LSSTApplications  19.0.0-14-gb0260a2+72efe9b372,20.0.0+7927753e06,20.0.0+8829bf0056,20.0.0+995114c5d2,20.0.0+b6f4b2abd1,20.0.0+bddc4f4cbe,20.0.0-1-g253301a+8829bf0056,20.0.0-1-g2b7511a+0d71a2d77f,20.0.0-1-g5b95a8c+7461dd0434,20.0.0-12-g321c96ea+23efe4bbff,20.0.0-16-gfab17e72e+fdf35455f6,20.0.0-2-g0070d88+ba3ffc8f0b,20.0.0-2-g4dae9ad+ee58a624b3,20.0.0-2-g61b8584+5d3db074ba,20.0.0-2-gb780d76+d529cf1a41,20.0.0-2-ged6426c+226a441f5f,20.0.0-2-gf072044+8829bf0056,20.0.0-2-gf1f7952+ee58a624b3,20.0.0-20-geae50cf+e37fec0aee,20.0.0-25-g3dcad98+544a109665,20.0.0-25-g5eafb0f+ee58a624b3,20.0.0-27-g64178ef+f1f297b00a,20.0.0-3-g4cc78c6+e0676b0dc8,20.0.0-3-g8f21e14+4fd2c12c9a,20.0.0-3-gbd60e8c+187b78b4b8,20.0.0-3-gbecbe05+48431fa087,20.0.0-38-ge4adf513+a12e1f8e37,20.0.0-4-g97dc21a+544a109665,20.0.0-4-gb4befbc+087873070b,20.0.0-4-gf910f65+5d3db074ba,20.0.0-5-gdfe0fee+199202a608,20.0.0-5-gfbfe500+d529cf1a41,20.0.0-6-g64f541c+d529cf1a41,20.0.0-6-g9a5b7a1+a1cd37312e,20.0.0-68-ga3f3dda+5fca18c6a4,20.0.0-9-g4aef684+e18322736b,w.2020.45
LSSTDataManagementBasePackage
Image Locators

(Return to Images)

Iterators provide access to an image, pixel by pixel. You often want access to neighbouring pixels (e.g. computing a gradient, or smoothing). Let's consider the problem of smoothing with a

1 2 1
2 4 2
1 2 1

kernel (the code's in image2.cc):

Start by including Image.h defining a namespace for clarity:

#include "lsst/geom.h"
namespace image = lsst::afw::image;
typedef image::Image<int> ImageT;
int main() {

Declare an Image

ImageT in(lsst::geom::Extent2I(10, 6));

Set the image to a ramp

for (int y = 0; y != in.getHeight(); ++y) {
for (ImageT::xy_locator ptr = in.xy_at(0, y), end = in.xy_at(in.getWidth(), y); ptr != end;
++ptr.x()) {
*ptr = y;
}
}

That didn't gain us much, did it? The code's a little messier than using x_iterator. But now we can add code to calculate the smoothed image. First make an output image, and copy the input pixels:

//
// Convolve with a pseudo-Gaussian kernel ((1, 2, 1), (2, 4, 2), (1, 2, 1))
//
ImageT out(in.getDimensions()); // Make an output image the same size as the input image
out.assign(in);

(we didn't need to copy all of them, just the ones around the edge that we won't smooth, but this is an easy way to do it).

Now do the smoothing:

for (int y = 1; y != in.getHeight() - 1; ++y) {
for (ImageT::xy_locator ptr = in.xy_at(1, y), end = in.xy_at(in.getWidth() - 1, y),
optr = out.xy_at(1, y);
ptr != end; ++ptr.x(), ++optr.x()) {
*optr = ptr(-1, -1) + 2 * ptr(0, -1) + ptr(1, -1) + 2 * ptr(-1, 0) + 4 * ptr(0, 0) +
2 * ptr(1, 0) + ptr(-1, 1) + 2 * ptr(0, 1) + ptr(1, 1);
}
}

(N.b. you don't really want to do this; not only is this kernel separable into 1 2 1 in first the x then the y directions, but lsst::afw::math can do convolutions for you).

