static void
output_series_to_spc (const int *list, const DATASET *dset,
int t1, int t2, FILE *fp)
{
int i, t, done = 0;
for (t=t1; t<=t2 && !done; t++) {
for (i=1; i<=list[0] && !done; i++) {
if (na(dset->Z[list[i]][t])) {
fputs(" missingcode=-99999\n", fp);
done = 1;
}
}
}
fputs(" data=(\n", fp);
for (t=t1; t<=t2; t++) {
for (i=1; i<=list[0]; i++) {
if (na(dset->Z[list[i]][t])) {
fputs("-99999 ", fp);
} else {
fprintf(fp, "%.15g ", dset->Z[list[i]][t]);
}
}
fputc('\n', fp);
}
fputs(" )\n", fp);
}
static int anova_print_means (struct anova *v, const double *xt,
const double *y, double ybar,
int t1, int t2, PRN *prn)
{
double d, *csd = malloc(v->nt * sizeof *csd);
int c1, c2, c3, c4;
int i, t;
if (csd == NULL) {
return E_ALLOC;
}
for (i=0; i<v->nt; i++) {
csd[i] = 0.0;
}
for (t=t1; t<=t2; t++) {
if (!na(xt[t]) && !na(y[t])) {
for (i=0; i<v->nt; i++) {
if (xt[t] == v->tvals->val[i]) {
d = y[t] - v->cmeans[i];
csd[i] += d * d;
break;
}
}
}
}
c1 = g_utf8_strlen(_("Level"), -1);
c2 = g_utf8_strlen(_("n"), -1);
c3 = g_utf8_strlen(_("mean"), -1);
c4 = g_utf8_strlen(_("std. dev"), -1);
c1 = (c1 < 8)? 8 : c1;
c2 = (c2 > 6)? c2 + 1 : (c2 < 6)? 6 : c2;
c3 = (c3 > 10)? c3 + 1 : (c3 < 10)? 10 : c3;
c4 = (c4 > 12)? c4 + 1 : (c4 < 12)? 12 : c4;
pprintf(prn, " %-*s %*s %*s %*s\n\n", c1, _("Level"), c2, _("n"),
c3, _("mean"), c4, _("std. dev"));
for (i=0; i<v->nt; i++) {
if (v->ccount[i] > 1) {
csd[i] /= v->ccount[i] - 1;
csd[i] = sqrt(csd[i]);
pprintf(prn, " %-*g %*d %*g %#*.5g\n", c1, v->tvals->val[i],
c2, v->ccount[i], c3, v->cmeans[i], c4, csd[i]);
} else {
pprintf(prn, " %-*g %*d %*g %*s\n", c1, v->tvals->val[i],
c2, v->ccount[i], c3, v->cmeans[i], c4, "NA");
}
}
pprintf(prn, "\n %s = %g\n\n", _("Grand mean"), ybar);
free(csd);
return 0;
}
static void audio_rsqline (const MODEL *pmod, PRN *prn)
{
if (!na(pmod->rsq)) {
pprintf(prn, "Unadjusted R-squared %.3f.\n", pmod->rsq);
}
if (!na(pmod->adjrsq)) {
pprintf(prn, "Adjusted R-squared %.3f.\n", pmod->adjrsq);
}
}
static int import_prune_columns (DATASET *dset)
{
int allmiss = 1, ndel = 0;
int i, t, err = 0;
for (i=dset->v-1; i>0 && allmiss; i--) {
for (t=0; t<dset->n; t++) {
if (!na(dset->Z[i][t])) {
allmiss = 0;
break;
}
}
if (allmiss) ndel++;
}
if (ndel == dset->v - 1) {
gretl_errmsg_set(_("No numeric data were found"));
err = E_DATA;
} else if (ndel > 0) {
fprintf(stderr, "Sheet has %d trailing empty variables\n", ndel);
err = dataset_drop_last_variables(dset, ndel);
}
return err;
}
mat rotation_matrix( const vec &a, double angle ) {
// init cross-product
mat cp( 3, 3 );
