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NLMSvariants
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removed free(localWeights), changed help function from -x to -g true for graphing

This commit is contained in:
gurkenhabicht 2018-05-24 14:15:36 +02:00
parent 9955d5871b
commit 70cb5e399b
2 changed files with 244 additions and 249 deletions
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8
src/ansi_c_implementation/NLMSvariants.c
View File

@ -265,7 +265,7 @@ 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);
@ -353,7 +353,7 @@ 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);
}
@ -438,7 +438,7 @@ 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);
@ -884,7 +884,7 @@ void usage ( char **argv ) {
printf("\t-c <color>\t\tUse this color channel from inputfile.\n");
printf("\t-w <digit>\t\tCount of used weights (windowSize).\n");
printf("\t-l <digit>\t\tLearnrate, 0 < learnrate < 1.\n");
printf("\t-x true\t\t\tLogfiles only, no graph building.\n\t\t\t\tChoose for intense amount of input data.\n");
printf("\t-g true\t\t\tGraph building.\n\t\t\t\tChoose for n < 1200.\n");
printf("\t-s <digit>\t\tDigit for random seed generator.\n\t\t\t\tSame Digits produce same random values. Default is srand by time.\n");
printf("\n\n");
printf("%s compares prediction methods of least mean square filters.\nBy default it reads ppm file format and return logfiles as well\nas an svg graphs as an output of said least mean square methods.\n\nExample:\n\t%s -i myimage.ppm -w 3 -c green -s 5 -x true\n", &argv[0][0], &argv[0][0]);

17
src/cpp_implementation/NLMSvariants.cpp
View File

@ -116,8 +116,7 @@ int main(int argc, char **argv) {
sscanf(&argv[1][3], "%s", xBuffer);
if ( strstr(xBuffer, istrue) ) {
include = 1;
}
else {
} else {
printf( "Wrong Argruments: %s\n", argv[1]);
usage(argv);
}
@ -151,8 +150,7 @@ 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)
}
@ -805,19 +803,16 @@ 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 );
}
@ -889,7 +884,7 @@ void usage(char **argv) {
printf("\t-c <color>\t\tUse this color channel from inputfile.\n");
printf("\t-w <digit>\t\tCount of used weights (windowSize).\n");
printf("\t-l <digit>\t\tLearnrate, 0 < learnrate < 1.\n");
printf("\t-x true\t\t\tLogfiles only, no graph building.\n\t\t\t\tChoose for intense amount of input data.\n");
printf("\t-g true\t\t\tGraph building.\n\t\t\t\tChoose for n < 1200.\n");
printf("\t-s <digit>\t\tDigit for random seed generator.\n\t\t\t\tSame Digits produce same random values. Default is srand by time.\n");
printf("\n\n");
printf("%s compares prediction methods of least mean square filters.\nBy default it reads ppm file format and return logfiles as well\nas an svg graphs as an output of said least mean square methods.\n\nExample:\n\t%s -i myimage.ppm -w 3 -c green -s 5 -x true\n", &argv[0][0], &argv[0][0]);