118 lines
3.8 KiB
Python
118 lines
3.8 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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分析官方APP的CSV文件，提取真实的脉冲时长
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"""
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import csv
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import statistics
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def parse_csv(filename):
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"""解析CSV文件，提取脉冲时长"""
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times = []
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states = []
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with open(filename, 'r', encoding='utf-8') as f:
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reader = csv.DictReader(f)
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for row in reader:
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time_str = row['Time'].replace(' ms', '')
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time_us = float(time_str) * 1000 # 转换为微秒
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state = int(row['Ch01'])
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times.append(time_us)
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states.append(state)
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return times, states
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def calculate_pulses(times, states):
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"""计算脉冲时长"""
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pulses = []
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# 跳过第一个时间戳（通常是0或很大的初始值）
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# 从第二个开始计算差值
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for i in range(2, len(times)):
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duration = times[i] - times[i-1]
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# 只保留合理的脉冲时长（100μs - 20000μs）
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if 100 < duration < 20000:
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pulses.append(int(duration))
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return pulses
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def analyze_pulses(pulses):
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"""分析脉冲时长，找出引导码、数据码等"""
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print(f"总脉冲数: {len(pulses)}")
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print(f"\n前20个脉冲:")
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for i, pulse in enumerate(pulses[:20]):
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print(f" [{i}]: {pulse}μs")
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# 统计脉冲时长分布
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pulse_counts = {}
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for pulse in pulses:
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# 四舍五入到最近的50μs
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rounded = round(pulse / 50) * 50
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pulse_counts[rounded] = pulse_counts.get(rounded, 0) + 1
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print(f"\n脉冲时长分布（出现次数 > 5）:")
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for duration in sorted(pulse_counts.keys()):
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count = pulse_counts[duration]
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if count > 5:
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print(f" {duration}μs: {count}次")
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# 找出最常见的脉冲时长
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common_pulses = sorted(pulse_counts.items(), key=lambda x: x[1], reverse=True)[:10]
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print(f"\n最常见的10个脉冲时长:")
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for duration, count in common_pulses:
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print(f" {duration}μs: {count}次")
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# 分析引导码（前2个脉冲）
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if len(pulses) >= 2:
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print(f"\n引导码分析:")
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print(f" 引导码高: {pulses[0]}μs")
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print(f" 引导码低: {pulses[1]}μs")
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# 分析数据码（跳过引导码）
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data_pulses = pulses[2:-1] # 跳过引导码和停止码
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# 找出高电平脉冲（偶数位置）
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high_pulses = [data_pulses[i] for i in range(0, len(data_pulses), 2)]
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# 找出低电平脉冲（奇数位置）
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low_pulses = [data_pulses[i] for i in range(1, len(data_pulses), 2)]
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print(f"\n数据码分析:")
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print(f" 数据高电平: 平均{int(statistics.mean(high_pulses))}μs, "
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f"中位数{int(statistics.median(high_pulses))}μs")
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# 低电平有两种：短（0）和长（1）
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low_pulses_sorted = sorted(low_pulses)
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mid_point = len(low_pulses_sorted) // 2
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short_lows = low_pulses_sorted[:mid_point]
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long_lows = low_pulses_sorted[mid_point:]
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print(f" 数据0低电平: 平均{int(statistics.mean(short_lows))}μs, "
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f"中位数{int(statistics.median(short_lows))}μs")
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print(f" 数据1低电平: 平均{int(statistics.mean(long_lows))}μs, "
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f"中位数{int(statistics.median(long_lows))}μs")
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# 停止码
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if len(pulses) > 0:
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print(f"\n停止码: {pulses[-1]}μs")
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def main():
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files = [
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'正确的csv文档/官方app制冷.csv',
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'正确的csv文档/官方app制热.csv',
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'正确的csv文档/官方app送风模式.csv',
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'正确的csv文档/官方app抽湿.csv',
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]
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for filename in files:
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print(f"\n{'='*60}")
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print(f"分析文件: {filename}")
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print(f"{'='*60}")
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times, states = parse_csv(filename)
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pulses = calculate_pulses(times, states)
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analyze_pulses(pulses)
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if __name__ == '__main__':
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main()
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