292 lines
11 KiB
Python
292 lines
11 KiB
Python
# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.
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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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from itertools import product
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import pandas as pd
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from datetime import datetime
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from config import DATETIME_FORMAT
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import config
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import sql_statements
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import models
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import sql_statements
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import controller
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from decimal import Decimal, getcontext
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from util import smooth_data, calc_one_cattle
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import util
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import math
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SPLIT_LINE = "----------------------------------------"
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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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#
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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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#
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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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#
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# return result_dict
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def weight_wave_menu(rfid, buy_weight, time_std): # TODO: 需要修改为可以多个输入ID
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weight_wave_lst = controller.get_weight_wave(rfid, time_std)
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if not weight_wave_lst:
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print('未找到体重数据，请重新输入牛只ID')
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return -1
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print(SPLIT_LINE)
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for weight_wave in weight_wave_lst:
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print(str(weight_wave))
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print(SPLIT_LINE)
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while True:
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weight_wave_id = input('请输入体重波ID（或输入-1返回）:')
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if weight_wave_id == '-1':
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cattle_menu(time_std)
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elif not any(str(i.id) == weight_wave_id for i in weight_wave_lst):
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print('输入不合法，请重试')
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else:
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item = next((obj for obj in weight_wave_lst if obj.id == int(weight_wave_id)), None)
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diff_s = (datetime.strptime(item.end_time, DATETIME_FORMAT) - datetime.strptime(item.start_time,
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DATETIME_FORMAT)).total_seconds()
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if item is not None:
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duration = item.start_time + " ~ " + item.end_time + " ( " + str(diff_s) + "s )"
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print('正在获取体重日志...')
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weight_wave_logs = controller.get_weight_wave_log(item, time_std)
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print('正在显示图表...')
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show_log_diagram(weight_wave_logs, buy_weight, daily_weight=item.weight, duration=duration,
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rfid_frq=item.max_frq, id=item.id)
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def show_log_diagram(weight_wave_logs, buy_weight, daily_weight, duration, rfid_frq, id):
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index = 0
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x = []
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y = []
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for item in weight_wave_logs:
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y.append(float(item.weight))
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x.append(item.time)
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index += 1
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y_smooth = smooth_data(y, max(5, int(len(weight_wave_logs) * (
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12 / 100)) // 2 * 2 + 1))
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m_daily_weight = calc_one_cattle(smooth_data(y, max(5, int(len(weight_wave_logs) * (
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12 / 100)) // 2 * 2 + 1)))
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plt.figure(1, figsize=(20, 4))
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plt.plot(x, y, color='blue', linestyle='-', linewidth=1)
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# 添加横向分割线
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plt.axhline(y=math.ceil(float(buy_weight)), color='red', linestyle='--', linewidth=1,
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label='buy_weight: ' + str(math.ceil(float(buy_weight))))
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if not np.isnan(m_daily_weight): # TODO: 为什么 4 - 1307 - 8311 体重波没有稳定值但是记录了 486.0952
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plt.axhline(y=math.ceil(m_daily_weight), color='green', linestyle='--', linewidth=1,
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label='daily_weight: ' + str(math.ceil(m_daily_weight)))
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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(
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"id: " + str(id) + " len: " + str(len(weight_wave_logs)) + " duration: " + duration + " rfid_frq: " + str(rfid_frq))
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plt.figure(2, figsize=(20, 4))
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plt.plot(x, y_smooth, color='blue', linestyle='-', linewidth=1)
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plt.axhline(y=math.ceil(float(buy_weight)), color='red', linestyle='--', linewidth=1,
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label='buy_weight: ' + str(math.ceil(float(buy_weight))))
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if not np.isnan(m_daily_weight): # TODO: 为什么 4 - 1307 - 8311 体重波没有稳定值但是记录了 486.0952
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plt.axhline(y=math.ceil(m_daily_weight), color='green', linestyle='--', linewidth=1,
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label='daily_weight: ' + str(math.ceil(m_daily_weight)))
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# 添加标签和图例
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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(
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"id: " + str(id) + " len: " + str(len(weight_wave_logs)) + " duration: " + duration + " rfid_frq: " + str(rfid_frq))
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plt.show()
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return
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def cattle_menu(time_std):
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rfid_lst = sorted(controller.get_rfid_all(), key=lambda x: x.id) # 获取所有牛只的RFID，根据记录主键从小到达排序
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print(SPLIT_LINE)
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for item in rfid_lst:
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print(vars(item))
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print(SPLIT_LINE)
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while True:
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cattle_id = input('请输入id（返回输入-1）：')
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if cattle_id == '-1':
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main_menu()
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elif not any(i.id == int(cattle_id) for i in rfid_lst):
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print('输入无效请重新输入')
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continue
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else:
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item = next((obj for obj in rfid_lst if obj.id == int(cattle_id)), None)
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print('RFID：', item.rfid)
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buy_weight = controller.get_buy_weight(item.rfid)
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rt = weight_wave_menu(item.rfid, buy_weight, time_std)
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if rt == -1:
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continue
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# daily_weight_lst = controller.get_daily_weight(item.rfid)
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# if not daily_weight_lst:
