func (fg FlowGenerator) makeFlows(logger chan LogEvent) EventQueue {
lambda := (fg.bandwidth * 1e9 * fg.load) / (fg.cdf.meanFlowSize() * 1500 * 8)
lambda /= 143
creationQueue := make(EventQueue, 0)
defer func() {
creationQueue = nil
}()
heap.Init(&creationQueue)
for i := 0; i < NUM_HOSTS; i++ {
for j := 0; j < NUM_HOSTS; j++ {
if i == j {
continue
}
f := &Flow{Start: 1e6 + (rand.ExpFloat64()/lambda)*1e6, Size: fg.cdf.value(), Source: uint8(i), Dest: uint8(j), LastTime: 0, FinishEvent: nil}
heap.Push(&creationQueue, makeCreationEvent(f))
}
}
eventQueue := make(EventQueue, 0)
for uint(len(eventQueue)) < fg.numFlows {
ev := heap.Pop(&creationQueue).(*Event)
logger <- LogEvent{Time: 0, Type: LOG_FLOW_GEN, Flow: ev.Flow}
eventQueue = append(eventQueue, makeArrivalEvent(ev.Flow))
nextTime := ev.Time + (rand.ExpFloat64()/lambda)*1e6
f := &Flow{Start: nextTime, Size: fg.cdf.value(), Source: ev.Flow.Source, Dest: ev.Flow.Dest, LastTime: 0, FinishEvent: nil}
heap.Push(&creationQueue, makeCreationEvent(f))
}
return eventQueue
}
func BenchmarkReadFloat(b *testing.B) {
b.StopTimer()
c := new(Context)
rand.Seed(time.Now().UnixNano())
max := 512
floats := make([]*bytes.Buffer, max)
for i := 0; i < max; i++ {
w := new(bytes.Buffer)
v := rand.ExpFloat64() - rand.ExpFloat64()
w.Write([]byte{ettNewFloat})
binary.Write(w, binary.BigEndian, math.Float64bits(v))
floats[i] = w
}
b.StartTimer()
for i := 0; i < b.N; i++ {
in := floats[i%max]
_, err := c.Read(in)
if err != io.EOF && err != nil {
b.Fatal(err)
}
}
}
func s(numTrains int, safetyTime int, rideTime int, minTransTime int, avgTransTime int) []int {
d := make([]int, 0)
trains := make([]int, numTrains)
c := 0
avg := float64(avgTransTime - minTransTime)
t := 0
dep := minTransTime + int(rand.ExpFloat64()*avg)
t = dep
trains[c] = dep + rideTime
c = (c + 1) % numTrains
d = append(d, dep)
for t < 43200 { //in seconds
if trains[c] > t {
t = trains[c]
}
t += minTransTime + int(rand.ExpFloat64()*avg)
if t < dep+safetyTime {
t = dep + safetyTime
}
dep = t
d = append(d, dep)
}
fmt.Println(d)
return d
}
func TestCompressionRatio(t *testing.T) {
r := rand.New(rand.NewSource(0))
mean := 0.0
count := 100
for i := 0; i < count; i++ {
length := r.Intn(5000) + 100
c := NewCompressionBuffer()
data := []float64{}
value := rand.ExpFloat64() * 1e-5
for j := 0; j < length; j++ {
if rand.Intn(10) != 0 {
value += rand.ExpFloat64()
}
data = append(data, value)
}
c.Compress(data)
c.Finalize()
compressed := c.Bytes()
compressionRatio := float64(length*8) / float64(len(compressed))
if compressionRatio < 1 {
t.Errorf("Data size was increased when compressed")
t.Errorf("Compression ratio: %f; original %d: compressed %d", float64(length*8)/float64(len(compressed)), length*8, len(compressed))
}
mean += compressionRatio
}
mean = mean / float64(count)
t.Logf("mean compression ratio: %f", mean)
}
func singleServer() {
for i := 0; i < 1000; i++ {
fmt.Println("NormFloat64", rand.NormFloat64(),
"Int63n", rand.Int63n(100),
"ExpFloat64", rand.ExpFloat64())
}
}
// Evolve implements the inner loop of the evolutionary algorithm.
