quick cleanup, also speedup was 4x in last commit

main.jl

@@ -524,7 +524,7 @@ function calc_cost(rollout::Vector{Int}, cdata::contourdata, vd::voxdata, mat::m
 end
 
 
-#function construct_cost(cdata::contourdata, vd::voxdata, mat::material)
+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)]
 
@@ -544,32 +544,7 @@ end
     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 + $c)
-    #     voxtimes[i] = v_time
-    # end
-    # voxtimes_expression = :[]
-    # voxtimes_expression.args = voxtimes
-    # replace!(x-> x==:() ? 0 : x, voxtimes_expression.args)
-
-    a = quote
+    return quote
         function cost_f(rl::Vector{Int})
             # println("Cumulative Sum") # 100k
             timestart = cumsum([$contour_times[c] for c in rl])
@@ -601,8 +576,8 @@ end
             return cost
         end
     end
-    # return
-#end
+end
+
 
 function clean_contour(c::contour)
     # remove first element of array if second element is the same
@@ -640,10 +615,7 @@ obj = "/Users/jayant/phd/tempaware/" * "M1"
 contours = clean_contour.(contour.(JSON.parse(open(obj * "contours.json"))))
 cdata = contourdata(contours, 5, 5) # contour data
 @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
 calc_cost(rl, cdata, vd, ABS) # 500/second
 
 
@@ -653,7 +625,7 @@ n = length(rl)
 k = 5
 cost_val = Inf
 o=0
-@time for l in 1:10
+@time for l in 1:100
     println(l)
     println(cost_val)
     costs = Dict()
@@ -661,7 +633,7 @@ o=0
         for j in i+1:min(i+k,n)
             if valid_swap(rl, i, j, cdata)
                 swap!(rl, i, j)
-                costs[i,j] = calc_cost(rl, cdata, vd, ABS)
+                costs[i,j] = cost_f(rl)
                 swap!(rl, i, j)
                 o += 1
             end