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Commit a67612f2 authored by Jayant Khatkar's avatar Jayant Khatkar
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2x speed up of slowest part of cost function

parent 039bada7
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main.jl
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......@@ -6,6 +6,7 @@ using NearestNeighbors
using Statistics
using BenchmarkTools
using Plots
using LinearAlgebra
struct material
......@@ -34,6 +35,7 @@ struct voxmap
seglen::Vector{Float64}
segoffset::Vector{Float64}
segcontours::Vector{Int}
c::Number
end
......@@ -170,7 +172,7 @@ function voxmap(vox::Vector{Float64}, vox_d::Number, cdata::contourdata)
t_start = 0
if l > length(cdata.layers)
return voxmap(seglen, segoffset, segcontours)
return voxmap(seglen, segoffset, segcontours, 0)
end
for cid in cdata.layers[l]
......@@ -328,7 +330,7 @@ function voxmap(vox::Vector{Float64}, vox_d::Number, cdata::contourdata)
# for those contours find exact segments
end
return voxmap(seglen, segoffset, segcontours)
return voxmap(seglen./sum(seglen), segoffset, segcontours, Float64(segoffset ⋅ seglen)/sum(seglen))
end
......@@ -522,21 +524,85 @@ function calc_cost(rollout::Vector{Int}, cdata::contourdata, vd::voxdata, mat::m
end
function construct_cost(cdata::contourdata, vd::voxdata, mat::material)
a = 1
b = :($a + 5) # using $ 'interpolates' literal expression into the 'quoted' expression
c = :(5*5 + a)
#function construct_cost(cdata::contourdata, vd::voxdata, mat::material)
# store contour time lengths inside function
contour_times = [cdata.contours[c].time[end] for c in 1:length(cdata.contours)]
d = :($b + $c) #interpolate other expressions to form larger expressions
# considered voxels
not_empty_voxels = length.([m.seglen for m in vd.maps]) .>0
considered_voxels = (1:length(vd.below))[(vd.below.!=0) .& not_empty_voxels]
considered_voxels = considered_voxels[not_empty_voxels[vd.below[considered_voxels]]]
ex1 = :(i*2) # construct this according to voxels and contours
ex2 = quote
function cost_f(i::Int)
return $ex1
# calculate stresses at each voxel
F = (2/mat.σ̄[1,1]^2 - 1/mat.σ̄[3,3]^2)/2
G = 1/(2*mat.σ̄[3,3]^2)
L = 1/(2*mat.σ̄[1,2]^2)
M = 1/(2*mat.σ̄[1,3]^2)
# voxtimes = [:(sum($(v.seglen).*($(v.segoffset) + timestart[$(v.segcontours)]))/$(sum(v.seglen))) for v in vd.maps]
# voxtimes = voxtimes[considered_voxels]
relmaps = vd.maps[considered_voxels]
relbelows = vd.below[considered_voxels]
rel_voxels = vd.voxels[considered_voxels,:]
# trying to flatten to one equation
# n = length(relmaps)
# voxtimes = [:() for i in 1:length(vd.maps)]
# for i in 1:length(vd.maps)
# v = vd.maps[i]
# if length(v.segcontours) == 0
# continue
# end
# c = 0
# for j in 1:length(v.segcontours)
# if j == 1
# v_time = :(timestart[$(v.segcontours[j])] * $(v.seglen[j]/sum(v.seglen)))
# else
# v_time = :($v_time + timestart[$(v.segcontours[j])] * $(v.seglen[j]/sum(v.seglen)))
# end
# c += v.segoffset[j] *v.seglen[j]/sum(v.seglen)
# end
# v_time = :($v_time + $c)
# voxtimes[i] = v_time
# end
# voxtimes_expression = :[]
# voxtimes_expression.args = voxtimes
# replace!(x-> x==:() ? 0 : x, voxtimes_expression.args)
a = quote
