main.jl 15.4 KB
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using DataFrames
using CSV
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using JSON
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using LightGraphs
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using NearestNeighbors
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using Statistics
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using BenchmarkTools
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using Plots
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struct contour
    pos
    time
end


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struct contourdata
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    contours::Vector{contour}
    G::SimpleDiGraph
    layers::Vector
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    travel_dists::Dict
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    layer_height::Number
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end


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struct voxmap
    seglen::Vector{Float64}
    segoffset::Vector{Float64}
    segcontours::Vector{Int}
end


struct voxdata
    voxels::DataFrame
    maps::Vector{voxmap}
    below::Vector{Int}
    width::Number
end


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function vecvec_to_matrix(vecvec)
    # convert vector of vectors int a matrix
    dim1 = length(vecvec)
    dim2 = length(vecvec[1])
    my_array = zeros(Float32, dim1, dim2)
    for i in 1:dim1
        for j in 1:dim2
            my_array[i,j] = vecvec[i][j]
        end
    end
    return my_array
end


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function contour(d::Dict)
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    return contour(vecvec_to_matrix(d["pos"]), d["time"])
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end
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function contourdata(cons::Vector{contour}, max_layers::Int, min_dist::Number)
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    G = LightGraphs.SimpleDiGraph(0)
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    # separate contours into layers
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    layer_heights = sort(collect(Set([c.pos[end,3] for c in cons])))
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    layers = [[] for i in 1:length(layer_heights)]
    clayeri = []
    contour_trees = []

    # place contours in layers and construct KDTree for each contour
    for i in 1:length(cons)
        l = searchsorted(layer_heights, cons[i].pos[1,3])[1]
        push!(layers[l], i)
        push!(clayeri, l)
        add_vertex!(G)
        push!(contour_trees, KDTree(transpose(cons[i].pos)))
    end

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    # loop through contours from previous layer and compare waypoints
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    for i in 1:length(cons)
        l = clayeri[i]

        # add contours from max_layers below
        if l > max_layers
            for c in layers[l-max_layers]
                add_edge!(G, c, i)
            end
        end

        if l == 1 || max_layers == 1
            continue
        end

        for c in layers[l-1]
            # if any points in contour i within min_dist of any points in contour c
            if any([length(b) > 0 for b in inrange(contour_trees[c], transpose(cons[i].pos), min_dist)])
                add_edge!(G, c, i) # mark i dependent on c
            end
        end
    end
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    return contourdata(cons, G, layers, Dict(), layer_heights[1])
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end


function seg_helper_orientation(p,q,r)
    val = (q[2]-p[2]) * (r[1]-q[1]) - (q[1]-p[1]) * (r[2]-q[2])
    if val > 0
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        return 1 # clockwise
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    elseif val < 0
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        return 2 # anticlockwise
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    else
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        return 0 # colinear
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    end
end


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function onseg(p,q,r)
    # check if q lies on segment pr assuming 3 points are colinear
    return ((q[1] <= max(p[1], r[1])) && (q[1] >= min(p[1], r[1])) &&
    (q[2] <= max(p[2], r[2])) && (q[2] >= min(p[2], r[2])))
end


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function seg_intersect(p1,q1,p2,q2)

    o1 = seg_helper_orientation(p1, q1, p2)
    o2 = seg_helper_orientation(p1, q1, q2)
    o3 = seg_helper_orientation(p2, q2, p1)
    o4 = seg_helper_orientation(p2, q2, q1)

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    if (o1  o2) && (o3  o4) ||
        o1==0 && onseg(p1, p2, q1) ||
        o2==0 && onseg(p1, q2, q1) ||
        o3==0 && onseg(p2, p1, q2) ||
        o4==0 && onseg(p2, q1, q2)
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        return true
    end

    return false
end

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dist(p1, p2) = √sum((p1 -p2).^2)
interpolate(p1, p2, xi, axis) = p1 + (p2-p1)*(xi-p1[axis])/(p2[axis]-p1[axis])
interpolate(p1, p2, x1, xi, x2) = p1 + (p2-p1)*(xi-x1)/(x2-x1)
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function voxmap(vox::Vector{Float64}, vox_d::Number, cdata::contourdata)
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    # for one vox, get all contours which pass through it
    # only need to search contours in its layer
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    l = Int(round((vox[3] + cdata.layer_height/2)/cdata.layer_height))
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    voxx1 = vox[1] + vox_d/2
    voxx2 = vox[1] - vox_d/2
    voxy1 = vox[2] + vox_d/2
    voxy2 = vox[2] - vox_d/2
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    seg_now = false
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    seglen = Vector{Number}()
    segoffset = Vector{Number}()
    segcontours = Vector{Int}()
    seglen_sofar = 0
    t_start = 0

