Shear transformation

[Mattriks]

This PR:

• Closes Affine transformations #115 (Rotation, Reflection and Shearing are the 3 main transformations)
• Adds example test to examples/transformations.jl
• Adds gallery example + documentation

set_default_graphic_size(15cm, 5cm)

f_points = [(.1, .1), (.9, .1), (.9, .2), (.2, .2), (.2, .4), (.6, .4),
    (.6, .5), (.2, .5), (.2, .9), (.1, .9), (.1, .1)]
f_points = (x->0.5.*x.+0.3).(f_points)

ctxl(θ, x, y) = (context(rotation=Rotation(θ, x, y)), circle(x,y, 0.01), 
    line([(x-0.5,y),(x+0.5,y)]))
fpoly(c::String) = (context(),  polygon(f_points), fill(c) )
ctxf(θ, ϕ, s, x, y,c) = (context(rotation=Rotation(-θ, x, y), 
        shear=Shear(s, ϕ, x, y)), fpoly(c))

x, y, θ  = 0.5, 0.5, -π/6

img1 = compose(context(), stroke("black"), ctxl(θ,x,y),  ctxf(0,0,0,x,y, "yellow"),
#    (context(), arc(x,y,0.3,π+θ,π-0.15), arrow())
)
img2 = compose(context(), stroke("black"), ctxl(0,x,y),
    ctxf(θ,0,1.8,x,y,"transparent"), ctxf(θ,0,0,x,y,"yellow"),
    text(0.5, 0.1, "x' = x+y*shear", hcenter, vcenter) )
img3 = compose(context(), stroke("black"), 
    ctxl(θ, x, y), ctxf(0,θ,1.8,x,y,"yellow") )

hstack(img1, img2, img3)

[codecov-io]

Codecov Report

Merging #333 into master will increase coverage by 0.26%.
The diff coverage is 88.23%.

@@            Coverage Diff            @@
##           master    #333      +/-   ##
=========================================
+ Coverage   32.54%   32.8%   +0.26%     
=========================================
  Files          18      18              
  Lines        3073    3088      +15     
=========================================
+ Hits         1000    1013      +13     
- Misses       2073    2075       +2

Impacted Files	Coverage Δ
src/Compose.jl	12.04% <ø> (ø)	⬆️
src/container.jl	44.85% <100%> (+0.68%)	⬆️
src/measure.jl	40.33% <83.33%> (+4.82%)	⬆️

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[gregconner]

It would be easy to add an option to multiply a context by a 2x2 matrix instead of making users who are interested in this feature decompose their matrix into a product of elementary matrices and then rewrite those as reflections, shears and scalings. I can write the code if you would like.

[Mattriks]

@gregconner An interesting suggestion! Yes we're happy to look at PRs