func function(config *config.Config) error {
config.Uncertainty.Variance = 1.0
if len(*sampleSeed) > 0 {
if number, err := strconv.ParseInt(*sampleSeed, 0, 64); err != nil {
return err
} else {
config.Assessment.Seed = number
}
}
if len(*sampleCount) > 0 {
if number, err := strconv.ParseUint(*sampleCount, 0, 64); err != nil {
return err
} else {
config.Assessment.Samples = uint(number)
}
}
if config.Assessment.Samples == 0 {
return errors.New("the number of samples should be positive")
}
output, err := database.Create(*outputFile)
if err != nil {
return err
}
defer output.Close()
system, err := system.New(&config.System)
if err != nil {
return err
}
auncertainty, err := uncertainty.NewAleatory(system, &config.Uncertainty)
if err != nil {
return err
}
aquantity, err := quantity.New(system, auncertainty, &config.Quantity)
if err != nil {
return err
}
ni, no := aquantity.Dimensions()
ns := config.Assessment.Samples
points := support.Generate(ni, ns, config.Assessment.Seed)
log.Printf("Evaluating the original model at %d points...\n", ns)
values := quantity.Invoke(aquantity, points)
if err := output.Put("points", points, ni, ns); err != nil {
return err
}
if err := output.Put("values", values, no, ns); err != nil {
return err
}
return nil
}
func generate(into, from quantity.Quantity, ns uint, seed int64) []float64 {
ni, _ := into.Dimensions()
nf, _ := from.Dimensions()
zi := make([]float64, ni*ns)
zf := support.Generate(nf, ns, seed)
for i := uint(0); i < ns; i++ {
copy(zi[i*ni:(i+1)*ni], into.Forward(from.Backward(zf[i*nf:(i+1)*nf])))
}
return zi
}
