template <class DATA> void
Statistics<DATA>::update
(
)
const
{
matrix_set_scaled(m_mean,1.0/m_counter,m_sum);
if (m_counter<2)
{
matrix_set_scalar(m_variance,0);
}
else
{
for (int i=0;i<m_variance.rows();++i)
m_variance(i) = sqrt(1.0/(m_counter-1) *
(m_squared_sum(i) - SQR(m_mean(i))*m_counter));
}
m_changed = false;
}
/*Rueckgabe 0 - inc, 1 - inc_err, 2 - abs, 3 - abs_err, 4-8 reserviert*/
double *m_fit(dataset *dat, fit_conf *conf, double inclin, double absol) {
double *vari, *res, vsum, v_sq_x, v_x, v_xy, v_sq_y, v_y, v_sq, rez_d,
chi_sq;
int k;
/*Ansetzen der Varianzgewichtung fuer gegebenes inclin */
vari = m_variance(dat, conf, inclin);
if (vari == NULL)
return NULL;
res = malloc(9 * sizeof(double));
if (res == NULL) {
free(vari);
return NULL;
}
/*ausrechnen der Summen */
v_sq = 0; /* 1/sigma_i^2*/
vsum = 0; /* Summe 1/sigma_i^2*/
v_sq_x = 0; /*x^2 / v_sq*/
v_x = 0; /*x / v_sq*/
v_xy = 0; /*xy / v_sq*/
v_sq_y = 0; /*y^2 / v_sq*/
v_y = 0; /*y / v_sq*/
chi_sq = 0; /* Guete des Fits */
for (k = conf->start; k < conf->start + conf->len; ++k) {
v_sq = vari[k];
vsum += 1. / v_sq;
v_sq_x += pow(dat->data[dat->x][k], 2) / v_sq;
v_x += dat->data[dat->x][k] / v_sq;
v_xy += (dat->data[dat->x][k] * dat->data[dat->y][k]) / v_sq;
v_sq_y += pow(dat->data[dat->y][k], 2) / v_sq;
v_y += dat->data[dat->y][k] / v_sq;
chi_sq += pow(
dat->data[dat->y][k] - inclin * dat->data[dat->x][k] - absol, 2)
/ v_sq;
}
chi_sq /= conf->len - 2;
/*Steigungsberechnung */
rez_d = vsum * v_sq_x - pow(v_x, 2);
rez_d = 1. / rez_d;
res[0] = vsum * v_xy - v_x * v_y;
res[0] *= rez_d;
/*Fehler der Steigung */
res[1] = rez_d * vsum;
res[1] = sqrt(res[1]);
/*Absolutes Glied*/
res[2] = v_y - (res[0] * v_x);
res[2] /= vsum;/*Varianzgemittelte Mittelwerte*/
/*Fehler Absolutes Glied*/
res[3] = res[1] * v_x / vsum;
res[3] = sqrt(res[3]);
/* hier muss evtl. noch gegausst werden! */
/* Korellationskoeffizient -> wird in uebergeorndeter Funktion berechnet*/
res[4] = 0;
/* reserviert fuer Abbruchinformationen */
res[5] = 0;
/* reserviert fuer Anzahl Iterationen */
res[6] = 0;
/* reserviert fuer letzte Aenderung*/
res[7] = 0;
/* chi_sq Guete des Fits */
res[8] = chi_sq;
free(vari);
return res;
}
