Sat, 04 Dec 2021 09:12:46 +0200
Update metadata to Julia 1.7 format
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Denoising routine for testing + visualisation tools
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1 | ################################################## |
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2 | # Visualising and data-collecting iteration tools |
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3 | ################################################## |
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4 | |
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5 | module Visualise |
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6 | |
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7 | using Printf |
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8 | using FileIO |
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9 | using Setfield |
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10 | #using Plots |
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11 | #using Measures |
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12 | import GR |
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13 | |
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14 | using AlgTools.Util |
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15 | using AlgTools.StructTools |
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16 | using AlgTools.LinkedLists |
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Use Channel comms helper tools form AlgTools.
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17 | using AlgTools.Comms |
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Add ColourTools for colourmapped images
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18 | using ..ColourTools |
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19 | |
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20 | ############## |
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21 | # Our exports |
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22 | ############## |
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23 | |
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24 | export LogEntry, |
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25 | bg_visualise, |
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26 | visualise, |
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27 | secs_ns, |
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28 | iterate_visualise, |
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29 | initialise_visualisation, |
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30 | finalise_visualisation |
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31 | |
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32 | ################## |
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33 | # Data structures |
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34 | ################## |
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35 | |
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36 | struct LogEntry <: IterableStruct |
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37 | iter :: Int |
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38 | time :: Float64 |
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39 | function_value :: Float64 |
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40 | end |
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41 | |
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42 | struct State |
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43 | vis :: Union{Channel,Bool,Nothing} |
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44 | visproc :: Union{Nothing,Task} |
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45 | start_time :: Union{Real,Nothing} |
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46 | wasted_time :: Real |
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47 | log :: LinkedList{LogEntry} |
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48 | end |
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49 | |
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50 | ################## |
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51 | # Helper routines |
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52 | ################## |
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53 | |
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54 | @inline function secs_ns() |
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55 | return convert(Float64, time_ns())*1e-9 |
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56 | end |
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57 | |
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58 | ################ |
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59 | # Visualisation |
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60 | ################ |
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61 | |
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62 | function bg_visualise(rc) |
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63 | process_channel(do_visualise, rc) |
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64 | end |
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65 | |
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66 | # function do_visualise(imgs) |
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67 | # plt = im -> plot(grayimg(im), showaxis=false, grid=false, aspect_ratio=:equal, margin=2mm) |
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68 | # display(plot([plt(imgs[i]) for i =1:length(imgs)]..., reuse=true, margin=0mm)) |
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69 | # end |
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70 | |
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71 | grayGR = x -> begin |
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72 | y = round(UInt32, 0xff*clip(x)) |
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73 | return 0x010101*y + 0xff000000 |
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74 | end |
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75 | |
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76 | function fill_viewport(vp, c) |
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77 | GR.savestate() |
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78 | GR.selntran(0) |
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79 | GR.setscale(0) |
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80 | GR.setfillintstyle(GR.INTSTYLE_SOLID) |
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81 | GR.setfillcolorind(c) |
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82 | GR.fillrect(vp...) |
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83 | GR.selntran(1) |
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84 | GR.restorestate() |
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85 | end |
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86 | |
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87 | function do_visualise(imgs; refresh=true, fullscreen=false) |
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88 | n = length(imgs) |
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89 | # Get device dimensions in metres and pixels |
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90 | scrw, scrh, pw, ph = GR.inqdspsize() |
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91 | imgaspect = n > 0 ? float(size(imgs[1], 1))/float(size(imgs[1], 2)) : 1 |
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92 | # Scaling to maximum size window |
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93 | sc=0.7 |
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94 | # Set up window and transformations |
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95 | GR.clearws() |
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96 | GR.setscale(0); |
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97 | GR.selntran(1) |
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98 | # - First OS window size |
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99 | if fullscreen |
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100 | w, h = float(scrw), float(scrh) |
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101 | elseif scrw/n>scrh |
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102 | w, h = float(sc*scrh*n), float(sc*scrh*imgaspect) |
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103 | else |
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104 | w, h = float(sc*scrw), float(sc*scrw/n*imgaspect) |
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105 | end |
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106 | GR.setwsviewport(0, w, 0, h) |
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107 | # NDC to device |
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108 | if w>h |
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109 | canvas=[0, 1, 0, h/w] |
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110 | else |
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111 | canvas=[0, w/h, 0, 1] |
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112 | end |
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113 | GR.setwswindow(canvas...) |
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114 | fill_viewport(canvas, 1) |
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115 | # World coordinates to NDC |
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116 | if imgaspect/n<h/w |
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117 | y0 = (canvas[3]+canvas[4])/2 |
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118 | ww = (canvas[2]-canvas[1])/2 |
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119 | y1 = y0-ww*(imgaspect/n) |
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120 | y2 = y0+ww*(imgaspect/n) |
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121 | GR.setviewport(canvas[1], canvas[2], y1, y2) |
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122 | else |
