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https://github.com/gonum/gonum.git
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internal/rand: delete shim package
This commit is contained in:
Dan Kortschak
@@ -1,393 +0,0 @@
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// Copyright ©2024 The Gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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// Copyright 2009 The Go Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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// Package rand implements pseudo-random number generators.
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//
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// Random numbers are generated by a Source. Top-level functions, such as
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// Float64 and Int, use a default shared Source that produces a deterministic
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// sequence of values each time a program is run. Use the Seed function to
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// initialize the default Source if different behavior is required for each run.
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// The default Source, a LockedSource, is safe for concurrent use by multiple
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// goroutines, but Sources created by NewSource are not. However, Sources are small
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// and it is reasonable to have a separate Source for each goroutine, seeded
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// differently, to avoid locking.
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//
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// For random numbers suitable for security-sensitive work, see the crypto/rand
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// package.
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package rand
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import (
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"math/rand/v2"
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"sync"
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)
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// A Source represents a source of uniformly-distributed
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// pseudo-random int64 values in the range [0, 1<<64).
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type Source interface {
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Uint64() uint64
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Seed(seed uint64)
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}
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// NewSource returns a new pseudo-random Source seeded with the given value.
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func NewSource(seed uint64) Source {
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return &pcgShim{rand.NewPCG(seed, seed)}
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}
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type pcgShim struct {
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*rand.PCG
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}
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func (p *pcgShim) Seed(seed uint64) {
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p.PCG.Seed(seed, seed)
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}
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// A Rand is a source of random numbers.
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type Rand struct {
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src Source
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// readVal contains remainder of 64-bit integer used for bytes
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// generation during most recent Read call.
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// It is saved so next Read call can start where the previous
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// one finished.
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readVal uint64
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// readPos indicates the number of low-order bytes of readVal
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// that are still valid.
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readPos int8
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}
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// New returns a new Rand that uses random values from src
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// to generate other random values.
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func New(src Source) *Rand {
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return &Rand{src: src}
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}
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func (r *Rand) NormFloat64() float64 {
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return rand.New(r.src).NormFloat64()
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}
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func (r *Rand) ExpFloat64() float64 {
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return rand.New(r.src).ExpFloat64()
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}
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// Seed uses the provided seed value to initialize the generator to a deterministic state.
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// Seed should not be called concurrently with any other Rand method.
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func (r *Rand) Seed(seed uint64) {
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if lk, ok := r.src.(*LockedSource); ok {
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lk.seedPos(seed, &r.readPos)
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return
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}
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r.src.Seed(seed)
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r.readPos = 0
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}
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// Uint64 returns a pseudo-random 64-bit integer as a uint64.
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func (r *Rand) Uint64() uint64 { return r.src.Uint64() }
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// Int63 returns a non-negative pseudo-random 63-bit integer as an int64.
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func (r *Rand) Int63() int64 { return int64(r.src.Uint64() &^ (1 << 63)) }
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// Uint32 returns a pseudo-random 32-bit value as a uint32.
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func (r *Rand) Uint32() uint32 { return uint32(r.Uint64() >> 32) }
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// Int31 returns a non-negative pseudo-random 31-bit integer as an int32.
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func (r *Rand) Int31() int32 { return int32(r.Uint64() >> 33) }
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// Int returns a non-negative pseudo-random int.
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func (r *Rand) Int() int {
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u := uint(r.Uint64())
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return int(u << 1 >> 1) // clear sign bit.
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}
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const maxUint64 = (1 << 64) - 1
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// Uint64n returns, as a uint64, a pseudo-random number in [0,n).
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// It is guaranteed more uniform than taking a Source value mod n
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// for any n that is not a power of 2.
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func (r *Rand) Uint64n(n uint64) uint64 {
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if n&(n-1) == 0 { // n is power of two, can mask
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if n == 0 {
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panic("invalid argument to Uint64n")
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}
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return r.Uint64() & (n - 1)
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}
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// If n does not divide v, to avoid bias we must not use
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// a v that is within maxUint64%n of the top of the range.
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v := r.Uint64()
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if v > maxUint64-n { // Fast check.
