DM-23624: Get MEDIAN_PER_ROW overscan correction moved to afw, or find numpy replacement #212
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czwa
changed the title
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That .1s is presumably per-amp, right? So this is actually more like a ~2s speedup for the full chip? If so, this is wonderful news! If not, I'm super sorry that I said this was a big deal if it really was only 0.1s total 😬 |
Yes, sorry. The numbers are per-amp. |
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This looks great! I would suggest renaming the PR subject for clarity about what's going on here (we have not moved it to afw, nor have we found a numpy replacement!). |
| afw::math::StatisticsControl statControl; | ||
| statControl.setAndMask(overscan.getMask()->getPlaneBitMask(badPixelMask)); | ||
| const int x0 = overscan.getX0(); | ||
| const int y0 = overscan.getY0(); |
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I suggest moving some things outside of the loop, so that objects won't keep being built on each iteration, and it will allow you to eliminate the branch in the loop (which branch prediction should be good about after a few iterations, but why not make it easier?
auto origin = geom::Point2I(x0 + x, y0);
geom::Extent2I shifter;
geom::Extent2I extents;
if (isTransposed) {
shifter = geom::Extent2I(1, 0);
extents = geom::Extent2I(1, height);
} else {
shifter = geom::Extent2I(0,1);
extents = geom::Extent2I(width, 1);
}
for (int x = 0; x < length; ++x) {
MaskedImage mi = MaskedImage(overscan, geom::Box2I(origin, extents));
values[x] = afw::math::makeStatistics(mi, afw::math::MEDIAN, statControl).getValue():
origin.shift(shifter);
}
| void fitOverscanImage( | ||
| std::shared_ptr<lsst::afw::math::Function1<FunctionT> > &overscanFunction, | ||
| template<typename ImagePixelT> | ||
| std::vector<double> fitOverscanImage( |
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Are you sure no one is going to want this interface?
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The one that's being replaced? I don't think anyone even noticed it was there until I found it last week.
Repurpose unused fitOverscanImage function for MEDIAN_PER_ROW.
This was already written as a pybind11 wrapped C++ function, but was unused in
ip_isr. This changes the function to calculate the MEDIAN_PER_ROW method, improving processing time significantly (from ~.1s to ~1e-3s).