utils.jl 17.7 KB
Newer Older
1
2
3
4
5
6
7
8
9
using DataFrames
using CSV
using JSON
using LightGraphs
using NearestNeighbors
using Statistics
using BenchmarkTools
using Plots
using LinearAlgebra
10
import Plots: plot, plot!
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573


struct material
    α::Number
    E::Number
    σ̄::AbstractArray{Number, 2} # Yield stress \sigma\bar
    T_cutoff::Number
end


mutable struct contour
    pos
    time
end


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


struct voxmap
    seglen::Vector{Float64}
    segcontours::Vector{Int}
    c::Number
end


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


struct tempdecay
    extrusion::Number
    ambient::Number
    decay_rate::Number
end


function visualise_tempdecay(td::tempdecay; tmax=200)
    Temp(t::Number) = td.ambient + (td.extrusion-td.ambient)*^(-td.decay_rate*t)
    plot(Temp, 0, tmax)
end


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


function contour(d::Dict)
    return contour(vecvec_to_matrix(d["pos"]), d["time"])
end


function contourdata(cons::Vector{contour}, max_layers::Int, min_dist::Number)
    G = LightGraphs.SimpleDiGraph(0)

    # separate contours into layers
    layer_heights = sort(collect(Set([c.pos[end,3] for c in cons])))
    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

    # loop through contours from previous layer and compare waypoints
    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

    return contourdata(cons, G, layers, Dict(), layer_heights[1])
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
        return 1 # clockwise
    elseif val < 0
        return 2 # anticlockwise
    else
        return 0 # colinear
    end
end


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


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)

    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)
        return true
    end

    return false
end


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)


function voxmap(vox::Vector{Float64}, vox_d::Number, cdata::contourdata)

    # for one vox, get all contours which pass through it
    # only need to search contours in its layer
    l = Int(round((vox[3] + cdata.layer_height/2)/cdata.layer_height))
    voxx1 = vox[1] + vox_d/2
    voxx2 = vox[1] - vox_d/2
    voxy1 = vox[2] + vox_d/2
    voxy2 = vox[2] - vox_d/2

    seg_now = false
    seglen = Vector{Number}()
    segoffset = Vector{Number}()
    segcontours = Vector{Int}()
    seglen_sofar = 0
    t_start = 0

    if l > length(cdata.layers)
        return voxmap(seglen, segcontours, 0)
    end

    for cid in cdata.layers[l]

        c = cdata.contours[cid]

        # check if contour passes thorough this vox
        for i in 2:size(c.pos)[1]

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

            # 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 ||
                c.pos[i,2] > voxy1 && c.pos[i-1, 2] > voxy1

                # segment outside vox entirely
                if seg_now
                    println("Something's gone wrong: segment entirely outside voxel, but last segment inside")
                end
                continue
            end

            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

                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
                        println("Whole segment inside but something wrong")
                    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])
                elseif cross_side2 || cross_side4
                    # 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
                        # contour end on the first segment
                        t_start = 0
                        seglen_sofar = 0
                    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
                else
                    # start new contour
                    t_start = t_i
                    seglen_sofar = dist(p_i, c.pos[i, :])
                    seg_now = true
                end
                continue

            elseif sum([cross_side1, cross_side2, cross_side3, cross_side4]) >= 2
                # intersects twice
                p_is = []
                t_is = []
                if cross_side1
                    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
                end
                if cross_side2
                    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
                end
                if cross_side3
                    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
                end
                if cross_side4
                    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
                end

                if seg_now
                    print("Something's wrong")
                end

                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
                else
                    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))
                end
            end
        end

        # 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

        # for those contours find exact segments
    end
    c = Float64(segoffset  seglen)/sum(seglen) # constant used for cost calc
    new_seglen = Vector{Float64}()
    new_segcontours = Vector{Int64}()
    for i in 1:length(segcontours)
        if !(segcontours[i] in new_segcontours)
            push!(new_segcontours, segcontours[i])
            push!(new_seglen, sum(seglen[segcontours.==segcontours[i]]))
        end
    end
    return voxmap(new_seglen./sum(new_seglen), new_segcontours, c)
end


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"]]))
    println("Assumed width ", w)
    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)
    done_contours = Set{Int}()
    avail_contours = Set(cdata.layers[1])
    todo_contours = Set(1:length(cdata.contours))
    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
            elseif length(inneighbors(cdata.G, i)) == 0
                push!(avail_contours, i)
                continue
            end

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

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

    return rollout
end


function valid_swap(rollout::Vector{Int}, i::Int, j::Int, cdata::contourdata)
    # 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
    # TODO, leave for now, use check_validity to double check at the end

    if i>j
        i,j = j,i
    elseif i==j
        return true
    end

    c1 = rollout[i]
    c2 = rollout[j]
    c2_dependson = inneighbors(cdata.G, c2)

    if c1 in c2_dependson
        return false
    end

    c1_dependents = outneighbors(cdata.G, c1)
    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


