func (g *generator) Distance() (matrix.Matrix, error) {
m := matrix.Matrix(make([][]matrix.Element, g.n))
for i := 0; i < g.n; i++ {
m[i] = make([]matrix.Element, g.n)
for j := 0; j < g.n; j++ {
m[i][j] = matrix.Element(rand.Float64())
}
}
return m, nil
}
func (g *generator) Flow(spread float64) (matrix.Matrix, error) {
if spread < 0 || spread >= 1 {
return nil, fmt.Errorf("Error: spread must be between 0 and 1.")
}
// Create Zipf generator
scale := 1000
r := rand.New(rand.NewSource(0))
zipf := rand.NewZipf(r, 1.01, float64(g.n), uint64(scale))
// Populate frequencies of unigrams
k := make([]float64, g.n)
for i := 0; i < g.n; i++ {
k[i] = float64(zipf.Uint64())
}
// Populate ideal bigram matrix
m := matrix.Matrix(make([][]matrix.Element, g.n))
for i := 0; i < g.n; i++ {
m[i] = make([]matrix.Element, g.n)
for j := 0; j < g.n; j++ {
e := (rand.Float64() - 0.5) * spread
m[i][j] = matrix.Element((k[i] * k[j]) * (1 + e))
}
}
// Scale back to 100,000 total freq
totalF := m.Sum()
s := g.fscale / totalF
for i := 0; i < g.n; i++ {
for j := 0; j < g.n; j++ {
m[i][j] = matrix.Element(math.Floor(float64(m[i][j]) * s))
}
}
return m, nil
}