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    for cid in cdata.layers[l]
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        c = cdata.contours[cid]
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        # check if contour passes thorough this vox
        for i in 2:size(c.pos)[1]

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            # make sure it is a line segment, not a point
            if c.pos[i-1,1:2] == c.pos[i,1:2]
                continue
            end

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            # is this line segment completely outside vox?
            if c.pos[i, 1] > voxx1 && c.pos[i-1, 1] > voxx1 ||
                c.pos[i,1] < voxx2 && c.pos[i-1, 1] < voxx2 ||
                c.pos[i,2] < voxy2 && c.pos[i-1, 2] < voxy2 ||
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                c.pos[i,2] > voxy1 && c.pos[i-1, 2] > voxy1
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                # segment outside vox entirely
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                if seg_now
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                    println("Something's gone wrong: segment entirely outside voxel, but last segment inside")
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                end
                continue
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            end
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            p1inside = c.pos[i-1, 1] < voxx1 && c.pos[i-1, 1] > voxx2 && c.pos[i-1, 2] > voxy2 && c.pos[i-1, 2] < voxy1
            p2inside = c.pos[i, 1] < voxx1 && c.pos[i,1] > voxx2 && c.pos[i,2] > voxy2 && c.pos[i,2] < voxy1
            # is this line segment completely inside vox?
            if p1inside && p2inside
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                seglen_sofar += dist(c.pos[i], c.pos[i-1]) # append to existing contour
                if !seg_now # start new seg
                    t_start = 0 #  0 bc contour must be starting for this case
                    seg_now = true

                    if i!=2
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                        println("Whole segment inside but something wrong")
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                    end
                    continue
                end
            end

            cross_side1 = seg_intersect(c.pos[i-1,:], c.pos[i,:], [voxx1, voxy1], [voxx1, voxy2])
            cross_side2 = seg_intersect(c.pos[i-1,:], c.pos[i,:], [voxx1, voxy1], [voxx2, voxy1])
            cross_side3 = seg_intersect(c.pos[i-1,:], c.pos[i,:], [voxx2, voxy1], [voxx2, voxy2])
            cross_side4 = seg_intersect(c.pos[i-1,:], c.pos[i,:], [voxx2, voxy2], [voxx1, voxy2])

            # does this line segment intersect with vox only once
            if p1inside  p2inside

                # find intersection point
                if cross_side1 || cross_side3
                    # intersection with x
                    xi = [voxx1, voxx2][[cross_side1, cross_side3]][1]
                    p_i = interpolate(c.pos[i-1,:], c.pos[i,:], xi, 1)
                    t_i = interpolate(c.time[i-1], c.time[i], c.pos[i-1,1], xi, c.pos[i,1])
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                elseif cross_side2 || cross_side4
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                    # intersection with y
                    yi = [voxy1, voxy2][[cross_side2, cross_side4]][1]
                    p_i = interpolate(c.pos[i-1,:], c.pos[i,:], yi, 2)
                    t_i = interpolate(c.time[i-1], c.time[i], c.pos[i-1,2], yi, c.pos[i,2])
                end

