def createStackBarPlot(self,predictDate,payment) :
loadedModel = joblib.load(self.modelName)
inputDataGetter = InputDataGetter
inputData = inputDataGetter.getInputData()
predictor = Predictor(inputData)
predictData = predictor.executePrediction(loadedModel)
predictData = predictData.loc[predictDate]
# 전기요금 계산 필드 추가
elecFeeCalculator = ElecFeeCalculator(predictData)
# period 0 : 시간 당 전기요금 계산
# contractElec : 시간 당 전기요금이기 때문에 입력 필요 x->0으로 입력
finalData = elecFeeCalculator.calElecFee(0,payment,0)
finalData = calculateGasFee(finalData)
# print(finalData)
graph = [
go.Bar(x=finalData.index,y=finalData['cElec'],name='CCHP 발전 전력 사용량'),
go.Bar(x=finalData.index,y=finalData['kElec'],name='한전 전력 사용량'),
go.Layout(
colorway=['#5E0DAC','#2dce89'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': 'CCHP 스케쥴링', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="예측 전력 사용량 (kwh)",
tickformat = ".0f"
),
barmode='stack'
),
go.Scatter(x=finalData.index, y=finalData['elecFee'], name='한국 전력 사용 요금',mode='lines+markers',marker=dict(
color='#2dce89',
size=7)
),
go.Scatter(x=finalData.index, y=finalData['gasFee'], name='CCHP 발전 사용 요금',mode='lines+markers',marker=dict(
color='#5E0DAC',
size=7)),
go.Layout(
colorway=['#2dce89', '#5E0DAC'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': '전력 사용 요금 비교', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="전력 사용 요금 (원)",
tickformat = ".0f"
)
)
]
graphJSON = json.dumps(graph, cls=plotly.utils.PlotlyJSONEncoder)
# print("graphJSON : " + graphJSON)
return graphJSON
def createSchLinePlot(self,predictDate) :
loadedModel = joblib.load(self.modelName)
inputDataGetter = InputDataGetter
inputData = inputDataGetter.getInputData().loc[predictDate]
predictor = Predictor(inputData)
predictData = predictor.executePrediction(loadedModel)
# predictData = predictData.loc[predictDate]
newData = inputData
newData['consumption'] = predictData['consumption']
# print(predictData)
# print(inputData)
feature = ['consumption','temperature','humidity','windSpeed']
newData = newData[feature].astype(float)
graph = [
go.Scatter(x=newData.index,y=newData['consumption'],name='예측 전력 사용량',mode='lines+markers',marker=dict(
color='#2dce89',
size=4
)),
go.Layout(
colorway=['#2dce89'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': '예측 전력 사용량', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="예측 전력 사용량 (kwh)",
tickformat = ".0f"
)
),
go.Scatter(x=newData.index,y=newData['temperature'],name='기온', mode='lines+markers',marker=dict(
color='#5E0DAC',
size=4
)),
go.Layout(
colorway=['#5E0DAC'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': '기온', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="기온 (℃)",
tickformat = ".0f"
)
),
go.Scatter(x=newData.index,y=newData['humidity'],name='습도',mode='lines+markers',marker=dict(
color='#2dce89',
size=4
)),
go.Layout(
colorway=['#2dce89'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': '습도', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="습도 %",
tickformat = ".0f"
)
),
go.Scatter(x=newData.index,y=newData['windSpeed'],name='풍속',mode='lines+markers',marker=dict(
color='#5E0DAC',
size=4
)),
go.Layout(
colorway=['#5E0DAC'],
template='plotly_dark',
paper_bgcolor='rgba(0, 0, 0, 0)',
plot_bgcolor='rgba(0, 0, 0, 0)',
# margin={'autoexpand' : True},
# height=100,
hovermode='x',
# autosize=True,
title={'text': '풍속', 'font': {'color': 'white'}, 'x': 0.5},
xaxis=dict(
rangeselector=dict(
buttons=list([
dict(count=1,