// zero out the response
cp.zeros( 3, 3 );
vec na(a);
// create a new rotation matrix
mat rm( 3, 3 );
// zero out the response
rm.zeros( 3, 3 );
// calculate cp
cp( 0, 1 ) = -a( 2 );
cp( 1, 2 ) = -a( 0 );
cp( 2, 0 ) = -a( 1 );
cp( 0, 2 ) = a( 1 );
cp( 1, 0 ) = a( 2 );
cp( 2, 1 ) = a( 0 );
// calculate rotation matrix
rm = ( cos( angle ) * eye( 3, 3 )
+ 1 - cos( angle )) * a * a.t()
+ sin( angle ) * cp;
return rm;
}
static int few_vals (int t1, int t2, const double *x, double *ratio)
{
double test[FEWVALS];
int match;
int i, t, n = 0, nv = 0;
for (t=t1; t<=t2; t++) {
if (!na(x[t])) {
match = 0;
for (i=0; i<nv; i++) {
if (x[t] == test[i]) {
match = 1;
break;
}
}
if (!match) {
if (nv == FEWVALS) {
nv++;
break;
}
test[nv++] = x[t];
}
n++;
}
}
*ratio = (double) nv / n;
return nv;
}
int gretl_iscount (int t1, int t2, const double *x)
{
int t, xi;
int g1 = 0;
int ret = 1;
for (t=t1; t<=t2; t++) {
if (na(x[t])) {
continue;
}
if (x[t] < 0.0) {
ret = 0;
break;
}
xi = x[t];
if (x[t] != (double) xi) {
ret = 0;
break;
}
if (x[t] > 1.0) {
g1 = 1;
}
}
if (g1 == 0) {
ret = 0;
}
return ret;
}
ATTR_TYPE getPlugAttrType(const char *plugName, MFnDependencyNode& dn)
{
MDGContext ctx = MDGContext::fsNormal;
MStatus stat = MS::kSuccess;
MPlug plug = dn.findPlug(plugName, &stat);
if( !stat )
return ATTR_TYPE::ATTR_TYPE_NONE;
MObject attObj = plug.attribute(&stat);
MFnAttribute att(attObj);
if( !stat )
return ATTR_TYPE::ATTR_TYPE_NONE;
if(att.isUsedAsColor())
return ATTR_TYPE::ATTR_TYPE_COLOR;
if( attObj.apiType() == MFn::kNumericAttribute)
{
MFnNumericAttribute na(attObj, &stat);
if( !stat )
return ATTR_TYPE::ATTR_TYPE_NONE;
if( na.unitType() == MFnNumericData::Type::kFloat )
return ATTR_TYPE::ATTR_TYPE_FLOAT;
}
return ATTR_TYPE::ATTR_TYPE_NONE;
}
double sur_loglik (equation_system *sys)
{
int m = sys->neqns;
int T = sys->T;
gretl_matrix *tmp;
double ldet;
int err = 0;
tmp = gretl_matrix_alloc(m, m);
if (tmp == NULL) {
return NADBL;
}
gls_sigma_from_uhat(sys, tmp, 0);
ldet = gretl_vcv_log_determinant(tmp, &err);
if (na(ldet)) {
sys->ll = NADBL;
} else {
sys->ll = -(m * T / 2.0) * (LN_2_PI + 1.0);
sys->ll -= (T / 2.0) * ldet;
}
gretl_matrix_free(tmp);
return sys->ll;
}
galera::ReplicatorSMM::InitConfig::InitConfig(gu::Config& conf,
const char* const node_address)
{
Replicator::register_params(conf);
std::map<std::string, std::string>::const_iterator i;
for (i = defaults.map_.begin(); i != defaults.map_.end(); ++i)
{
if (i->second.empty())
conf.add(i->first);
else
conf.add(i->first, i->second);
}
// what is would be a better protection?