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# print('未找到体重数据，请重新输入牛只ID')
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# continue
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# for daily_weight in daily_weight_lst:
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# print(daily_weight)
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def main_menu():
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while True:
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print('主菜单')
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print(SPLIT_LINE)
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print('0 - 退出程序')
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print('1 - 初始化体重数据（设备时间）')
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print('2 - 查看牛只日体重（设备时间）')
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print('3 - 初始化体重数据（服务器时间）')
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print('4 - 查看牛只日体重（服务器时间）')
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print('5 - 重置本地数据库')
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print(SPLIT_LINE)
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ctrl = input('请输入：')
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if ctrl == '-1':
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test()
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break
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elif ctrl == '0':
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break
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elif ctrl == '1':
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controller.clear_data_by_time_std(1)
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controller.init_data(1)
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cattle_menu(1)
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elif ctrl == '2':
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cattle_menu(1)
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elif ctrl == '3':
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controller.clear_data_by_time_std(2)
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controller.init_data(2)
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cattle_menu(2)
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elif ctrl == '4':
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cattle_menu(2)
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elif ctrl == '5':
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confirm = input('确定要清除所有数据吗？y ：确定 / any key：退出')
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if confirm == 'y' or 'Y':
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controller.clear_all_data()
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print('重置成功！')
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continue
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else:
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print('输入错误，请重新输入')
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continue
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def test():
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data = [1, 2, 4, 7, 2, 3, 7, 10, 12, 5, 6, 5, 5, 20, 23, 21, 20, 23, 22, 19]
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util.calc_one_cattle(data)
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return
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if __name__ == '__main__':
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main_menu()
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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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#
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# final_weight_result = time_data_suppl(timestamp_seq, clean_weight_result)
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# weight_wave_log = controller.get_weight_wave_log()
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# time_seq = []
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# weight_seq = [float(item.get('biz_data')) for item in weight_wave_log]
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# # weight_seq = [100, 90, 110, 130, 150, 170, 190, 192, 195, 199, 210, 220, 230, 240, 248, 255, 245, 248, 250, 252,
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# # 253, 253, 257, 254, 250, 255, 259, 265, 275, 285, 295, 310, 320, 305, 295, 283, 273, 263, 253, 240,
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# # 229, 209, 190, 174, 162, 150, 139, 114, 100, 90, 100, 101, 102, 100, 95, 97]
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# index_seq = [i for i in range(1, len(weight_seq) + 1)]
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# print('weight_seq: ' + str(weight_seq) + '\nindex_seq: ' + str(index_seq))
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# weight_seq_smooth = (smooth_data(weight_seq))
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# plt.figure(figsize=(20, 4))
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# plt.plot(index_seq, weight_seq_smooth, color='blue', linestyle='-', linewidth=1)
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# plt.xlabel('sequence')
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# plt.ylabel('weight(kg)')
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# plt.title('weight_wave')
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# plt.show()
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# calc_one_cattle(weight_seq)
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"""
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x = np.linspace(0, 10, 100)
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y1 = np.sin(x)
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y2 = np.cos(x)
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# 第1个图形窗口
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plt.figure(1)
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plt.plot(x, y1, color='r')
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plt.title("Figure 1: Sine Function")
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# 第2个图形窗口
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plt.figure(2)
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plt.plot(x, y2, color='b')
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plt.title("Figure 2: Cosine Function")
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# 显示所有窗口
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plt.show()
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"""
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# index = 1
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# for log in weight_wave_log:
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# m_dt = datetime.strftime(log.get('biz_time'), controller.DATETIME_FORMAT)
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# print(m_dt)
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# time_seq.append(m_dt)
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# index_seq.append(index)
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# weight_seq.append(log.get('biz_data'))
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# index += 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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#
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# # 添加图例
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# plt.legend()
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#
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#
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# result = models.get_logs(floor_scale_id ="2404049517", start_time ="2024-09-01 00:00:00", end_time ="2024-09-02 00:00:00")
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# result = models.get_ear_tag('9057970969300989')
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# print(result)
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# floor_scale_id, start_time, end_time, max_weight, max_weight_time, max_frq_ear_tag, max_frq_rfid, time_std
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# weight_wave = ('floor_scale_id', '2024-12-01 00:00:00',
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# '2024-12-07 00:00:00',
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# 100.00, '2024-12-06 19:00:00', 'max_frq_ear_tag',
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# 'max_frq_rfid', 1)
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# parent_id = models.add_weight_wave(False, weight_wave, False)
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# rfid_frq = []
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# for i in range(1, 11):
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# rfid_frq.append(
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# (str(parent_id), str(i), 'rfid' + str(i), i, 1))
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# models.add_rfid_frq(True, rfid_frq,True)
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#
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# print('parent_id:'+str(parent_id))
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#
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# models.delete_weight_wave(False)
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# models.delete_rfid_frq(True)
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# controller.init_data()
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# controller.clean_data()
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