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

    for c in rollout
        c_dependson = inneighbors(cdata.G, c)

        if !issubset(c_dependson, done_contours)
            return false
        end

        push!(done_contours, c)
    end
    return true
end


function swap!(rollout::Vector{Int}, i::Int, j::Int)
    # swap values at ith and jth indices
    rollout[i], rollout[j] = rollout[j], rollout[i]
end


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]
    cdata = contourdata(contours, 1, 1)
    vm = voxmap(vox, vox_d, cdata)
    return vm
end


function clean_contour(c::contour)
    # remove first element of array if second element is the same
    while c.pos[1,:] == c.pos[2,:]
        c.pos = c.pos[2:end, :]
    end
    return c
end


function stress_multiplier!(a::DataFrame, mul::Number)
    a.Sx = a.Sx*mul
    a.Sy = a.Sy*mul
    a.Sz = a.Sz*mul
    a.Txy = a.Txy*mul
    a.Tyz = a.Tyz*mul
    a.Txz = a.Txz*mul
    return
end


function construct_cost(cdata::contourdata, vd::voxdata, mat::material, td::tempdecay, fname::Symbol=:cost_f)
    contour_times = [cdata.contours[c].time[end] for c in 1:length(cdata.contours)]

    # considered voxels
    not_empty_voxels = length.([m.seglen for m in vd.maps]) .>0
    valid_voxels = (1:length(vd.below))[(vd.below.!=0) .& not_empty_voxels]
    valid_voxels = valid_voxels[not_empty_voxels[vd.below[valid_voxels]]]

    considered_voxels = valid_voxels
    relbelows = vd.below[valid_voxels]
    rel_voxels = vd.voxels[considered_voxels,:]
    relmaps = vd.maps

    # voxtimes vectorize
    max_contours_per_voxel = maximum([length(r.seglen) for r in relmaps])
    vox_contour_id = ones(Int64, length(relmaps), max_contours_per_voxel)
    for i in 1:length(relmaps)
        vox_contour_id[i, 1:length(relmaps[i].segcontours)] = relmaps[i].segcontours
    end
    vox_c = [Float64(v.c) for v in relmaps]
    vox_seglen = zeros(length(relmaps), max_contours_per_voxel)
    for i in 1:length(relmaps)
        vox_seglen[i, 1:length(relmaps[i].seglen)] = relmaps[i].seglen
    end

    # precompute constant values
    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)

    a = quote
        function $fname(rl::Vector{Int})
            # voxel times
            timestart = cumsum([$contour_times[c] for c in rl])
            voxtimes = sum($vox_seglen .* timestart[$vox_contour_id], dims=2) .+ $vox_c

            # voxel temps
            Δt = voxtimes[$considered_voxels] - voxtimes[$relbelows]
            ΔT = $(mat.T_cutoff.-td.ambient) .- $(td.extrusion-td.ambient).*.^(-$td.decay_rate.*Δt)
            replace!(x-> x<0 ? 0 : x, ΔT)

            # voxel stresses
            rel_v= $rel_voxels
            σ11 = rel_v.Sx + $(mat.E*mat.α)*ΔT
            σ22 = rel_v.Sy + $(mat.E*mat.α)*ΔT
            σ33 = rel_v.Sz
            σ12 = rel_v.Txy
            σ23 = rel_v.Tyz + $((cdata.layer_height/vd.width)*mat.E*mat.α)*ΔT
            σ31 = rel_v.Txy + $((cdata.layer_height/vd.width)*mat.E*mat.α)*ΔT
            return sum($F * (σ11 - σ22).^2 +
                $G * ((σ33 - σ11).^2 + (σ33 - σ22).^2) +
                $(2 * L) * (σ12).^2 +
                $(2 * M) * (σ23 + σ31).^2)
        end
    end
    return eval(a)
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
end


function plot(vd::voxdata, i::Int, cdata::contourdata)
    vm = vd.maps[i]
    loc = Array(vd.voxels[i, ["x", "y", "z"]])
    w = vd.width/2

    sq_x = [loc[1]-w, loc[1]-w, loc[1]+w, loc[1]+w, loc[1]-w]
    sq_y = [loc[2]+w, loc[2]-w, loc[2]-w, loc[2]+w, loc[2]+w]

    plt = plot(sq_x, sq_y, aspect_ratio=:equal, label="Voxel", lw=3, color="black")
    for (c,l) in zip(vm.segcontours, vm.seglen)
        plot!(plt,
            cdata.contours[c].pos[:,1],
            cdata.contours[c].pos[:,2],
            label=l)
    end
    plt
593
end