#include <cmath>
#include <iostream>
#include <limits>
#include <memory>
using ImgStat = math::Statistics;
using MaskedVectorF = math::MaskedVector<float>;
template <typename Image>
void printStats(Image &img, math::StatisticsControl const &sctrl) {
img,
sctrl);
}
int main() {
int const wid = 1024;
MaskedImageF mimg(img.getDimensions());
MaskedVectorF mv(wid * wid);
for (int j = 0; j != img.getHeight(); ++j) {
int k = 0;
MaskedImageF::x_iterator mip = mimg.row_begin(j);
for (ImageF::x_iterator ip = img.row_begin(j); ip != img.row_end(j); ++ip) {
double const xUniform = M_PI *
static_cast<ImageF::Pixel
>(
std::rand()) / RAND_MAX;
double xLorentz = xUniform;
if (
static_cast<double>(
std::rand()) / RAND_MAX < 0.01) {
xLorentz = NAN;
}
*ip = xLorentz;
*mip = MaskedImageF::Pixel(xLorentz, (k % 2) ? 0x1 : 0x0, (k % 2) ? 1.0e99 : 1.0);
v.push_back(xLorentz);
++k;
++mip;
}
}
int j = 0;
for (MaskedVectorF::iterator mvp = mv.begin(); mvp != mv.end(); ++mvp) {
*mvp = MaskedVectorF::Pixel(v[j], (j % 2) ? 0x1 : 0x0, 10.0);
++j;
}
math::StatisticsControl sctrl;
sctrl.setNumIter(3);
sctrl.setNumSigmaClip(5.0);
sctrl.setAndMask(0x1);
sctrl.setNanSafe(true);
printStats(img, sctrl);
printStats(mimg, sctrl);
printStats(v, sctrl);
printStats(mv, sctrl);
printStats(*vF, sctrl);
sctrl.setWeighted(true);
sctrl.setAndMask(0x0);
printStats(mimg, sctrl);
return 0;
}
A class to represent a 2-dimensional array of pixels.
A class to manipulate images, masks, and variance as a single object.
Statistics makeStatistics(lsst::afw::image::Image< Pixel > const &img, lsst::afw::image::Mask< image::MaskPixel > const &msk, int const flags, StatisticsControl const &sctrl=StatisticsControl())
Handle a watered-down front-end to the constructor (no variance)
Backwards-compatibility support for depersisting the old Calib (FluxMag0/FluxMag0Err) objects.
Statistics makeStatistics(lsst::afw::image::Image< Pixel > const &img, lsst::afw::image::Mask< image::MaskPixel > const &msk, int const flags, StatisticsControl const &sctrl=StatisticsControl())
Handle a watered-down front-end to the constructor (no variance)
@ ERRORS
Include errors of requested quantities.
@ VARIANCECLIP
estimate sample N-sigma clipped variance (N set in StatisticsControl, default=3)
@ MIN
estimate sample minimum
@ STDEV
estimate sample standard deviation
@ STDEVCLIP
estimate sample N-sigma clipped stdev (N set in StatisticsControl, default=3)
@ VARIANCE
estimate sample variance
@ MEDIAN
estimate sample median
@ MAX
estimate sample maximum
@ SUM
find sum of pixels in the image
@ IQRANGE
estimate sample inter-quartile range
@ MEAN
estimate sample mean
@ MEANCLIP
estimate sample N-sigma clipped mean (N set in StatisticsControl, default=3)
@ NPOINT
number of sample points