def getStackInfo(que, i, sta_codes, ah_stas, sta_names):
try:
print('***********正在计算“' + sta_names[i] + '”强度中***********')
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[i])
rs_en = obj.getDataByBAS()[0]
rs_ah = obj.getDataByCLS(ah_sta=ah_stas[i])[0]
# rs_ah=obj.getDataByCLS(ah_sta=ah_stas[i],isEndAhCount=True)[0]
# return
# print(rs_en)
if rs_ah is not False and rs_en is not False:
#确保目录存在
mkdir('./strengths/' + sta_names[i])
write = pd.ExcelWriter(r'./strengths/' + sta_names[i] + '/' +
sta_data_date.split(' ')[0] + '强度数据统计.xlsx')
rs_ah.to_excel(write, '簇累计充放容量数据', index=False)
rs_en.to_excel(write, '堆累计充放电量数据', index=False)
write.save()
print('√√√√√√√√√√√√ data is saved! √√√√√√√√√√√√')
else:
print('data not need to save!')
except:
print(sta_names[i] + '‘s data get meet error!')
traceback.print_exc()
print(que.get())
que.task_done()
def getStackInfo(que, i, sta_codes, ah_stas, sta_names, sta_data_date,
end_data_date):
global need_data
print('***********正在计算“' + sta_names[i] + '”强度中***********')
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[i])
rs_en = obj.getDataByBAS()[0]
# rs_ah=[]
# rs_ah=obj.getDataByCLS(ah_sta=ah_stas[i])[0]
# rs_ah=obj.getDataByCLS(ah_sta=ah_stas[i],isEndAhCount=True)[0]
# if rs_en is not False:
# mkdir('./strengths/'+sta_names[i])
# write=pd.ExcelWriter(r'./strengths/'+sta_names[i]+'/'+sta_data_date.split(' ')[0]+'强度数据统计.xlsx')
# rs_en.to_excel(write,'堆累计充放电量数据',index=False)
# write.save()
# print('√√√√√√√√√√√√ data is saved! √√√√√√√√√√√√')
# print(rs_en)
if rs_en is not False:
# if rs_ah is not False and rs_en is not False and rs_en.ix[0,5]>0:
#确保目录存在
mkdir('./201906_product_files/' + sta_names[i])
write = pd.ExcelWriter(r'./201906_product_files/' + sta_names[i] +
'/' + sta_data_date.split(' ')[0] +
'强度数据统计.xlsx')
# rs_ah.to_excel(write,'簇累计充放容量数据',index=False)
rs_en.to_excel(write, '堆累计充放电量数据', index=False)
write.save()
print('√√√√√√√√√√√√ data is saved! √√√√√√√√√√√√')
else:
print('data not need to save!')
print(que.get())
que.task_done()
def webfile(self, Jizu, start_date, end_date):
'''
keys:
Jizu:机组是系统1或2
start_date:起始时间
end_date:结束时间
return:
data:AGC,电池的联合数据(时标对应的)
time:时标，对应x轴
bat:电池系统1和2的联合数据(时标都存在的)
Agc:Agc数据(没做时标的联合,可能数据更大)
'''
if start_date is None and end_date is None:
print('接口查询必须给定时间和电站')
data = 0
time = 0
elif Jizu is None:
print('请在运行前给出所属机组')
else:
sta_data_date = start_date
end_data_date = end_date
a, b, c, d = self._Dataexist(sta_data_date, end_data_date)
if self.i in d:
A = getAPI.getStaWork(sta_data_date, end_data_date,
self.Aim_codes)
bat, df1, df2 = A.getEMSBat()
if Jizu == 1:
jizu = '01'
Agc = A.getEMSAgc(jizu)
else:
jizu = '02'
Agc = A.getEMSAgc(jizu)
DF = pd.merge(bat,
Agc,
right_index=True,
left_index=True,
how='inner')
time = pd.to_datetime(DF.index, format='%Y-%m-%d %H:%M:%S')
time.columns = ['time']
