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# Requires installation of [GLMakie](https://github.com/JuliaPlots/Makie.jl) | |
# Include this file as include("eigshow.jl"), then run eigshow() | |
using GLMakie, LinearAlgebra, Printf | |
# Toby Driscoll (driscoll@udel.edu), October 2021. Released under Creative Commons CC BY-NC 3.0 license. | |
# This function is inspired by EIGSHOW.M, which is held in copyright by The MathWorks, Inc and found at: | |
# Cleve Moler (2021). Cleve_Lab (https://www.mathworks.com/matlabcentral/fileexchange/59085-cleve_lab), MATLAB Central File Exchange. Retrieved October 25, 2021. | |
""" | |
eigshow() | |
Demonstrator of geometric intuition behind eigenvectors and singular vectors. | |
A figure opens showing a vector π₯ on the unit circle and its image π΄π₯ via a given 2x2 matrix π΄. | |
As you move the mouse around the circle, the image vectors trace out an ellipse. Click the mouse | |
to leave a marker for the current source and image vectors. | |
An eigenvector occurs when π΄π₯ and π₯ are parallel, and the associated eigenvalue is the multiplier. | |
When the toggle is moved to select "svd", then the images of two vectors π₯ and π¦ are shown while | |
π₯ and π¦ are kept perpendicular. When the image vectors are also perpendicular, then you are seeing | |
all of the left and right singular vectors. | |
The left panel includes a selector of different matrices. Some things to observe: Is the number of | |
eigenvectors (not counting trivial sign flips) the same in all cases? What about the singular vectors? | |
Does either set of vectors have any correspondence to the image ellipse? | |
""" | |
function eigshow() | |
fig = Figure(resolution=(1200,800)) | |
palette = cgrad(:seaborn_colorblind)[1:8] | |
ax = Axis(fig[1,2], | |
aspect=AxisAspect(1), | |
limits=((-1.6,1.6),(-1.6,1.6)), | |
xrectzoom=false,yrectzoom=false, | |
xpanlock=true,ypanlock=true, | |
titlesize=30, | |
title="" | |
) | |
# create matrix menu | |
mtx = [[5 0;0 3]/4, [5 0;0 -3]/4, [1 0;0 1], [0 1;1 0], [0 1;-1 0], [1 3;4 2]/4, [1 3;2 4]/4, [3 1;4 2]/4, [3 1;-2 4]/4, [2 4;2 4]/4,[2 4;-1 -2]/4, [6 4;-1 2]/4, nothing] | |
get_matrix(i) = i < 13 ? mtx[i] : 0.75*randn(2,2) | |
label = [ "[5 0;0 3]/4", "[5 0;0 -3]/4", "[1 0;0 1]", "[0 1;1 0]", "[0 1;-1 0]", "[1 3;4 2]/4", "[1 3;2 4]/4", "[3 1;4 2]/4", "[3 1;-2 4]/4", "[2 4;2 4]/4","[2 4;-1 -2]/4", "[6 4;-1 2]/4", "random" ] | |
menu = Menu(fig, options=zip(label,mtx),textsize=26,i_selected=6) | |
# nodes that define the primary values | |
A = @lift( get_matrix($(menu.i_selected)) ) | |
x = Observable([1.0,0.0]) | |
y = @lift([-$x[2],$x[1]]) | |
# pretty-print the matrix for the left panel | |
function sprint_matrix(B) | |
if Rational(B[1]).den > 99 | |
return @sprintf(" %5.2f %5.2f \n %5.2f %5.2f",B[[1,3,2,4]]...) | |
else | |
s = sprint.(show,Rational.(B[[1,3,2,4]])) | |
a,b,c,d = replace.(s,"//"=>"/") | |
s = " $a $b\n $c $d" | |
s = replace(s," -"=>"-") | |
return replace(s,r"(\S+)/1"=>s" \1 ") | |
end | |
end | |