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ceiling := maxUint64 - maxUint64%n
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for v >= ceiling {
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v = r.Uint64()
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}
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}
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return v % n
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}
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// Int63n returns, as an int64, a non-negative pseudo-random number in [0,n).
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// It panics if n <= 0.
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func (r *Rand) Int63n(n int64) int64 {
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if n <= 0 {
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panic("invalid argument to Int63n")
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}
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return int64(r.Uint64n(uint64(n)))
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}
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// Int31n returns, as an int32, a non-negative pseudo-random number in [0,n).
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// It panics if n <= 0.
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func (r *Rand) Int31n(n int32) int32 {
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if n <= 0 {
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panic("invalid argument to Int31n")
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}
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// TODO: Avoid some 64-bit ops to make it more efficient on 32-bit machines.
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return int32(r.Uint64n(uint64(n)))
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}
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// Intn returns, as an int, a non-negative pseudo-random number in [0,n).
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// It panics if n <= 0.
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func (r *Rand) Intn(n int) int {
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if n <= 0 {
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panic("invalid argument to Intn")
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}
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// TODO: Avoid some 64-bit ops to make it more efficient on 32-bit machines.
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return int(r.Uint64n(uint64(n)))
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}
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// Float64 returns, as a float64, a pseudo-random number in [0.0,1.0).
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func (r *Rand) Float64() float64 {
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// There is one bug in the value stream: r.Int63() may be so close
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// to 1<<63 that the division rounds up to 1.0, and we've guaranteed
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// that the result is always less than 1.0.
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//
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// We tried to fix this by mapping 1.0 back to 0.0, but since float64
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// values near 0 are much denser than near 1, mapping 1 to 0 caused
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// a theoretically significant overshoot in the probability of returning 0.
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// Instead of that, if we round up to 1, just try again.
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// Getting 1 only happens 1/2⁵³ of the time, so most clients
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// will not observe it anyway.
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again:
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f := float64(r.Uint64n(1<<53)) / (1 << 53)
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if f == 1.0 {
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goto again // resample; this branch is taken O(never)
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}
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return f
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}
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// Float32 returns, as a float32, a pseudo-random number in [0.0,1.0).
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func (r *Rand) Float32() float32 {
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// We do not want to return 1.0.
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// This only happens 1/2²⁴ of the time (plus the 1/2⁵³ of the time in Float64).
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again:
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f := float32(r.Float64())
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if f == 1 {
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goto again // resample; this branch is taken O(very rarely)
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}
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return f
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}
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// Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n).
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func (r *Rand) Perm(n int) []int {
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m := make([]int, n)
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// In the following loop, the iteration when i=0 always swaps m[0] with m[0].
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// A change to remove this useless iteration is to assign 1 to i in the init
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// statement. But Perm also effects r. Making this change will affect
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// the final state of r. So this change can't be made for compatibility
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// reasons for Go 1.
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for i := 0; i < n; i++ {
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j := r.Intn(i + 1)
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m[i] = m[j]
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m[j] = i
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}
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return m
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}
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// Shuffle pseudo-randomizes the order of elements.
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// n is the number of elements. Shuffle panics if n < 0.
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// swap swaps the elements with indexes i and j.
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func (r *Rand) Shuffle(n int, swap func(i, j int)) {
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if n < 0 {
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panic("invalid argument to Shuffle")
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}
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// Fisher-Yates shuffle: https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle
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// Shuffle really ought not be called with n that doesn't fit in 32 bits.
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// Not only will it take a very long time, but with 2³¹! possible permutations,
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// there's no way that any PRNG can have a big enough internal state to
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// generate even a minuscule percentage of the possible permutations.
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// Nevertheless, the right API signature accepts an int n, so handle it as best we can.
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i := n - 1
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for ; i > 1<<31-1-1; i-- {
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j := int(r.Int63n(int64(i + 1)))
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swap(i, j)
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}
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for ; i > 0; i-- {
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j := int(r.Int31n(int32(i + 1)))
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swap(i, j)
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}
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}
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// Read generates len(p) random bytes and writes them into p. It
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// always returns len(p) and a nil error.
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// Read should not be called concurrently with any other Rand method unless
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// the underlying source is a LockedSource.
