int main(void) {
REAL8TimeSeries *conv, *data, *response, *exactConv;
const UINT4 N = 101;
const LIGOTimeGPS zero = {0, 0};
UINT4 i;
conv = XLALCreateREAL8TimeSeries("FFT Convolution", &zero, 0.0, 0.01, &lalDimensionlessUnit, N);
data = XLALCreateREAL8TimeSeries("data", &zero, 0.0, 0.01, &lalDimensionlessUnit, N);
response = XLALCreateREAL8TimeSeries("response function", &zero, 0.0, 0.01, &lalDimensionlessUnit, N);
exactConv = XLALCreateREAL8TimeSeries("exact convolution", &zero, 0.0, 0.01, &lalDimensionlessUnit, N);
data->data->data[0] = 1.0;
for (i = 1; i < N; i++) {
/* Data is 1/i */
data->data->data[i] = 1.0 / i;
}
response->data->data[0] = 1.0;
for (i = 1; i <= (N-1)/2; i++) {
response->data->data[i] = exp(-(i/10.0)); /* Decaying exponential with time constant 10. */
response->data->data[N-i] = exp(-(i/10.0)); /* Same in the negative, wrapped dimension. */
}
if (N % 2 == 0) {
response->data->data[N/2] = exp(-(N/20.0));
}
/* Exact, O(N^2) convolution */
for (i = 0; i < N; i++) {
REAL8 sum = 0.0;
UINT4 j;
for (j = MAX_INT(0, ((int)i)-((int) N/2)); j <= MIN_INT(i+N/2, N-1); j++) {
UINT4 rIndex = (j > i ? i + (N - j) : i - j);
sum += data->data->data[j]*response->data->data[rIndex];
}
exactConv->data->data[i] = sum;
}
convolveTimeSeries(conv, data, response);
for (i = 0; i < N; i++) {
if (fabs(exactConv->data->data[i] - conv->data->data[i]) > 1e-8) {
fprintf(stderr, "Index %d differs (exact = %g, FFT = %g)\n",
i, exactConv->data->data[i], conv->data->data[i]);
}
}
XLALDestroyREAL8TimeSeries(conv);
XLALDestroyREAL8TimeSeries(data);
XLALDestroyREAL8TimeSeries(response);
XLALDestroyREAL8TimeSeries(exactConv);
return 0;
}
/**
* Стартовые статы при любых условиях должны соответствовать границам ролла.
* В случае старого ролла тут это всплывет из-за нулевых статов.
*/
bool bad_start_stats(CHAR_DATA *ch)
{
if (ch->get_start_stat(G_STR) > MAX_STR(ch)
|| ch->get_start_stat(G_STR) < MIN_STR(ch)
|| ch->get_start_stat(G_DEX) > MAX_DEX(ch)
|| ch->get_start_stat(G_DEX) < MIN_DEX(ch)
|| ch->get_start_stat(G_INT) > MAX_INT(ch)
|| ch->get_start_stat(G_INT) < MIN_INT(ch)
|| ch->get_start_stat(G_WIS) > MAX_WIS(ch)
|| ch->get_start_stat(G_WIS) < MIN_WIS(ch)
|| ch->get_start_stat(G_CON) > MAX_CON(ch)
|| ch->get_start_stat(G_CON) < MIN_CON(ch)
|| ch->get_start_stat(G_CHA) > MAX_CHA(ch)
|| ch->get_start_stat(G_CHA) < MIN_CHA(ch)
|| start_stats_count(ch) != SUM_ALL_STATS)
{
return 1;
}
return 0;
}
int backgroundBlit(void)
{
SDL_Rect *camera = sdlStore(NULL,GET_CAMERA);
if(camera == 0)
{
puts("DEBUG: backgroundBlit() 1");
return -1;
}
SDL_Surface *screen = sdlStore(NULL,GET_SCREEN);
if(screen == 0)
{
puts("DEBUG: backgroundBlit() 2");
return -1;
}
struct bgData *initData = sdlStore(NULL,GET_BACKGROUND);
if(initData == 0)
{
puts("DEBUG: backgroundBlit() 3");
return -1;
}
int *bgSizes = (int *)sdlStore(NULL,GET_BG_SIZE);
if(bgSizes == 0)
{
puts("DEBUG: backgroundBlit() 4");
return -1;
}
int bgOffset[BG_AMOUNT][COORDS];
int i;
for(i = 0;i < BG_AMOUNT;i++)
{
bgOffset[i][0] = ((camera->x * BG_MULT) / bgSizes[i]) % camera->w;
bgOffset[i][1] = ((camera->y * BG_MULT) / bgSizes[i]) % camera->h;
}
//DEBUG
//printf("bg0: x %d y %d cam: x %d y %d\n",bgOffset[0][0],bgOffset[0][1],camera->x,camera->y);
//Iterate over background layers
for(i = 0;i < BG_AMOUNT;i++)
{
//For tiling
int mw;
for(mw = 0;mw < (camera->w * 2);mw += BG_INIT_W_SIZE)
{
int mh;
for(mh = 0;mh < (camera->h * 2);mh += BG_INIT_H_SIZE)
{
int k;
for(k = 0;k < (MIN_INT(BG_INIT_W_SIZE,camera->w) * MIN_INT(BG_INIT_H_SIZE,camera->h)) /
