building!

README.md

@@ -69,7 +69,7 @@ As of v1.8.0, _data parallel_ processing of multiple input patterns in parallel
 
 ```Go
 net.InitExt(ctx) // clear any existing inputs
-for di := uint32(0); di < ctx.NetIndexes.NData; di++ {
+for di := uint32(0); di < ctx.NData; di++ {
  ev.Step()
  for _, lnm := range lays {
  ly := ss.Net.AxonLayerByName(lnm)
@@ -128,7 +128,7 @@ func (ss *Sim) NetViewCounters(tm etime.Times) {
  case time == etime.Trial:
  trl := ss.Stats.Int("Trial")
  row = trl
- for di := 0; di < int(ctx.NetIndexes.NData); di++ {
+ for di := 0; di < int(ctx.NData); di++ {
  ss.Stats.SetInt("Trial", trl+di)
  ss.TrialStats(di)
  ss.StatCounters(di)

axon/act-path.goal

@@ -54,19 +54,29 @@ type SynComParams struct {
  // type of conductance (G) communicated by this pathway
  GType PathGTypes
 
- // additional synaptic delay in msec for inputs arriving at this pathway. Must be <= MaxDelay which is set during network building based on MaxDelay of any existing Path in the network. Delay = 0 means a spike reaches receivers in the next Cycle, which is the minimum time (1 msec). Biologically, subtract 1 from biological synaptic delay values to set corresponding Delay value.
+ // additional synaptic delay in msec for inputs arriving at this pathway.
+ // Must be <= MaxDelay which is set during network building based on MaxDelay
+ // of any existing Path in the network. Delay = 0 means a spike reaches
+ // receivers in the next Cycle, which is the minimum time (1 msec).
+ // Biologically, subtract 1 from biological synaptic delay values to set
+ // corresponding Delay value.
  Delay uint32 `min:"0" default:"2"`
 
- // maximum value of Delay -- based on MaxDelay values when the BuildGBuf function was called when the network was built -- cannot set it longer than this, except by calling BuildGBuf on network after changing MaxDelay to a larger value in any pathway in the network.
+ // maximum value of Delay, based on MaxDelay values when the BuildGBuf
+ // function was called during [Network.Build]. Cannot set it longer than this,
+ // except by calling BuildGBuf on network after changing MaxDelay to a larger
+ // value in any pathway in the network.
  MaxDelay uint32 `edit:"-"`
 
- // probability of synaptic transmission failure -- if > 0, then weights are turned off at random as a function of PFail (times 1-SWt if PFailSwt)
+ // probability of synaptic transmission failure: if > 0, then weights are
+ //turned off at random as a function of PFail (times 1-SWt if PFailSwt).
  PFail float32
 
- // if true, then probability of failure is inversely proportional to SWt structural / slow weight value (i.e., multiply PFail * (1-SWt)))
+ // if true, then probability of failure is inversely proportional to SWt
+ // structural / slow weight value (i.e., multiply PFail * (1-SWt))).
  PFailSWt slbool.Bool
 
- // delay length = actual length of the GBuf buffer per neuron = Delay+1 -- just for speed
+ // delay length = actual length of the GBuf buffer per neuron = Delay+1; just for speed
  DelLen uint32 `display:"-"`
 
  pad, pad1 float32

axon/basic_test.go

@@ -106,7 +106,7 @@ func newTestNet(ctx *Context, nData int) *Network {
  testNet.Rubicon.Defaults()
 
  testNet.Build(ctx)
- ctx.NetIndexes.NData = uint32(nData)
+ ctx.NData = uint32(nData)
  testNet.Defaults()
  testNet.ApplyParams(ParamSets["Base"], false) // false) // true) // no msg
  testNet.InitWeights(ctx) // get GScale here
@@ -131,7 +131,7 @@ func newTestNetFull(ctx *Context, nData int) *Network {
  testNet.ConnectLayers(outLay, hidLay, full, BackPath)
 
  testNet.Build(ctx)
- ctx.NetIndexes.NData = uint32(nData)
+ ctx.NData = uint32(nData)
  testNet.Defaults()
  testNet.ApplyParams(ParamSets["Base"], false) // false) // true) // no msg
  testNet.InitWeights(ctx) // get GScale here
@@ -563,7 +563,7 @@ func NetDebugAct(t *testing.T, printValues bool, gpu bool, nData int, initWts bo
 // fine-grained diff test, e.g., see the GPU version.
 func RunDebugAct(t *testing.T, ctx *Context, testNet *Network, printValues bool, gpu bool, initWts bool) map[string]float32 {
 
- nData := int(ctx.NetIndexes.NData)
+ nData := int(ctx.NData)
  valMap := make(map[string]float32)
  inPats := newInPats()
  inLay := testNet.LayerByName("Input")
@@ -1025,7 +1025,7 @@ func NetDebugLearn(t *testing.T, printValues bool, gpu bool, maxData, nData int,
  testNet.ApplyParams(ParamSets["SubMean"], false)
  }
 
- ctx.NetIndexes.NData = uint32(nData)
+ ctx.NData = uint32(nData)
  return RunDebugLearn(t, ctx, testNet, printValues, gpu, initWts, slowAdapt)
 }
 
@@ -1034,7 +1034,7 @@ func NetDebugLearn(t *testing.T, printValues bool, gpu bool, maxData, nData int,
 // fine-grained diff test, e.g., see the GPU version.
 func RunDebugLearn(t *testing.T, ctx *Context, testNet *Network, printValues bool, gpu bool, initWts, slowAdapt bool) map[string]float32 {
 
- nData := int(ctx.NetIndexes.NData)
+ nData := int(ctx.NData)
  valMap := make(map[string]float32)
  inPats := newInPats()
  inLay := testNet.LayerByName("Input")