func main() {
// Temperature-dependent curves:
t := table.NewOutTable("Temp", "Energy", "Magnetization", "C", "Chi")
im := ising.New(ising.Grid2DType, 16)
t0 := time.Now()
for temp := 0.0; temp < 5.0; temp += 0.1 {
ising.Equilibriate(im, temp, 100)
es := make([]float64, 100)
ms := make([]float64, 100)
for i := 0; i < len(es); i++ {
ising.Equilibriate(im, temp, 1000/len(es))
es[i] = ising.AverageEnergy(im)
ms[i] = math.Abs(ising.AverageMag(im))
}
t.AddRow(temp, avg(es), avg(ms),
16*16*variance(es)/temp/temp,
16*16*variance(ms)/temp)
}
t1 := time.Now()
t.Write(table.KeepHeader, "temp.table")
println("ising seconds:", sec(t0, t1))
// Hysteresis loop:
t = table.NewOutTable("h", "Magnetization")
temp := 2.15
t2 := time.Now()
im = ising.New(ising.Grid2DType, 32)
update := func(mag float64) {
im.SetMag(mag)
ising.Equilibriate(im, temp, 20)
t.AddRow(mag, ising.AverageMag(im), ising.AverageEnergy(im),
ising.SpecificHeat(im), ising.Chi(im))
}
for mag := -1.5; mag <= 1.5; mag += 0.03 {
update(mag)
}
for mag := 1.5; mag >= -1.5; mag -= 0.03 {
update(mag)
}
t3 := time.Now()
println("hysteresis seconds:", sec(t2, t3))
t.Write(table.KeepHeader, "mag.table")
}
func main() {
t := table.NewOutTable("Time Step", "C Correlation", "X Correlation")
info := &ising.SweepInfo{
ising.New(ising.Grid2DType, widthPow),
ising.RandomSweep,
mcrand.New(mcrand.GoCrypto, int64(time.Now().UnixNano())),
temp,
}
stats := ising.SweepStatistics(info, initialSweeps, trials)
fCs, _ := ising.Tau(stats.EHistory)
fMags, _ := ising.Tau(stats.MagHistory)
if len(fCs) < len(fMags) {
for 0 < len(fMags)-len(fCs) {
fCs = append(fCs, 0.0)
}
} else {
for 0 < len(fCs)-len(fMags) {
fMags = append(fMags, 0.0)
}
}
info.Im.Print()
println("Total steps:", len(fMags))
for i := 0; i < len(fMags); i++ {
t.AddRow(float64(i), fCs[i], fMags[i])
}
t.Write(table.KeepHeader, "tau.table")
}
func main() {
fmt.Println("Run statistics:")
fmt.Printf(" %15s %5d\n", "Grid Width", 1<<widthPow)
fmt.Printf(" %15s %5d\n", "Initial Sweeps", initialSweeps)
fmt.Printf(" %15s %5d\n", "Trial Sweeps", trials)
fmt.Printf(" %15s %5d\n", "Runs", runs)
fmt.Printf(" %15s %5d\n", "Plot Points", int(points))
t0 := float64(time.Now().UnixNano())
infos := make([]*ising.SweepInfo, runs)
for i := 0; i < runs; i++ {
infos[i] = &ising.SweepInfo{
ising.New(ising.Grid2DType, widthPow),
ising.RandomSweep,
mcrand.New(mcrand.Xorshift, int64(time.Now().Nanosecond())),
minTemp,
}
}
t := table.NewOutTable("Temp", "Energy", "Mag", "S. Heat", "Chi")
stats := make([]*ising.SweepStats, runs)
print("Running simulation")
for point := 0.0; point < points; point++ {
print(".")
for i, info := range infos {
info.Temp = minTemp + (maxTemp-minTemp)*point/points
stats[i] = ising.SweepStatistics(info, initialSweeps, trials)
}
stat := ising.AvgSweepStats(stats)
t.AddRow(infos[0].Temp, stat.E, stat.Mag, stat.C, stat.X)
}
println()
t.Write(table.KeepHeader, fmt.Sprintf("temp%d.table", 1<<widthPow))
t1 := float64(time.Now().UnixNano())
fmt.Printf("Run time: %.3gs\n", (t1-t0)/1e9)
}
// This is too monolithic and should be pruned.
