oven02Max = 0.0;
refrigeratorError = 0.0;
refrigeratorNumObs = 0.0;
refrigeratorMin = 0.0;
refrigeratorMax = 0.0;
stoveError = 0.0;
stoveNumObs = 0.0;
stoveMin = 0.0;
stoveMax = 0.0;
for i in range(0,10000):
kitchOut2InputObs = float(kitchOut2Trace.readline().split()[1]);
kitchOut2OutputObs = float(kitchOut2OutputTrace.readline().split()[1]);
kitchOut2ActualObs = (kitchOut2Trainer.test([kitchOut2InputObs]));
kitchOut2ObsError = (kitchOut2ActualObs - kitchOut2OutputObs);
## if (kitchOut2ObsError > 0.5):
## print((kitchOut2ActualObs, kitchOut2OutputObs));
kitchOut2Error += abs(kitchOut2ObsError);
kitchOut2NumObs += 1;
kitchOut2Min = kitchOut2ObsError \
if (kitchOut2ObsError < kitchOut2Min) \
else kitchOut2Min;
kitchOut2Max = kitchOut2ObsError \
if (kitchOut2ObsError > kitchOut2Max) \
else kitchOut2Max;
## print(kitchOut2ActualObs, kitchOut2OutputObs);
kitchOut3InputObs = float(kitchOut3Trace.readline().split()[1]);
kitchOut3OutputObs = float(kitchOut3OutputTrace.readline().split()[1]);
class PecanStreetCE():
def __init__(self, funcOrder=3, numOfInputs=2, numHistoryStates=0):
self.inputData = []
self.outputData = []
self.flexCE = Tesla(order=funcOrder, numInputs=(numOfInputs+numHistoryStates));
self.aggregatedError = 0.0;
self.aggregatedCount = 0;
self.errorNumerator = 0.0;
self.errorDenominator = 0;
self.predictedList = [];
self.actualList = [];
self.testSetPredictedList = [];
self.testSetActualList = [];
self.numInputs = numOfInputs;
self.numHistoryStates = numHistoryStates;
def runTesla(self, csvFilepath):
with open(csvFilepath) as csvFile:
reader = csv.reader(csvFile);
i = 0;
for row in reader:
inputList = [];
historyList = [];
outputValue = 0.0;
if (i != 0 and i < self.numHistoryStates):
self.predictedList.append(0.0);
self.actualList.append(float(row[self.numInputs]));
elif (i != 0):
# Append the appropriate number of values from the CSV file to the input list.
for j in range(0,self.numInputs):
inputList.append(float(row[j]));
# Generate a list of history states to append to the inputs
for k in range(0, self.numHistoryStates):
historyList.append(-1-k);
# Append the history state as an additional inputs.
inputList += historyList;
outputValue = float(row[self.numInputs]);
self.inputData.append(inputList);
self.outputData.append(outputValue);
if (i >= self.numHistoryStates and i <= 17500):
self.flexCE.addSingleObservation(inputList,
outputValue);
# Append garbage data to predicted, since this is training.
self.predictedList.append(0.0);
self.actualList.append(outputValue);
elif (i > 17500 and i <= 35000):
predicted = self.flexCE.test(inputList);
if (predicted < 0):
predicted = 0.0;
actual = outputValue;
self.aggregatedError += pow(actual-predicted, 2);
self.aggregatedCount += 1;
# print(str(actual), "\t", str(predicted))
self.errorNumerator += abs((actual-predicted));
self.errorDenominator += 1;
self.predictedList.append(predicted);
self.actualList.append(actual);
self.testSetPredictedList.append(predicted);
self.testSetActualList.append(actual);
elif (i > 35000):
print(str(time.clock()));
break;
if (i == 17500):
print("Training data loaded");
startTime = time.clock()
self.flexCE.train();
elapsedTime = time.clock() - startTime;
print("CE trained, elapsed time:",
str(elapsedTime));
print(str(time.clock()));
i+=1;
##print(refrigeratorTrainer3.numObservations);
##print(refrigeratorTrainer3.coefficientVector[0]);
##print(refrigeratorTrainer4.numObservations);
##print(refrigeratorTrainer4.coefficientVector[0]);
testObs1 = float(refrigeratorTrace.readline().split()[1]);
testObs2 = float(refrigeratorTrace.readline().split()[1]);
testObs3 = float(refrigeratorTrace.readline().split()[1]);
for i in range(0,10001):
testObs4 = float(refrigeratorTrace.readline().split()[1]);
if (testObs4 > 300):
print((testObs4, refrigeratorTrainer1.test([testObs4])));
## print((testObs4, refrigeratorTrainer2.test([testObs3, testObs4])));
## print((testObs4, refrigeratorTrainer3.test([testObs2, testObs3, testObs4])));
## print((testObs4, refrigeratorTrainer4.test([testObs1, testObs2, testObs3, testObs4])));
testObs1 = testObs2;
testObs2 = testObs3;
testObs3 = testObs4;
refrigeratorTrace.close();
refrigeratorOutputTrace.close();
##if (not os.path.isfile(fridgeTraceFile)):
## for i in range(0, 86401):
## (timestamp, entry) = refridgeTrace.readline().split();
oven02Max = 0.0;
refrigeratorError = 0.0;
refrigeratorNumObs = 0.0;
refrigeratorMin = 0.0;
refrigeratorMax = 0.0;
stoveError = 0.0;
stoveNumObs = 0.0;
stoveMin = 0.0;
stoveMax = 0.0;
for i in range(0,10000):
kitchOut2InputObs = float(kitchOut2Trace.readline().split()[1]);
kitchOut2OutputObs = float(kitchOut2OutputTrace.readline().split()[1]);
kitchOut2ActualObs = round(kitchOut2Trainer.test([kitchOut2InputObs]));
kitchOut2ObsError = (kitchOut2ActualObs - kitchOut2OutputObs);
## if (kitchOut2ObsError > 0.5):
## print((kitchOut2ActualObs, kitchOut2OutputObs));
kitchOut2Error += abs(kitchOut2ObsError);
kitchOut2NumObs += 1;
kitchOut2Min = kitchOut2ObsError \
if (kitchOut2ObsError < kitchOut2Min) \
else kitchOut2Min;
kitchOut2Max = kitchOut2ObsError \
if (kitchOut2ObsError > kitchOut2Max) \
else kitchOut2Max;
## print(kitchOut2ActualObs, kitchOut2OutputObs);
kitchOut3InputObs = float(kitchOut3Trace.readline().split()[1]);
kitchOut3OutputObs = float(kitchOut3OutputTrace.readline().split()[1]);
