func GetWordTopicDist(m *MGLDA, vocabulary []string, wt *bufio.Writer) {
zGlCount := make([]int, m.GlobalK)
zLocCount := make([]int, m.LocalK)
wordGlCount := []map[int]int{}
wordLocCount := []map[int]int{}
for i := 0; i < m.GlobalK; i++ {
wordGlCount = append(wordGlCount, map[int]int{})
}
for i := 0; i < m.LocalK; i++ {
wordLocCount = append(wordLocCount, map[int]int{})
}
glog.Info("Get words distribution")
for d, doc := range *m.Docs {
for s, sent := range doc.Sentenses {
for w, wd := range sent.Words {
r := m.Rdsn[d][s][w]
z := m.Zdsn[d][s][w]
if r == globalTopic {
zGlCount[z] += 1
wordGlCount[z][wd] += 1
} else {
zLocCount[z] += 1
wordLocCount[z][wd] += 1
}
}
}
}
glog.Info("Done dist")
phiGl, phiLoc := m.WordDist()
for i := 0; i < m.GlobalK; i++ {
header := fmt.Sprintf("-- global topic: %d (%d words)\n", i, zGlCount[i])
wt.WriteString(header)
glog.Info(header)
rows := phiGl.RowCopy(i)
idx := []int{}
for j := 0; j < len(rows); j++ {
idx = append(idx, j)
}
floats.Argsort(rows, idx)
for j := len(idx) - 1; j > len(idx)-topicLimit; j-- {
w := idx[j]
tp := fmt.Sprintf("%s: %f (%d)\n",
vocabulary[w], phiGl.Get(i, w),
wordGlCount[i][w])
wt.WriteString(tp)
glog.Info(tp)
}
}
for i := 0; i < m.LocalK; i++ {
header := fmt.Sprintf("-- local topic: %d (%d words)\n", i, zLocCount[i])
wt.WriteString(header)
glog.Info(header)
rows := phiLoc.RowCopy(i)
idx := []int{}
for j := 0; j < len(rows); j++ {
idx = append(idx, j)
}
floats.Argsort(rows, idx)
for j := len(idx) - 1; j > len(idx)-topicLimit; j-- {
w := idx[j]
tp := fmt.Sprintf("%s: %f (%d)\n",
vocabulary[w], phiLoc.Get(i, w),
wordLocCount[i][w])
wt.WriteString(tp)
glog.Info(tp)
}
}
}
/*
Free up some synapses in this segment. We always free up inactive
synapses (lowest permanence freed up first) before we start to free up
active ones.
param numToFree number of synapses to free up
param inactiveSynapseIndices list of the inactive synapse indices.
*/
func (s *Segment) freeNSynapses(numToFree int, inactiveSynapseIndices []int) {
//Make sure numToFree isn't larger than the total number of syns we have
if numToFree > len(s.syns) {
panic("Number to free cannot be larger than existing synapses.")
}
if s.tp.params.Verbosity >= 5 {
fmt.Println("freeNSynapses with numToFree=", numToFree)
fmt.Println("inactiveSynapseIndices= ", inactiveSynapseIndices)
}
var candidates []int
// Remove the lowest perm inactive synapses first
if len(inactiveSynapseIndices) > 0 {
perms := make([]float64, len(inactiveSynapseIndices))
for idx, _ := range perms {
perms[idx] = s.syns[idx].Permanence
}
var indexes []int
floats.Argsort(perms, indexes)
//sort perms
cSize := mathutil.Min(numToFree, len(perms))
candidates = make([]int, cSize)
//indexes[0:cSize]
for i := 0; i < cSize; i++ {
candidates[i] = inactiveSynapseIndices[indexes[i]]
}
}
// Do we need more? if so, remove the lowest perm active synapses too
var activeSynIndices []int
if len(candidates) < numToFree {
for i := 0; i < len(s.syns); i++ {
if !utils.ContainsInt(i, inactiveSynapseIndices) {
activeSynIndices = append(activeSynIndices, i)
}
}
perms := make([]float64, len(activeSynIndices))
for i := range perms {
perms[i] = s.syns[i].Permanence
}
var indexes []int
floats.Argsort(perms, indexes)
moreToFree := numToFree - len(candidates)
//moreCandidates := make([]int, moreToFree)
for i := 0; i < moreToFree; i++ {
candidates = append(candidates, activeSynIndices[indexes[i]])
}
}
if s.tp.params.Verbosity >= 4 {
fmt.Printf("Deleting %v synapses from segment to make room for new ones: %v \n",
len(candidates), candidates)
fmt.Println("Before:", s.ToString())
}
// Delete candidate syns by copying undeleted to new slice
var newSyns []Synapse
for idx, val := range s.syns {
if !utils.ContainsInt(idx, candidates) {
newSyns = append(newSyns, val)
}
}
s.syns = newSyns
if s.tp.params.Verbosity >= 4 {
fmt.Println("After:", s.ToString())
}
}
// Inference runs a go routine for each doc.
