10 :
std::vector<double>() {
16 this->reserve(nScales);
17 const double sc = (minScale == maxScale ? minScale : (minScale +
maxScale) / 2.0);
22 this->reserve(nScales);
23 const double step = (maxScale -
minScale) / (nScales - 1);
25 for (
unsigned i = 1;
i < nScales - 1; ++
i)
26 push_back(minScale +
i * step);
33 :
std::vector<double>() {
35 if (!(minScale > 0.0 && maxScale > 0.0))
37 "In npstat::EquidistantInLogSpace constructor: " 38 "minimum and maximum scales must be positive");
44 this->reserve(nScales);
45 const double sc = (minScale == maxScale ? minScale :
sqrt(minScale * maxScale));
50 this->reserve(nScales);
51 const double logmax =
log(maxScale);
52 const double logmin =
log(minScale);
53 const double logstep = (logmax - logmin) / (nScales - 1);
55 for (
unsigned i = 1;
i < nScales - 1; ++
i)
56 push_back(
exp(logmin +
i * logstep));
EquidistantInLinearSpace()=delete
Equidistant sequences of points in either linear or log space.
Exceptions for the npstat namespace.
EquidistantInLogSpace()=delete