(BG_INIT_MAX_SPACING * BG_INIT_MAX_SPACING);k++)
{
int index = k * (i + 1);
SDL_Rect tmpRect;
tmpRect.x = initData[index].pos.x + mw - bgOffset[i][0];
tmpRect.y = initData[index].pos.y + mh - bgOffset[i][1];
//DEBUG
//printf("x %5d y %5d w %5d h %5d\n",tmpRect.x,tmpRect.y,tmpRect.w,tmpRect.h);
blitCircle(bgSizes[i],screen,tmpRect,(SDL_Color){255,255,255});
}
}
}
}
return 0;
}
/**
* Проверка стартовых и итоговых статов.
* Если невалидные стартовые статы - чар отправляется на реролл.
* Если невалидные только итоговые статы - идет перезапись со стартовых с учетом мортов и славы.
*/
bool check_stats(CHAR_DATA *ch)
{
// иммов травмировать не стоит
if (IS_IMMORTAL(ch))
{
return 1;
}
int have_stats = ch->get_inborn_str() + ch->get_inborn_dex() + ch->get_inborn_int() + ch->get_inborn_wis()
+ ch->get_inborn_con() + ch->get_inborn_cha();
// чар со старым роллом статов или после попыток поправить статы в файле
if (bad_start_stats(ch))
{
snprintf(buf, MAX_STRING_LENGTH, "\r\n%sВаши параметры за вычетом перевоплощений:\r\n"
"Сила: %d, Ловкость: %d, Ум: %d, Мудрость: %d, Телосложение: %d, Обаяние: %d\r\n"
"Если вы долго отсутствовали в игре, то изменения, касающиеся стартовых параметров были следующие:%s\r\n"
"\r\n"
"\tДобавлено ограничение на максимальный класс защиты:\r\n"
"\tВоры, наемники и дружинники - -250\r\n"
"\tКупцы, богатыри, витязи, охотники, кузнецы - -200\r\n"
"\tЛекари, волхвы - -150\r\n"
"\tКудесники, чернокнижники, колдуны, волшебники - -100\r\n"
"\r\n"
"\tТелосложение: изменились коэффициенты профессий и максимальное родное тело (50) в расчетах при\r\n"
"\tполучении уровня, поэтому изменены границы стартового телосложения у некоторых профессий,\r\n"
"\tв целом это увеличивает кол-во жизней персонажа тем сильнее, чем больше у него было ремортов.\r\n"
"\r\n",
CCIGRN(ch, C_SPR),
ch->get_inborn_str() - GET_REMORT(ch),
ch->get_inborn_dex() - GET_REMORT(ch),
ch->get_inborn_int() - GET_REMORT(ch),
ch->get_inborn_wis() - GET_REMORT(ch),
ch->get_inborn_con() - GET_REMORT(ch),
ch->get_inborn_cha() - GET_REMORT(ch),
CCNRM(ch, C_SPR));
SEND_TO_Q(buf, ch->desc);
// данную фигню мы делаем для того, чтобы из ролла нельзя было случайно так просто выйти
// сразу, не раскидав статы, а то много любителей тригов и просто нажатий не глядя
ch->set_str(MIN_STR(ch));
ch->set_dex(MIN_DEX(ch));
ch->set_int(MIN_INT(ch));
ch->set_wis(MIN_WIS(ch));
ch->set_con(MIN_CON(ch));
ch->set_cha(MIN_CHA(ch));
snprintf(buf, MAX_STRING_LENGTH, "%sПросим вас заново распределить основные параметры персонажа.%s\r\n",
CCIGRN(ch, C_SPR), CCNRM(ch, C_SPR));
SEND_TO_Q(buf, ch->desc);
SEND_TO_Q("\r\n* В связи с проблемами перевода фразы ANYKEY нажмите ENTER *", ch->desc);
STATE(ch->desc) = CON_RESET_STATS;
return 0;
}
// стартовые статы в поряде, но слава не сходится (снялась по времени или иммом)
if (bad_real_stats(ch, have_stats))
{
recalculate_stats(ch);
}
return 1;
}
int uwerr (char* append) {
const double epsilon = 2.0e-16;
int i, n, label;
int ndata, Wmax, W, Wopt, k;
double **a_b, *a_bb, *a_proj, a_bb_proj;
double *F_b, *F_bb, *F_bw;
double *Gamma_F, C_F, C_Fopt, v_Fbb, dv_Fbb, tau, *tau_int;
double *f_alpha, *h_alpha, *m_alpha, *data_ptr, func_res;
double value, dvalue, ddvalue, tau_intbb, dtau_intbb;
double chisqr, Qval, *p_r, p_r_mean, p_r_var, delta, lobd, *bins;
char filename[80], format[80];
FILE *ofs;
printf("[uwerr] The following arguments have been read:\n");
printf("[uwerr] nalpha = %d\n", nalpha);