int const pv(gu::from_string<int>(conf.get(Param::proto_max)));
if (pv > MAX_PROTO_VER)
{
log_warn << "Can't set '" << Param::proto_max << "' to " << pv
<< ": maximum supported value is " << MAX_PROTO_VER;
conf.add(Param::proto_max, gu::to_string(MAX_PROTO_VER));
}
conf.add(COMMON_BASE_HOST_KEY);
conf.add(COMMON_BASE_PORT_KEY);
if (node_address && strlen(node_address) > 0)
{
gu::URI na(node_address, false);
try
{
std::string const host = na.get_host();
if (host == "0.0.0.0" || host == "0:0:0:0:0:0:0:0" || host == "::")
{
gu_throw_error(EINVAL) << "Bad value for 'node_address': '"
<< host << '\'';
}
conf.set(BASE_HOST_KEY, host);
}
catch (gu::NotSet& e) {}
try
{
conf.set(BASE_PORT_KEY, na.get_port());
}
catch (gu::NotSet& e) {}
}
/* register variables and defaults from other modules */
gcache::GCache::register_params(conf);
gcs_register_params(reinterpret_cast<gu_config_t*>(&conf));
Certification::register_params(conf);
ist::register_params(conf);
}
static void single_series_view_print (windata_t *vwin)
{
series_view *sview = (series_view *) vwin->data;
char num_format[32];
double x;
PRN *prn;
int i, t, obslen;
int err = 0;
if (bufopen(&prn)) {
return;
}
if (sview->view == VIEW_STANDARD) {
int list[2] = { 1, sview->varnum };
/* regular printout: unsort if need be */
if (sview->sorted) {
series_view_unsort(sview);
}
err = printdata(list, NULL, dataset, OPT_O, prn);
if (err) {
gui_errmsg(err);
}
goto finalize;
}
obslen = max_obs_marker_length(dataset);
if (sview->format == 'g') {
sprintf(num_format, "%%#13.%dg\n", sview->digits);
} else {
sprintf(num_format, "%%13.%df\n", sview->digits);
}
pprintf(prn, "\n%*s ", obslen, " ");
pprintf(prn, "%13s\n\n", dataset->varname[sview->varnum]);
for (i=0; i<sview->npoints; i++) {
t = sview->points[i].obsnum;
x = sview->points[i].val;
print_obs_marker(t, dataset, obslen, prn);
if (na(x)) {
pputc(prn, '\n');
} else {
pprintf(prn, num_format, x);
}
}
finalize:
if (!err) {
textview_set_text(vwin->text, gretl_print_get_buffer(prn));
}
gretl_print_destroy(prn);
}
static gretl_matrix *cluster_var_values (const double *cvar,
MODEL *pmod,
int *err)
{
gretl_matrix *cvals = NULL;
int t;
if (pmod->missmask != NULL) {
double *ctmp = malloc(pmod->nobs * sizeof *ctmp);
if (ctmp == NULL) {
*err = E_ALLOC;
} else {
int i = 0;
for (t=pmod->t1; t<=pmod->t2 && !*err; t++) {
if (pmod->missmask[t] != '1') {
if (na(cvar[t])) {
*err = E_MISSDATA;
} else {
ctmp[i++] = cvar[t];
}
}
}
if (!*err) {
cvals = gretl_matrix_values(ctmp, pmod->nobs, OPT_S, err);
}
free(ctmp);
}
} else {
/* no interior missing values for y or X */
for (t=pmod->t1; t<=pmod->t2 && !*err; t++) {
if (na(cvar[t])) {
*err = E_MISSDATA;
}
}
if (!*err) {
cvals = gretl_matrix_values(cvar + pmod->t1, pmod->nobs,
OPT_S, err);
}
}
return cvals;
}
static int if_eval (const char *s, DATASET *dset, void *ptr, int *err)
{
GENERATOR *ifgen = NULL;
double val = NADBL;
int ret = -1;
#if IFDEBUG
fprintf(stderr, "if_eval: s = '%s'\n", s);
#endif
while (*s == ' ') s++;
if (ptr != NULL) {
/* We're being called from a loop, with the implicit
request that the if-condition be "compiled" (if
that's not already done) and subsequently executed
without having to be evaluated from scratch.
*/
ifgen = *(GENERATOR **) ptr;
if (ifgen == NULL) {
/* Generator not compiled yet: do it now. The
flags OPT_P and OPT_S indicate that we're
generating a "private" scalar.