Here's a faster way to do the same thing (the use of an Image::Ptr is just for variety)

//
// Do the same thing a faster way, using cached_location_t
//
std::shared_ptr<ImageT> out2(new ImageT(in.getDimensions()));
out2->assign(in);
typedef ImageT::const_xy_locator xy_loc;
for (int y = 1; y != in.getHeight() - 1; ++y) {
// "dot" means "cursor location" in emacs
xy_loc dot = in.xy_at(1, y), end = in.xy_at(in.getWidth() - 1, y);
xy_loc::cached_location_t nw = dot.cache_location(-1, -1);
xy_loc::cached_location_t n = dot.cache_location(0, -1);
xy_loc::cached_location_t ne = dot.cache_location(1, -1);
xy_loc::cached_location_t w = dot.cache_location(-1, 0);
xy_loc::cached_location_t c = dot.cache_location(0, 0);
xy_loc::cached_location_t e = dot.cache_location(1, 0);
xy_loc::cached_location_t sw = dot.cache_location(-1, 1);
xy_loc::cached_location_t s = dot.cache_location(0, 1);
xy_loc::cached_location_t se = dot.cache_location(1, 1);
for (ImageT::x_iterator optr = out2->row_begin(y) + 1; dot != end; ++dot.x(), ++optr) {
*optr = dot[nw] + 2 * dot[n] + dot[ne] + 2 * dot[w] + 4 * dot[c] + 2 * dot[e] + dot[sw] +
2 * dot[s] + dot[se];
}
}

The xy_loc::cached_location_t variables remember relative positions.

We can rewrite this to move setting nw, se etc. out of the loop:

//
// Do the same calculation, but set nw etc. outside the loop
//
xy_loc pix11 = in.xy_at(1, 1);
xy_loc::cached_location_t nw = pix11.cache_location(-1, -1);
xy_loc::cached_location_t n = pix11.cache_location(0, -1);
xy_loc::cached_location_t ne = pix11.cache_location(1, -1);
xy_loc::cached_location_t w = pix11.cache_location(-1, 0);
xy_loc::cached_location_t c = pix11.cache_location(0, 0);
xy_loc::cached_location_t e = pix11.cache_location(1, 0);
xy_loc::cached_location_t sw = pix11.cache_location(-1, 1);
xy_loc::cached_location_t s = pix11.cache_location(0, 1);
xy_loc::cached_location_t se = pix11.cache_location(1, 1);
for (int y = 1; y != in.getHeight() - 1; ++y) {
// "dot" means "cursor location" in emacs
xy_loc dot = in.xy_at(1, y), end = in.xy_at(in.getWidth() - 1, y);
for (ImageT::x_iterator optr = out2->row_begin(y) + 1; dot != end; ++dot.x(), ++optr) {
*optr = dot[nw] + 2 * dot[n] + dot[ne] + 2 * dot[w] + 4 * dot[c] + 2 * dot[e] + dot[sw] +
2 * dot[s] + dot[se];
}
}

You may have noticed that that kernel isn't normalised. We could change the coefficients, but that'd slow things down for integer images (such as the one here); but we can normalise after the fact by making an Image that shares pixels with the central part of out2 and manipulating it via overloaded operator/=

//
// Normalise the kernel. I.e. divide the smoothed parts of image2 by 16
//
{
ImageT center = ImageT(
*out2,
center /= 16;
}

N.b. you can use the iterator embedded in the locator directly if you really want to, e.g.

for (int y = 0; y != in.getHeight(); ++y) {
for (ImageT::xy_x_iterator ptr = in.xy_at(0, y).x(), end = in.xy_at(in.getWidth(), y).x(); ptr != end;
++ptr) {
*ptr = 0;
}
}

we called the iterator xy_x_iterator, not x_iterator, for consistency with MaskedImage.

Finally write some output files and close out main():

//
// Save those images to disk
//
out.writeFits("foo.fits");
out2->writeFits("foo2.fits");
return 0;
}
y
int y
Definition: SpanSet.cc:49
lsst::afw::image
Backwards-compatibility support for depersisting the old Calib (FluxMag0/FluxMag0Err) objects.
Definition: imageAlgorithm.dox:1
lsst::afw::image::LOCAL
@ LOCAL
Definition: ImageBase.h:94
std::shared_ptr< ImageT >
Image.h
lsst::jointcal.check_logged_chi2.main
def main()
Definition: check_logged_chi2.py:272
end
int end
Definition: BoundedField.cc:105
lsst::afw.display.ds9.dot
def dot(symb, c, r, frame=None, size=2, ctype=None, origin=afwImage.PARENT, *args, **kwargs)
Definition: ds9.py:101
image
afw::table::Key< afw::table::Array< ImagePixelT > > image
Definition: HeavyFootprint.cc:216
ptr
uint64_t * ptr
Definition: RangeSet.cc:88
lsst::geom::Point< int, 2 >
lsst::geom::Box2I
An integer coordinate rectangle.
Definition: Box.h:55
w
double w
Definition: CoaddPsf.cc:69
lsst::afw::image::Image
A class to represent a 2-dimensional array of pixels.
Definition: Image.h:58
lsst::geom::Extent< int, 2 >
geom.h