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NLMSvariants
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This commit is contained in:
gurkenhabicht 2018-05-24 18:28:28 +02:00
parent 69fcfadd5a
commit 140483465a
2 changed files with 60 additions and 100 deletions
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80
src/ansi_c_implementation/NLMSvariants.c
View File

@ -19,23 +19,22 @@ Created by Stefan Friese on 26.04.2018
typedef SSIZE_T ssize_t;
#endif
double *xSamples; // Input values
mldata_t *mlData = NULL; // Machine learning
double *xSamples; // Input color values from PPM
mldata_t *mlData = NULL; // Machine learning realted data
point_t *points = NULL; // Graphing
/* *graph building* */
/* *Graph building* */
static imagePixel_t * rdPPM(char *fileName); // Read PPM file format
void mkPpmFile(char *fileName, imagePixel_t *image); // Writes PPM file
int ppmColorChannel(FILE* fp, imagePixel_t *image, // Writes colorChannel from PPM file to log file
char *colorChannel, mldata_t *mlData);
void colorSamples(FILE* fp, mldata_t *mlData); // Stores color channel values in xSamples
/* *file handling* */
char * mkFileName ( char* buffer,
/* *File handling* */
char * mkFileName ( char* buffer, // Date+suffix as filename
size_t max_len, int suffixId );
char *fileSuffix ( int id );
char *fileSuffix ( int id ); // Filename ending of logs
char *fileHeader ( int id ); // Header inside the logfiles
//void myLogger ( FILE* fp, point_t points[] );
void bufferLogger(char *buffer, point_t points[]); // Writes points to graph template
void mkSvgGraph ( point_t points[] ); // Parses graph template and calls bufferLogger()
void weightsLogger ( double *weights, int suffix ); // Writes updated weights to a file
@ -142,8 +141,7 @@ int main( int argc, char **argv ) {
char fileName[50]; // Logfiles and their names
mkFileName(fileName, sizeof(fileName), TEST_VALUES);
FILE* fp5 = fopen(fileName, "w");
//xLength =
ppmColorChannel(fp5, image, colorChannel, mlData); // Returns length of ppm input values, debugging
ppmColorChannel(fp5, image, colorChannel, mlData);
FILE* fp6 = fopen(fileName, "r");
colorSamples(fp6, mlData);
@ -161,18 +159,15 @@ int main( int argc, char **argv ) {
printf("[%d] %lf\n", k, mlData->weights[k]);
}
mkFileName(fileName, sizeof(fileName), PURE_WEIGHTS); // Logfile weights
FILE *fp0 = fopen(fileName, "w");
for (k = 0; k < mlData->windowSize; k++) {
fprintf(fp0, "[%d]%lf\n", k, mlData->weights[k]);
fprintf(fp0, "[%d]%lf\n", k, mlData->weights[k]);
}
fclose(fp0);
/* *math magic* */
localMean ( mlData, points );
directPredecessor ( mlData, points);
localMean ( mlData, points ); // math magic functions
directPredecessor ( mlData, points );
differentialPredecessor( mlData, points );
if ( include == 1 ) {
@ -201,8 +196,8 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
localWeights = mlData->weights;
char fileName[50];
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n)
memset(xError, 0.0, mlData->samplesCount); // Initialize xError-array with Zero
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n) = x - xPred
memset(xError, 0.0, mlData->samplesCount); // Initialize xError with zero
unsigned i, xCount = 0; // Runtime vars
mkFileName(fileName, sizeof(fileName), LOCAL_MEAN); // Create Logfile and its filename
@ -218,7 +213,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double xPredicted = 0.0;
double xActual = 0.0;
for ( xCount = 1; xCount < mlData->samplesCount-1; 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;
@ -255,7 +250,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0;
// printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength; // Mean
double deviation = 0.0;
