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Examples

The following examples show some LEL expressions (equally valid in C++ or Glish).

Note that LEL is readonly; i.e. it does not change any value in the images given. A function in the image client has to be used to do something with the result (e.g. storing in another image).

lat1+lat2
adds 2 lattices

mean(myimage:nomask)
results in a scalar value giving the mean of the image. No mask is used for the image, thus all pixels are used. The scalar value can be used as a lattice. E.g. it can be used as the source in the image function replacemaskedpixels to set all masked-off elements of a lattice to the mean.

complex(lat1,lat2)
results in a complex lattice formed by lat1 as the real part and lat2 as the imaginary part.

min(lat1, 2*mean(lat1))
results in a lattice where lat1 is clipped at twice its mean value.

min(myimage, 2*mean(mymage[myregion]))
results in an image where myimage is clipped at twice the mean value of region myregion in the image..

lat1[lat1>2*min(lat1)]
results in a lattice with a mask. Only the pixels greater than twice the minimum are valid.

replace(lat1)
results in a lattice where each masked-off element in lat1 is replaced by 0.

iif(lat1<mean(lat1),lat1*2,lat1/2)
results in a lattice where the elements less than the mean are doubled and the elements greater or equal to the mean are divided by 2.

Here follows a sample Glish session showing some of the LEL capabilities and how Glish variables can be used in LEL.

duw01> glish -l image.g
- a := array(1:50,5,10)              # make some data
- global im1 := imagefromarray('im1', a);   # fill an image with it
- im1.shape()
[5 10]
- local pixels, mask
- im1.getregion(pixels, mask);       # get pixels and mask
- mask[1,1] := F                     # set some mask elements to False
- mask[3,4] := F
- im1.putregion(mask=mask);          # put new mask back
- global reg:=drm.box([1,1],[4,4]);  # a box region
- im2 := imagecalc(pixels='$im1[$reg]')     # read-only image applying region
- local pixels2, mask2
- im2.getregion(pixels2, mask2);     # get the pixels and mask
- print pixels2
[[1:4,]
    1 6 11 16
    2 7 12 17
    3 8 13 18
    4 9 14 19] 
- print mask2
[[1:4,]
    F T T T
    T T T T
    T T T F
    T T T T] 
- im1.replacemaskedpixels ('mean(im2)'); # replace masked-off values
- im1.getregion (pixels2, mask2);        # by mean of masked-on in im2
- print pixels2
[[1:5,]
    10.0714283 6  11 16         21 26 31 36 41 46
    2          7  12 17         22 27 32 37 42 47
    3          8  13 10.0714283 23 28 33 38 43 48
    4          9  14 19         24 29 34 39 44 49
    5          10 15 20         25 30 35 40 45 50]