WIP: Use Makie: faster, but many issues

test/REQUIRE

@@ -1,4 +1,4 @@
 Test
-Plots
+Makie
 BenchmarkTools
 CSV

test/spatial_pooler_test.jl

@@ -7,6 +7,7 @@ module HTMt
 using BenchmarkTools
 using CSV
 using Printf
+using Makie
 import Random.seed!
 seed!(0)
 
@@ -26,8 +27,10 @@ display_evaluation(t,sp,sp_activity,spDims)= begin
   #heatmap(@> sp.b.a_Tmean reshape(64,32))|> display
   #heatmap(sp.proximalSynapses.synapses)|> display
 end
-process_data!(encHistory,spHistory,encANDspHistory,tN,data,encParams,sp)=
-  for t in 1:tN
+function process_data!(encHistory,spHistory,encANDspHistory,tN,data,encParams,sp)
+  AbstractPlotting.inline!(true)
+  scene= Scene()
+  for t in 1:tN÷4
     z,a= _process_sp(t,tN,data,encParams,sp,display_evaluation)
     encHistory[:,t]= z; spHistory[:,t]= a
     # when were the most similar SDRs to z,a in history? These indices correspond to times
@@ -36,9 +39,10 @@ process_data!(encHistory,spHistory,encANDspHistory,tN,data,encParams,sp)=
     encOnlyIdx= setdiff(similarEncIdx, similarSpIdx)
     spOnlyIdx= setdiff(similarSpIdx, similarEncIdx)
     encANDspHistory[t]= (encANDsp= intersect(similarEncIdx,similarSpIdx), Nenc= length(similarEncIdx))
-    t%10==0 && plot_ts_similarEncSp(t,data.power_hourly_kw,
-                                    encOnlyIdx,spOnlyIdx,encANDspHistory)
+    t%80==0 && plot_ts_similarEncSp(t,data.power_hourly_kw,
+                                    encOnlyIdx,spOnlyIdx,encANDspHistory,scene)
   end
+end
 
 # Define Spatial Pooler
 inputDims= ((16*25,5*25,3*25),)
@@ -59,7 +63,7 @@ sp= SpatialPooler(SPParams(
 data,tN= read_gympower()
 encParams= initenc_powerDay(data.power_hourly_kw, data.hour, data.is_weekend,
                  encoder_size=inputDims[1], w=(21,27,27))
-using Plots; gr()
+
 encHistory= falses(map(sum,inputDims)|>prod,tN)
 spHistory= falses(spDims|>prod,tN)
 encANDspHistory= Vector{NamedTuple{(:encANDsp,:Nenc),Tuple{Vector{Int},Int}}}(undef,tN)

test/utils/utils.jl

@@ -30,28 +30,35 @@ top_similar_sdr(sdrHist,k)= begin
 end
 
 
-plot_ts_similarEncSp(t,ts,encOnly,spOnly,encANDspHistory)=
-    if t>1 _plot_ts_similarEncSP(t,ts,encOnly,spOnly,encANDspHistory)
-    end
-function _plot_ts_similarEncSP(t,ts,encOnly,spOnly,encANDspHistory)
+plot_ts_similarEncSp(t,ts,encOnly,spOnly,encANDspHistory,scene::Scene=Scene())=
+    t>1 ? _plot_ts_similarEncSP(scene,t,ts,encOnly,spOnly,encANDspHistory) : nothing
+function _plot_ts_similarEncSP(scene,t,ts,encOnly,spOnly,encANDspHistory)
   graph_ts()= begin
-    graph_ts= plot(ts, label="power", dpi=192, ylims=(minimum(ts),maximum(ts)))
-    scatter!(graph_ts, encOnly, ts[encOnly], label="encoding only")
-    scatter!(graph_ts, spOnly, ts[spOnly], label="SP only")
-    scatter!(graph_ts, encANDspHistory[t][1], ts[encANDspHistory[t][1]],
-              label="overlapping encoding & SP", legendfontsize=6)
-    vline!(graph_ts,[t], label="")
-    title!(graph_ts, "Spatial Pooler mapping property evaluation", titlefont=font(12))
+    axislims= FRect(1, 0.9minimum(ts), length(ts), 1.05maximum(ts)-0.9minimum(ts))
+    graph_ts= lines(ts, color=:blue, limits=axislims)
+    scatter!(graph_ts, encOnly, ts[encOnly], markersize=18, alpha=0.8, color=:red)
+    scatter!(graph_ts, spOnly, ts[spOnly], markersize=18, alpha=0.8, color=:yellow)
+    scatter!(graph_ts, encANDspHistory[t][1], ts[encANDspHistory[t][1]], markersize=18,
+              alpha=0.8, color=:green)
+    lines!(graph_ts,[t,t],[minimum(ts),maximum(ts)], limits=axislims)
+    lgd= legend([graph_ts[2],graph_ts[3],graph_ts[4],graph_ts[5]],
+                ["power", "encoding only", "SP only", "overlapping"],
+                camera=campixel!, raw=true)
+    graph_ts= vbox(graph_ts,lgd)
     return graph_ts
   end
   graph_ovp(overlapFraction)= begin
-    graph_ovp= plot(1:t,overlapFraction*100, label="", linestyle=:dash, shape=:circle,
-        msize=3, mcolor=:red, mscolor=:green, dpi=192,
-        ylabel="overlap%",ylims=(0,100),xlims=(1,length(ts)))
-    title!(graph_ovp, "Percentage of overlapping encoder and SP SDRs", titlefont=font(12))
+    axislims= FRect(1,0,length(ts),101)
+    graph_ovp= lines(1:t,overlapFraction*100, linestyle=:dash, color=:blue, limits=axislims)
+    scatter!(graph_ovp, 1:t,overlapFraction*100, markersize=8, alpha=0.2, transparency=true,
+             strokewidth=3.0, color=:red, limits=axislims)
+    #ylabel="overlap%",ylims=(0,100),xlims=(1,length(ts)))
     return graph_ovp
   end
   overlapFraction= map(x->length(x.encANDsp)/x.Nenc, encANDspHistory[1:t])
   overlapFraction[isnan.(overlapFraction)].= 1.0
-  plot(graph_ts(),graph_ovp(overlapFraction), layout=(2,1))|> display
+  #t1="Spatial Pooler mapping property evaluation"
+  #t2="Percentage of overlapping encoder and SP SDRs"
+  scene= hbox(graph_ovp(overlapFraction), graph_ts())|> display
+  scene
 end