@ -268,10 +263,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
// free(localWeights);
free(xErrorPtr);
free(xError);
fclose(fp4);
//weightsLogger( local_weights, USED_WEIGHTS );
}
/*
@ -295,14 +287,14 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
double xActual = 0.0;
double xPredicted = 0.0;
mkFileName(fileName, sizeof(fileName), DIRECT_PREDECESSOR); // Logfile and name handling
mkFileName(fileName, sizeof(fileName), DIRECT_PREDECESSOR); // Logfile and name handling
FILE *fp3 = fopen(fileName, "w");
fprintf( fp3, fileHeader(DIRECT_PREDECESSOR_HEADER) );
mkFileName ( fileName, sizeof(fileName), USED_WEIGHTS_DIR_PRED);
FILE *fp9 = fopen(fileName, "w");
for (xCount = 1; xCount < mlData->samplesCount-1; 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];
@ -332,15 +324,11 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
points[xCount].yVal[2] = xPredicted;
points[xCount].xVal[5] = xCount;
points[xCount].yVal[5] = xError[xCount];
// weightsLogger( fp, localWeights, USED_WEIGHTS );
}
fclose(fp9);
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0; // Stored length in [0] , won't be used anyway. Bit dirty
//printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength; // Mean
double deviation = 0.0;
@ -413,7 +401,7 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
fprintf( fp9, "%lf\n", localWeights[i] );
}
fprintf(fp6, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]); // Write to logfile
fprintf(fp6, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]); // Write to logfile
points[xCount].xVal[3] = xCount;
points[xCount].yVal[3] = xPredicted;
@ -425,7 +413,6 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0;
// printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength;
double deviation = 0.0;
@ -441,9 +428,6 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
// free(localWeights);
free(xErrorPtr);
free(xError);
// weightsLogger( localWeights, USED_WEIGHTS );
}
/*
@ -514,11 +498,11 @@ char * fileHeader ( int id ) {
weightsLogger
Logs used weights to logfile
Logs used weights to logfile - not used right now
======================================================================================================
*/
void weightsLogger (double *weights, int val ) {
void weightsLogger (double *weights, int val ) {
char fileName[512];
unsigned i;
mkFileName(fileName, sizeof(fileName), val);
@ -547,8 +531,7 @@ formats output of mkSvgGraph -- Please open graphResults.html to see the output-
*/
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);
char _buffer[512] = "";
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);
@ -559,7 +542,7 @@ void bufferLogger(char *buffer, point_t points[]) {
strcat(buffer, _buffer);
}
strcat(buffer, "\" fill=\"none\" id=\"svg_2\" stroke=\"green\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n");
for (i = 1; i <= mlData->samplesCount - 1; i++) { //xPredicted from directPredecessor
for (i = 1; i <= mlData->samplesCount - 2; i++) { //xPredicted from directPredecessor
sprintf(_buffer, "L %f %f\n", points[i].xVal[2], points[i].yVal[2]);
strcat(buffer, _buffer);
}
@ -609,11 +592,10 @@ double *popNAN(double *xError) {
for ( i = 0; i < mlData->samplesCount - 1; i++ ) {
counter ++;
more_tmp = (double *) realloc ( tmp, counter*(sizeof(double) ));
more_tmp = (double *) realloc ( tmp, counter*(sizeof(double) )); // Dynamically sized array, as described in realloc() manual
if ( !isnan(xError[i]) ) {
tmp = more_tmp;
tmp[counter - 1] = xError[i];
//printf("xERROR:%lf\n", tmp[counter - 1]);
tmp[counter - 1] = xError[i];
tmpLength++;
}
}
@ -673,8 +655,7 @@ void mkSvgGraph(point_t points[]) {
exit(EXIT_FAILURE);
}
char buffer[131072] = ""; // Bit dirty