printf("[uwerr] nreplica = %d\n", nreplica);
for(i=0; i<nreplica; i++) {
printf("[uwerr] n_r(%2d) = %d\n", i, n_r[i]);
}
printf("[uwerr] npara = %d\n", npara);
for(i=0; i<npara; i++) {
printf("[uwerr] para(%2d) = %e\n", i, para[i]);
}
printf("[uwerr] ipo = %d\n", ipo);
printf("[uwerr] s_tau = %e\n", s_tau);
printf("[uwerr] obsname = %s\n", obsname);
printf("[uwerr] append = %s\n", append);
fprintf(stdout, "[uwerr]: Starting ...\n");
/*************************************************************
* check if combination of values in ipo an func are allowed *
*************************************************************/
label = ipo;
if(ipo>0 && func!=NULL) {
ipo = 0;
}
else if ( ipo==0 && func==NULL) {
fprintf(stdout, "[uwerr] illegal values of func and ipo, return");
return(1);
}
fprintf(stdout, "[uwerr]: checked ipo and func\n");
/* ndata - total number of rows in data */
for( i=1, ndata = *n_r; i<nreplica; ndata += *(n_r + i++) );
/* Wmax - longest possible summation index + 1 */
MIN_INT(n_r, nreplica, &Wmax);
fprintf(stdout, "[uwerr]: have ndata and Wmax ready\n");
/*******************
* allocate memory *
*******************/
F_b = (double *)calloc(nreplica, sizeof(double));
F_bb = (double *)calloc(1, sizeof(double));
F_bw = (double *)calloc(1, sizeof(double));
Gamma_F = (double *)calloc(Wmax, sizeof(double));
tau_int = (double *)calloc(Wmax, sizeof(double));
if (ipo==0 && func!=NULL) /* only necessary in case of derived quantity */ {
a_b = (double**)calloc(nreplica, sizeof(double*));
a_bb = (double *)calloc(nalpha, sizeof(double));
for(n=0; n<nreplica; n++) { *(a_b+n)=(double*)calloc(nalpha, sizeof(double)); }
}
fprintf(stdout, "[uwerr]: allocated memory\n");
/*********************************************************************
* calculate estimators for primary observable/derived quantity *
*********************************************************************/
if(ipo>0 && func==NULL) /* here estimators for one of the prim. observables */ {
data_ptr = *(data+ipo-1); /* points to column of ipo in data */
for(n=0; n<nreplica; n++) {
ARITHMEAN(data_ptr, *(n_r+n), F_b+n); /* arithmetic mean for replia */
data_ptr = data_ptr + *(n_r+n); /* pointer set to beginning of next replia */
/* test */
fprintf(stdout, "[uwerr] F_b(%d) = %18.16e\n", n, *(F_b+n));
}
ARITHMEAN(*(data+ipo-1), ndata, F_bb); /* mean including all data for ipo */
/* test */
fprintf(stdout, "[uwerr] F_bn = %18.16e\n", *F_bb);
}
else if (ipo==0 && func!=NULL) { /* estimators for derived quantity */
/* calculate means per replica and total mean */
for(i=0; i<nalpha; i++) {
data_ptr = *(data+i);
for(n=0; n<nreplica; n++) {
ARITHMEAN(data_ptr, *(n_r+n), *(a_b+n)+i);
data_ptr += *(n_r+n);
}
ARITHMEAN(*(data+i), ndata, a_bb+i);
}
/* calculate estimators per replica for derived quatity */
for(n=0; n<nreplica; n++) {
func(nalpha, *(a_b+n), npara, para, F_b+n); /* est. for means per replicum */
}
func(nalpha, a_bb, npara, para, F_bb); /* est. for total mean */
}
/* in case of more than one replica
calculate weighed mean of F_b's with weights n_r */
if(nreplica > 1) {
WEIGHEDMEAN(F_b, nreplica, F_bw, n_r);
/* test */
fprintf(stdout, "[uwerr] F_bw = %18.16e\n", *F_bw);
}
fprintf(stdout, "[uwerr]: have estimators ready\n");
/***********************************************
* calculate projection of data and mean value *
***********************************************/
if(ipo>0 && func==NULL) {
a_proj = *(data + ipo - 1); /* data is projectet to itself in case of prim.
