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updated

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gurkenhabicht 2018-05-23 11:17:31 +02:00
parent 9a888d99df
commit 89db53dc63
1 changed files with 16 additions and 12 deletions
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src/ansi_c_implementation/NLMSvariants.c
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@ -11,7 +11,6 @@ Created by Stefan Friese on 26.04.2018
#include <time.h> #include <time.h>
#include <stdlib.h> #include <stdlib.h>
#include <string.h> #include <string.h>
//#include <float.h> // DBL_MAX
#include "nlms_types.h" // added types #include "nlms_types.h" // added types
#define RGB_COLOR 255 #define RGB_COLOR 255
@ -193,8 +192,8 @@ Variant (1/3), substract local mean.
*/ */
void localMean ( mldata_t *mlData, point_t points[] ) { void localMean ( mldata_t *mlData, point_t points[] ) {
double *localWeights = (double *) malloc ( sizeof(double) * mlData->windowSize + 1); 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;
char fileName[50]; char fileName[50];
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n) double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n)
memset(xError, 0.0, mlData->samplesCount); // Initialize xError-array with Zero memset(xError, 0.0, mlData->samplesCount); // Initialize xError-array with Zero
@ -213,7 +212,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double xPredicted = 0.0; double xPredicted = 0.0;
double xActual = 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 unsigned _arrayLength = ( xCount > mlData->windowSize ) ? mlData->windowSize + 1 : xCount; // Ensures corect length at start
xMean = (xCount > 0) ? windowXMean(_arrayLength, xCount) : 0; xMean = (xCount > 0) ? windowXMean(_arrayLength, xCount) : 0;
xPredicted = 0.0; xPredicted = 0.0;
@ -281,9 +280,11 @@ substract direct predecessor
*/ */
void directPredecessor( mldata_t *mlData, point_t points[]) { void directPredecessor( mldata_t *mlData, point_t points[]) {
double *localWeights = ( double * ) malloc ( sizeof(double) * mlData->windowSize + 1 ); double *localWeights = ( double * ) malloc ( sizeof(double) * mlData->windowSize + 1 );
memcpy ( localWeights, mlData->weights, mlData->windowSize ); localWeights = mlData->weights;
char fileName[512]; char fileName[512];
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1 ); double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1 );
memset(xError, 0.0, mlData->samplesCount);
unsigned xCount = 0, i; unsigned xCount = 0, i;
double xActual = 0.0; double xActual = 0.0;
double xPredicted = 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); mkFileName ( fileName, sizeof(fileName), USED_WEIGHTS_DIR_PRED);
FILE *fp9 = fopen(fileName, "w"); 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; unsigned _arrayLength = ( xCount > mlData->windowSize ) ? mlData->windowSize + 1 : xCount;
xPredicted = 0.0; xPredicted = 0.0;
xActual = xSamples[xCount]; xActual = xSamples[xCount];
@ -363,9 +364,12 @@ differential predecessor.
*/ */
void differentialPredecessor ( mldata_t *mlData, point_t points[] ) { void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
double *localWeights = (double *) malloc ( sizeof(double) * mlData->windowSize + 1 ); double *localWeights = (double *) malloc ( sizeof(double) * mlData->windowSize + 1 );
memcpy( localWeights, mlData->weights, mlData->windowSize ); localWeights = mlData->weights;
char fileName[512]; char fileName[512];
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1);
memset(xError, 0.0, mlData->samplesCount);
unsigned xCount = 0, i; unsigned xCount = 0, i;
double xPredicted = 0.0; double xPredicted = 0.0;
double xActual = 0.0; double xActual = 0.0;
@ -377,7 +381,7 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
mkFileName ( fileName, sizeof(fileName), USED_WEIGHTS_DIFF_PRED); mkFileName ( fileName, sizeof(fileName), USED_WEIGHTS_DIFF_PRED);
FILE *fp9 = fopen(fileName, "w"); 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; unsigned _arrayLength = (xCount > mlData->windowSize) ? mlData->windowSize + 1 : xCount;
xPredicted = 0.0; xPredicted = 0.0;
@ -539,22 +543,22 @@ void bufferLogger(char *buffer, point_t points[]) {
unsigned i; unsigned i;
char _buffer[512] = ""; // TODO: resize buffer and _buffer so greater sampleval can be choosen char _buffer[512] = ""; // TODO: resize buffer and _buffer so greater sampleval can be choosen
// char *_buffer = (char *) malloc ( sizeof(char) * 512 + 1); // 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]); sprintf(_buffer, "L %f %f\n", points[i].xVal[0], points[i].yVal[0]);
strcat(buffer, _buffer); strcat(buffer, _buffer);
} }
strcat(buffer, "\" fill=\"none\" id=\"svg_1\" stroke=\"black\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n"); 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]); sprintf(_buffer, "L %f %f\n", points[i].xVal[1], points[i].yVal[1]);
strcat(buffer, _buffer); strcat(buffer, _buffer);
} }
strcat(buffer, "\" fill=\"none\" id=\"svg_2\" stroke=\"green\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n"); 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]); sprintf(_buffer, "L %f %f\n", points[i].xVal[2], points[i].yVal[2]);
strcat(buffer, _buffer); strcat(buffer, _buffer);
} }
strcat(buffer, "\" fill=\"none\" id=\"svg_3\" stroke=\"blue\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n"); 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]); sprintf(_buffer, "L %f %f\n", points[i].xVal[3], points[i].yVal[3]);
strcat(buffer, _buffer); strcat(buffer, _buffer);
} }