float fuzzy_system(float inputs[], fuzzy_system_rec fz) {
int i, j;
short variable_index, fuzzy_set;
float sum1 = 0.0, sum2 = 0.0, weight;
float m_values[MAX_NO_OF_INPUTS];
for (i = 0; i < fz.no_of_rules; i++) {
for (j = 0; j < fz.no_of_inputs; j++) {
variable_index = fz.rules[i].inp_index[j];
fuzzy_set = fz.rules[i].inp_fuzzy_set[j];
m_values[j] = trapz(inputs[variable_index],
fz.inp_mem_fns[variable_index][fuzzy_set]);
} /* end j */
weight = min_of(m_values, fz.no_of_inputs);
sum1 += weight * fz.output_values[fz.rules[i].out_fuzzy_set];
sum2 += weight;
} /* end i */
if (fabs(sum2) < TOO_SMALL) {
cout << "\r\nFLPRCS Error: Sum2 in fuzzy_system is 0. Press key: " << endl;
//~ getch();
exit(1);
return 0.0;
}
return (sum1 / sum2);
} /* end fuzzy_system */
void simpson(int *m1, int *n1, double *x, double *y, double *out) {
int k, j;
double *yptr;
double dx1, dx2;
double alpha, a0, a1, a2;
int n = *n1;
int m = *m1;
if (m<3) {
trapz(m1,n1,x,y,out);
}
else {
for (k=0; k<n; k++)
out[k] = 0.0;
for (j=0; j<m-2; j=j+2) {
dx1 = x[j+1] - x[j];
dx2 = x[j+2] - x[j+1];
alpha = (dx1+dx2)/dx1/6.0;
a0 = alpha*(2.0*dx1-dx2);
a1 = alpha*(dx1+dx2)*(dx1+dx2)/dx2;
a2 = alpha*dx1/dx2*(2.0*dx2-dx1);
yptr = y;
for (k=0; k<n; k++) {
out[k] += a0*yptr[j] + a1*yptr[j+1] +a2*yptr[j+2];
yptr += m;
}
}
if (m%2==0) {
yptr = y;
for (k=0; k<n; k++) {
alpha = x[m-3]*x[m-2]*(x[m-3]-x[m-2]) -
x[m-3]*x[m-1]*(x[m-3]-x[m-1]) +
x[m-2]*x[m-1]*(x[m-2]-x[m-1]);
a0 = yptr[m-3]*(x[m-2]-x[m-1]) - yptr[m-2]*(x[m-3]-x[m-1]) +
yptr[m-1]*(x[m-3]-x[m-2]);
a1 = yptr[m-3]*(x[m-1]*x[m-1]-x[m-2]*x[m-2]) -
yptr[m-2]*(x[m-1]*x[m-1]-x[m-3]*x[m-3]) +
yptr[m-1]*(x[m-2]*x[m-2]-x[m-3]*x[m-3]);
a2 = x[m-3]*x[m-2]*yptr[m-1]*(x[m-3]-x[m-2]) -
x[m-3]*yptr[m-2]*x[m-1]*(x[m-3]-x[m-1]) +
yptr[m-3]*x[m-2]*x[m-1]*(x[m-2]-x[m-1]);
a0 /= alpha; a1 /= alpha; a2 /= alpha;
out[k] += a0*(x[m-1]*x[m-1]*x[m-1]-x[m-2]*x[m-2]*x[m-2])/3 +
a1*(x[m-1]*x[m-1]-x[m-2]*x[m-2])/2 + a2*(x[m-1]-x[m-2]);
yptr += m;
}
}
}
}
/* SRSF Inner Product */
void innerprod_q(int *m1, double *t, double *q1, double *q2, double *out) {
int k;
double *q;
int m = *m1;
int n1 = 1;
q = (double *) malloc(m*sizeof(double));
for (k=0; k<m; k++)
q[k] = q1[k]*q2[k];
trapz(m1, &n1, t, q, out);
free(q);
}
void norm(double * function_1, double left_endpoint, double right_endpoint, int num_points, double * integral){
//cast ii as int so use in for loop.
int ii;
//creating the pointer psi_hat and dynamically allocating memory for it.
double * psi_hat;
psi_hat = (double*)malloc(num_points*sizeof(double));
//multiplying the two vectors(functions).
for(ii=0;ii<num_points;ii++){
psi_hat[ii] = function_1[ii] * function_1[ii];
}
//calling trapz function to integrate the new psi_hat function.
trapz(psi_hat, left_endpoint, right_endpoint, num_points, integral);
//computes the norm by taking the square root of the computed integral.