observable */
a_bb_proj = *F_bb; /* projected mean is total mean */
}
else if (ipo==0 && func!=NULL) {
f_alpha = (double *)calloc(nalpha, sizeof(double));
h_alpha = (double *)calloc(nalpha, sizeof(double));
m_alpha = (double *)calloc(ndata, sizeof(double));
a_proj = (double *)calloc(ndata, sizeof(double));
/* calculate derivatives of func with respect to A_alpha */
for(i=0; i<nalpha; i++) { /* loop over all prim. observables */
SET_TO(h_alpha, nalpha, 0.0);
STDDEV(*(data+i), ndata, h_alpha+i);
/* test */
fprintf(stdout, "[uwerr] halpha = %18.16e\n", *(h_alpha+i));
if(*(h_alpha+i)==0.0) {
fprintf(stdout, "[uwerr] Warning: no fluctuation in primary observable %d\n", i);
*(f_alpha + i) = 0.0;
}
else {
ADD_ASSIGN(m_alpha, a_bb, h_alpha, nalpha);
func(nalpha, m_alpha, npara, para, &func_res);
*(f_alpha+i) = func_res;
SUB_ASSIGN(m_alpha, a_bb, h_alpha, nalpha);
func(nalpha, m_alpha, npara, para, &func_res);
*(f_alpha+i) -= func_res;
*(f_alpha+i) = *(f_alpha+i) / (2.0 * *(h_alpha+i));
}
}
SET_TO(a_proj, ndata, 0.0);
a_bb_proj = 0.0;
for(i=0; i<nalpha; i++) {
for(n=0; n<ndata; n++) {
*(a_proj + n) = *(a_proj + n) + ( *(*(data+i)+n) ) * ( *(f_alpha+i) );
}
a_bb_proj = a_bb_proj + *(a_bb+i) * (*(f_alpha+i));
}
free(m_alpha);
free(f_alpha);
free(h_alpha);
for(n=0; n<nreplica; n++) { free(*(a_b+n)); }
free(a_b);
free(a_bb);
}
fprintf(stdout, "[uwerr]: have projected data ready\n");
/**********************************************************************
* calculate error, error of the error; automatic windowing condition *
**********************************************************************/
/* (1) Gamma_F(t), t=0,...,Wmax */
SET_TO(Gamma_F, Wmax, 0.0);
SET_TO(tau_int, Wmax, 0.0);
for(i=0,v_Fbb=0.0; i<ndata; i++) {
v_Fbb = v_Fbb + SQR( (*(a_proj+i) - a_bb_proj) );
}
v_Fbb /= (double)ndata;
C_F = v_Fbb;
*Gamma_F = v_Fbb;
/* test */
fprintf(stdout, "[uwerr] a_bb_proj = %18.16e\n", a_bb_proj);
fprintf(stdout, "[uwerr] Gamma_F(%1d) = %18.16e\n", 0, *Gamma_F);
if (*Gamma_F==0.0) {
fprintf(stderr, "[uwerr] ERROR, no fluctuations; return\n");
strcpy(filename, obsname);
strcat(filename,"_uwerr");
ofs = fopen(filename, append);
if ((void*)ofs==NULL) {
fprintf(stderr, "[uwerr] Could not open file %s\n", filename);
return(1);
}
fprintf(ofs, "%d\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t"\
"%18.16e\t%18.16e\n", label, *F_bb, 0.0, 0.0, 0.0, \
0.0, -1.0, 0.0, 0.0);
if (fclose(ofs)!=0) {
fprintf(stderr, "[uwerr] Could not close file %s\n", filename);
return(1);
}
return(-5);
}
*tau_int = 0.5;
for(W=1; W<Wmax-1; W++) {
/* calculate Gamma_F(W) */
data_ptr = a_proj;
for(n=0; n<nreplica; n++) {
for(i=0; i<(*(n_r+n)-W); i++) {
*(Gamma_F+W) += (*(data_ptr+i) - a_bb_proj) * (*(data_ptr+i+W) - a_bb_proj);
}
data_ptr = data_ptr + *(n_r+n);
}
