runningActual.append(output)
runningActualHigh = [x for x in runningActual if x > 0]
avgActual = sum(runningActualHigh) / (1.0 * len(runningActualHigh))
netLoadingTime = 0
for i in range(numTrainingSamples):
netLoadingTime += teslaTimestamps["load" + str(i)]
netExecuteTime = 0
runningMAE = 0.0
runningRMSE = 0.0
for i in range(numExecuteSamples):
netExecuteTime += teslaTimestamps["test" + str(i)]
runningMAE += teslaTimestamps["delta" + str(i)]
runningRMSE += pow(float(teslaTimestamps["delta" + str(i)]), 2)
runningMAE = runningMAE / (1.0 * avgActual * numExecuteSamples)
runningRMSE = pow((runningRMSE / numExecuteSamples), 0.5) / avgActual
print("Loading time (tot): " + str(netLoadingTime) + " seconds")
print("Loading time (avg): " + str(netLoadingTime /
(1.0 * numTrainingSamples)) + " seconds")
print("Training time: " + str(teslaTimestamps["train"]) + " seconds")
print("Execute time (tot): " + str(netExecuteTime) + " seconds")
print("Execute time (avg): " + str(netLoadingTime /
(1.0 * numExecuteSamples)) + " seconds")
print("MAE: " + str(runningMAE))
print("RMSE: " + str(runningRMSE))
print("Correlation Values: " + str(algorithmTest.getCorrelationValues()))
teslaTimestamps["delta" + str(executeSample)] = abs(output - theor);
runningActual.append(output);
runningActualHigh = [x for x in runningActual if x > 0];
avgActual = sum(runningActualHigh)/(1.0*len(runningActualHigh));
netLoadingTime = 0;
for i in range(numTrainingSamples):
netLoadingTime += teslaTimestamps["load" + str(i)];
netExecuteTime = 0;
runningMAE = 0.0;
runningRMSE = 0.0;
for i in range(numExecuteSamples):
netExecuteTime += teslaTimestamps["test" + str(i)];
runningMAE += teslaTimestamps["delta" + str(i)];
runningRMSE += pow(float(teslaTimestamps["delta" + str(i)]),2);
runningMAE = runningMAE/(1.0*avgActual*numExecuteSamples);
runningRMSE = pow((runningRMSE/numExecuteSamples),0.5)/avgActual;
print("Loading time (tot): " + str(netLoadingTime) + " seconds");
print("Loading time (avg): " + str(netLoadingTime/(1.0*numTrainingSamples)) + " seconds");
print("Training time: " + str(teslaTimestamps["train"]) + " seconds");
print("Execute time (tot): " + str(netExecuteTime) + " seconds");
print("Execute time (avg): " + str(netLoadingTime/(1.0*numExecuteSamples)) + " seconds");
print("MAE: " + str(runningMAE));
print("RMSE: " + str(runningRMSE));
print("Correlation Values: " + str(algorithmTest.getCorrelationValues()));
