def get_df(self):
"""
通过调用 base_setting.AutoSelectTickets得到英文标签
通过调用import_data.ImportData得到df
:return:
"""
# 中文标签
tickets_list = ["时间",
"机组运行模式",
"变频器主机igbt温度",
"变频器从机igbt温度",
"变流器发电机转速",
"叶轮速度2",
"变频器主机冷却液温度",
"变频器主机风扇运行1",
"变频器主机水泵运行",
"变频器从机冷却液温度",
"变频器从机风扇运行1",
"变频器从机水泵运行",
"变频器主机冷却液压力",
"变频器从机冷却液压力"
]
auto_select_tickets = base_setting.AutoSelectTickets(self.tickets_file_path)
# 得到英文标签，可能存在缺失情况！
self.tickets = auto_select_tickets.select_tickets_by_project(self.project_index, tickets_list)
# 如果df是None 则开启第二种模式，创建df
if self.df is None:
# 记录缺失位置
for i in range(len(self.tickets)):
if not self.tickets[i]:
self.missing_tickets.append(i)
# 创建一个临时列表用于读取df，倒序移除缺失元素
# 深拷贝 防止修改原self.tickets
li = copy.deepcopy(self.tickets)
for i in range(len(li) - 1, -1, -1):
if not li[i]:
del li[i]
# 记录缺失位置，用于在df中插入空列
import__data = import_data.ImportData(self.import_file_path, li)
self.df = import__data.handle_import_data()
self.df.insert(0, "time", pd.to_datetime(self.df[li[0]]))
for i in range(len(self.missing_tickets)):
self.df.insert(self.missing_tickets[i], self.missing_tickets[i], np.nan)
def get_df(self):
"""
通过调用 base_setting.AutoSelectTickets得到英文标签
通过调用import_data.ImportData得到df
:return:
"""
# 中文标签
tickets_list = [
"时间", "机组运行模式", "液压系统压力", "液压泵1开", "液压泵2开", "顺时针偏航", "逆时针偏航",
"偏航制动出口压力1", "偏航制动出口压力2", "偏航制动入口压力1", "偏航制动入口压力2", "偏航半释放阀",
"液压主泵处油温", "液压泵出口压力", "液压回油口油温", "叶轮锁定压力1", "叶轮锁定压力2", "叶轮锁蓄能器压力1",
"叶轮锁蓄能器压力2"
]
auto_select_tickets = base_setting.AutoSelectTickets(
self.tickets_file_path)
# 得到英文标签，可能存在缺失情况！
self.tickets = auto_select_tickets.select_tickets_by_project(
self.project_index, tickets_list)
# 如果df是None 则开启第二种模式，创建df
if self.df is None:
# 记录缺失位置
for i in range(len(self.tickets)):
if not self.tickets[i]:
self.missing_tickets.append(i)
# 创建一个临时列表用于读取df，倒序移除缺失元素
# 深拷贝 防止修改原self.tickets
li = copy.deepcopy(self.tickets)
for i in range(len(li) - 1, -1, -1):
if not li[i]:
del li[i]
# 记录缺失位置，用于在df中插入空列
import__data = import_data.ImportData(self.import_file_path, li)
self.df = import__data.handle_import_data()
self.df.insert(0, "time", pd.to_datetime(self.df[li[0]]))
for i in range(len(self.missing_tickets)):
self.df.insert(self.missing_tickets[i],
self.missing_tickets[i], np.nan)
def get_df(self):
"""
如果是小文件模式：
通过调用 base_setting.AutoSelectTickets得到英文标签
通过调用import_data.ImportData得到df
如果是大文件模式：
直接返回
:return:
"""
if self.mode == 1:
# 中文标签
print("开始")
tickets_list = [
# 齿轮箱 1
"时间",
"机组运行模式",
"齿轮箱主轴承温度",
"齿轮箱轮毂侧轴承温度",
"齿轮箱发电机侧轴承温度",
"齿轮箱油温",
"齿轮箱离线过滤泵处油温",
"齿轮箱主泵处油温",
"润滑油冷却器入口油温",
"润滑油冷却器出口油温",
"齿轮箱水泵出口温度",
"齿轮箱水泵入口温度1",
"齿轮箱水泵入口温度2",
"齿轮箱A1口温度",