*(Gamma_F+W) = *(Gamma_F+W) / (double)(ndata-nreplica*W);
/* test */
fprintf(stdout, "[uwerr] Gamma_F(%d) = %18.16e\n", W, *(Gamma_F+W));
C_F = C_F + 2.0 * *(Gamma_F+W);
*tau_int = C_F / (2.0*v_Fbb);
if(*tau_int < 0.5) {
fprintf(stdout, "[uwerr] Warning: tau_int < 0.5; tau set to %f\n", TINY);
tau = TINY;
}
else {
tau = s_tau / log( (*tau_int+0.5) / (*tau_int-0.5) );
}
/* test */
fprintf(stdout, "[uwerr] tau(%d) = %18.16e\n", W, tau);
if( exp(-(double)W / tau) - tau / sqrt((double)(W*ndata)) < 0.0 ) {
Wopt = W;
/* test */
fprintf(stdout, "[uwerr] Wopt = %d\n", Wopt);
break;
}
}
if(W==Wmax-1) {
fprintf(stdout, "[uwerr] windowing condition failed after W = %d\n", W);
return(1);
}
else {
SUM(Gamma_F+1, Wopt, &C_Fopt);
C_Fopt = 2.0 * C_Fopt + *Gamma_F;
/* test */
fprintf(stdout, "[uwerr] before: C_Fopt = %18.16e\n", C_Fopt);
for(W=0; W<=Wopt; W++) {
*(Gamma_F+W) = *(Gamma_F+W) + C_Fopt/((double)ndata);
}
SUM(Gamma_F+1, Wopt, &C_Fopt);
C_Fopt = 2.0 * C_Fopt + *Gamma_F;
/* test */
fprintf(stdout, "[uwerr] after: C_Fopt = %18.16e\n", C_Fopt);
v_Fbb = *Gamma_F;
*tau_int = 0.5*v_Fbb;
for(W=1; W<=Wopt; W++) *(tau_int+W) = *(tau_int+W-1) + *(Gamma_F+W);
for(W=0; W<=Wopt; W++) *(tau_int+W) /= v_Fbb;
}
fprintf(stdout, "[uwerr]: perfomed automatic windowing\n");
/***********************************
* bias cancellation of mean value *
***********************************/
if(nreplica > 1 ) {
*F_bb = ( (double)nreplica * *F_bb - *F_bw ) / ((double)(nreplica-1));
}
fprintf(stdout, "[uwerr]: leading bias cancelled\n");
/**************************
* calculation of results *
**************************/
value = *F_bb;
dvalue = sqrt(C_Fopt/((double)ndata));
ddvalue = dvalue * sqrt((Wopt + 0.5)/ndata);
tau_intbb = C_Fopt / (2.0 * v_Fbb);
dtau_intbb = sqrt( 2.0 * ( 2.0*Wopt-3.0*tau_intbb + 1 + \
1/(4.0*tau_intbb))/((double)ndata) ) * tau_intbb;
dv_Fbb = sqrt(2.0*(tau_intbb + 1/(4.0*tau_intbb)) / (double)ndata) * v_Fbb;
/*******************************************
* consistency checks in case nreplica > 0 *
*******************************************/
if(nreplica>1) {
/* (1) calculate Q-value <---> determine goodness of the fit
F_b(n) = F_bw = const. */
chisqr = 0.0;
for(n=0; n<nreplica; n++) {
chisqr = chisqr + SQR( *(F_b+n) - *F_bw ) / (C_Fopt/(double)(*(n_r+n)));
}
/* test */
fprintf(stdout, "[uwerr]: chisqr = %18.16e\n", chisqr);
fprintf(stdout, "[uwerr]: n = %d \n", (nreplica-1)/2);
Qval = 1.0 - incomp_gamma(chisqr/2.0, (nreplica-1)/2);
/* (2) inspection of p_r's defined below in a histogramm */
p_r = (double *)calloc(nreplica, sizeof(double));
for(n=0; n<nreplica; n++) {
*(p_r+n) = (*(F_b+n) - *F_bw) / \
(dvalue*sqrt(((double)ndata/(double)(*(n_r+n)))-1.0));
}
ARITHMEAN(p_r, nreplica, &p_r_mean);
VAR(p_r, nreplica, &p_r_var);
k = 1 + (int)rint(log((double)nreplica)/log(2.0));
