100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
# Press ⌃R to execute it or replace it with your code.
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# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.
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import db_dao as dd
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.dates as mdates
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import pandas as pd
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from datetime import datetime,timedelta
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m_weight = []
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m_datetime = []
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m_start_time = '2024-09-09 06:50:00'
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m_end_time = '2024-09-09 07:10:00'
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# m_reader = '2405085412' # 客户看不到视频
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m_weighbridge_reader = '2405085474' # 客户可以看到设备
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# m_reader = '2404049517'
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# m_reader = '2405085489'
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m_rfid_reader = '0A26AE180665' # 对应地磅的 2405085474
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date_format = "%Y-%m-%d %H:%M:%S"
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# Press the green button in the gutter to run the script.
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# 创建查询时间范围的序列
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def create_timestamp_seq():
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# 将起止时间转换为 datetime 对象
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m_datetime_start_obj = datetime.strptime(m_start_time, date_format)
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m_datetime_end_obj = datetime.strptime(m_end_time, date_format)
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# 计算时间差并转为秒数
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time_diff = m_datetime_end_obj - m_datetime_start_obj
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seconds = time_diff.total_seconds()+1
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# 创建时间序列，单位为秒
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start_time = pd.Timestamp(m_start_time)
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time_seconds_seq = pd.date_range(start=start_time, periods=int(seconds), freq='s') # 生成日期差秒数个时间点，每个时间点间隔1秒
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return time_seconds_seq
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# 补充缺失的时间秒数
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def time_data_suppl(timestamp,data):
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i = 1
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sorted_data = []
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for ts in timestamp:
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format_ts = ts.strftime(date_format)
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if format_ts not in data:
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sorted_data.append(0)
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else:
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sorted_data.append(float(data[format_ts]))
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# print(str(i)+' 存在数据：'+format_ts+' ------> '+data[format_ts])
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i += 1
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return sorted_data
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# 对相同时间的数据去重复，取体重最大值
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def time_data_dedup(data):
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result_dict = {}
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for row in data:
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key = row[0].strftime(date_format)
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if key not in result_dict or float(row[1]) > float(result_dict[key]):
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result_dict[key] = float(row[1])
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return result_dict
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# rfid数据去重
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def rfid_data_dedup(data):
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# 保留顺序的去重方法
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seen = set()
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unique_tuple_list = []
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for item in data:
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if item not in seen:
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unique_tuple_list.append(item)
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seen.add(item)
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return unique_tuple_list
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if __name__ == '__main__':
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timestamp_seq = create_timestamp_seq()
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mysql_weight_result = dd.get_cattle_weight_by_datetime(m_start_time, m_end_time, m_weighbridge_reader)
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mysql_rfid_result = dd.get_rfid_by_datetime(m_start_time, m_end_time, m_rfid_reader)
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dd.close()
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clean_weight_result = time_data_dedup(mysql_weight_result)
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clean_rfid_result = rfid_data_dedup(mysql_rfid_result)
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final_weight_result = time_data_suppl(timestamp_seq, clean_weight_result)
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plt.figure(figsize=(24, 4))
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plt.plot(timestamp_seq, final_weight_result, color='blue', linestyle='-', linewidth=1)
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for rst in clean_rfid_result:
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# 添加纵向分割线
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plt.axvline(x=rst[0], color='r', linestyle='--', label=rst[1], linewidth = 0.5)
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# 添加图例
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plt.legend()
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plt.xlabel('datetime')
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plt.ylabel('weight(kg)')
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plt.title('reader: ' + m_weighbridge_reader + '\n' + m_start_time + ' ---> ' + m_end_time)
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plt.show() |