double tolupp(std::string str, double sign)
{
size_t start = 0;
reltypes_et reltype;
double val1, val2, factor;
reltype = is_relative(str);
if(ABS==reltype){
// absolute tolerance value
// first number
val1 = norm_value(str,start);
//second number
val2 = norm_value(str,start);
if(isnan(val2)) return sign*abs(val1); // if only one value - negative lower bound
if(sign*val2>sign*val1) return val2;
return val1;
}else{
//relative tolerance value
factor = getfactor(reltype);
// first number
val1 = getval(str,start) * factor;
//second number
val2 = getval(str,start) * factor;
if(isnan(val2)) return sign*abs(val1); // if only one value - negative lower bound
if(sign*val2>sign*val1) return val2;
return val1;
}
}
double CSVop::getHighest(int col, vector<int> rows)
{
double maxval;
unsigned i;
if(0==rows.size()) return NAN;
maxval = norm_value(tab.Tableread(rows[0], col));
for(i=1;i<rows.size();i++){
maxval = max(maxval,norm_value(tab.Tableread(rows[i], col)));
}
return maxval;
}
double CSVop::getHighest(int col)
{
double maxval;
int i;
if(0==tab.getNorows()) return NAN;
maxval = norm_value(tab.Tableread(0, col));
for(i=1;i<getNorows();i++){
maxval = max(maxval,norm_value(tab.Tableread(i, col)));
}
return maxval;
}
double CSVop::getLowest(int col)
{
double minval;
int i;
if(0==tab.getNorows()) return NAN;
minval = norm_value(tab.Tableread(0, col));
for(i=1;i<getNorows();i++){
minval = min(minval,norm_value(tab.Tableread(i, col)));
}
return minval;
}
double CSVop::getNearest(int col, double val, vector<int> rows)
{
double minval, retval, tabval;
unsigned i;
if(0==rows.size()) return NAN;
retval = norm_value(tab.Tableread(rows[0], col));
minval = abs(retval-val);
for(i=1;i<rows.size();i++){
tabval = norm_value(tab.Tableread(rows[i], col));
if(abs(tabval-val)<minval){
minval = abs(tabval-val);
retval = tabval;
}
}
return retval;
}
double CSVop::getNearest(int col, double val)
{
double minval, retval, tabval;
int i;
if(0==tab.getNorows()) return NAN;
retval = norm_value(tab.Tableread(0, col));
minval = abs(retval-val);
for(i=1;i<getNorows();i++){
tabval = norm_value(tab.Tableread(i, col));
if(abs(tabval-val)<minval){
minval = abs(tabval-val);
retval = tabval;
}
}
return retval;
}
vector<int> CSVop::getrowswtol(vector<int> irows, int col, double val, double prec, bool absolute)
{
unsigned i;
double tabval;
vector<int> rows;
rows.clear();
if(absolute){
for(i=0;i<irows.size();i++){
tabval = norm_value(tab.Tableread(irows[i],col));
if((val-prec < tabval) && (tabval < val+prec)){
rows.push_back(irows[i]);
}
}
}else{
for(i=0;i<irows.size();i++){
tabval = norm_value(tab.Tableread(irows[i],col));
if((val*(1-prec) < tabval) && (tabval < val*(1+prec))){
rows.push_back(irows[i]);
}
}
}
return rows;
}
vector<int> CSVop::getrowswtol(int col, double val, double prec, bool absolute)
{
int i;
double tabval;
vector<int> rows;
rows.clear();
if(absolute){
for(i=0;i<tab.getNorows();i++){
tabval = norm_value(tab.Tableread(i,col));
if((val-prec < tabval) && (tabval < val+prec)){
rows.push_back(i);
}
}
}else{
for(i=0;i<tab.getNorows();i++){
tabval = norm_value(tab.Tableread(i,col));
if((val*(1-prec) < tabval) && (tabval < val*(1+prec))){
rows.push_back(i);
}
}
}
return rows;
}
vector<int> CSVop::findbestrows(vector<int> rows, datapair_t sortdata)
{
int col;
vector<int> rrows;
if(2>rows.size()) return rows;
col = tab.findcol(sortdata.fieldname, 0, 0, sortdata.namecontains,sortdata.strcontainsname);
if(sortdata.lowest){
rrows = getLowestrows(rows, col, sortdata.precision, false);
}else if(sortdata.highest){
rrows = getHighestrows(rows, col, sortdata.precision, false);
}else if(sortdata.nearest){
rrows = getNearestrows(rows, col, norm_value(sortdata.fieldentry), sortdata.precision, false);
}else{
rrows = rows;
}
return rrows;
}
static void
make_expected(void)
{
float *pe = expected;
int i, j;
for (j = 0; j < TEXTURE_HEIGHT; j++)
for (i = 0; i < TEXTURE_WIDTH; i++) {
if (comptype == SHADOW_T) {
*pe++ = shadow_compare(norm_value(pixel_value(i, j + 1)));
*pe++ = shadow_compare(norm_value(pixel_value(i + 1, j + 1)));
*pe++ = shadow_compare(norm_value(pixel_value(i + 1, j)));
*pe++ = shadow_compare(norm_value(pixel_value(i, j)));
}
else {
*pe++ = norm_value(pixel_value(i, j + 1));
*pe++ = norm_value(pixel_value(i + 1, j + 1));
*pe++ = norm_value(pixel_value(i + 1, j));
*pe++ = norm_value(pixel_value(i, j));
}
}
}
static void
make_expected(void)
{
float *pe = expected;
int i, j;
for (j = 0; j < texture_height; j++)
for (i = 0; i < texture_width; i++) {
if (comptype == SHADOW_T) {
if (use_offsets) {
*pe++ = shadow_compare(norm_value(pixel_value(i, j, 0)));
*pe++ = shadow_compare(norm_value(pixel_value(i, j, 1)));
*pe++ = shadow_compare(norm_value(pixel_value(i, j, 2)));
*pe++ = shadow_compare(norm_value(pixel_value(i, j, 3)));
} else {
*pe++ = shadow_compare(norm_value(pixel_value(i, j + 1, 0)));
*pe++ = shadow_compare(norm_value(pixel_value(i + 1, j + 1, 0)));
*pe++ = shadow_compare(norm_value(pixel_value(i + 1, j, 0)));
*pe++ = shadow_compare(norm_value(pixel_value(i, j, 0)));
}
}
else {
if (use_offsets) {
*pe++ = norm_value(pixel_value(i, j, 0));
*pe++ = norm_value(pixel_value(i, j, 1));
*pe++ = norm_value(pixel_value(i, j, 2));
*pe++ = norm_value(pixel_value(i, j, 3));
} else {
*pe++ = norm_value(pixel_value(i, j + 1, 0));
*pe++ = norm_value(pixel_value(i + 1, j + 1, 0));
*pe++ = norm_value(pixel_value(i + 1, j, 0));
*pe++ = norm_value(pixel_value(i, j, 0));
}
}
}
}
