LSST Applications 30.0.7,g0e76e35be5+e8e946ae08,g19811a7679+138f7293ba,g199a45376c+5e234f8357,g1fd858c14a+2f48dbc4c4,g262e1987ae+fb36cac54d,g29ae962dfc+d9108a0941,g2c21b0017a+4f59a27f16,g31e44d4a5c+b0138be388,g33ac35c1f1+28b9f72785,g35bb328faa+b0138be388,g40c9b15c53+823ad735c1,g47891489e3+bcc48a0b46,g53246c7159+b0138be388,g64539dfbff+e8e946ae08,g67b6fd64d1+bcc48a0b46,g74acd417e5+422380537a,g76965917b2+a5ca99c4d9,g786e29fd12+796b79145d,g7aefaa3e3d+dc0c200193,g86b635cae8+734fe384f0,g87389fa792+d8b5378923,g89139ef638+bcc48a0b46,g8bbb235e95+3f4f7f9447,g8ea07a8fe4+78a4c88802,g9290983e33+ffdc83c6f7,g92c671f44c+e8e946ae08,gaa753fd333+03f406da14,gbf99507273+b0138be388,gc49b57b85e+8df26ee1f0,gca7fc764a6+bcc48a0b46,gd7ef33dd92+bcc48a0b46,gdab6d2f7ff+422380537a,ge1c02a5578+b0138be388,ge410e46f29+bcc48a0b46,ge80df9fc40+e6db5413d1,geaed405ab2+1de65a85c6,gf5dcc679e7+35a0ce2edd,gf5f1c85443+e8e946ae08
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():