*/
GENERATOR **pgen = (GENERATOR **) ptr;
*pgen = ifgen = genr_compile(s, dset, OPT_P | OPT_S, err);
}
}
if (ifgen != NULL) {
val = evaluate_if_cond(ifgen, dset, err);
} else {
*err = 0;
val = generate_scalar(s, dset, err);
}
#if IFDEBUG
fprintf(stderr, "if_eval: generate returned %d\n", *err);
#endif
if (*err) {
gretl_errmsg_set(_("error evaluating 'if'"));
} else if (na(val)) {
*err = 1;
gretl_errmsg_set(_("indeterminate condition for 'if'"));
} else {
ret = (int) val;
}
#if IFDEBUG
fprintf(stderr, "if_eval: returning %d\n", ret);
#endif
return ret;
}
void CMlStaticStructLearn::CreateResultBNet(CDAG* pDAG)
{
int i, j, k, ns;
int nnodes = m_nNodes;
CDAG* iDAG = pDAG->TopologicalCreateDAG(m_vResultRenaming);
nodeTypeVector vnt;
m_pGrModel->GetNodeTypes(&vnt);
intVector na(nnodes);
const int* nas = m_pGrModel->GetNodeAssociations();
for(i=0; i<nnodes; i++) na[i] = nas[m_vResultRenaming[i]];
m_pResultBNet = CBNet::Create(nnodes, vnt.size(), &vnt.front(),
&na.front(), static_cast<CGraph*>(iDAG));
const CNodeType* nt;
int nEv = m_Vector_pEvidences.size();
CEvidence** pEv = new CEvidence*[nEv];
intVector obsnodes(nnodes);
for(i=0; i<nnodes; i++) obsnodes[i] = i;
valueVector new_data;
const Value* val;
for(i = 0 ; i < nEv; i++)
{
for(j=0; j<nnodes; j++)
{
val = m_Vector_pEvidences[i]->GetValue(m_vResultRenaming[j]);
nt = m_pResultBNet->GetNodeType(j);
if(nt->IsDiscrete())
{
new_data.push_back(*val);
}
else
{
ns = nt->GetNodeSize();
for(k=0; k<ns; k++)
new_data.push_back(*(val+k));
}
}
pEv[i] = CEvidence::Create(m_pResultBNet, nnodes, &obsnodes.front(), new_data);
new_data.clear();
}
vnt.clear();
intVector vFamily;
m_pResultBNet->AllocFactors();
for(i=0; i<nnodes; i++)
{
vFamily.clear();
iDAG->GetParents(i, &vFamily);
vFamily.push_back(i);
CCPD* iCPD = ComputeFactor(vFamily, m_pResultBNet, pEv);
m_pResultBNet->AttachFactor(iCPD);
}
for(i=0; i<nEv; i++)delete pEv[i];
delete[] pEv;
}
static int qr_make_hac (MODEL *pmod, const DATASET *dset,
gretl_matrix *XTXi)
{
gretl_matrix *X, *XOX, *V = NULL;
gretl_matrix umat;
VCVInfo vi;
int T = pmod->nobs;
int err = 0;
X = make_data_X(pmod, dset);
if (X == NULL) {
return E_ALLOC;
}
/* pmod->uhat is a full-length series: we must take an offset
into it, equal to the offset of the data on which the model
is actually estimated.