// char *buffer = (char *) malloc ( sizeof(char) * ( ( 3 * mlData->samplesCount ) + fpLength + 1 ) );
char buffer[131072] = ""; // Really really dirty
memset(buffer, '\0', sizeof(buffer));
while (!feof(input)) { // parses file until "firstGraph" has been found
@ -712,7 +693,7 @@ static imagePixel_t *rdPPM(char *fileName) {
perror(fileName);
exit(EXIT_FAILURE);
}
if (buffer[0] != 'P' || buffer[1] != '6') {
if (buffer[0] != 'P' || buffer[1] != '6') { // PPM files start with P6
fprintf(stderr, "No PPM file format\n");
exit(EXIT_FAILURE);
}
@ -721,7 +702,7 @@ static imagePixel_t *rdPPM(char *fileName) {
fprintf(stderr, "malloc() failed");
}
c = getc(fp);
while (c == '#') {
while (c == '#') { // PPM Comments start with #
while (getc(fp) != '\n');
c = getc(fp);
}
@ -747,7 +728,7 @@ static imagePixel_t *rdPPM(char *fileName) {
printf("Changing \"-n\" to %d, image max data size\n", ( image->x * image->y ) );
tmp = (double *) realloc ( xSamples, sizeof(double) * (image->x * image->y) );
xSamples = tmp;
mlData->samplesCount = (image->x * image->y ) / sizeof(double);
mlData->samplesCount = (image->x * image->y );
}
if ( fread( image->data, 3 * image->x, image->y, fp) != image->y) {
fprintf(stderr, "Loading image failed");
@ -832,8 +813,7 @@ void colorSamples ( FILE* fp, mldata_t *mlData ) {
while (!feof(fp)) {
if (fgets(buffer, mlData->samplesCount, fp) != NULL) {
sscanf(buffer, "%lf", &xSamples[i]);
//printf("%lf\n", xSamples[i] );
sscanf(buffer, "%lf", &xSamples[i]);
points[i].yVal[0] = xSamples[i]; // Fills points so actual input values can be seen as a graph
points[i].xVal[0] = i;
++i;
@ -855,7 +835,7 @@ double windowXMean(int _arraylength, int xCount) {
double sum = 0.0;
double *ptr;
for (ptr = &xSamples[xCount - _arraylength]; ptr != &xSamples[xCount]; ptr++) { // Set ptr to beginning of window
for (ptr = &xSamples[xCount - _arraylength]; ptr != &xSamples[xCount]; ptr++) { // Set ptr to beginning of window and iterate through array
sum += *ptr;
}
return sum / (double)_arraylength;
@ -892,7 +872,7 @@ void usage ( char **argv ) {
init_mldata_t
Contains meachine learning data
Init meachine learning data
======================================================================================================
*/

80
src/cpp_implementation/NLMSvariants.cpp
View File

@ -19,23 +19,22 @@ Created by Stefan Friese on 26.04.2018
typedef SSIZE_T ssize_t;
#endif
double *xSamples; // Input values
mldata_t *mlData = NULL; // Machine learning
double *xSamples; // Input color values from PPM
mldata_t *mlData = NULL; // Machine learning realted data
point_t *points = NULL; // Graphing
/* *graph building* */
/* *Graph building* */
static imagePixel_t * rdPPM(char *fileName); // Read PPM file format
void mkPpmFile(char *fileName, imagePixel_t *image); // Writes PPM file
int ppmColorChannel(FILE* fp, imagePixel_t *image, // Writes colorChannel from PPM file to log file
char *colorChannel, mldata_t *mlData);
void colorSamples(FILE* fp, mldata_t *mlData); // Stores color channel values in xSamples
/* *file handling* */
char * mkFileName ( char* buffer,
/* *File handling* */
char * mkFileName ( char* buffer, // Date+suffix as filename
size_t max_len, int suffixId );
char *fileSuffix ( int id );
char *fileSuffix ( int id ); // Filename ending of logs
char *fileHeader ( int id ); // Header inside the logfiles
//void myLogger ( FILE* fp, point_t points[] );
void bufferLogger(char *buffer, point_t points[]); // Writes points to graph template
void mkSvgGraph ( point_t points[] ); // Parses graph template and calls bufferLogger()
void weightsLogger ( double *weights, int suffix ); // Writes updated weights to a file
@ -142,8 +141,7 @@ int main( int argc, char **argv ) {
char fileName[50]; // Logfiles and their names