function cost_f(rl::Vector{Int})
# println("Cumulative Sum") # 100k
timestart = cumsum([$contour_times[c] for c in rl])
#println("Vox times") # 600
voxtimes = [v.seglen ⋅ timestart[v.segcontours] + v.c for v in vd.maps]
# println("time diff") # 28k
Δt = voxtimes[considered_voxels] - voxtimes[relbelows]
#println("Temp diff") # 6k
ΔT = Tcutoff .- (Tc .+ $(T0-Tc).*ℯ.^(-k.*Δt))
# println("Temp diff clean") # 82k
replace!(x-> x<0 ? 0 : x, ΔT)
# println("Stresses") # 6k
σ11 = rel_voxels.Sx + $(mat.E*mat.α)*ΔT
σ22 = rel_voxels.Sy + $(mat.E*mat.α)*ΔT
σ33 = rel_voxels.Sz
σ12 = rel_voxels.Txy
σ23 = rel_voxels.Tyz + $((cdata.layer_height/vd.width)*mat.E*mat.α)*ΔT
σ31 = rel_voxels.Txy + $((cdata.layer_height/vd.width)*mat.E*mat.α)*ΔT
cost = sum($F * (σ11 - σ22).^2 +
$G * ((σ33 - σ11).^2 + (σ33 - σ22).^2) +
$(2 * L) * (σ12).^2 +
$(2 * M) * (σ23 + σ31).^2)
return cost
end
end
return eval(ex2) # return the contructed function
end
# return
#end
function clean_contour(c::contour)
# remove first element of array if second element is the same
......@@ -559,13 +625,13 @@ end
# ABS material properties
α_ABS = 100 # 78 - 108
E_ABS = 2.5e9 # 1.19e9 - 2.9e9
σ̄ = 3e7
α_ABS = 10e-6#100 # 78 - 108 #10-6
E_ABS = 2.5e9 # 1.19e9 - 2.9e9
σ̄ = 6e7 # mega
σ̄_ABS = [
[σ̄ σ̄*0.5 σ̄*0.5]
[σ̄*0.5 σ̄ σ̄*0.5]
[σ̄*0.5 σ̄*0.5 σ̄*0.75]
[σ̄ σ̄*0.5 σ̄*0.375]
[σ̄*0.5 σ̄ σ̄*0.375]
[σ̄*0.375 σ̄*0.375 σ̄*0.75 ]
]
ABS = material(α_ABS, E_ABS, σ̄_ABS)
......@@ -573,11 +639,11 @@ ABS = material(α_ABS, E_ABS, σ̄_ABS)
obj = "/Users/jayant/phd/tempaware/" * "M1"
contours = clean_contour.(contour.(JSON.parse(open(obj * "contours.json"))))
cdata = contourdata(contours, 5, 5) # contour data
vd = voxdata(obj * "_voxels.csv", cdata) # TODO Need to debug
stress_multiplier!(vd.voxels, 0.5)
@time vd = voxdata(obj * "_voxels.csv", cdata)
#stress_multiplier!(vd.voxels, 0.5)
rl = random_rollout(cdata)
@benchmark rl = random_rollout(cdata) # 20/second
@benchmark valid_swap(rl, rand(1:length(contours)), rand(1:length(contours)), cdata) # 1mil/second
#@benchmark rl = random_rollout(cdata) # 20/second
#@benchmark valid_swap(rl, rand(1:length(contours)), rand(1:length(contours)), cdata) # 1mil/second
calc_cost(rl, cdata, vd, ABS) # 500/second
......@@ -586,7 +652,8 @@ o_rl = copy(rl)
n = length(rl)
k = 5
cost_val = Inf
for l in 1:10
o=0
@time for l in 1:10
println(l)
println(cost_val)
costs = Dict()
......@@ -596,6 +663,7 @@ for l in 1:10
swap!(rl, i, j)
costs[i,j] = calc_cost(rl, cdata, vd, ABS)
swap!(rl, i, j)
o += 1
end
end
end
......@@ -604,4 +672,5 @@ for l in 1:10
cost_val = v
swap!(rl, i, j)
end
end
\ No newline at end of file
end
println(o)
\ No newline at end of file
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