*/
gretl_matrix_init(&umat);
umat.rows = T;
umat.cols = 1;
umat.val = pmod->uhat + pmod->t1;
XOX = HAC_XOX(&umat, X, &vi, 0, &err);
if (!err) {
V = gretl_matrix_alloc(XOX->rows, XOX->rows);
if (V == NULL) {
err = E_ALLOC;
}
}
if (!err) {
gretl_matrix_qform(XTXi, GRETL_MOD_TRANSPOSE, XOX,
V, GRETL_MOD_NONE);
/* Transcribe vcv into triangular representation */
err = qr_make_vcv(pmod, V, VCV_ROBUST);
}
if (!err) {
gretl_model_set_full_vcv_info(pmod, vi.vmaj, vi.vmin,
vi.order, vi.flags,
vi.bw);
if (!na(vi.bw)) {
gretl_model_set_double(pmod, "hac_bw", vi.bw);
} else {
gretl_model_set_double(pmod, "hac_bw", (double) vi.order);
}
}
gretl_matrix_free(X);
gretl_matrix_free(XOX);
gretl_matrix_free(V);
return err;
}
static double normal_ll (const garch_container *DH)
{
double e2t, ht, ll = 0.0;
int t;
for (t=DH->t1; t<=DH->t2; t++) {
e2t = DH->e2[t];
ht = DH->h[t];
if (na(e2t) || na(ht)) {
return NADBL;
}
ll -= log(ht) + e2t / ht;
}
ll *= 0.5;
ll -= (DH->t2 - DH->t1 + 1) * LN_SQRT_2_PI;
return ll;
}
static int column_is_blank (wsheet *sheet, int k, int n)
{
int t, s = (sheet->colheads)? 1 : 0;
for (t=0; t<n; t++) {
if (!na(sheet->Z[k][s++])) {
return 0;
}
}
return 1;
}
static int cval_count (MODEL *pmod, double cvi, const double *cZ)
{
int t, cc = 0;
for (t=pmod->t1; t<=pmod->t2; t++) {
if (!na(pmod->uhat[t]) && cZ[t] == cvi) {
cc++;
}
}
return cc;
}
int transcribe_array (double *targ, const double *src,
const DATASET *dset)
{
int t, n = 0;
for (t=dset->t1; t<=dset->t2; t++) {
if (!na(src[t])) {
targ[n++] = src[t];
}
}
return n;
}
int gretl_rand_normal_full (double *a, int t1, int t2,
double mean, double sd)
{
int t;
if (na(mean) && na(sd)) {
mean = 0.0;
sd = 1.0;
} else if (na(mean) || na(sd) || sd <= 0.0) {
return E_INVARG;
}
gretl_rand_normal(a, t1, t2);
if (mean != 0.0 || sd != 1.0) {
for (t=t1; t<=t2; t++) {
a[t] = mean + a[t] * sd;
}
}
return 0;
}
int gretl_iszero (int t1, int t2, const double *x)
{
double sum = 0.0;
int t;
for (t=t1; t<=t2; t++) {
if (!na(x[t])) {
sum += x[t] * x[t];
}
}
return floateq(sum, 0.0);
}
int gretl_isint (int t1, int t2, const double *x)
{
int t, ret = 1;
for (t=t1; t<=t2; t++) {
if (!na(x[t]) && x[t] != floor(x[t])) {
ret = 0;
break;
}
}
return ret;
}
static int results_agree (MODEL *pmod, int digits, int errs, int *abort)
{
int i, j;
char v1[48], v2[48];
for (i=0; i<pmod->ncoeff; i++) {
j = find_coeff_number(pmod, tester.coeffs[i].name);
if (j < 0) {
fprintf(stderr, "%s: ERROR: Couldn't find param '%s'\n",
tester.datname, tester.coeffs[i].name);
continue;
}
if (errs == 0) {
sprintf(v1, "%#.*g", digits, tester.coeffs[i].val);
sprintf(v2, "%#.*g", digits, pmod->coeff[j]);
if (na(pmod->coeff[j])) *abort = 1;
if (doubles_differ(v1, v2)) {
char s[32];
sprintf(s, "coeff for %s", tester.coeffs[i].name);
print_result_error(digits, v1, v2, s);
return 0;
}
} else {
sprintf(v1, "%#.*g", digits, tester.coeffs[i].sderr);
sprintf(v2, "%#.*g", digits, pmod->sderr[j]);
if (na(pmod->sderr[j])) *abort = 1;
if (doubles_differ(v1, v2)) {
char s[32];
sprintf(s, "std err for %s", tester.coeffs[i].name);
print_result_error(digits, v1, v2, s);
return 0;
}
}
}
return 1;
}
void na49geomfile()
{
// Before executing this macro, the file makegeometry.C must have been executed
//