data = pd.DataFrame(columns=['Agc', 'Pdg', 'Pall', 'Pbat'])
data['Agc'], data['Pdg'], data['Pbat'] = DF[jizu + 'AGC'], DF[
jizu + '机组出力'], DF['01储能'] + DF['02储能']
data['Pall'] = data['Pdg'] + data['Pbat']
data.index = pd.to_datetime(data.index, format=None)
bat.index = pd.to_datetime(bat.index, format=None)
Agc.index = pd.to_datetime(Agc.index, format=None)
elif self.i in c:
print(self.Aim_names_Chinese + '无数据，请尝试换一个电站')
print('经查询：电站' + str(a) + '无数据 \n' + '电站' + str(b) + '有数据')
data = pd.DataFrame()
bat = pd.DataFrame()
Agc = pd.DataFrame()
time = 0
return data, time, bat, Agc
def getStackInfo(i,sta_codes,ah_stas,sta_names):
print('***********正在计算“'+sta_names[i]+'”强度中***********')
obj=getStaWork(sta_data_date, end_data_date,sta_code=sta_codes[i])
rs_en=obj.getDataByBAS()
rs_ah=obj.getDataByCLS(ah_sta=ah_stas[i])
if rs_ah is not False and rs_en is not False and rs_en.ix[0,2]>0:
#确保目录存在
mkdir('./strengths/'+sta_names[i])
write=pd.ExcelWriter(r'./strengths/'+sta_names[i]+'/'+sta_data_date.split(' ')[0]+'强度数据统计.xlsx')
rs_ah.to_excel(write,'簇累计充放容量数据')
rs_en.to_excel(write,'堆累计充放电量数据')
write.save()
print('√√√√√√√√√√√√ data is saved! √√√√√√√√√√√√')
def getStackInfo(i, sta_codes, sta_names, sta_data_date, end_data_date):
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[i])
#6-3-3 3pack sbox=5,ebox=6,sba=2,eba=3,scl=2,ecl=3,sp=2,ep=3
rs = obj.getCellDataByPack()
if len(rs) > 0:
df_rs = pd.DataFrame(rs)
df_rs = pd.concat(
[pd.DataFrame([[sta_data_date, end_data_date]]), df_rs])
df_rs.columns = ['描述', '电压']
mkdir('./BMUQS/')
df_rs.to_excel('./BMUQS/' + sta_data_date.split(' ')[0] +
sta_names[i] + '.xlsx',
index=False)
print('发现如下问题[描述，12s电压]，已存入BMUQS目录下')
else:
print('所选时间段内没有发现任何问题')
def Dataexist(self, start_date, end_date):
Nodata = []
Nodata_loc = []
Ysdata = []
Ysdata_loc = []
for i in range(0, len(self.index)):
Aim_codes = self.sta_codes[self.index[i]]
sta_data_date = start_date
end_data_date = end_date
A = getStaWork(sta_data_date, end_data_date, Aim_codes)
print('开始检查电站：' + self.index_name[i])
Agc1, Agc2 = A.getEMSexist()
if Agc1.empty and Agc2.empty:
Nodata.append(self.index_name[i])
Nodata_loc.append(i)
else:
Ysdata.append(self.index_name[i])
Ysdata_loc.append(i)
return Nodata, Ysdata, Nodata_loc, Ysdata_loc
Created on 2019年5月9日
下一步计划，插入多线程函数，可选模式，以簇或堆或箱或电站进行多线程
@author: 逻辑的使命
'''
from getAPI import getStaWork
import pandas as pd
from mkdir import mkdir
sta_data_date = "2019-04-19 00:00:00"
end_data_date = "2019-04-19 12:00:00"
if __name__ == '__main__':
sta_config = pd.read_excel('./assets/sta_cl_ah_config.xlsx')
sta_codes, sta_names = sta_config['code'], sta_config['name']
sta_i = 1 #云河编号
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[sta_i])
mkdir('./curs_datas/' + sta_names[sta_i])
sbox, ebox = 1, 2
sba, eba = 0, 2
scl, ecl = 0, 3
mode = ['getDateTime', 'getCurs']