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123 | x0 = (canvas[1]+canvas[2])/2 |
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124 | hh = (canvas[4]-canvas[3])/2 |
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125 | x1 = x0-hh*(n/imgaspect) |
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126 | x2 = x0+hh*(n/imgaspect) |
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127 | GR.setviewport(x1, x2, canvas[3], canvas[4]) |
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128 | end |
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129 | GR.setwindow(0, n, 0, 1) |
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130 | # Clear background |
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131 | # Plot images |
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132 | for i=1:n |
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133 | im = imgs[i]' |
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134 | sz = size(im) |
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135 | GR.drawimage(i-1, i, 0, 1, sz[1], sz[2], grayGR.(im)) |
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136 | end |
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137 | if refresh |
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138 | GR.updatews() |
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139 | end |
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140 | end |
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141 | |
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142 | function visualise(channel_or_toggle, imgs) |
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143 | if isa(channel_or_toggle, Channel) |
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144 | put_onlylatest!(channel_or_toggle, imgs) |
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145 | elseif isa(channel_or_toggle, Bool) && channel_or_toggle |
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146 | do_visualise(imgs) |
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147 | end |
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148 | end |
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149 | |
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150 | ###################################################### |
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151 | # Iterator that does visualisation and log collection |
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152 | ###################################################### |
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153 | |
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154 | function iterate_visualise(st :: State, |
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155 | step :: Function, |
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156 | params :: NamedTuple) where DisplacementT |
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157 | try |
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158 | for iter=1:params.maxiter |
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159 | st = step() do calc_objective |
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160 | if isnothing(st.start_time) |
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161 | # The Julia precompiler is a miserable joke, apparently not crossing module |
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162 | # boundaries, so only start timing after the first iteration. |
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163 | st = @set st.start_time=secs_ns() |
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164 | end |
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165 | |
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166 | verb = params.verbose_iter!=0 && mod(iter, params.verbose_iter) == 0 |
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167 | |
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168 | if verb || iter ≤ 20 || (iter ≤ 200 && mod(iter, 10) == 0) |
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169 | verb_start = secs_ns() |
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170 | tm = verb_start - st.start_time - st.wasted_time |
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171 | value, x = calc_objective() |
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172 | |
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173 | entry = LogEntry(iter, tm, value) |
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174 | |
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175 | # (**) Collect a singly-linked list of log to avoid array resizing |
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176 | # while iterating |
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177 | st = @set st.log=LinkedListEntry(entry, st.log) |
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178 | |
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179 | if verb |
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180 | @printf("%d/%d J=%f\n", iter, params.maxiter, value) |
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181 | visualise(st.vis, (x,)) |
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182 | end |
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183 | |
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184 | if params.save_iterations |
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185 | fn = t -> "$(params.save_prefix)_$(t)_iter$(iter).png" |
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186 | save(File(format"PNG", fn("reco")), grayimg(x)) |
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187 | end |
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188 | |
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189 | st = @set st.wasted_time += (secs_ns() - verb_start) |
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190 | end |
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191 | |
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192 | return st |
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193 | end |
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194 | end |
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195 | catch ex |
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196 | if isa(ex, InterruptException) |
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197 | # If SIGINT is received (user pressed ^C), terminate computations, |
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198 | # returning current status. Effectively, we do not call `step()` again, |
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199 | # ending the iterations, but letting the algorithm finish up. |
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200 | # Assuming (**) above occurs atomically, `st.log` should be valid, but |
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201 | # any results returned by the algorithm itself may be partial, as for |
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202 | # reasons of efficiency we do *not* store results of an iteration until |
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203 | # the next iteration is finished. |
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204 | printstyled("\rUser interrupt—finishing up.\n", bold=true, color=202) |
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205 | else |
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206 | throw(ex) |
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207 | end |
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208 | end |
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209 | |
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210 | return st |
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211 | end |
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212 | |
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213 | #################### |
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214 | # Launcher routines |
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215 | #################### |
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216 | |
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217 | function initialise_visualisation(visualise; iterator=iterate_visualise) |
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218 | # Create visualisation |
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219 | if visualise |
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221 | visproc = Threads.@spawn bg_visualise(rc) |
27 | 222 | bind(rc, visproc) |
223 | vis = rc | |
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224 | else |
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225 | vis = false |
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226 | visproc = nothing |
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227 | end |
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228 | |
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229 | st = State(vis, visproc, nothing, 0.0, nothing) |
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230 | iterate = curry(iterate_visualise, st) |
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231 | |
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232 | return st, iterate |
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233 | end |
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234 | |
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235 | function finalise_visualisation(st) |
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236 | if isa(st.vis, Channel) |
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237 | # Tell subprocess to finish, and wait |
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238 | put!(st.vis, nothing) |
27 | 239 | close(st.vis) |
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240 | wait(st.visproc) |
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241 | end |
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242 | end |
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243 | |
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244 | end # Module |