"齿轮箱A2口温度",
"齿轮箱A3口温度",
"齿轮箱A4口温度",
"齿轮箱主泵1_1高速",
"齿轮箱主泵1_2高速",
"齿轮箱主泵1_1低速",
"齿轮箱主泵1_2低速",
"齿轮箱A1口压力",
"齿轮箱主泵2_1高速",
"齿轮箱主泵2_2高速",
"齿轮箱主泵2_1低速",
"齿轮箱主泵2_2低速",
"齿轮箱A2口压力",
"齿轮箱A3口压力",
"发电机润滑泵3_1",
"发电机润滑泵3_2",
"齿轮箱A4口压力",
"齿轮箱主泵1_1出口压力",
"齿轮箱主泵1_2出口压力",
"齿轮箱主泵2_1出口压力",
"齿轮箱主泵2_2出口压力",
"齿轮箱冷却泵出口压力",
"齿轮箱冷却泵",
"齿轮箱过滤泵",
"齿轮箱过滤泵出口压力",
"齿轮箱油位",
"齿轮箱水泵1启动",
"齿轮箱水冷风扇1高速启动",
"齿轮箱水泵2启动",
"齿轮箱水冷风扇2高速启动",
"齿轮箱水泵1出口压力",
"齿轮箱水泵1入口压力",
"齿轮箱水泵2出口压力",
"齿轮箱水泵2入口压力",
# 发电机 2
"时间",
"机组运行模式",
"发电机绕组温度1",
"发电机绕组温度2",
"发电机绕组温度3",
"发电机绕组温度4",
"发电机绕组温度5",
"发电机绕组温度6",
"发电机齿轮箱侧轴承温度",
"发电机机舱侧轴承温度",
"变流器功率",
"发电机空空冷内循环入口温度1",
"发电机空空冷内循环入口温度2",
"发电机空空冷内循环出口温度1",
"发电机空空冷内循环出口温度2",
"发电机空空冷外循环入口温度1",
"发电机空空冷外循环入口温度2",
"发电机空空冷外循环出口温度1",
"发电机空空冷外循环出口温度2",
# 变流器 3
"时间",
"机组运行模式",
"变频器主机igbt温度",
"变频器从机igbt温度",
"变流器发电机转速",
"叶轮速度2",
"变频器主机冷却液温度",
"变频器主机风扇运行1",
"变频器主机水泵运行",
"变频器从机冷却液温度",
"变频器从机风扇运行1",
"变频器从机水泵运行",
"变频器主机冷却液压力",
"变频器从机冷却液压力",
# 变桨 4
"时间",
"机组运行模式",
"变桨驱动柜温度1",
"变桨驱动柜温度2",
"变桨驱动柜温度3",
"桨叶角度1A",
"桨叶角度2A",
"桨叶角度3A",
"桨叶角度1B",
"桨叶角度2B",
"桨叶角度3B",
"叶轮速度1",
"叶轮速度2",
"风速",
"变桨电机温度1",
"变桨电机温度2",
"变桨电机温度3",
"变桨驱动柜散热器温度1",
"变桨驱动柜散热器温度2",
"变桨驱动柜散热器温度3",
"变桨后备电源柜温度1",
"变桨后备电源柜温度2",
"变桨后备电源柜温度3",
# 液压 5
"时间",
"机组运行模式",
"液压系统压力",
"液压泵1开",
"液压泵2开",
"顺时针偏航",
"逆时针偏航",
"偏航制动出口压力1",
"偏航制动出口压力2",
"偏航制动入口压力1",
"偏航制动入口压力2",
"偏航半释放阀",
"液压主泵处油温",
"液压泵出口压力",
"液压回油口油温",
"叶轮锁定压力1",
"叶轮锁定压力2",
"叶轮锁蓄能器压力1",
"叶轮锁蓄能器压力2",
# 传感器 6
"时间",
"机组运行模式",
"箱式变压器温度",
"塔筒第一层平台温度",
"塔基柜温度",
"机舱高压柜温度",
"机舱温度",
"机舱低压柜温度",
"变频器温度1",
"变频器温度2",
"变频器温度3",
"变频器温度4",
"变频器温度5",
"变频器温度6",
"变频器温度7",
"变频器温度8",
"变频器温度9",
"变频器温度10",
"变频器温度11",
"变频器温度12",
"变频器温度13",
"变频器温度14",
"变频器温度15",
"变频器温度16",
"变频器温度17"
]
auto_select_tickets = base_setting.AutoSelectTickets(
self.tickets_file_path)
self.tickets = auto_select_tickets.select_tickets_by_project(
self.project_index, tickets_list)
# 记录缺失位置
for i in range(len(self.tickets)):
if not self.tickets[i]:
self.missing_tickets.append(i)
# 创建一个临时列表用于读取df，倒序移除缺失元素
# 深拷贝 防止修改原self.tickets
li = copy.deepcopy(self.tickets)
for i in range(len(li) - 1, -1, -1):
if not li[i]:
del li[i]
# 记录缺失位置，用于在df中插入空列
import__data = import_data.ImportData(self.import_file_path, li)
self.df = import__data.handle_import_data()
self.df.insert(0, "time", pd.to_datetime(self.df[li[0]]))
for i in range(len(self.missing_tickets)):
self.df.insert(self.missing_tickets[i],
self.missing_tickets[i], np.nan)
print("结束")
self.signal_return_data.emit(
[int(1), self.df, self.project_index,
int(6)])
elif self.mode == 2:
"""
大文件则发送
"""
self.signal_return_data.emit(
[int(2), None, self.project_index,
int(1)])
self.over()