def ldcurve_rx_data(self, data):
"data: 表示返回帧数据域（已做减33H处理）, 格式为字符串数组"
import meter
# 将data转为字符串，方便使用正则表达式进行提取
data_str = " ".join(data)
# 匹配组提取所需的数据信息
r = r'.*A0 A0 [\da-fA-F]{2} (\d{2} \d{2} \d{2} \d{2} \d{2} )(.*)AA (.*)AA (.*)AA (.*)AA (.*)AA (.*)AA [\da-fA-F]{2} E5'
# 每个数据项占用字节数列表，按照负荷曲线数据项的顺序配置，第一项为数据标识
bl = [
[5], # 存储时刻
[2, 2, 2, 3, 3, 3, 2], # 电压、电流、频率
[3] * 8, # 有、无功功率
[2] * 4, # 功率因数
[4] * 4, # 有、无功总电能
[4] * 4, # 四象限无功总电能
[3] * 4 # 有、无功需量、零线电流、总视在功率
]
# 每个数据项的数据格式列表
df = [
["YYMMDDhhmm"], # 存储时刻
[
"XXX.X", "XXX.X", "XXX.X", "XXX.XXX", "XXX.XXX", "XXX.XXX",
"XX.XX"
], # 电压、电流、频率
[
"XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX",
"XX.XXXX", "XX.XXXX", "XX.XXXX"
], # 有、无功功率
["X.XXX", "X.XXX", "X.XXX", "X.XXX"], # 功率因数
["XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX"], # 有、无功总电能
["XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX"], # 四象限无功总电能
["XX.XXXX", "XX.XXXX", "XXX.XXX", "XX.XXXX"] # 有、无功需量、零线电流、总视在功率
]
# 提取匹配数据
data_matched = re.match(r, data_str)
result = []
if data_matched:
data_matched = data_matched.groups()
# 将tuple类型转化为list，因为需要修改数据的值
data_matched = list(data_matched)
# 对数据项进行分组、反序处理
for i in range((len(data_matched))):
data_matched[i] = meter.splitByLen(data_matched[i].split(),
bl[i])
for j in range(len(data_matched[i])):
data_matched[i][j].reverse()
# 针对数据项进行数据格式处理
for i in range(len(data_matched)):
if data_matched[i]:
for j in range(len(data_matched[i])):
data_matched[i][j] = meter.id.format(
"".join(data_matched[i][j]), df[i][j])
result = []
for i in data_matched:
result.extend(i)
else:
result = ["返回数据区为空"]
return result
def eng_rx_data(self, data):
"data: 表示返回帧数据域（已做减33H处理）, 格式为字符串数组"
import meter
# 数据标识和每一项电能量数据均占用4字节，按4字节对每一项数据进行分组并反向
all_items = [item[::-1] for item in meter.splitByLen(data, [4] * 9)]
result = []
for item in all_items[1::]:
result.append(self.format("".join(item), "XXXXXX.XX"))
return result
def dmd_rx_data(self, data):
"data: 返回帧数据已做减33H处理, 格式为字符串数组"
import meter
# 数据标识和每一项需量数据均占用8字节，按8字节对每一项数据进行分组并反向
all_items = [item[::-1] for item in meter.splitByLen(data, [4] + [8] * 9)]
result = []
for item in all_items[1::]:
result.append(self.format("".join(item[5:] + item[:5]), "XX.XXXX,YYMMDDhhmm"))
return result
def eng_rx_data(self, data):
"data: 表示返回帧数据域（已做减33H处理）, 格式为字符串数组"
import meter
# 数据标识和每一项电能量数据均占用4字节，按4字节对每一项数据进行分组并反向
all_items = [item[::-1] for item in meter.splitByLen(data, [4] * 9)]
result = []
for item in all_items[1::]:
result.append(self.format("".join(item), "XXXXXX.XX"))
return result
def get_slice_name(self, id, slice_name):
# 需要使用meter模块的splitByLen函数，为防止互相引用导致错误，在此处引用
import meter
# 将数据标识进行拆分为4个部分DI3 DI2 DI1 DI0
split_id = [i.upper() for i in meter.splitByLen(id, [2, 2, 2, 2])]
# 根据DI3 DI2 DI1 DI0的值从slice_name中获取具体的表示名称数组
result = []
for index in range(len(split_id)):
result.append(slice_name[index][split_id[index]])
return result