rs = obj.getDataByCLS(quickly=False,
sbox=sbox,
ebox=ebox,
sba=sba,
eba=eba,
scl=scl,
ecl=ecl,
mode=mode)
# -*- coding: utf-8 -*-
'''
Created on 2019年5月9日
@author: Administrator
'''
from getAPI import getStaWork
sta_data_date = "2019-02-01 00:00:00"
end_data_date = "2019-04-20 00:00:00"
if __name__ == '__main__':
obj = getStaWork(sta_data_date, end_data_date, sta_code='0005')
rs_curs = obj.getDataByCLS(quickly=False,
sbox=1,
ebox=2,
sba=1,
eba=2,
scl=0,
ecl=2,
mode='getCurs')
rs_curs.columns = ['时间', '2箱2堆1簇', '2箱2堆2簇']
print(rs_curs)
rs_curs.to_csv('电流数据2-2-1/2.csv')
def getStackInfo(que, sta_i, sta_codes, sta_names):
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[sta_i])
mkdir('./temp_datas/' + sta_names[sta_i])
#默认 0 -1
sbox, ebox = 0, -1
sba, eba = 0, -1
scl, ecl = 0, -1
sp, ep = 0, -1
#默认以包，簇，堆
mode = ['']
rs = obj.getCellDataByPack(quickly=False,
sbox=sbox,
ebox=ebox,
sba=sba,
eba=eba,
scl=scl,
ecl=ecl,
sp=sp,
ep=ep,
mode=mode)
# rs=pd.read_excel('D:\\python_works\\ClouPy\works\\API_Class\\temp_datas\\河北宣化电厂储能电站\\2019-05-26.xlsx',sheet_name=0,index_col=0)
# rs=np.array(rs)
# print(rs)
pack_bmu_num = obj.pack_bmu_num
if ebox == -1:
ebox = obj.box_num
if ep == -1:
ep = obj.pack_num
# rs=[[[25.0, 23.0, 2.0, 24.333333333333332], [25.0, 23.0, 1.0, 24.166666666666668], [26.0, 23.0, 1.0, 25.166666666666668], [25.0, 23.0, 1.0, 24.166666666666668], [25.0, 23.0, 1.0, 24.833333333333332], [25.0, 24.0, 1.0, 25.0], [25.0, 23.0, 1.0, 24.666666666666668], [25.0, 23.0, 2.0, 24.666666666666668], [25.0, 23.0, 1.0, 24.666666666666668], [25.0, 23.0, 1.0, 24.666666666666668], [25.0, 23.0, 1.0, 24.666666666666668], [25.0, 23.0, 1.0, 24.833333333333332], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN]], [[26.0, 23.0, 2.0, 24.555555555555557], [26.0, 23.0, 2.0, 24.62962962962963], [25.0, 23.0, 2.0, 24.555555555555557], [25.0, 23.0, 2.0, 24.77777777777778], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN],[np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN], [np.NaN,np.NaN,np.NaN,np.NaN]], [[26.0, 23.0, 2.0, 24.970807875084862], [np.NaN,np.NaN,np.NaN,np.NaN]]]
print([eba, ep, pack_bmu_num])
print(rs)
# obj.cl_num_list=[4,5]
print(obj.cl_num_list)
if len(rs) == len(mode):
write = pd.ExcelWriter("./temp_datas/" + sta_names[sta_i] + '/' +
sta_data_date.split(' ')[0] + ".xlsx")
for i in range(len(rs)):
#对数据格式化处理，便于画图
formatRs, ys, xs, fxs = [], [], [], []
for box in range(sbox + 1, ebox + 1):
boxformatRs = [] #每一箱
Flag_ba = False
if eba == -1:
eba = obj.ba_num_list[box - 1 - sbox]
print('%s-------:' % eba)
Flag_ba = True
for ba in range(sba + 1, eba + 1):
xba = str(ba) + '堆'
A = sum(obj.ba_num_list[0:box - 1 - sbox]
) #(box-sbox-1)*(eba-sba)#已经循环过的堆数
if mode[i] == 'getDTempsByBA':
try:
boxformatRs.append(rs[i][(ba - sba - 1) + A])
fxs.append(str(box) + '箱-' + xba)
except:
boxformatRs.append(