A_lbl = Label(fig,@lift(sprint_matrix($A)),textsize=30,font="mono") | |
# toggle for eigen/svd | |
toggle = Toggle(fig; active=false) | |
labels = [Label(fig,"eigen",textsize=26),Label(fig,"svd",textsize=26)] | |
# widget panel | |
panel = fig[1,1] = vgrid!( | |
Label(fig,"Choose a matrix",height=30,valign=:bottom,textsize=26), | |
menu, | |
A_lbl, | |
hgrid!(labels[1],toggle,labels[2], tellheight=false), | |
) | |
# sets up all the visuals for either vector x, y | |
function setup_show(v,c,t) | |
vals = Observable{Vector{typeof(v[])}}([]) | |
dots = scatter!(@lift(Point2.($vals)),color=c[1],markersize=4) | |
Avals = Observable{Vector{typeof(v[])}}([]) | |
Adots = scatter!(@lift(Point2.($Avals)),color=c[2],markersize=4) | |
arr = arrows!(ax,[Point2(0.,0.)],@lift([Vec2($v)]),color=c[1],linewidth=5,arrowsize=20) | |
arrA = arrows!(ax,[Point2(0.,0.)],@lift([Vec2($A*$v)]),color=c[2],linewidth=5,arrowsize=20) | |
txt = text!(L"%$t",position=@lift(Tuple(1.08*$v).+(0.05,0.05)),color=c[1],textsize=36) | |
txtA = text!(L"A%$t",position=@lift(Tuple(1.08*$A*$v).+(0.05,0.05)),color=c[2],textsize=36) | |
marked = Observable{Vector{typeof(x[])}}([]) | |
scat = scatter!(@lift(Point2.($marked)),color=c[3],markersize=18) | |
return vals,Avals,marked,(;arr,arrA,txt,txtA,scat) | |
end | |
# create the visuals: source traces, image traces, marked values, visible objects | |
x_vals,x_Avals,x_marked,x_obj = setup_show(x,palette,"x") | |
y_vals,y_Avals,y_marked,y_obj = setup_show(y,palette,"y") | |
# listen when mouse button is clicked: add a marked point | |
on(events(fig).mousebutton, priority=1) do event | |
if event.button == Mouse.left | |
if event.action == Mouse.press | |
else | |
if norm(mouseposition(ax.scene)) < 1.5 | |
append!(x_marked[],[x[],A[]*x[]]) | |
#append!(y_marked[],[y[],A[]*y[]]) | |
notify.((x_marked,y_marked)) | |
end | |
end | |
end | |
# Do not consume the event | |
return Consume(false) | |
end | |
# listen when the pointer is moved: add dots to traces | |
on(events(fig).mouseposition) do event | |
z = mouseposition(ax.scene) | |
if norm(z) < 1.5 | |
x[] = normalize(z) | |
push!(x_vals[],x[]) | |
push!(x_Avals[],A[]*x[]) | |
push!(y_vals[],y[]) | |
push!(y_Avals[],A[]*y[]) | |
notify.((x_vals,x_Avals,y_vals,y_Avals)) | |
end | |
return Consume(false) | |
end | |
# clear the dot trails | |
function clear_dots(dummy) | |
obj = (x_vals,x_Avals,x_marked,y_vals,y_Avals,y_marked) | |
[ deleteat!(foo[],eachindex(foo[])) for foo in obj] | |
notify.(obj) | |
end | |
# listen when a matrix is selected | |
on(clear_dots,menu.i_selected) | |
# listen for change in the toggle | |
on(toggle.active) do value | |
if value | |
ax.title = "Make π΄π₯ perpendicular to π΄π¦" | |
[ u.visible = true for u in values(y_obj) ] | |
else | |
ax.title = "Make π΄π₯ parallel to π₯" | |
[ u.visible = false for u in values(y_obj) ] | |
end | |
clear_dots(nothing) | |
end | |
# notify initial state | |
toggle.active[] = false | |
return fig | |
end |
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