double norm = pow(*integral,0.5);
/*this section would normalize the vector, if you wanted to do something like that.
for(ii=0;ii<num_points;ii++){
psi_hat[ii] = function_1[ii] / norm;
}/*/
free(psi_hat);
}
/* R interface for trapz function. */
void trapz_R(int *N, double *x, double *y, double *result){
result[0] = trapz(N[0], x, y);
}
void SqrtMeanInverse(int *T1, int *n1, double *ti, double *gami, double *out){
int T = *T1, n = *n1;
double psi[T*n], gam[T*n], mu[T], vec[T*n], v[T], y[T], tmpi, len, vm[T], mnpsi[T], dqq[n];
double eps = DBL_EPSILON, tmpv[T], min = 0.0, binsize, tmp, gam_mu[T];
int k, iter, l, n2 = 1, min_ind = 0;
int maxiter = 30, tt = 1;
double lvm[maxiter];
double *x = malloc(sizeof(double)*(T));
for (k=0; k<maxiter; k++)
lvm[k] = 0;
for (k=0; k<T; k++)
gam_mu[k] = 0;
for (k=0; k<T; k++)
x[k] = (double)k/((double)(T-1));
double *psi_ptr, *gam_ptr, *tmp1_ptr, *y_ptr, *gam_mu_ptr;
binsize = 0;
for (k=0; k<T-1; k++)
binsize += ti[k+1]-ti[k];
binsize = binsize/(T-1);
for (k=0; k<T*n; k++){
gam[k] = gami[k];
}
psi_ptr = psi; gam_ptr = gam;
gradient(&T,&n,gam_ptr,&binsize,psi_ptr);
for (k=0; k<T*n; k++)
psi[k] = sqrt(fabs(psi[k])+eps);
for (k=0; k<T; k++){
tmp = 0;
for(l=0; l<n; l++)
tmp += psi[k+l*T];
mnpsi[k] = tmp/n;
}
for (k=0; k<n; k++){
for(l=0; l<T; l++)
tmpv[l] = psi[k*T+l]-mnpsi[l];
tmp = 0;
for(l=0; l<T; l++)
tmp += tmpv[l];
dqq[k] = tmp;
}
for (k=0; k<n; k++) {
if (k==0) {
min_ind = 0;
min = dqq[k];
}
else{
if (dqq[k]<min){
min = dqq[k];
min_ind = k;
}
}
}
for (k=0; k<T; k++)
mu[k] = psi[(min_ind-1)*T+k];
for (iter=1; iter<maxiter; iter++){
for (k=0; k<n; k++){
for(l=0; l<T; l++)
v[l] = psi[k*T+l] - mu[l];
for(l=0; l<T; l++)
y[l] = psi[k*T+l]*mu[l];
y_ptr = y;
trapz(T1, &n2, ti, y_ptr, &tmpi);
if (tmpi > 1){
tmpi = 1;
}
else if (tmpi < (-1)){
tmpi = 1;
}
len = acos(tmpi);
if (len > 0.0001){
for(l=0; l<T; l++)
vec[k*T+l] = (len/sin(len))*(psi[k*T+l]-cos(len)*mu[l]);
}
else {
for(l=0; l<T; l++)
vec[k*T+l] = 0;
}
}
for (k=0; k<T; k++){
tmp = 0;
for(l=0; l<n; l++){
tmp += vec[k+l*T];
}
vm[k] = tmp/n;
}
for (k=0; k<T; k++)
tmpv[k] = vm[k]*vm[k];
tmp = 0;
for (k=0; k<T; k++)
tmp += tmpv[k];
lvm[iter] = sqrt(tmp*binsize);
if (lvm[iter] == 0){
break;
}
for (k=0; k<T; k++)
mu[k] = cos(tt*lvm[iter])*mu[k]+(sin(tt*lvm[iter])/lvm[iter])*vm[k];
if (lvm[iter] < 1e-6 || iter >= maxiter)
break;
}
for (k=0; k<T; k++)
tmpv[k] = mu[k]*mu[k];
tmp1_ptr = tmpv;
gam_mu_ptr = gam_mu;
cumtrapz(T1,ti,tmp1_ptr,gam_mu_ptr);
for (k=0; k<T; k++)
gam_mu_ptr[k] = (gam_mu_ptr[k] - gam_mu_ptr[0])/(gam_mu_ptr[T-1]-gam_mu_ptr[0]);
invertGamma(T, gam_mu_ptr, out);
free(x);
return;
}