func (m *MGLDA) Inference() {
for d, doc := range *m.Docs {
for s, sent := range doc.Sentenses {
for w, wd := range sent.Words {
v := m.Vdsn[d][s][w]
r := m.Rdsn[d][s][w]
z := m.Zdsn[d][s][w]
if r == globalTopic {
m.Nglzw.Set(z, wd, m.Nglzw.Get(z, wd)-1)
m.Nglz.Set(z, 0, m.Nglz.Get(z, 0)-1)
m.Ndvgl[d][s+v] -= 1
m.Ndglz.Set(d, z, m.Ndglz.Get(d, z)-1)
m.Ndgl.Set(d, 0, m.Ndgl.Get(d, 0)-1)
} else {
m.Nloczw.Set(z, wd, m.Nloczw.Get(z, wd)-1)
m.Nlocz.Set(z, 0, m.Nlocz.Get(z, 0)-1)
m.Ndvloc[d][s+v] -= 1
m.Ndvlocz[d][s+v][z] -= 1
}
m.Ndsv[d][s][v] -= 1
m.Nds[d][s] -= 1
m.Ndv[d][s+v] -= 1
pvrz := []float64{}
newVs := []int{}
newRs := []string{}
newZs := []int{}
for vt := 0; vt < m.T; vt++ {
for zt := 0; zt < m.GlobalK; zt++ {
newVs = append(newVs, vt)
newRs = append(newRs, globalTopic)
newZs = append(newZs, zt)
term1 := (m.Nglzw.Get(zt, wd) + m.GlobalBeta) / (m.Nglz.Get(zt, 0) + float64(m.W)*m.GlobalBeta)
term2 := (m.Ndsv[d][s][vt] + m.Gamma) / (m.Nds[d][s] + float64(m.T)*m.Gamma)
term3 := (m.Ndvgl[d][s+vt] + m.GlobalAlphaMix) / (m.Ndv[d][s+vt] + m.GlobalAlphaMix + m.LocalAlphaMix)
term4 := (m.Ndglz.Get(d, zt) + m.GlobalAlpha) / (m.Ndgl.Get(d, 0) + float64(m.GlobalK)*m.GlobalAlpha)
pvrz = append(pvrz, term1*term2*term3*term4)
}
for zt := 0; zt < m.LocalK; zt++ {
newVs = append(newVs, vt)
newRs = append(newRs, localTopic)
newZs = append(newZs, zt)
term1 := (m.Nloczw.Get(zt, wd) + m.LocalBeta) / (m.Nlocz.Get(zt, 0) + float64(m.W)*m.LocalBeta)
term2 := (m.Ndsv[d][s][vt] + m.Gamma) / (m.Nds[d][s] + float64(m.T)*m.Gamma)
term3 := (m.Ndvloc[d][s+vt] + m.LocalAlphaMix) / (m.Ndv[d][s+vt] + m.GlobalAlphaMix + m.LocalAlphaMix)
term4 := (m.Ndvlocz[d][s+vt][zt] + m.LocalAlpha) / (m.Ndvloc[d][s+vt] + float64(m.LocalK)*m.LocalAlpha)
pvrz = append(pvrz, term1*term2*term3*term4)
}
}
// sampling from multinomial distribution
origIdx := []int{}
var sum float64
for j, item := range pvrz {
sum += item
origIdx = append(origIdx, j)
}
floats.Argsort(pvrz, origIdx)
var randIdx int
idxCount := map[int]int{}
for i := 0; i < 100; i++ {
var partialSum float64
threshold := rand.Float64()
for j := len(pvrz) - 1; j >= 0; j-- {
partialSum += pvrz[j] / sum
if partialSum >= threshold {
idxCount[origIdx[j]] += 1
break
}
}
}
var maxCount int
for idx, cnt := range idxCount {
if cnt > maxCount {
randIdx = idx
}
}
newV := newVs[randIdx]
newR := newRs[randIdx]
newZ := newZs[randIdx]
// update
if newR == globalTopic {
m.Nglzw.Set(newZ, wd, m.Nglzw.Get(newZ, wd)+1)
m.Nglz.Set(newZ, 0, m.Nglz.Get(newZ, 0)+1)
m.Ndvgl[d][s+newV] += 1
m.Ndglz.Set(d, newZ, m.Ndglz.Get(d, newZ)+1)
m.Ndgl.Set(d, 0, m.Ndgl.Get(d, 0)+1)
} else {
m.Nloczw.Set(newZ, wd, m.Nloczw.Get(newZ, wd)+1)
m.Nlocz.Set(newZ, 0, m.Nlocz.Get(newZ, 0)+1)
m.Ndvloc[d][s+newV] += 1
m.Ndvlocz[d][s+newV][newZ] += 1
}
m.Ndsv[d][s][newV] += 1
m.Nds[d][s] += 1
m.Ndv[d][s+newV] += 1
m.Vdsn[d][s][w] = newV
m.Rdsn[d][s][w] = newR
m.Zdsn[d][s][w] = newZ
}
}
}
}