                if p1inside
                    # end existing segment
                    if !seg_now
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                        # contour end on the first segment
                        t_start = 0
                        seglen_sofar = 0
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                    end
                    seglen_sofar += dist(c.pos[i-1, :], p_i)
                    push!(segcontours, cid)
                    push!(seglen, seglen_sofar)
                    push!(segoffset, (t_i + t_start)/2)
                    seglen_sofar = 0
                    seg_now = false
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                else
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                    # start new contour
                    t_start = t_i
                    seglen_sofar = dist(p_i, c.pos[i, :])
                    seg_now = true
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                end
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                continue
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            elseif sum([cross_side1, cross_side2, cross_side3, cross_side4]) >= 2
                # intersects twice
                p_is = []
                t_is = []
                if cross_side1
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                    p = interpolate(c.pos[i-1,:], c.pos[i,:], voxx1, 1)
                    if !isnan(p[1])
                        push!(p_is, p)
                        push!(t_is, interpolate(c.time[i-1], c.time[i], c.pos[i-1,1], voxx1, c.pos[i,1]))
                    end
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                end
                if cross_side2
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                    p = interpolate(c.pos[i-1,:], c.pos[i,:], voxy1, 2)
                    if !isnan(p[1])
                        push!(p_is,p)
                        push!(t_is, interpolate(c.time[i-1], c.time[i], c.pos[i-1,2], voxy1, c.pos[i,2]))
                    end
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                end
                if cross_side3
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                    p = interpolate(c.pos[i-1,:], c.pos[i,:], voxx2, 1)
                    if !isnan(p[1])
                        push!(p_is,p)
                        push!(t_is, interpolate(c.time[i-1], c.time[i], c.pos[i-1,1], voxx2, c.pos[i,1]))
                    end
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                end
                if cross_side4
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                    p = interpolate(c.pos[i-1,:], c.pos[i,:], voxy2, 2)
                    if !isnan(p[1])
                        push!(p_is, p)
                        push!(t_is, interpolate(c.time[i-1], c.time[i], c.pos[i-1,2], voxy2, c.pos[i,2]))
                    end
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                end
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                if seg_now
                    print("Something's wrong")
                end

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                if length(p_is) >= 2
                    push!(segoffset, mean(t_is))
                    push!(segcontours, cid)
                    if length(p_is) == 2
                        push!(seglen, dist(p_is[1], p_is[2]))
                    else
                        push!(seglen, dist(p_is[1], p_is[3]))
                    end
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                else
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                    p1inside = c.pos[i-1, 1] <= voxx1 && c.pos[i-1, 1] >= voxx2 &&
                            c.pos[i-1, 2] >= voxy2 && c.pos[i-1, 2] <= voxy1
                    p = p1inside ? c.pos[i-1,:] : c.pos[i,:]
                    t = p1inside ? c.time[i-1] : c.time[i]

                    push!(segcontours, cid)
                    push!(segoffset, (t + t_is[1])/2)
                    push!(seglen, dist(p_is[1], p))
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                end
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            end
        end

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        # if contour ends inside the voxel
        if seg_now
            # end segment
            push!(segcontours, cid)
            push!(seglen, seglen_sofar)
            push!(segoffset, (t_start + last(c.time))/2)
            seglen_sofar = 0
            t_start = 0
            seg_now = false
        end

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        # for those contours find exact segments
    end
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    return voxmap(seglen, segoffset, segcontours)
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end

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function voxdata(fname::String, cdata::contourdata)
    voxels = DataFrames.DataFrame(CSV.File(fname))
    w = dist(Vector(voxels[1, ["x","y","z"]]), Vector(voxels[2, ["x","y","z"]]))
    vpos = [[v.x, v.y, v.z] for v in eachrow(voxels)]
    voxms = [voxmap(v, w, cdata) for v in vpos]
    below = indexin([v - [0,0,cdata.layer_height] for v in vpos], vpos)
    replace!(below, nothing=>0)
    return voxdata(voxels, voxms, below, w)
end


function random_rollout(cdata::contourdata)
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    done_contours = Set{Int}()
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    avail_contours = Set(cdata.layers[1])
    todo_contours = Set(1:length(cdata.contours))
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    rollout = Vector{Int}()

    while length(avail_contours) > 0
        c = rand(avail_contours)
        push!(rollout, c)

        # remove selected contour from todo and avail, add to done
        delete!(avail_contours, c)
        delete!(todo_contours, c)
        push!(done_contours, c)

        # update available contours
        for i in todo_contours
            if i in avail_contours
                continue
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            elseif length(inneighbors(cdata.G, i)) == 0
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                push!(avail_contours, i)
                continue
            end

            add = true
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            for j in inneighbors(cdata.G, i)
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                if !(j in done_contours)
                    add = false
                    break
                end
            end

            if add
                push!(avail_contours, i)
            end
        end
    end

    return rollout
end


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function valid_swap(rollout::Vector{Int}, i::Int, j::Int, cdata::contourdata)
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    # would swapping indices i and j in rollout result in another valid rollout?
    # NOTE THIS FUNCTION DOESNT WORK
    # IT ONLY CHECKS DEPENDENCIES TO A DEPTH OF 1
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    # TODO, leave for now, use check_validity to double check at the end
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    if i>j
        i,j = j,i
    elseif i==j
        return true
    end

    c1 = rollout[i]
    c2 = rollout[j]
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    c2_dependson = inneighbors(cdata.G, c2)
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    if c1 in c2_dependson
        return false
    end

