328 lines
7.5 KiB
C
328 lines
7.5 KiB
C
//
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//
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// NLMSvariants.c
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//
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// Created by FBRDNLMS on 26.04.18.
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// Copyright © 2018 FBRDNLMS. All rights reserved.
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//
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#include <stdio.h>
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#include <math.h>
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#include <time.h>
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#include <stdlib.h>
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#include <string.h>
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#include <float.h> // DBL_MAX
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#define M 1000
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#define tracking 40 //Count of weights
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#define learnrate 1.0
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#define PURE_WEIGHTS 0
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#define USED_WEIGHTS 1
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#define RESULTS 2
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#define DIRECT_PREDECESSOR 3
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double x[] = {0};
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double _x[M] = {0};
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double w [M][M]={{0},{0}};
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/* *file handling* */
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char * mkFileName( char* buffer, size_t max_len, int suffixId );
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char *fileSuffix( int id );
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void myLogger( FILE* fp, int myVar);
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/* *rand seed functions* */
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double r2( void );
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double rndm( void );
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/* *math functions * */
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double sum_array( double x[], int length );
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void directPredecessor( void );
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void localMean( void );
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int main(int argc, char **argv ) {
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char fileName[50];
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int i;
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srand( (unsigned int) time(NULL) );
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for (i = 0; i < M; i++) {
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_x[i] += ((255.0 / M) * i); // Init test values
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for (int k = 1; k < M; k++){
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w[k][i] = rndm(); // Init weights
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}
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}
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mkFileName( fileName, sizeof(fileName), PURE_WEIGHTS);
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// save plain test_array before math magic happens
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FILE *fp0 = fopen(fileName,"w");
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for (i = 0; i < tracking; i++){
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for ( int k = 1; k < tracking; k++ ){
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fprintf(fp0, "[%d][%d] %lf\n", k, i, w[k][i]);
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}
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}
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fclose(fp0);
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// math magic
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//directPredecessor(); // TODO: needs some love!
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localMean();
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// save test_array after math magic happened
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// memset( fileName, '\0', sizeof(fileName) );
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mkFileName( fileName, sizeof(fileName), USED_WEIGHTS);
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FILE *fp1 = fopen(fileName,"w");
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for (i = 0; i < tracking; i++) {
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for (int k = 1; k < tracking; k++) {
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fprintf(fp1, "[%d][%d] %lf\n", k,i, w[k][i]);
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}
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}
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fclose(fp1);
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// getchar();
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printf("DONE!");
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}
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/*
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=======================================================================================
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localMean
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Variant (1/3), substract local mean.
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=======================================================================================
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*/
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void localMean( void ) {
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char fileName[50];
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double xError[M]; // includes e(n)
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memset(xError, 0, M);// initialize xError-array with Zero
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int xCount = 0; // runtime var
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int i;
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for (xCount = 1; xCount < M; xCount++){
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//double xPartArray[xCount]; //includes all values at the size of runtime var
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double xMean = ( xCount > 0 ) ? ( sum_array(_x, xCount) / xCount ) : 0;// xCount can not be zero
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double xPredicted = 0.0;
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double xActual = _x[xCount + 1];
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for ( i = 1; i < xCount; i++ ){ //get predicted value
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xPredicted += ( w[i][xCount] * ( _x[xCount - i] - xMean )) ;
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}
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xPredicted += xMean;
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xError [xCount] = xActual - xPredicted;
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double xSquared = 0.0;
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for ( i = 1; i < xCount; i++ ){ //get x squared
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xSquared =+ pow(_x[xCount-i],2);
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}
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for ( i - 1; i < xCount; i++ ){ //update weights
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w[i][xCount+1] = w[i][xCount] + learnrate * xError[xCount] * (_x[xCount - i] / xSquared);
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}
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}
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int xErrorLength = sizeof(xError) / sizeof(xError[0]);
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double mean = sum_array(xError, xErrorLength) / M;
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double deviation = 0.0;
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// Mean square
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for( i = 0; i < M - 1; i++ ){
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deviation += pow( xError[i], 2 );
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}
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deviation /= xErrorLength;
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// write in file
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mkFileName( fileName, sizeof(fileName), RESULTS );
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FILE *fp2 = fopen(fileName, "w+");
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fprintf(fp2, "quadr. Varianz(x_error): {%f}\nMittelwert:(x_error): {%f}\n\n", deviation, mean);
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fclose(fp2);
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}
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/*
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===================================