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func (r *Rand) Read(p []byte) (n int, err error) {
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if lk, ok := r.src.(*LockedSource); ok {
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return lk.Read(p, &r.readVal, &r.readPos)
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}
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return read(p, r.src, &r.readVal, &r.readPos)
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}
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func read(p []byte, src Source, readVal *uint64, readPos *int8) (n int, err error) {
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pos := *readPos
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val := *readVal
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rng, _ := src.(*pcgShim)
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for n = 0; n < len(p); n++ {
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if pos == 0 {
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if rng != nil {
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val = rng.Uint64()
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} else {
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val = src.Uint64()
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}
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pos = 8
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}
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p[n] = byte(val)
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val >>= 8
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pos--
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}
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*readPos = pos
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*readVal = val
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return
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}
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/*
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* Top-level convenience functions
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*/
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var globalRand = New(&LockedSource{src: *NewSource(1).(*pcgShim)})
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// Type assert that globalRand's source is a LockedSource whose src is a PCGSource.
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var _ pcgShim = globalRand.src.(*LockedSource).src
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// Seed uses the provided seed value to initialize the default Source to a
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// deterministic state. If Seed is not called, the generator behaves as
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// if seeded by Seed(1).
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// Seed, unlike the Rand.Seed method, is safe for concurrent use.
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func Seed(seed uint64) { globalRand.Seed(seed) }
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// Int63 returns a non-negative pseudo-random 63-bit integer as an int64
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// from the default Source.
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func Int63() int64 { return globalRand.Int63() }
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// Uint32 returns a pseudo-random 32-bit value as a uint32
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// from the default Source.
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func Uint32() uint32 { return globalRand.Uint32() }
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// Uint64 returns a pseudo-random 64-bit value as a uint64
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// from the default Source.
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func Uint64() uint64 { return globalRand.Uint64() }
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// Int31 returns a non-negative pseudo-random 31-bit integer as an int32
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// from the default Source.
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func Int31() int32 { return globalRand.Int31() }
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// Int returns a non-negative pseudo-random int from the default Source.
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func Int() int { return globalRand.Int() }
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// Int63n returns, as an int64, a non-negative pseudo-random number in [0,n)
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// from the default Source.
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// It panics if n <= 0.
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func Int63n(n int64) int64 { return globalRand.Int63n(n) }
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// Int31n returns, as an int32, a non-negative pseudo-random number in [0,n)
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// from the default Source.
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// It panics if n <= 0.
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func Int31n(n int32) int32 { return globalRand.Int31n(n) }
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// Intn returns, as an int, a non-negative pseudo-random number in [0,n)
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// from the default Source.
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// It panics if n <= 0.
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func Intn(n int) int { return globalRand.Intn(n) }
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// Float64 returns, as a float64, a pseudo-random number in [0.0,1.0)
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// from the default Source.
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func Float64() float64 { return globalRand.Float64() }
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// Float32 returns, as a float32, a pseudo-random number in [0.0,1.0)
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// from the default Source.
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func Float32() float32 { return globalRand.Float32() }
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// Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n)
|
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// from the default Source.
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func Perm(n int) []int { return globalRand.Perm(n) }
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|
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// Shuffle pseudo-randomizes the order of elements using the default Source.
|
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// n is the number of elements. Shuffle panics if n < 0.
|
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// swap swaps the elements with indexes i and j.
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func Shuffle(n int, swap func(i, j int)) { globalRand.Shuffle(n, swap) }
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|
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// Read generates len(p) random bytes from the default Source and
|
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// writes them into p. It always returns len(p) and a nil error.
|
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// Read, unlike the Rand.Read method, is safe for concurrent use.