// The population calls the Evolve method of each genome, in parallel. Then,
// each receiver returns a value to replace it in the next generation.
func (q *queens) Evolve(matingPool ...evo.Genome) evo.Genome {
// Crossover:
// We're implementing a diffusion model. For each member of the population,
// we receive a small mating pool containing only our neighbors. We choose
// a mate using a random binary tournament and create a child with
// partially mapped crossover.
mate := sel.BinaryTournament(matingPool...).(*queens)
child := &queens{gene: pool.Get().([]int)}
perm.PMX(child.gene, q.gene, mate.gene)
// Mutation:
// Perform n random swaps where n is taken from an exponential distribution.
mutationCount := math.Ceil(rand.ExpFloat64() - 0.5)
for i := float64(0); i < mutationCount; i++ {
j := rand.Intn(len(child.gene))
k := rand.Intn(len(child.gene))
child.gene[j], child.gene[k] = child.gene[k], child.gene[j]
}
// Replacement:
// Only replace if the child is better or equal.
if q.Fitness() > child.Fitness() {
return q
}
return child
}
func randomSlice(n int) []float64 {
slice := make([]float64, n)
for i := range slice {
slice[i] = rand.ExpFloat64()
}
return slice
}
func gaussianNoise(data []float64) []float64 {
result := make([]float64, len(data))
for i := range data {
result[i] = data[i] + rand.ExpFloat64()
}
return result
}
func main() {
end = make(map[int64]int)
b := big.NewInt(int64(10))
for i := 0; i < size; i++ {
r, _ := c_rand.Int(c_rand.Reader, b)
m := r.Int64()
end[m]++
}
for i, j := range end {
fmt.Print(i)
for m := 0; m < j/(size/100); m++ {
fmt.Print("*")
}
fmt.Println(" ", j)
}
for i := 0; i < 11; i++ {
fmt.Println(c_rand.Prime(c_rand.Reader, 64))
}
for i := 0; i < 11; i++ {
fmt.Println(m_rand.ExpFloat64())
}
}
// Generate and send a random GetValuesSingle request.
func (l *Load) sendMulti(client *gen.HFileServiceClient, diff *gen.HFileServiceClient) {
numKeys := int(math.Abs(rand.ExpFloat64()*10) + 1)
keys := l.randomKeys(numKeys)
r := &gen.SingleHFileKeyRequest{HfileName: &l.collection, SortedKeys: keys}
before := time.Now()
resp, err := client.GetValuesMulti(r)
if err != nil {
log.Println("[GetValuesMulti] Error fetching value:", err, util.PrettyKeys(keys))
}
report.TimeSince(l.rtt+".overall", before)
report.TimeSince(l.rtt+".getValuesMulti", before)
if diff != nil {
beforeDiff := time.Now()
diffResp, diffErr := diff.GetValuesMulti(r)
if diffErr != nil {
log.Println("[GetValuesMulti] Error fetching diff value:", diffErr, util.PrettyKeys(keys))
}
report.TimeSince(l.diffRtt+".overall", beforeDiff)
report.TimeSince(l.diffRtt+".getValuesMulti", beforeDiff)
if err == nil && diffErr == nil && !reflect.DeepEqual(resp, diffResp) {
report.Inc("diffs")
report.Inc("diffs.getValuesMulti")
log.Printf("[DIFF-getValuesMulti] req: %v\n \torig: %v\n\n\tdiff: %v\n", r, resp, diffResp)
}
}
}
// Generate and send a random GetValuesSingle request.
