量:
columns:
- CH{0-15} # 展开为 CH0, CH1, ..., CH15
- ALGO{0-1}_CH{0-2} # 多段展开: ALGO0_CH0, ALGO0_CH1, ..., ALGO1_CH2
column_mapping:
rawdata[{0-1}]: Rawdata{0-1} # rawdata[0]->Rawdata0, rawdata[1]->Rawdata1
acc[0]: ACCX # acc[0] 是字面量列名
内置芯片规则
| 芯片 | 文件 | 描述 |
|---|---|---|
| GH3220 | rules/chip/gh3220.yaml |
Goodix PPG传感器 |
| GH3036 | rules/chip/gh3036.yaml |
Goodix健康传感器 |
| GH3036_EVK | rules/chip/gh3036_evk.yaml |
GH3036 评估板 |
开发
环境设置
# 克隆仓库
git clone https://github.com/yourusername/health_tools.git
cd health_tools
# 创建虚拟环境
python -m venv venv
source venv/bin/activate # Linux/Mac
# 或
.\venv\Scripts\activate # Windows
# 安装开发依赖
pip install -e ".[dev]"
运行测试
pytest
代码格式化
black src/
ruff check src/
许可证
MIT License
贡献
欢迎提交 Issue 和 Pull Request!
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