label="1m",
step="month",
stepmode="backward"),
dict(count=1,
label="1y",
step="year",
stepmode="backward"),
dict(step="all")
]),
bgcolor='rgba(0,0,0,0)',
activecolor = 'rgba(0,0,0,1)'
),
rangeslider=dict(
visible=True
),
type="date"
),
yaxis=dict(
title="풍속 (M/s)",
tickformat = ".0f"
)
)
]
graphJSON = json.dumps(graph, cls=plotly.utils.PlotlyJSONEncoder)
# print("graphJSON : " + graphJSON)
return graphJSON
def addData():
today = datetime.datetime.now() - datetime.timedelta(hours=1)
# weekday
weekday = today.weekday()
# isHoliday : weekday가 주말이면 1
isHoliday = 0
if weekday == 5 or weekday == 6:
isHoliday = 1
# 초단기 실황 : api 제공시간 - 정각 + 40분
base_date = str(today.year) + str(today.month).zfill(2) + str(
today.day).zfill(2)
# base_time = str(today.hour).zfill(2) + '00'
base_time = str(today.hour).zfill(2) + '00'
# date
date = datetime.datetime.strptime(base_date + base_time, '%Y%m%d%H%M')
# get weather data
serviceKey = "52s6pZxbOiLmg7H76y%2BN1Rs2tXn4ru798V6iWXFOFWzwKDzqkzuVuxdhol%2FuBCEYc9IOUIKfeJBn2XcEzKXZbg%3D%3D"
url = 'http://apis.data.go.kr/1360000/VilageFcstInfoService/getUltraSrtNcst'
queryParams = '?ServiceKey=' + serviceKey + '&pageNo=1&numOfRows=50000&dataType=JSON&base_date=' + base_date + '&base_time=' + base_time + '&nx=62&ny=126'
response = requests.get(url + queryParams)
html = response.text
data = json.loads(html)
tempData = data['response']['body']['items']['item']
for i in range(0, len(tempData)):
item = tempData[i]
category = item['category']
# temperature
if category == 'T1H':
temperature = item['obsrValue']
# humidity
elif category == 'REH':
humidity = item['obsrValue']
# windSpeed
elif category == 'WSD':
windSpeed = item['obsrValue']
# set isHoliday
serviceKey = "52s6pZxbOiLmg7H76y%2BN1Rs2tXn4ru798V6iWXFOFWzwKDzqkzuVuxdhol%2FuBCEYc9IOUIKfeJBn2XcEzKXZbg%3D%3D"
url = 'http://apis.data.go.kr/B090041/openapi/service/SpcdeInfoService/getRestDeInfo'
holidayList = []
queryParams = '?ServiceKey=' + serviceKey + '&pageNo=1&numOfRows=100&solYear=' + str(
today.year) + '&solMonth=' + str(today.month).zfill(2)
response = requests.get(url + queryParams)
html = response.text
soup = BeautifulSoup(html, 'html.parser')
holiday = soup.find_all('locdate')
for i in range(0, len(holiday)):
holidayStr = holiday[i].text
year = holidayStr[0:4]
month = holidayStr[4:6]
day = holidayStr[6:8]
holidayList.append(year + '-' + month + '-' + day)
for i in range(0, len(holidayList)):
dateStr = str(today.year) + '-' + str(
today.month).zfill(0) + '-' + str(today.day).zfill(0)
if dateStr == holidayList[i]:
isHoliday = 1
# change type
temperature = float(temperature)
humidity = float(humidity)
windSpeed = float(windSpeed)
# prediction
modelName = 'sejong_power_consumption_model2.pkl'
loadedModel = joblib.load(modelName)
month = date.month
hour = date.hour
dataDict = {"temperature": [temperature], "humidity": [humidity], "windSpeed": [windSpeed], \
"weekday" : [weekday], "isHoliday" : [isHoliday], "date" : [date], "month" : [month], \
"hour" : [hour]}
dataDf = pd.DataFrame(dataDict).set_index('date')
predictor = Predictor(dataDf)
predictData = predictor.executePrediction(loadedModel)
dataDf['consumption'] = predictData['consumption']
consumption = dataDf.loc[date]['consumption']
dataVO = DataVO(date, consumption, temperature, humidity, windSpeed,
weekday, isHoliday)
connector = DBConnector()
dataGetter = DataGetter(connector)
# data type: dataFrame
dataGetter.insertData(dataVO)
