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NLMSvariants
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updated cpp src-code and uploading cpp .exe and renamed cs .exe

This commit is contained in:
kbecke23 2018-05-23 11:04:00 +02:00
parent 0233a4c997
commit 9a888d99df
3 changed files with 250 additions and 245 deletions
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bin/CPP_NLMS.exe Normal file
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bin/CS_NMLS_with_UI.exe → bin/CS_NLMS_with_UI.exe
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41
src/cpp_implementation/NLMSvariants.cpp
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@ -11,7 +11,6 @@ Created by Stefan Friese on 26.04.2018
#include <time.h>
#include <stdlib.h>
#include <string.h>
//#include <float.h> // DBL_MAX
#include "nlms_types.h" // added types
#define RGB_COLOR 255
@ -145,7 +144,8 @@ int main( int argc, char **argv ) {
if ((seed != NULL)) {
srand(*seed); // Seed for random number generating
printf("srand is reproducable\n");
} else {
}
else {
srand((unsigned int)time(NULL));
printf("srand depends on time\n"); // Default seed is time(NULL)
}
@ -193,7 +193,7 @@ Variant (1/3), substract local mean.
*/
void localMean(mldata_t *mlData, point_t points[]) {
double *localWeights = (double *)malloc(sizeof(double) * mlData->windowSize + 1);
memcpy ( localWeights, mlData->weights, mlData->windowSize ); // Copy weights so they can be changed locally
localWeights = mlData->weights; // Copy weights so they can be changed locally
char fileName[50];
double *xError = (double *)malloc(sizeof(double) * mlData->samplesCount + 1); // Includes e(n)
@ -213,7 +213,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double xPredicted = 0.0;
double xActual = 0.0;
for ( xCount = 1; xCount < mlData->samplesCount; xCount++ ) { // First value will not get predicted
for (xCount = 1; xCount < mlData->samplesCount-1; xCount++) { // First value will not get predicted
unsigned _arrayLength = (xCount > mlData->windowSize) ? mlData->windowSize + 1 : xCount; // Ensures corect length at start
xMean = (xCount > 0) ? windowXMean(_arrayLength, xCount) : 0;
xPredicted = 0.0;
@ -260,7 +260,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
deviation /= xErrorLength; // Deviation
printf("mean:%lf, devitation:%lf\t\tlocal Mean\n", mean, deviation);
fprintf(fp4, "\nQuadratische Varianz(x_error): %f\nMittelwert:(x_error): %f\n\n", deviation, mean); // Write to logfile
free(localWeights);
//free(localWeights);
free(xErrorPtr);
free(xError);
@ -281,9 +281,10 @@ substract direct predecessor
*/
void directPredecessor(mldata_t *mlData, point_t points[]) {
double *localWeights = (double *)malloc(sizeof(double) * mlData->windowSize + 1);
memcpy ( localWeights, mlData->weights, mlData->windowSize );
localWeights = mlData->weights;
char fileName[512];
double *xError = (double *)malloc(sizeof(double) * mlData->samplesCount + 1);
memset(xError, 0.0, mlData->samplesCount);
unsigned xCount = 0, i;
double xActual = 0.0;
double xPredicted = 0.0;
@ -295,7 +296,7 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
mkFileName(fileName, sizeof(fileName), USED_WEIGHTS_DIR_PRED);
FILE *fp9 = fopen(fileName, "w");
for (xCount = 1; xCount < mlData->samplesCount; xCount++) { // first value will not get predicted
for (xCount = 1; xCount < mlData->samplesCount-1; xCount++) { // first value will not get predicted
unsigned _arrayLength = (xCount > mlData->windowSize) ? mlData->windowSize + 1 : xCount;
xPredicted = 0.0;
xActual = xSamples[xCount];
@ -346,7 +347,7 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
printf("mean:%lf, devitation:%lf\t\tdirect Predecessor\n", mean, deviation);
fprintf(fp3, "\nQuadratische Varianz(x_error): %f\nMittelwert:(x_error): %f\n\n", deviation, mean);
fclose(fp3);
free(localWeights);
//free(localWeights);
free(xErrorPtr);
free(xError);
}
@ -363,9 +364,10 @@ differential predecessor.