mkFileName(fileName, sizeof(fileName), TEST_VALUES);
FILE* fp5 = fopen(fileName, "w");
//xLength =
ppmColorChannel(fp5, image, colorChannel, mlData); // Returns length of ppm input values, debugging
ppmColorChannel(fp5, image, colorChannel, mlData);
FILE* fp6 = fopen(fileName, "r");
colorSamples(fp6, mlData);
@ -161,18 +159,15 @@ int main( int argc, char **argv ) {
printf("[%d] %lf\n", k, mlData->weights[k]);
}
mkFileName(fileName, sizeof(fileName), PURE_WEIGHTS); // Logfile weights
FILE *fp0 = fopen(fileName, "w");
for (k = 0; k < mlData->windowSize; k++) {
fprintf(fp0, "[%d]%lf\n", k, mlData->weights[k]);
fprintf(fp0, "[%d]%lf\n", k, mlData->weights[k]);
}
fclose(fp0);
/* *math magic* */
localMean ( mlData, points );
directPredecessor ( mlData, points);
localMean ( mlData, points ); // math magic functions
directPredecessor ( mlData, points );
differentialPredecessor( mlData, points );
if ( include == 1 ) {
@ -201,8 +196,8 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
localWeights = mlData->weights;
char fileName[50];
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n)
memset(xError, 0.0, mlData->samplesCount); // Initialize xError-array with Zero
double *xError = (double *) malloc ( sizeof(double) * mlData->samplesCount + 1); // Includes e(n) = x - xPred
memset(xError, 0.0, mlData->samplesCount); // Initialize xError with zero
unsigned i, xCount = 0; // Runtime vars
mkFileName(fileName, sizeof(fileName), LOCAL_MEAN); // Create Logfile and its filename
@ -218,7 +213,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double xPredicted = 0.0;
double xActual = 0.0;
for ( xCount = 1; xCount < mlData->samplesCount-1; 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;
@ -255,7 +250,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0;
// printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength; // Mean
double deviation = 0.0;
@ -268,10 +263,7 @@ void localMean ( mldata_t *mlData, point_t points[] ) {
// free(localWeights);
free(xErrorPtr);
free(xError);
fclose(fp4);
//weightsLogger( local_weights, USED_WEIGHTS );
}
/*
@ -295,14 +287,14 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
double xActual = 0.0;
double xPredicted = 0.0;
mkFileName(fileName, sizeof(fileName), DIRECT_PREDECESSOR); // Logfile and name handling
mkFileName(fileName, sizeof(fileName), DIRECT_PREDECESSOR); // Logfile and name handling
FILE *fp3 = fopen(fileName, "w");
fprintf( fp3, fileHeader(DIRECT_PREDECESSOR_HEADER) );
mkFileName ( fileName, sizeof(fileName), USED_WEIGHTS_DIR_PRED);
FILE *fp9 = fopen(fileName, "w");
for (xCount = 1; xCount < mlData->samplesCount-1; 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];
@ -332,15 +324,11 @@ void directPredecessor( mldata_t *mlData, point_t points[]) {
points[xCount].yVal[2] = xPredicted;
points[xCount].xVal[5] = xCount;
points[xCount].yVal[5] = xError[xCount];
// weightsLogger( fp, localWeights, USED_WEIGHTS );
}
fclose(fp9);
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0; // Stored length in [0] , won't be used anyway. Bit dirty
//printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength; // Mean
double deviation = 0.0;
@ -413,7 +401,7 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
fprintf( fp9, "%lf\n", localWeights[i] );
}
fprintf(fp6, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]); // Write to logfile
fprintf(fp6, "%d\t%f\t%f\t%f\n", xCount, xPredicted, xActual, xError[xCount]); // Write to logfile
points[xCount].xVal[3] = xCount;
points[xCount].yVal[3] = xPredicted;
@ -425,7 +413,6 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
double *xErrorPtr = popNAN(xError); // delete NAN values from xError[]
double xErrorLength = *xErrorPtr; // Watch popNAN()!