[np.NaN, np.NaN, np.NaN, np.NaN])
if box == sbox + 1:
xs.append(xba)
else:
if ecl == -1:
ecl = obj.cl_num_list[ba - 1 - sba +
A] #(box-1-sbox)*(eba-sba)
print(ecl)
FLag = True
for cl in range(scl + 1, ecl + 1):
xcl = xba + '-' + str(cl)
# B=(A+(ba-sba-1))*(ecl-scl)
B = sum(
obj.cl_num_list[0:ba - 1 - sba +
A]) #(box-1-sbox)*(eba-sba)
if mode[i] == 'getDTempsByCL':
try:
boxformatRs.append(rs[i][(cl - scl - 1) +
B])
fxs.append(str(box) + '箱-' + xcl)
except:
boxformatRs.append(
[np.NaN, np.NaN, np.NaN, np.NaN])
if box == sbox + 1:
xs.append(xcl)
else:
for p in range(sp + 1, ep + 1):
xp = xcl + '-Pack' + str(p)
C = (B + (cl - scl - 1)) * (ep - sp)
if mode[i] == 'getDTempsByPack':
try:
fxs.append(str(box) + '箱-' + xp)
boxformatRs.append(
rs[i][(p - sp - 1) + C])
except:
boxformatRs.append([
np.NaN, np.NaN, np.NaN, np.NaN
])
if box == sbox + 1:
xs.append(xp)
else:
for bmu in range(1, pack_bmu_num + 1):
xb = xp + '-BMU' + str(bmu)
D = (C +
(p - sp - 1)) * pack_bmu_num
if 'getDTempsByBMU' in mode:
try:
fxs.append(
str(box) + '箱-' + xb)
boxformatRs.append(
rs[i][(bmu - 1) + D])
except:
boxformatRs.append([
np.NaN, np.NaN, np.NaN,
np.NaN
])
if box == sbox + 1:
xs.append(xb)
if FLag:
ecl = -1
if Flag_ba:
eba = -1
formatRs.append(boxformatRs)
ys.append('第%s箱' % box)
if len(xs) > 0:
xs_split = xs[0].split('-')
if len(xs_split) == 1:
xlabel = '堆'
txt = '各堆'
elif len(xs_split) == 2:
xlabel = '堆-簇'
txt = '各簇'
elif len(xs_split) == 3:
xlabel = '堆-簇-包'
txt = '各包'
elif len(xs_split) == 4:
xlabel = '堆-簇-包-BMU'
txt = '各BMU'
#保留原格式数据到表格
df_r = pd.DataFrame(rs[i])
print(df_r)
df_r.columns = ['最高温度/℃', '最低温度/℃', '最大温差/℃', '最大平均温度/℃']
print(fxs)
df_r.index = fxs
df_r.to_excel(write, sta_names[sta_i] + txt + "温度数据", index=True)
#画图最高温度与最大温差，最大平均与最低温度不画
maxTs, max_dif_Ts = [], []
for it_box in formatRs:
maxTs.append([it[0] for it in it_box])
max_dif_Ts.append([it[2] for it in it_box])
df = pd.DataFrame(maxTs)
# print(df)
df.index = ys
df.columns = xs
f, (ax1, ax2) = plt.subplots(figsize=(10, 8), nrows=2)
cmap = sns.cubehelix_palette(start=1.5,
rot=3,
gamma=0.8,
as_cmap=True)
try:
sns.heatmap(df,
linewidths=0.05,
ax=ax1,
annot=True,
annot_kws={'weight': 'bold'},
vmax=max(np.max(df)),
vmin=min(np.min(df)),
cmap=cmap)
ax1.set_title(
sta_data_date.split(' ')[0] + sta_names[sta_i] + txt +
'最高温度')
ax1.set_xlabel('')
ax1.set_xticklabels([]) #设置x轴图例为空值
ax1.set_ylabel('箱')
except:
print('图像绘制失败')
df = pd.DataFrame(max_dif_Ts)
df.index = ys
df.columns = xs
try:
sns.heatmap(df,
ax=ax2,
cmap=sns.color_palette("Reds", 7),
cbar=False,
annot=True,
mask=df < max(np.max(df)),
annot_kws={
"weight": "bold",
'size': 25
})
sns.heatmap(df,
linewidths=0.05,
vmax=max(np.max(df)),
vmin=min(np.min(df)),
cmap=sns.color_palette("Reds", 7),
ax=ax2,
annot=True,
mask=df >= max(np.max(df)))
# rainbow为 matplotlib 的colormap名称
ax2.set_title(