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directPredecessor
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Variant (2/3),
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substract direct predecessor
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===================================
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*/
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void directPredecessor( void ) {
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char fileName[50];
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double xError [M];
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int xCount = 0, i;
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double xActual;
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// File handling
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mkFileName( fileName, sizeof(fileName), DIRECT_PREDECESSOR);
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FILE *fp3 = fopen(fileName, "w");
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for ( xCount = 1; xCount < M+1; xCount++ ){
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xActual = _x[xCount+1];
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double xPredicted = 0.0;
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for ( i = 1; i < xCount; i++ ){
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xPredicted += ( w[i][xCount] * ( _x[xCount - i] - _x[xCount - i - 1] ));
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}
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xPredicted += _x[xCount-1];
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xError[xCount] = xActual - xPredicted;
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fprintf(fp3, "{%d}.\txPredicted{%f}\txActual{%f}\txError{%f}\n", xCount, xPredicted, xActual, xError[xCount]);
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double xSquared = 0.0;
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//get x squared
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for ( i = 1; i < xCount; i++ ){
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xSquared += pow( _x[xCount - i] - _x[xCount - i - 1], 2); // substract direct predecessor
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}
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for ( i = 1; i < xCount; i++){
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w[i][xCount+1] = w[i][xCount] + learnrate * xError[xCount] * ( ( _x[xCount - i - 1] ) / xSquared ); //TODO: double val out of bounds
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}
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}
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int xErrorLength = sizeof(xError) / sizeof(xError[0]);
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double mean = sum_array(xError, xErrorLength) / xErrorLength;
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double deviation = 0.0;
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for ( i = 0; i < xErrorLength -1; i++ ){
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deviation += pow( xError[i] - mean, 2);
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}
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fprintf(fp3, "{%d}.\tLeast Mean Squared{%f}\tMean{%f}\n\n", xCount, deviation, mean);
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fclose(fp3);
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}
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/*
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=========================================================================
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mkFileName
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Writes the current date plus the suffix with index suffixId
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into the given buffer. If[M ?K the total length is longer than max_len,
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only max_len characters will be written.
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=========================================================================
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*/
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char *mkFileName( char* buffer, size_t max_len, int suffixId) {
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const char * format_str = "%Y-%m-%d_%H_%M_%S";
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size_t date_len;
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const char * suffix = fileSuffix( suffixId );
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time_t now = time(NULL);
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strftime( buffer, max_len, format_str, localtime(&now) );
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date_len = strlen(buffer);
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strncat( buffer, suffix, max_len - date_len );
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}
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/*
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=========================================================================
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fileSuffix
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Contains and returns every suffix for all existing filenames
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==========================================================================
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*/
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char * fileSuffix( int id ) {
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char * suffix[] = {"_weights_pure.txt", "_weights_used.txt", "direct_predecessor.txt", "ergebnisse.txt"};
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return suffix[id];
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}
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/*
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==========================================================================
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myLogger
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Pipes to stdout or files by using a filepointer for logging purposes
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==========================================================================
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*/
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void myLogger ( FILE* fp, int myVar ){
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fprintf( fp, "Logging: %d\n", myVar);
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}
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/*
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=========================================================================
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sum_array
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Sum of all elements in x within a defined length
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=========================================================================
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*/
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double sum_array( double x[], int length ){
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int i = 0;
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double sum = 0.0;
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for( i=0; i< length; i++ ) {
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sum += x[i];
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}
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return sum;
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}
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/*
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==========================================================================
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r2
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returns a random double value between 0 and 1
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==========================================================================
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*/
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double r2( void ) {
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return((rand() % 10000) / 10000.0);
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}
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/*
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==========================================================================
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rndm
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fills a double variable with random value and returns it
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=========================================================================
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*/
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double rndm( void ) {
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double rndmval= r2();
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return rndmval;
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}
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