xErrorPtr[0] = 0.0;
// printf("Xerrorl:%lf", xErrorLength);
double mean = sum_array(xErrorPtr, xErrorLength) / xErrorLength;
double deviation = 0.0;
@ -441,9 +428,6 @@ void differentialPredecessor ( mldata_t *mlData, point_t points[] ) {
// free(localWeights);
free(xErrorPtr);
free(xError);
// weightsLogger( localWeights, USED_WEIGHTS );
}
/*
@ -514,11 +498,11 @@ char * fileHeader ( int id ) {
weightsLogger
Logs used weights to logfile
Logs used weights to logfile - not used right now
======================================================================================================
*/
void weightsLogger (double *weights, int val ) {
void weightsLogger (double *weights, int val ) {
char fileName[512];
unsigned i;
mkFileName(fileName, sizeof(fileName), val);
@ -547,8 +531,7 @@ formats output of mkSvgGraph -- Please open graphResults.html to see the output-
*/
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);
char _buffer[512] = "";
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);
@ -559,7 +542,7 @@ void bufferLogger(char *buffer, point_t points[]) {
strcat(buffer, _buffer);
}
strcat(buffer, "\" fill=\"none\" id=\"svg_2\" stroke=\"green\" stroke-width=\"0.4px\"/>\n<path d=\"M0 0\n");
for (i = 1; i <= mlData->samplesCount - 1; i++) { //xPredicted from directPredecessor
for (i = 1; i <= mlData->samplesCount - 2; i++) { //xPredicted from directPredecessor
sprintf(_buffer, "L %f %f\n", points[i].xVal[2], points[i].yVal[2]);
strcat(buffer, _buffer);
}
@ -609,11 +592,10 @@ double *popNAN(double *xError) {
for ( i = 0; i < mlData->samplesCount - 1; i++ ) {
counter ++;
more_tmp = (double *) realloc ( tmp, counter*(sizeof(double) ));
more_tmp = (double *) realloc ( tmp, counter*(sizeof(double) )); // Dynamically sized array, as described in realloc() manual
if ( !isnan(xError[i]) ) {
tmp = more_tmp;
tmp[counter - 1] = xError[i];
//printf("xERROR:%lf\n", tmp[counter - 1]);
tmp[counter - 1] = xError[i];
tmpLength++;
}
}
@ -673,8 +655,7 @@ void mkSvgGraph(point_t points[]) {
exit(EXIT_FAILURE);
}
char buffer[131072] = ""; // Bit dirty
// char *buffer = (char *) malloc ( sizeof(char) * ( ( 3 * mlData->samplesCount ) + fpLength + 1 ) );
char buffer[131072] = ""; // Really really dirty
memset(buffer, '\0', sizeof(buffer));
while (!feof(input)) { // parses file until "firstGraph" has been found
@ -712,7 +693,7 @@ static imagePixel_t *rdPPM(char *fileName) {
perror(fileName);
exit(EXIT_FAILURE);
}
if (buffer[0] != 'P' || buffer[1] != '6') {
if (buffer[0] != 'P' || buffer[1] != '6') { // PPM files start with P6
fprintf(stderr, "No PPM file format\n");
exit(EXIT_FAILURE);
}
@ -721,7 +702,7 @@ static imagePixel_t *rdPPM(char *fileName) {
fprintf(stderr, "malloc() failed");
}
c = getc(fp);
while (c == '#') {
while (c == '#') { // PPM Comments start with #
while (getc(fp) != '\n');
c = getc(fp);
}
@ -747,7 +728,7 @@ static imagePixel_t *rdPPM(char *fileName) {
printf("Changing \"-n\" to %d, image max data size\n", ( image->x * image->y ) );
tmp = (double *) realloc ( xSamples, sizeof(double) * (image->x * image->y) );
xSamples = tmp;
mlData->samplesCount = (image->x * image->y ) / sizeof(double);
mlData->samplesCount = (image->x * image->y );
}
if ( fread( image->data, 3 * image->x, image->y, fp) != image->y) {
fprintf(stderr, "Loading image failed");
@ -832,8 +813,7 @@ void colorSamples ( FILE* fp, mldata_t *mlData ) {
while (!feof(fp)) {
if (fgets(buffer, mlData->samplesCount, fp) != NULL) {
sscanf(buffer, "%lf", &xSamples[i]);
//printf("%lf\n", xSamples[i] );
sscanf(buffer, "%lf", &xSamples[i]);
points[i].yVal[0] = xSamples[i]; // Fills points so actual input values can be seen as a graph
points[i].xVal[0] = i;
++i;
@ -855,7 +835,7 @@ double windowXMean(int _arraylength, int xCount) {
double sum = 0.0;
double *ptr;
for (ptr = &xSamples[xCount - _arraylength]; ptr != &xSamples[xCount]; ptr++) { // Set ptr to beginning of window
for (ptr = &xSamples[xCount - _arraylength]; ptr != &xSamples[xCount]; ptr++) { // Set ptr to beginning of window and iterate through array
sum += *ptr;
}
return sum / (double)_arraylength;
@ -892,7 +872,7 @@ void usage ( char **argv ) {
init_mldata_t
Contains meachine learning data
Init meachine learning data
======================================================================================================
*/