void JCCoordinator::InitFromVarInfo()
{
DeallocateVectors();
num_time_vals = 1; // for multivariate, time variable is not supported
is_any_time_variant = false;
is_any_sync_with_global_time = false;
ref_var_index = -1;
for (int i=0; i<var_info.size(); i++) {
if (var_info[i].is_time_variant && var_info[i].sync_with_global_time) {
num_time_vals = (var_info[i].time_max - var_info[i].time_min) + 1;
if (num_time_vals < var_info[i].min.size()) {
num_time_vals = var_info[i].min.size();
}
is_any_sync_with_global_time = true;
ref_var_index = i;
break;
}
}
for (int i=0; i<var_info.size(); i++) {
if (var_info[i].is_time_variant) {
is_any_time_variant = true;
break;
}
}
AllocateVectors();
int num_var = data.size();
for (int i=0; i<num_var; i++) {
int tms_at_var = data[i].size();
for (int j=0; j<tms_at_var; j++) {
for (int k=0; k<num_obs; k++) {
data_vecs[i][j][k] = data[i][j][k];
}
}
}
//StandardizeData();
GalElement* w = weights->gal;
// get undef_tms across multi-variables
for (int v=0; v<data_vecs.size(); v++) {
for (int t=0; t<data_vecs[v].size(); t++) {
for (int i=0; i<num_obs; i++) {
undef_tms[t][i] = undef_tms[t][i] || undef_data[v][t][i];
}
// the isolates should be excluded as undefined
for (int i=0; i<num_obs; i++) {
if (w[i].Size() == 0) {
undef_tms[t][i] = true;
}
}
}
}
CalcMultiLocalJoinCount();
CalcPseudoP();
}
void DisparityTool::init( int rho, int theta, int mode, double overlap, int xo, int yo, int xr, int yr, int actR) {
_img = SetParam( rho, theta, mode, overlap, xo, yo, xr, yr );
_actRings = actR;
AllocateVectors();
LoadShiftMap();
computeCountVector( _count );
cout << "RINGS" << actR << endl;
}
BOOL CHistogram::Init32f(int numChannels, Ipp32f* ppLevels[4], Ipp32f* ppHist[4], int pnLevels[4])
{
m_numChannels = numChannels;
if (!SetMinMaxLevel(ppLevels, pnLevels)) return FALSE;
AllocateVectors(ppLevels, pnLevels);
ExpandVectors(ppLevels, ppHist, pnLevels);
UpdateHist();
ScaleLevels();
ScaleHist();
m_bInit = TRUE;
return TRUE;
}
void CHistogram::AllocateVectors(Ipp32f* ppLevels[4], int pnLevels[4])
{
SetNumLevels(ppLevels, pnLevels);
AllocateVectors();
}
/** We assume only that var_info is initialized correctly.
ref_var_index, is_any_time_variant, is_any_sync_with_global_time and
num_time_vals are first updated based on var_info */
void LisaCoordinator::InitFromVarInfo()
{
DeallocateVectors();
num_time_vals = 1;
is_any_time_variant = false;
is_any_sync_with_global_time = false;
ref_var_index = -1;
if (lisa_type != differential) {
for (int i=0; i<var_info.size(); i++) {
if (var_info[i].is_time_variant && var_info[i].sync_with_global_time) {
num_time_vals = (var_info[i].time_max - var_info[i].time_min) + 1;
is_any_sync_with_global_time = true;
ref_var_index = i;
break;
}
}
for (int i=0; i<var_info.size(); i++) {
if (var_info[i].is_time_variant) {
is_any_time_variant = true;
break;
}
}
}
AllocateVectors();
if (lisa_type == differential) {
int t=0;
for (int i=0; i<num_obs; i++) {
int t0 = var_info[0].time;
int t1 = var_info[1].time;
data1_vecs[0][i] = data[0][t0][i] - data[0][t1][i];
}
} else if (lisa_type == univariate || lisa_type == bivariate) {
for (int t=var_info[0].time_min; t<=var_info[0].time_max; t++) {
int d1_t = t - var_info[0].time_min;
for (int i=0; i<num_obs; i++) {
data1_vecs[d1_t][i] = data[0][t][i];
}
}
if (lisa_type == bivariate) {
for (int t=var_info[1].time_min; t<=var_info[1].time_max; t++) {
int d2_t = t - var_info[1].time_min;
for (int i=0; i<num_obs; i++) {
data2_vecs[d2_t][i] = data[1][t][i];
}
}
}
} else { // lisa_type == eb_rate_standardized
std::vector<bool> undef_res(num_obs, false);
double* smoothed_results = new double[num_obs];
double* E = new double[num_obs]; // E corresponds to var_info[0]
double* P = new double[num_obs]; // P corresponds to var_info[1]
// we will only fill data1 for eb_rate_standardized and
// further lisa calcs will treat as univariate
for (int t=0; t<num_time_vals; t++) {
int v0_t = var_info[0].time_min;
if (var_info[0].is_time_variant &&
var_info[0].sync_with_global_time) {
v0_t += t;
}
for (int i=0; i<num_obs; i++) E[i] = data[0][v0_t][i];
int v1_t = var_info[1].time_min;
if (var_info[1].is_time_variant &&
var_info[1].sync_with_global_time) {
v1_t += t;
}
for (int i=0; i<num_obs; i++) P[i] = data[1][v1_t][i];
bool success = GdaAlgs::RateStandardizeEB(num_obs, P, E,
smoothed_results,
undef_res);
if (!success) {
map_valid[t] = false;
map_error_message[t] << "Emprical Bayes Rate ";
map_error_message[t] << "Standardization failed.";
} else {
for (int i=0; i<num_obs; i++) {
data1_vecs[t][i] = smoothed_results[i];
}
}
}
if (smoothed_results) delete [] smoothed_results;
if (E) delete [] E;
if (P) delete [] P;
}
StandardizeData();
CalcLisa();
if (calc_significances) CalcPseudoP();
}