func (l *Load) sendPrefixes(client *gen.HFileServiceClient, diff *gen.HFileServiceClient) {
numKeys := int(math.Abs(rand.ExpFloat64()*10) + 1)
fullKeys := l.randomKeys(numKeys)
prefixes := make([][]byte, len(fullKeys))
for i, v := range fullKeys {
prefixes[i] = v[:len(v)-2]
}
sort.Sort(util.Keys(prefixes))
r := &gen.PrefixRequest{HfileName: &l.collection, SortedKeys: prefixes}
before := time.Now()
resp, err := client.GetValuesForPrefixes(r)
if err != nil {
log.Println("[GetValuesForPrefixes] Error fetching value:", err, util.PrettyKeys(prefixes))
}
report.TimeSince(l.rtt+".overall", before)
report.TimeSince(l.rtt+".GetValuesForPrefixes", before)
if diff != nil {
beforeDiff := time.Now()
diffResp, diffErr := diff.GetValuesForPrefixes(r)
if diffErr != nil {
log.Println("[GetValuesForPrefixes] Error fetching diff value:", diffErr, util.PrettyKeys(prefixes))
}
report.TimeSince(l.diffRtt+".overall", beforeDiff)
report.TimeSince(l.diffRtt+".GetValuesForPrefixes", beforeDiff)
if err == nil && diffErr == nil && !reflect.DeepEqual(resp, diffResp) {
report.Inc("diffs")
report.Inc("diffs.GetValuesForPrefixes")
log.Printf("[DIFF-GetValuesForPrefixes] req: %v\n \torig: %v\n\n\tdiff: %v\n", r, resp, diffResp)
}
}
}
func main() {
rand.Seed(time.Now().UnixNano())
// taking "set" literally from task description
s := map[float64]bool{}
// pick number of elements to add to set
n := rand.Intn(11)
// add random numbers, also throw in an occasional NaN or Inf.
for i := 0; i < n; i++ {
switch rand.Intn(10) {
case 0:
s[math.NaN()] = true
case 1:
s[math.Inf(1)] = true
default:
s[rand.ExpFloat64()] = true
}
}
fmt.Print("s:")
for e := range s {
fmt.Print(" ", e)
}
fmt.Println()
switch lg, ok, nan := largest(s); {
case ok && !nan:
fmt.Println("largest:", lg)
case ok:
fmt.Println("largest:", lg, "(NaN present in data)")
case nan:
fmt.Println("no largest, all data NaN")
default:
fmt.Println("no largest, empty set")
}
}
// Generates sample from general Levy-stable distibution.
func Sample(alpha float64, beta float64, mu float64, sigma float64) float64 {
if beta == 0.0 {
return symmetric(alpha, mu, sigma)
}
v := math.Pi * (rand.Float64() - 0.5)
w := 0.0
for w == 0.0 {
w = rand.ExpFloat64()
}
if alpha == 1.0 {
x := ((0.5*math.Pi+beta*v)*math.Tan(v) -
beta*math.Log(0.5*math.Pi*w*math.Cos(v)/(0.5*math.Pi+beta*v))) / (0.5 * math.Pi)
return sigma*x + beta*sigma*math.Log(sigma)/(0.5*math.Pi) + mu
}
t := beta * math.Tan(0.5*math.Pi*alpha)
s := math.Pow(1.0+t*t, 1.0/(2.0*alpha))
b := math.Atan(t) / alpha
x := s * math.Sin(alpha*(v+b)) *
math.Pow(math.Cos(v-alpha*(v+b))/w, (1.0-alpha)/alpha) /
math.Pow(math.Cos(v), 1.0/alpha)
return sigma*x + mu
}
// Helper function, makes pseudo-random slices.
func makeRandSlice(length uint) (randslice []float64) {
randslice = make([]float64, length)
for i := range randslice {
randslice[i] = rand.ExpFloat64()
}
return
}
// Creates pseudo-random vectors, does scalar multiplication with pseudo-random
// floats, then checks if the result is correct. It checks both the in-place
// and the non-destructive version.
func TestScale(t *testing.T) {
var i, j uint
for i = 0; i < 100; i++ {
a := makeRandomVector(i)
x := rand.ExpFloat64()
b := Scale(a, x)
for j = 0; j < i; j++ {
if b.dims[j] != a.dims[j]*x {
t.Error("Scalar Multiplication failed, ",
"didn't get expected values.")
t.Logf("%f * %f != %f", a.dims[j], x, b.dims[j])
}
}
// Test in-place scalar multiplication
b = a.Copy()
b.Scale(x)
for j = 0; j < i; j++ {
if b.dims[j] != a.dims[j]*x {
t.Error("In-place Scalar Multiplication failed, ",
"didn't get expected values.")