gBenchmark->Start("geometry");
TGeometry *n49 = (TGeometry *)gROOT->FindObject("na49");
if (n49) {
TFile na("na49.root", "RECREATE");
n49->Write();
na.Write();
}
gBenchmark->Show("geometry");
}
static void
real_arima_difference_series (double *dx, const double *x,
int t1, int t2, int *delta,
int k)
{
int i, p, t, s = 0;
for (t=t1; t<=t2; t++) {
dx[s] = x[t];
for (i=0; i<k && !na(dx[s]); i++) {
if (delta[i] != 0) {
p = t - i - 1;
if (p < 0 || na(x[p])) {
dx[s] = NADBL;
} else {
dx[s] -= delta[i] * x[p];
}
}
}
s++;
}
}
static void estimates_ok (MODEL *pmod)
{
int i, j;
char v1[48], v2[48];
for (i=0; i<pmod->ncoeff; i++) {
j = find_coeff_number(pmod, tester.coeffs[i].name);
if (j < 0) {
fprintf(stderr, "%s: ERROR: Couldn't find param '%s'\n",
tester.datname, tester.coeffs[i].name);
continue;
}
/* coefficients */
total_coeffs++;
sprintf(v1, "%#.*g", CHECK_DIGITS, tester.coeffs[i].val);
sprintf(v2, "%#.*g", CHECK_DIGITS, pmod->coeff[j]);
if (na(pmod->coeff[j])) {
continue;
}
if (doubles_differ(v1, v2) == 0) {
ok_coeffs++;
}
/* standard errors -- Lanczos1 is a special case */
if (strcmp(tester.datname, "Lanczos1")) {
total_sderrs++;
sprintf(v1, "%#.*g", CHECK_DIGITS, tester.coeffs[i].sderr);
sprintf(v2, "%#.*g", CHECK_DIGITS, pmod->sderr[j]);
if (na(pmod->sderr[j])) {
continue;
}
if (doubles_differ(v1, v2) == 0) {
ok_sderrs++;
}
}
}
}
static void min_max (const double *x, double *min, double *max,
int n)
{
int i;
*min = *max = x[0];
for (i=1; i<n; i++) {
if (!na(x[i])) {
if (x[i] < *min) *min = x[i];
if (x[i] > *max) *max = x[i];
}
}
}
int gretl_rand_uniform_minmax (double *a, int t1, int t2,
double min, double max)
{
int t;
if (na(min) && na(max)) {
min = 0.0;
max = 1.0;
} else if (na(min) || na(max) || max <= min) {
return E_INVARG;
}
for (t=t1; t<=t2; t++) {
if (use_dcmt) {
a[t] = to_real2(dcmt_rand32()) * (max - min) + min;
} else {
/* FIXME use native array functionality? */
a[t] = to_real2(sfmt_rand32()) * (max - min) + min;
}
}
return 0;
}
const char *series_table_get_string (series_table *st, double val)
{
const char *ret = NULL;
if (!na(val)) {
int k = val;
if (k > 0 && k <= st->n_strs) {
ret = st->strs[k-1];
}
}
return ret;
}
static void xlsx_check_top_left (xlsx_info *xinfo, int r, int c,
int stringcell, const char *s,
double x)
{
if (r == xinfo->yoffset + 1 && c == xinfo->xoffset + 1) {
/* We're in the top left cell of the reading area:
this could be blank, or could hold the first
varname, could hold "obs" or similar, or could
be the first numerical value.
*/
#if XDEBUG
fprintf(stderr, "xlsx_check_top_left: r=%d, c=%d, x=%g, stringcell=%d, "
"s='%s'\n", r, c, x, stringcell, s);
#endif
if (!na(x)) {
/* got a valid numerical value: that means we don't
have variable names on the top row */
xinfo->flags |= BOOK_AUTO_VARNAMES;
} else if (stringcell && import_obs_label(s)) {
/* blank or "obs" or similar */
xinfo->flags |= BOOK_OBS_LABELS;
xinfo->obscol = c;
}
if (!na(x) || stringcell) {
/* record the fact that the top-left corner is not empty */
xinfo->flags &= ~BOOK_TOP_LEFT_EMPTY;
}
} else if (r == xinfo->yoffset + 1 && c == xinfo->xoffset + 2) {
/* first row, second column */
if (!na(x)) {
/* got a number, not a varname */
xinfo->flags |= BOOK_AUTO_VARNAMES;
} else {
xinfo->namerow = r;
}
}
}
