def algo1Handler():
if request.method == 'POST':
f = request.files['datafile']
f.save(secure_filename(f.filename))
arima(f.filename)
return send_file("sent.xlsx", as_attachment=True)
def arguments_convey(self):
# print("hello")
self.circle = self.select_circle.currentText()
self.sensor_list = []
for item in self.checkBox_list:
if item.isChecked():
self.sensor_list.append(int(
re.findall(r"\d+", item.text())[0]))
# print(self.circle)
# print(self.sensor_list)
if (self.sensor_list == []):
self.error_output2.clear()
self.output_widget2.clear()
self.show_message2("请先选择传感器")
else:
self.error_output2.clear()
self.output_widget2.clear()
self.show_message2("predicting...")
ari = arima.arima()
output, error, predict, available = ari.predict(
self.sensor_list, int(self.circle[-1]), self.path)
ari.draw_image(self.name, available, predict, int(self.circle[-1]))
self.output_widget2.clear()
self.show_message2(output)
self.show_error2(error)
self.output_figure2.setPixmap(QPixmap("./result_img/arima.png"))
def arimaTemp(filename):
processTemp()
predictions = []
r = pr.R(RCMD="C:\\Program Files\\R\\R-3.1.2\\bin\\R", use_numpy=True, use_pandas=True)
datetimes = np.arange('2008-07-01 00:00:00','2008-07-08 00:00:00',dtype='datetime64[h]')
for j in range(1,12):
data = pd.read_csv('../data/outputs/temp_history_processed_station_%s.csv'%j, parse_dates='datetime')
subts = data["value"]
print 'Predictions for zone %s'%j
results = arima(subts,r)
results = pd.DataFrame(results, columns=['value'])
results['datetime'] = datetimes
results['station_id'] = j
predictions.append(results)
concatPredictions = pd.concat(predictions)
concatPredictions.to_csv(filename, index=False, date_format='%Y-%m-%d %H:%M:%S', mode='a')
def predict(self, algorithm, params, data, time):
alg_name = algorithm.lower()
if alg_name == 'arima':
arima_model = arima(params)
arima_model.fit(data)
result = arima_model.predict(time)
return result
if alg_name == 'prophet':
prophet_model = Prophet(params)
prophet_model.fit(data)
result = prophet_model.predict(time)
print(result)
return result
def arguments_convey(self):
self.circle = self.select_circle.currentText()
self.sensor_list = []
for item in self.checkBox_list:
if item.isChecked():
self.sensor_list.append(int(item.text()[-2:]))
# print(self.sensor_list)
self.error_output.clear()
self.output_widget.clear()
self.show_message("predicting...")
ari = arima.arima()
output, error = ari.predict(self.sensor_list, int(self.circle[-1]),
self.path)
self.output_widget.clear()
self.show_message(output)
self.show_error(error)