*/
void differentialPredecessor(mldata_t *mlData, point_t points[]) {
double *localWeights = (double *)malloc(sizeof(double) * mlData->windowSize + 1);
memcpy( localWeights, mlData->weights, mlData->windowSize );
localWeights = mlData->weights;
char fileName[512];
double *xError = (double *)malloc(sizeof(double) * mlData->samplesCount + 1);
memset(xError, 0.0, mlData->samplesCount);
unsigned xCount = 0, i;
double xPredicted = 0.0;
double xActual = 0.0;
@ -377,7 +379,7 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
mkFileName(fileName, sizeof(fileName), USED_WEIGHTS_DIFF_PRED);
FILE *fp9 = fopen(fileName, "w");
for (xCount = 1; xCount < mlData->samplesCount; xCount++) { // First value will not get predicted
for (xCount = 1; xCount < mlData->samplesCount-1; xCount++) { // First value will not get predicted
unsigned _arrayLength = (xCount > mlData->windowSize) ? mlData->windowSize + 1 : xCount;
xPredicted = 0.0;
@ -428,7 +430,7 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
printf("mean:%lf, devitation:%lf\t\tdifferential Predecessor\n", mean, deviation);
fprintf(fp6, "\nQuadratische Varianz(x_error): %f\nMittelwert:(x_error): %f\n\n", deviation, mean);
fclose(fp6);
free(localWeights);
//free(localWeights);
free(xErrorPtr);
free(xError);
@ -539,22 +541,22 @@ void bufferLogger(char *buffer, point_t points[]) {
unsigned i;
char _buffer[512] = ""; // TODO: resize buffer and _buffer so greater sampleval can be choosen
// char *_buffer = (char *) malloc ( sizeof(char) * 512 + 1);
for (i = 0; i < mlData->samplesCount - 1; i++) { // xActual
for (i = 1; i < mlData->samplesCount - 1; i++) { // xActual
sprintf(_buffer, "L %f %f\n", points[i].xVal[0], points[i].yVal[0]);
strcat(buffer, _buffer);
}
strcat(buffer, "\" fill=\"none\" id=\"svg_1\" stroke=\"black\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n");
for (i = 0; i < mlData->samplesCount - 1; i++) { // xPredicted from localMean
for (i = 1; i < mlData->samplesCount - 1; i++) { // xPredicted from localMean
sprintf(_buffer, "L %f %f\n", points[i].xVal[1], points[i].yVal[1]);
strcat(buffer, _buffer);
}
strcat(buffer, "\" fill=\"none\" id=\"svg_2\" stroke=\"green\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n");
for (i = 0; i <= mlData->samplesCount - 1; i++) { //xPredicted from directPredecessor
for (i = 1; i <= mlData->samplesCount - 1; i++) { //xPredicted from directPredecessor
sprintf(_buffer, "L %f %f\n", points[i].xVal[2], points[i].yVal[2]);
strcat(buffer, _buffer);
}
strcat(buffer, "\" fill=\"none\" id=\"svg_3\" stroke=\"blue\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n");
for (i = 0; i < mlData->samplesCount - 1; i++) { //xPredicted from diff Pred
for (i = 1; i < mlData->samplesCount - 1; i++) { //xPredicted from diff Pred
sprintf(_buffer, "L %f %f\n", points[i].xVal[3], points[i].yVal[3]);
strcat(buffer, _buffer);
}
@ -793,16 +795,19 @@ int ppmColorChannel(FILE* fp, imagePixel_t *image, char *colorChannel, mldata_t
for (i = 0; i < mlData->samplesCount - 1; i++) {
fprintf(fp, "%d\n", image->data[i].green);
}
} else if ( strcmp(colorChannel, "red") == 0 ){
}
else if (strcmp(colorChannel, "red") == 0) {
for (i = 0; i < mlData->samplesCount - 1; i++) {
fprintf(fp, "%d\n", image->data[i].red);
}
} else if ( strcmp(colorChannel, "blue") == 0 ) {
}
else if (strcmp(colorChannel, "blue") == 0) {
for (i = 0; i < mlData->samplesCount - 1; i++) {
fprintf(fp, "%d\n", image->data[i].blue);
}
} else {
}
else {
printf("Colorchannels are red, green and blue. Pick one of them!");
exit(EXIT_FAILURE);
}