def reverse_setting_data(self, setting):
"""setting-为命令的设置参数部分
如命令为:set-cycle-display xxxxxxxx xxxxxxxx,nn，则
setting的值为xxxxxxxx,nn
"""
import meter
reverse_list = []
set_list = setting.split(',')
for set in set_list:
reverse_list.extend(
meter.splitByLen(set, [2] * (len(set) // 2))[::-1])
return reverse_list
def get_slice_name(self, id, slice_name):
# 需要使用meter模块的splitByLen函数，为防止互相引用导致错误，在此处引用
import meter
# 将数据标识进行拆分为4个部分DI3 DI2 DI1 DI0
split_id = [i.upper() for i in meter.splitByLen(id, [2, 2, 2, 2])]
# 根据DI3 DI2 DI1 DI0的值从slice_name中获取具体的表示名称数组
result = []
for index in range(len(split_id)):
result.append(slice_name[index][split_id[index]])
return result
def reverse_setting_data(self, setting):
"""setting-为命令的设置参数部分
如命令为:set-cycle-display xxxxxxxx xxxxxxxx,nn，则
setting的值为xxxxxxxx,nn
"""
import meter
reverse_list = []
set_list = setting.split(",")
for set in set_list:
reverse_list.extend(meter.splitByLen(set, [2] * (len(set) // 2))[::-1])
return reverse_list
def ldcurve_rx_data(self, data):
"data: 表示返回帧数据域（已做减33H处理）, 格式为字符串数组"
import meter
# 将data转为字符串，方便使用正则表达式进行提取
data_str = " ".join(data)
# 匹配组提取所需的数据信息
r = r".*A0 A0 [\da-fA-F]{2} (\d{2} \d{2} \d{2} \d{2} \d{2} )(.*)AA (.*)AA (.*)AA (.*)AA (.*)AA (.*)AA [\da-fA-F]{2} E5"
# 每个数据项占用字节数列表，按照负荷曲线数据项的顺序配置，第一项为数据标识
bl = [
[5], # 存储时刻
[2, 2, 2, 3, 3, 3, 2], # 电压、电流、频率
[3] * 8, # 有、无功功率
[2] * 4, # 功率因数
[4] * 4, # 有、无功总电能
[4] * 4, # 四象限无功总电能
[3] * 4, # 有、无功需量、零线电流、总视在功率
]
# 每个数据项的数据格式列表
df = [
["YYMMDDhhmm"], # 存储时刻
["XXX.X", "XXX.X", "XXX.X", "XXX.XXX", "XXX.XXX", "XXX.XXX", "XX.XX"], # 电压、电流、频率
["XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX", "XX.XXXX"], # 有、无功功率
["X.XXX", "X.XXX", "X.XXX", "X.XXX"], # 功率因数
["XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX"], # 有、无功总电能
["XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX", "XXXXXX.XX"], # 四象限无功总电能
["XX.XXXX", "XX.XXXX", "XXX.XXX", "XX.XXXX"], # 有、无功需量、零线电流、总视在功率
]
# 提取匹配数据
data_matched = re.match(r, data_str)
result = []
if data_matched:
data_matched = data_matched.groups()
# 将tuple类型转化为list，因为需要修改数据的值
data_matched = list(data_matched)
# 对数据项进行分组、反序处理
for i in range((len(data_matched))):
data_matched[i] = meter.splitByLen(data_matched[i].split(), bl[i])
for j in range(len(data_matched[i])):
data_matched[i][j].reverse()
# 针对数据项进行数据格式处理
for i in range(len(data_matched)):
if data_matched[i]:
for j in range(len(data_matched[i])):
data_matched[i][j] = meter.id.format("".join(data_matched[i][j]), df[i][j])
result = []
for i in data_matched:
result.extend(i)
else:
result = ["返回数据区为空"]
return result
def dmd_rx_data(self, data):
"data: 返回帧数据已做减33H处理, 格式为字符串数组"
import meter
# 数据标识和每一项需量数据均占用8字节，按8字节对每一项数据进行分组并反向
all_items = [
item[::-1] for item in meter.splitByLen(data, [4] + [8] * 9)
]
result = []
for item in all_items[1::]:
result.append(
self.format("".join(item[5:] + item[:5]),
"XX.XXXX,YYMMDDhhmm"))
return result
