LSST Applications 28.0.0,g1653933729+a8ce1bb630,g1a997c3884+a8ce1bb630,g28da252d5a+5bd70b7e6d,g2bbee38e9b+638fca75ac,g2bc492864f+638fca75ac,g3156d2b45e+07302053f8,g347aa1857d+638fca75ac,g35bb328faa+a8ce1bb630,g3a166c0a6a+638fca75ac,g3e281a1b8c+7bbb0b2507,g4005a62e65+17cd334064,g414038480c+5b5cd4fff3,g41af890bb2+4ffae9de63,g4e1a3235cc+0f1912dca3,g6249c6f860+3c3976f90c,g80478fca09+46aba80bd6,g82479be7b0+77990446f6,g858d7b2824+78ba4d1ce1,g89c8672015+f667a5183b,g9125e01d80+a8ce1bb630,ga5288a1d22+2a6264e9ca,gae0086650b+a8ce1bb630,gb58c049af0+d64f4d3760,gc22bb204ba+78ba4d1ce1,gc28159a63d+638fca75ac,gcf0d15dbbd+32ddb6096f,gd6b7c0dfd1+3e339405e9,gda3e153d99+78ba4d1ce1,gda6a2b7d83+32ddb6096f,gdaeeff99f8+1711a396fd,gdd5a9049c5+b18c39e5e3,ge2409df99d+a5e4577cdc,ge33fd446bb+78ba4d1ce1,ge79ae78c31+638fca75ac,gf0baf85859+64e8883e75,gf5289d68f6+e1b046a8d7,gfa443fc69c+91d9ed1ecf,gfda6b12a05+8419469a56
LSST Data Management Base Package
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MaskedImage Locators

(Return to Images)

(You might be interested to compare this example with the discussion of Image locators ; apart from an include file and a typedef, the only difference is the use of ImageT::Pixel(y, 0x1, 10) as the assigned pixel value instead of y).

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 maskedImage2.cc):

Start by including MaskedImage.h, defining a namespace for clarity:

Declare a MaskedImage

Set the image (but not the mask or variance) to a ramp

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:

(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:

(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)

The xy_loc::cached_location_t variables remember relative positions.

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

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/=

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

Note that this isn't quite the same x_iterator as before, due to the need to make the x_iterator move the underlying xy_locator.

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