stefan
/
NLMSvariants
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

cleanup

This commit is contained in:
Friese 2018-05-14 19:31:50 +02:00
parent 89c7f9f2ce
commit 7a05d71d62
1 changed files with 1 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
bin/NLMSvariants.c
View File

@ -31,7 +31,6 @@ enum fileSuffix_t{ // used in conjunction with mkFileName()
DIFFERENTIAL_PREDECESSOR DIFFERENTIAL_PREDECESSOR
}; };
//double x[] = { 0.0 };
double xSamples[NUMBER_OF_SAMPLES] = { 0.0 }; double xSamples[NUMBER_OF_SAMPLES] = { 0.0 };
/* *svg graph building* */ /* *svg graph building* */
@ -158,12 +157,9 @@ void localMean(double weights[WINDOWSIZE][NUMBER_OF_SAMPLES]) {
double xActual = 0.0; double xActual = 0.0;
for (xCount = 1; xCount < NUMBER_OF_SAMPLES; xCount++) { // first value will not get predicted for (xCount = 1; xCount < NUMBER_OF_SAMPLES; xCount++) { // first value will not get predicted
//double xPartArray[1000]; //includes all values at the size of runtime var
//int _sourceIndex = (xCount > WINDOWSIZE) ? xCount - WINDOWSIZE : xCount;
int _arrayLength = ( xCount > WINDOWSIZE ) ? WINDOWSIZE + 1 : xCount; int _arrayLength = ( xCount > WINDOWSIZE ) ? WINDOWSIZE + 1 : xCount;
//printf("xCount:%d, length:%d\n", xCount, _arrayLength);
xMean = (xCount > 0) ? windowXMean(_arrayLength, xCount) : 0; xMean = (xCount > 0) ? windowXMean(_arrayLength, xCount) : 0;
// printf("WINDOWSIZE:%f\n", windowXMean(_arrayLength, xCount));
xPredicted = 0.0; xPredicted = 0.0;
xActual = xSamples[xCount + 1]; xActual = xSamples[xCount + 1];
// weightedSum += _x[ xCount-1 ] * w[xCount][0]; // weightedSum += _x[ xCount-1 ] * w[xCount][0];
@ -181,26 +177,19 @@ void localMean(double weights[WINDOWSIZE][NUMBER_OF_SAMPLES]) {
xSquared = 0.0; xSquared = 0.0;
for (i = 1; i < _arrayLength; i++) { //get xSquared for (i = 1; i < _arrayLength; i++) { //get xSquared
xSquared += pow(xSamples[xCount - i] - xMean, 2); xSquared += pow(xSamples[xCount - i] - xMean, 2);
// printf("xSquared:%f\n", xSquared);
} }
if (xSquared == 0.0) { // Otherwise returns Pred: -1.#IND00 in some occassions if (xSquared == 0.0) { // Otherwise returns Pred: -1.#IND00 in some occassions
xSquared = 1.0; xSquared = 1.0;
} }
//printf("%f\n", xSquared);
for (i = 1; i < _arrayLength; i++) { //update weights for (i = 1; i < _arrayLength; i++) { //update weights
local_weights[i][xCount+1] = local_weights[i][xCount] + learnrate * xError[xCount] * ((xSamples[xCount - i] - xMean) / xSquared); local_weights[i][xCount+1] = local_weights[i][xCount] + learnrate * xError[xCount] * ((xSamples[xCount - i] - xMean) / xSquared);
// printf("NEU::%lf\n", local_weights[i][xCount]);
} }
fprintf(fp4, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]); fprintf(fp4, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]);
} }
// int xErrorLength = sizeof(xError) / sizeof(xError[0]);
// printf("vor:%d", xErrorLength);
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[] double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
//printf("%lf", xErrorPtr[499]);
double xErrorLength = *xErrorPtr; // Watch popNAN()! double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0; xErrorPtr[0] = 0.0;
printf("Xerrorl:%lf", xErrorLength); printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength; double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength;
double deviation = 0.0; double deviation = 0.0;