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    c1_dependents = outneighbors(cdata.G, c1)
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    c_between = rollout[i+1:j-1]

    for c in c_between
        if c in c1_dependents || c in c2_dependson
            return false
        end
    end

    return true
end


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function check_validity(rollout::Vector{Int}, cdata::contourdata)
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    # make sure a given rollout is valid
    done_contours = Set{Int}()

    for c in rollout
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        c_dependson = inneighbors(cdata.G, c)
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        if !issubset(c_dependson, done_contours)
            return false
        end

        push!(done_contours, c)
    end
    return true
end


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function test_voxmap()
    # create vox
    vox = [0,0,0.5]
    vox_d = 2
    pos1 = [[0.5, -0.5] ones(2)*0.5 ones(2)]
    time1 = [0,1]
    pos2 = [[1.5, 0.5, -0.5, -1.5] ones(4)*0.5 ones(4)]
    time2 = Vector(0:3)
    pos3 = [[-0.5, -0.5] [2, -2] ones(2)]
    time3 = [0, 2.5]
    pos4 = [[0.5, 2.5] [-1.5, -0.5] ones(2)]
    time4 = [0,1]
    pos5 = [[-2,2] [-2,2] ones(2)]
    time5 = [0,1]
    contour1 = contour(pos1, time1)
    contour2 = contour(pos2,time2)
    contour3 = contour(pos3,time3)
    contour4 = contour(pos4,time4)
    contour5 = contour(pos5,time5)

    contours = [contour1, contour2, contour3, contour4, contour5]
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    cdata = contourdata(contours, 1, 1)
    vm = voxmap(vox, vox_d, cdata)
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    return vm
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end


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function rollout2time(rollout::Vector{Int}, cdata::contourdata)
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    # start time of each contour, assuming no travel time
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    return cumsum([cdata.contours[c].time[end] for c in rollout])
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end

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# Temperature function
T0 = 215 # extrusion temp
Tc = 25 # room temp
Tcutoff = 100 # temperature above which strain isn't happening
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k = 0.02 #value unknown
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Temp(t::Number) = Tc + (T0-Tc)*^(-k*t)
# see shape of temp function
#x = 1:100
#y = Temp.(x)
#plot(x,y)
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function calc_cost(rollout::Vector{Int}, cdata::contourdata, vd::voxdata)
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    # go from rollout to timestart for each contour
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    timestart = rollout2time(rollout, cdata)
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    # calculate time at each voxel
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    voxtimes = [sum(v.seglen.*(v.segoffset + timestart[v.segcontours]))/sum(v.seglen) for v in vd.maps]
    println("Empty voxels: ", sum(isnan.(voxtimes)))
    #replace!(voxtimes, NaN=>0)
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    # calculate temp difference from voxel below it
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    considered_voxels = (1:length(vd.below))[(below.!=0) .& (.!isnan.(voxtimes))] # cannot calculate cost is no voxel underneath
    considered_voxels = considered_voxels[.!isnan.(voxtimes[below[considered_voxels]])]
    Δt = voxtimes[considered_voxels] - voxtimes[below[considered_voxels]]
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    ΔT = Tcutoff .- Temp.(Δt)
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    # calculate stresses at each voxel

    # calculate cost func at each voxel

    # sum over the voxels
end


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function construct_cost(cdata::contourdata)
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    a = 1
    b = :($a + 5) # using $ 'interpolates' literal expression into the 'quoted' expression
    c = :(5*5 + a)

    d = :($b + $c) #interpolate other expressions to form larger expressions

    ex1 = :(i*2) # construct this according to voxels and contours
    ex2 = quote
        function cost_f(i::Int)
            return $ex1
        end
    end
    return eval(ex2) # return the contructed function
end


contours = contour.(JSON.parse(open("tensilecontours.json")))
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cdata = contourdata(contours, 5, 5) # contour data
vd = voxdata("tensile-1-1.csv", cdata)
@benchmark random_rollout(cdata)
rl = random_rollout(cdata)