t.Logf("%f * %f != %f", a.dims[j], x, b.dims[j])
}
}
}
}
func init() {
for i := 0; i < len(DataZeroFloats); i++ {
DataZeroFloats[i] = point{float64(0), uint32(i * 60)}
}
for i := 0; i < len(DataSameFloats); i++ {
DataSameFloats[i] = point{float64(1234.567), uint32(i * 60)}
}
for i := 0; i < len(DataSmallRangePosInts); i++ {
DataSmallRangePosInts[i] = point{TwoHoursData[i%120].v, uint32(i * 60)}
}
for i := 0; i < len(DataSmallRangePosFloats); i++ {
v := float64(TwoHoursData[i%120].v) * 1.2
DataSmallRangePosFloats[i] = point{v, uint32(i * 60)}
}
for i := 0; i < len(DataLargeRangePosFloats); i++ {
v := (float64(TwoHoursData[i%120].v) / 1000) * math.MaxFloat64
DataLargeRangePosFloats[i] = point{v, uint32(i * 60)}
}
for i := 0; i < len(DataRandomPosFloats); i++ {
DataRandomPosFloats[i] = point{rand.ExpFloat64(), uint32(i * 60)}
}
for i := 0; i < len(DataRandomFloats); i++ {
DataRandomFloats[i] = point{rand.NormFloat64(), uint32(i * 60)}
}
}
func (b *Exponential) Run() {
var err error
λ := 1.0
for {
select {
case ruleI := <-b.inrule:
// set a parameter of the block
rule, ok := ruleI.(map[string]interface{})
if !ok {
b.Error(errors.New("couldn't assert rule to map"))
}
λ, err = util.ParseFloat(rule, "rate")
if err != nil {
b.Error(err)
}
case <-b.quit:
// quit the block
return
case <-b.inpoll:
// deal with a poll request
b.out <- map[string]interface{}{
"sample": rand.ExpFloat64(),
}
case c := <-b.queryrule:
// deal with a query request
c <- map[string]interface{}{
"rate": λ,
}
}
}
}
func TestTopK(t *testing.T) {
stream := New(10)
ss := []*Stream{New(10), New(10), New(10)}
m := make(map[string]int)
for _, s := range ss {
for i := 0; i < 1e6; i++ {
v := fmt.Sprintf("%x", int8(rand.ExpFloat64()))
s.Insert(v)
m[v]++
}
stream.Merge(s.Query())
}
var sm Samples
for x, s := range m {
sm = append(sm, &Element{x, s})
}
sort.Sort(sort.Reverse(sm))
g := stream.Query()
if len(g) != 10 {
t.Fatalf("got %d, want 10", len(g))
}
for i, e := range g {
if sm[i].Value != e.Value {
t.Errorf("at %d: want %q, got %q", i, sm[i].Value, e.Value)
}
}
}
func TestRand() {
fmt.Println("rand.Int()=", rand.Int())
fmt.Println("rand.Intn(10)=", rand.Intn(10))
fmt.Println("rand.Int31()=", rand.Int31())
fmt.Println("rand.Int31n(10)=", rand.Int31n(10))
fmt.Println("rand.Int63()=", rand.Int63())
fmt.Println("rand.Int63n(10)=", rand.Int63n(10))
fmt.Println("rand.Float32()=", rand.Float32())
fmt.Println("rand.Float64()=", rand.Float64())
fmt.Println("rand.Perm(10)=", rand.Perm(10))
fmt.Println("rand.ExpFloat64()=", rand.ExpFloat64())
fmt.Println("rand.Uint32()=", rand.Uint32())
r := rand.New(rand.NewSource(12346789))
fmt.Println("r.Int()=", r.Int())
fmt.Println("r.Intn(10)=", r.Intn(10))
fmt.Println("r.Int31()=", r.Int31())
fmt.Println("r.Int31n(10)=", r.Int31n(10))
fmt.Println("r.Int63()=", r.Int63())
fmt.Println("r.Int63n(10)=", r.Int63n(10))
fmt.Println("r.Float32()=", r.Float32())
fmt.Println("r.Float64()=", r.Float64())
fmt.Println("r.Perm(10)=", r.Perm(10))
fmt.Println("r.ExpFloat64()=", r.ExpFloat64())
fmt.Println("r.Uint32()=", r.Uint32())
}
// Example_boxPlots draws vertical boxplots.