func main() {
sampleTemp := minSampleTemp
maximumTable := table.NewOutTable("L", "1/L",
"Critical Temperature", "Max Specific Heat", "Max Specific Heat Per Site")
maximumTable.SetHeader(fmt.Sprintf("Created with %g trials per grid.",
math.Pow(10, maxTrialsPow)))
for widthPow := minPow; widthPow <= maxPow; widthPow++ {
cols := make([]string, 1+2*(maxTrialsPow-minTrialsPow+1))
cols[0] = "Temperature"
fcols := make([][]float64, int((maxTemp-minTemp)/tempStep))
for i := 0; i < len(fcols); i++ {
fcols[i] = make([]float64, 1+2*(maxTrialsPow-minTrialsPow+1))
}
secs1 := 0.0
secs2 := 0.0
fmt.Printf("\n%d-Width Grid:\n", 1<<widthPow)
for i := 0; i <= maxTrialsPow-minTrialsPow; i++ {
trials := int(math.Pow(10, float64(minTrialsPow+i)))
fmt.Printf(" Running %d trial suite\n", trials)
cols[2*i+1] = fmt.Sprintf("E (%d)", trials)
cols[2*i+2] = fmt.Sprintf("C (%d)", trials)
info := &ising.SweepInfo{
ising.New(ising.Grid2DType, uint32(widthPow)),
ising.IterSweep,
mcrand.New(mcrand.Xorshift, int64(time.Now().UnixNano())),
sampleTemp,
}
t0 := time.Now().UnixNano()
ising.SweepStatistics(info, initialSweeps, trials)
t1 := time.Now().UnixNano()
secs1 += float64(t1-t0) / 1e9
h := info.Im.EnergyHistogram()
minValidTemp, maxValidTemp := maxTemp, minTemp
for j := 0; j < len(fcols); j++ {
temp := minTemp + float64(j)*tempStep
E := h.Energy(sampleTemp, temp)
C := h.SpecificHeat(sampleTemp, temp)
if !math.IsNaN(C) && !math.IsInf(C, 0) {
if temp > maxValidTemp {
maxValidTemp = temp
}
if temp < minValidTemp {
minValidTemp = temp
}
}
fcols[j][2*i+1] = E / float64(info.Im.Sites())
fcols[j][2*i+2] = C / float64(info.Im.Sites())
}
if i+minTrialsPow == maxTrialsPow {
tCrit := h.CriticalTemp(sampleTemp, minValidTemp, maxValidTemp)
cCrit := h.SpecificHeat(sampleTemp, tCrit)
maximumTable.AddRow(float64(int(1<<widthPow)),
1.0/float64(int(1<<widthPow)), tCrit,
cCrit, cCrit/float64(info.Im.Sites()))
sampleTemp = tCrit
}
t2 := time.Now().UnixNano()
secs2 += float64(t2-t1) / 1e9
}
headerString := fmt.Sprintf(
"%16s: %g\n%16s: %d\n%16s: %d\n"+
"%16s: %s\n%16s: %s\n%16s: %g\n%20s: %g",
"Sample Temperature", sampleTemp,
"Initial Sweeps", initialSweeps,
"Width", 1<<widthPow,
"Generator", "Xorshift",
"Sweep Pattern", "IterSweep",
"Total Sweep Time", secs1,
"Total Histogram Time", secs2)
t := table.NewOutTable(cols...)
t.SetHeader(headerString)
for i := 0; i < len(fcols); i++ {
if !math.IsNaN(fcols[i][1]) {
fcols[i][0] = minTemp + tempStep*float64(i)
t.AddRow(fcols[i]...)
}
}
t.Write(table.KeepHeader,
fmt.Sprintf("tables/iter/hist-temp%d.table", 1<<widthPow))
}
maximumTable.Write(table.KeepHeader, "tables/iter/hist-maximum.table")
}