sta_data_date.split(' ')[0] + sta_names[sta_i] + txt +
'最大温差')
ax2.set_xlabel(xlabel)
ax2.set_ylabel('箱')
plt.savefig("./temp_datas/" + sta_names[sta_i] + '/' +
sta_data_date.split(' ')[0] + txt +
'最高温度与最大温差.png')
except:
print('图像绘制失败')
write.save()
print(que.get())
que.task_done()
'''
Created on 2019年8月7日
@author: JesisW
'''
from getAPI import getStaWork
import os
import sys
import pandas as pd
if __name__ == '__main__':
# sys.path
# os.chdir(sys.path[0])
sta_config = pd.read_excel('./assets/sta_cl_ah_config.xlsx')
index = [0, 1, 2, 5, 6, 7, 14, 15, 16, 33] #调频电站序号
sta_codes, sta_names = sta_config['code'], sta_config['name']
Aim_codes, Aim_names = sta_codes[0], sta_names[0]
a = getStaWork('2019-04-17 00:00:00', '2019-04-17 01:00:00', Aim_codes)
df1, df2 = a.getEMSAgc()
def getStackInfo(que, i, sta_codes, sta_names, sta_data_date, end_data_date,
mode):
sbox, ebox = 0, -1
sba, eba = 0, -1
scl, ecl = 0, -1
sp, ep = 0, -1
if len(mode) == 1 and 'sta' in mode:
#i就表示电站id
pass
#mode=[id,'box']
elif len(mode) == 2 and 'box' in mode:
sbox, ebox = i, i + 1
i = mode[0]
elif len(mode) == 3 and 'ba' in mode:
sba, eba = i, i + 1
i = mode[0]
sbox, ebox = mode[1], mode[1] + 1
elif len(mode) == 4 and 'cl' in mode:
scl, ecl = i, i + 1
i = mode[0]
sbox, ebox = mode[1], mode[1] + 1
sba, eba = mode[2], mode[2] + 1
elif len(mode) == 5 and 'pack' in mode:
sp, ep = i, i + 1
i = mode[0]
sbox, ebox = mode[1], mode[1] + 1
sba, eba = mode[2], mode[2] + 1
scl, ecl = mode[3], mode[3] + 1
obj = getStaWork(sta_data_date, end_data_date, sta_code=sta_codes[i])
#6-3-3 3pack sbox=5,ebox=6,sba=2,eba=3,scl=2,ecl=3,sp=2,ep=3
rs = obj.getCellDataByPack(sbox=sbox,
ebox=ebox,
sba=sba,
eba=eba,
scl=scl,
ecl=ecl,
sp=sp,
ep=ep)
if len(rs) > 0:
rs = rs[0]
df_rs = pd.DataFrame(rs)
df_rs = pd.concat(
[pd.DataFrame([[sta_data_date, end_data_date]]), df_rs])
df_rs.columns = ['描述', '电压']
mkdir('./BMUQS/太阳宫/')
fileH = './BMUQS/太阳宫/' + sta_data_date.split(' ')[0] + sta_names[i]
if 'sta' in mode:
fileN = fileH + '.xlsx'
elif 'box' in mode:
# fileN=fileH+str(mode[0]+1)+'箱.xlsx'
fileN = fileH + str(sbox + 1) + '箱.xlsx'
elif 'ba' in mode:
# fileN=fileH+str(mode[0]+1)+'箱'+str(mode[1]+1)+'堆.xlsx'
fileN = fileH + str(mode[1] + 1) + '箱' + str(sba + 1) + '堆.xlsx'
elif 'cl' in mode:
# fileN=fileH+str(mode[0]+1)+'箱'+str(mode[1]+1)+'堆'+str(mode[2]+1)+'簇.xlsx'
fileN = fileH + str(mode[1] + 1) + '箱' + str(
mode[2] + 1) + '堆' + str(scl + 1) + '簇.xlsx'
elif 'pack' in mode:
# fileN=fileH+str(mode[0]+1)+'箱'+str(mode[1]+1)+'堆'+str(mode[2]+1)+'簇'+str(mode[3]+1)+'包.xlsx'
fileN = fileH + str(mode[1] + 1) + '箱' + str(
mode[2] + 1) + '堆' + str(mode[3] + 1) + '簇' + str(sp +
1) + '包.xlsx'
else:
print('添加更多模式...')
df_rs.to_excel(fileN, index=False)
print('发现如下问题[描述，12s电压]，已存入BMUQS目录下')
else:
print('所选时间段内没有发现任何问题')
print(que.get())
que.task_done()