strcpy(filename, obsname);
strcat(filename, "_uwerr_hist");
ofs = fopen(filename, append);
fprintf(ofs, "# mean of p_r's:\tp_r_mean = %8.6e\n" \
"# variance of p_r's:\tp_r_var = %8.6e\n", \
p_r_mean, p_r_var);
strcpy(format, "%%dst p_r(%2d) = %18.16e\n");
for(n=0; n<nreplica; n++) {
fprintf(ofs, format, n, *(p_r+n));
}
if(k<3) /* not enough classes for a meaningful histogramm */ {
fprintf(ofs, "# [uwerr]: k = %d is to small\n", k);
}
else {
ABS_MAX_DBL(p_r, nreplica, &lobd); /* max{|p_r's|} */
lobd = lobd *(1.0+TINY);
delta = 2.0*lobd/(double)k; /* expected distribution around mean=0 */
lobd = -lobd; /* lower boundary of abscissa */
bins = (double *)calloc(k, sizeof(double)); /* contains number of entries */
SET_TO(bins, k, 0.0); /* for each class */
for(n=0; n<nreplica; n++) /* inc. bins(i) by 1, if p_r(n) is in class i */ {
i = (int)((*(p_r+n) - lobd)/delta);
*(bins + i) = *(bins + i) + 1.0;
}
fprintf(ofs, "# number of entries:\tnreplica = %d\n" \
"# number of classes:\tk = %d\n" \
"# lower boundary:\tlobd = %8.6e\n" \
"# bin width:\tdelta = %8.6e\n", \
nreplica, k, lobd, delta);
strcpy(format, "%%hst %18.16e\t%18.16e\n");
for(i=0; i<k; i++) {
fprintf(ofs, format, lobd+((double)i+0.5)*delta, *(bins+i));
}
}
fclose(ofs);
}
/**************************
* output *
**************************/
/* (1) value, dvalue, ... */
strcpy(filename, obsname);
strcat(filename,"_uwerr");
ofs = fopen(filename, append);
if ((void*)ofs==NULL) {
fprintf(stderr, "[uwerr] Could not open file %s\n", filename);
return(1);
}
strcpy(format, "%d\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\t%18.16e\n");
fprintf(ofs, format, label, value, dvalue, ddvalue, tau_intbb, dtau_intbb, Qval, v_Fbb, dv_Fbb);
if (fclose(ofs)!=0) {
fprintf(stderr, "[uwerr] Could not close file %s\n", filename);
return(1);
}
/* (2) Gamma_F */
strcpy(filename, obsname);
strcat(filename, "_uwerr_Gamma");
ofs = fopen(filename, append);
if ((void*)ofs==NULL) {
fprintf(stderr, "[uwerr] Could not open file %s\n", filename);
return(1);
}
strcpy(format, "%d\t%18.16e\n");
fprintf(ofs, "# obsname = %s \t ipo = %d", obsname, ipo);
for(W=0; W<=Wopt; W++) {
fprintf(ofs, format, W, *(Gamma_F+W));
}
if (fclose(ofs)!=0) {
fprintf(stderr, "[uwerr] Could not close file %s\n", filename);
return(1);
}
/* (3) tau_int */
strcpy(filename, obsname);
strcat(filename, "_uwerr_tauint");
ofs = fopen(filename, append);
fprintf(ofs, "# obsname = %s \t ipo = %d", obsname, ipo);
for(W=0; W<=Wopt; W++) {
fprintf(ofs, format, W, *(tau_int+W));
}
fclose(ofs);
fprintf(stdout, "[uwerr]: output written\n");
/*****************************
* free allocated disk space *
*****************************/
free(F_b);
free(F_bb);
free(F_bw);
free(Gamma_F);
free(tau_int);
if(ipo==0 && func!=NULL) {
free(a_proj);
}
return(0);
}
