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package gopter
import (
"math/rand"
"time"
)
// GenParameters encapsulates the parameters for all generators.
type GenParameters struct {
MinSize int
MaxSize int
MaxShrinkCount int
Rng *rand.Rand
}
// WithSize modifies the size parameter. The size parameter defines an upper bound for the size of
// generated slices or strings.
func (p *GenParameters) WithSize(size int) *GenParameters {
newParameters := *p
newParameters.MaxSize = size
return &newParameters
}
// NextBool create a random boolean using the underlying Rng.
func (p *GenParameters) NextBool() bool {
return p.Rng.Int63()&1 == 0
}
// NextInt64 create a random int64 using the underlying Rng.
func (p *GenParameters) NextInt64() int64 {
v := p.Rng.Int63()
if p.NextBool() {
return -v
}
return v
}
// NextUint64 create a random uint64 using the underlying Rng.
func (p *GenParameters) NextUint64() uint64 {
first := uint64(p.Rng.Int63())
second := uint64(p.Rng.Int63())
return (first << 1) ^ second
}
// CloneWithSeed clone the current parameters with a new seed.
// This is useful to create subsections that can rerun (provided you keep the
// seed)
func (p *GenParameters) CloneWithSeed(seed int64) *GenParameters {
return &GenParameters{
MinSize: p.MinSize,
MaxSize: p.MaxSize,
MaxShrinkCount: p.MaxShrinkCount,
Rng: rand.New(NewLockedSource(seed)),
}
}
// DefaultGenParameters creates default GenParameters.
func DefaultGenParameters() *GenParameters {
seed := time.Now().UnixNano()
return &GenParameters{
MinSize: 0,
MaxSize: 100,
MaxShrinkCount: 1000,
Rng: rand.New(NewLockedSource(seed)),
}
}
// MinGenParameters creates minimal GenParameters.
// Note: Most likely you do not want to use these for actual testing
func MinGenParameters() *GenParameters {
seed := time.Now().UnixNano()
return &GenParameters{
MinSize: 0,
MaxSize: 0,
MaxShrinkCount: 0,
Rng: rand.New(NewLockedSource(seed)),
}
}
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