func Example_boxPlots() *plot.Plot {
rand.Seed(int64(0))
n := 100
uniform := make(plotter.Values, n)
normal := make(plotter.Values, n)
expon := make(plotter.Values, n)
for i := 0; i < n; i++ {
uniform[i] = rand.Float64()
normal[i] = rand.NormFloat64()
expon[i] = rand.ExpFloat64()
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Box Plot"
p.Y.Label.Text = "plotter.Values"
// Make boxes for our data and add them to the plot.
p.Add(plotter.NewBoxPlot(vg.Points(20), 0, uniform),
plotter.NewBoxPlot(vg.Points(20), 1, normal),
plotter.NewBoxPlot(vg.Points(20), 2, expon))
// Set the X axis of the plot to nominal with
// the given names for x=0, x=1 and x=2.
p.NominalX("Uniform\nDistribution", "Normal\nDistribution",
"Exponential\nDistribution")
return p
}
func RunUpdateHook(box string) {
const MEAN = 5
const TIMEOUT = 5 * time.Second
log.Println("Executing ", box)
done := make(chan struct{})
cancelled := false
go func() {
time.Sleep(1*time.Second + time.Duration(1e9*rand.ExpFloat64()*MEAN))
close(done)
if !cancelled {
log.Println(" Completed ", box)
}
}()
// cmd := exec.Command(work.command)
// cmd.Start()
// go func() {
// cmd.Wait()
// close(done)
// }()
select {
case <-done:
return
case <-time.After(TIMEOUT):
cancelled = true
log.Println(" Cancelled ", box)
// cmd.Process.Kill()
}
}
// startUser simulates a stream of user events until the stopper
// indicates it's time to exit.
func startUser(ctx Context, stopper *stop.Stopper) {
for {
userID := 1 + int(rand.ExpFloat64()/rate)
op := randomOp()
if err := stopper.RunTask(func() {
err := runUserOp(ctx, userID, op.typ)
stats.Lock()
_ = stats.hist.RecordValue(int64(userID))
stats.totalOps++
stats.opCounts[op.typ]++
switch {
case err == errNoUser:
stats.noUserOps++
case err == errNoPhoto:
stats.noPhotoOps++
case err != nil:
stats.failedOps++
log.Printf("failed to run %s op for %d: %s", op.name, userID, err)
}
stats.Unlock()
}); err != nil {
return
}
}
}
func (link *Link) Delay() time.Duration {
link.Lock()
defer link.Unlock()
jitter := int64(rand.ExpFloat64() * float64(link.jitter))
latency := jitter + int64(link.spike) + int64(link.latency)
return time.Duration(latency) * time.Millisecond
}
func Example_groupedHorizontalQuartPlots() *plot.Plot {
rand.Seed(int64(0))
n := 100
uniform := make(plotter.Values, n)
normal := make(plotter.Values, n)
expon := make(plotter.Values, n)
for i := 0; i < n; i++ {
uniform[i] = rand.Float64()
normal[i] = rand.NormFloat64()
expon[i] = rand.ExpFloat64()
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Box Plot"
p.Y.Label.Text = "plotter.Values"
w := vg.Points(10)
for x := 0.0; x < 3.0; x++ {
b0 := must(plotter.MakeHorizQuartPlot(x, uniform)).(plotter.HorizQuartPlot)
b0.Offset = -w
b1 := must(plotter.MakeHorizQuartPlot(x, normal)).(plotter.HorizQuartPlot)
b2 := must(plotter.MakeHorizQuartPlot(x, expon)).(plotter.HorizQuartPlot)
b2.Offset = w
p.Add(b0, b1, b2)
}
p.Add(plotter.NewGlyphBoxes())
p.NominalY("Group 0", "Group 1", "Group 2")
return p
}
// Example_quartPlots draws vertical quartile plots.
func Example_quartPlots() *plot.Plot {
rand.Seed(int64(0))
n := 100
uniform := make(plotter.Values, n)
normal := make(plotter.Values, n)
expon := make(plotter.Values, n)
for i := 0; i < n; i++ {
uniform[i] = rand.Float64()
normal[i] = rand.NormFloat64()
expon[i] = rand.ExpFloat64()
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Quartile Plot"
p.Y.Label.Text = "plotter.Values"
p.Add(must(plotter.NewQuartPlot(0, uniform)).(*plotter.QuartPlot),
must(plotter.NewQuartPlot(1, normal)).(*plotter.QuartPlot),
must(plotter.NewQuartPlot(2, expon)).(*plotter.QuartPlot))
// Set the X axis of the plot to nominal with
// the given names for x=0, x=1 and x=2.
p.NominalX("Uniform\nDistribution", "Normal\nDistribution",
"Exponential\nDistribution")
return p
}
// Example_groupedBoxPlots draws vertical boxplots.
func Example_groupedBoxPlots() *plot.Plot {
rand.Seed(int64(0))
n := 100
uniform := make(plotter.Values, n)
normal := make(plotter.Values, n)
expon := make(plotter.Values, n)
for i := 0; i < n; i++ {
uniform[i] = rand.Float64()
normal[i] = rand.NormFloat64()
expon[i] = rand.ExpFloat64()
}
p, err := plot.New()
if err != nil {
panic(err)
}
p.Title.Text = "Box Plot"
p.Y.Label.Text = "plotter.Values"
w := vg.Points(20)
for x := 0.0; x < 3.0; x++ {
b0 := must(plotter.NewBoxPlot(w, x, uniform)).(*plotter.BoxPlot)
b0.Offset = -w - vg.Points(3)
b1 := must(plotter.NewBoxPlot(w, x, normal)).(*plotter.BoxPlot)
b2 := must(plotter.NewBoxPlot(w, x, expon)).(*plotter.BoxPlot)
b2.Offset = w + vg.Points(3)
p.Add(b0, b1, b2)
}
// Set the X axis of the plot to nominal with
// the given names for x=0, x=1 and x=2.
p.NominalX("Group 0", "Group 1", "Group 2")
return p
}
func TestSparseMatrix32(t *testing.T) {
svd := NewGoRedSVD()
assert.NotNil(t, svd)
sparseMatrix32 := make(map[int]map[int]float32)
for row := 0; row < 100; row++ {
sparseMatrix32[row] = make(map[int]float32)
for col := 0; col < 100; col++ {
if rand.Float64() < 0.2 {
sparseMatrix32[row][col] = float32(rand.ExpFloat64())
}
}
}
assert.Equal(t, 100, len(sparseMatrix32))
svd.SetMatrix32(100, 100, sparseMatrix32)
svd.RedSVD(10)
u := svd.MatrixU()
assert.NotNil(t, u)
assert.Equal(t, 100, len(u))
assert.Equal(t, 10, len(u[0]))
v := svd.MatrixV()
assert.NotNil(t, v)
assert.Equal(t, 100, len(v))
assert.Equal(t, 10, len(v[0]))
singularValues := svd.SingularValues()
assert.NotNil(t, singularValues)
assert.Equal(t, 10, len(singularValues))
svd.SetUnnormalized(true)
svd.RedSVD(10)
u = svd.MatrixUNotNormalized()
assert.NotNil(t, u)
assert.Equal(t, 100, len(u))
assert.Equal(t, 10, len(u[0]))
v = svd.MatrixVNotNormalized()
assert.NotNil(t, v)
assert.Equal(t, 100, len(v))
assert.Equal(t, 10, len(v[0]))
singularValues = svd.SingularValues()
assert.NotNil(t, singularValues)
assert.Equal(t, 10, len(singularValues))
norms := svd.GetColumnNorms()
assert.NotNil(t, norms)
assert.Equal(t, 10, len(norms))
DeleteGoRedSVD(svd)
}
func BenchmarkInsert10Bins(b *testing.B) {
b.StopTimer()
h := New(10)
b.StartTimer()
for i := 0; i < b.N; i++ {
f := rand.ExpFloat64()
h.Insert(f)
}
}
func addNoiseToSource(source func() ([]float64, int), strength float64) func() ([]float64, int) {
return func() ([]float64, int) {
data, period := source()
for i := range data {
data[i] += rand.ExpFloat64() * strength
}
return data, period
}
}
// Rand returns a random sample drawn from the distribution.
func (e Exponential) Rand() float64 {
var rnd float64
if e.Source == nil {
rnd = rand.ExpFloat64()
} else {
rnd = e.Source.ExpFloat64()
}
return rnd / e.Rate
}