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func Read(p []byte) (n int, err error) { return globalRand.Read(p) }
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|
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// NormFloat64 returns a normally distributed float64 in the range
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// [-math.MaxFloat64, +math.MaxFloat64] with
|
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// standard normal distribution (mean = 0, stddev = 1)
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// from the default Source.
|
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// To produce a different normal distribution, callers can
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// adjust the output using:
|
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//
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// sample = NormFloat64() * desiredStdDev + desiredMean
|
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func NormFloat64() float64 { return globalRand.NormFloat64() }
|
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|
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// ExpFloat64 returns an exponentially distributed float64 in the range
|
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// (0, +math.MaxFloat64] with an exponential distribution whose rate parameter
|
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// (lambda) is 1 and whose mean is 1/lambda (1) from the default Source.
|
||||
// To produce a distribution with a different rate parameter,
|
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// callers can adjust the output using:
|
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//
|
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// sample = ExpFloat64() / desiredRateParameter
|
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func ExpFloat64() float64 { return globalRand.ExpFloat64() }
|
||||
|
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// LockedSource is an implementation of Source that is concurrency-safe.
|
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// A Rand using a LockedSource is safe for concurrent use.
|
||||
//
|
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// The zero value of LockedSource is valid, but should be seeded before use.
|
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type LockedSource struct {
|
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lk sync.Mutex
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src pcgShim
|
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}
|
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func (s *LockedSource) Uint64() (n uint64) {
|
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s.lk.Lock()
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n = s.src.Uint64()
|
||||
s.lk.Unlock()
|
||||
return
|
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}
|
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|
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func (s *LockedSource) Seed(seed uint64) {
|
||||
s.lk.Lock()
|
||||
s.src.Seed(seed)
|
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s.lk.Unlock()
|
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}
|
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|
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// seedPos implements Seed for a LockedSource without a race condiiton.
|
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func (s *LockedSource) seedPos(seed uint64, readPos *int8) {
|
||||
s.lk.Lock()
|
||||
s.src.Seed(seed)
|
||||
*readPos = 0
|
||||
s.lk.Unlock()
|
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}
|
||||
|
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// Read implements Read for a LockedSource.
|
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func (s *LockedSource) Read(p []byte, readVal *uint64, readPos *int8) (n int, err error) {
|
||||
s.lk.Lock()
|
||||
n, err = read(p, &s.src, readVal, readPos)
|
||||
s.lk.Unlock()
|
||||
return
|
||||
}
|
||||
@@ -1,368 +0,0 @@
|
||||
// Copyright ©2024 The Gonum Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
// Copyright 2009 The Go Authors. All rights reserved.
|
||||
// Use of this source code is governed by a BSD-style
|
||||
// license that can be found in the LICENSE file.
|
||||
|
||||
package rand
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
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"math"
|
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"os"
|
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"runtime"
|
||||
"strings"
|
||||
"testing"
|
||||
"testing/iotest"
|
||||
)
|
||||
|
||||
const (
|
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numTestSamples = 10000
|
||||
)
|
||||
|
||||
type statsResults struct {
|
||||
mean float64
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||||
stddev float64
|
||||
closeEnough float64
|
||||
maxError float64
|
||||
}
|
||||
|
||||
func nearEqual(a, b, closeEnough, maxError float64) bool {
|
||||
absDiff := math.Abs(a - b)
|
||||
if absDiff < closeEnough { // Necessary when one value is zero and one value is close to zero.
|
||||
return true
|
||||
}
|
||||
return absDiff/max(math.Abs(a), math.Abs(b)) < maxError
|
||||
}
|
||||
|
||||
var testSeeds = []uint64{1, 1754801282, 1698661970, 1550503961}
|
||||
|
||||
// checkSimilarDistribution returns success if the mean and stddev of the
|
||||
// two statsResults are similar.
|
||||
func (sr *statsResults) checkSimilarDistribution(expected *statsResults) error {
|
||||
if !nearEqual(sr.mean, expected.mean, expected.closeEnough, expected.maxError) {
|
||||
s := fmt.Sprintf("mean %v != %v (allowed error %v, %v)", sr.mean, expected.mean, expected.closeEnough, expected.maxError)
|
||||
fmt.Println(s)
|
||||
return errors.New(s)
|
||||
}
|
||||
if !nearEqual(sr.stddev, expected.stddev, expected.closeEnough, expected.maxError) {
|
||||
s := fmt.Sprintf("stddev %v != %v (allowed error %v, %v)", sr.stddev, expected.stddev, expected.closeEnough, expected.maxError)
|
||||
fmt.Println(s)
|
||||
return errors.New(s)
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func getStatsResults(samples []float64) *statsResults {
|
||||
res := new(statsResults)
|
||||
var sum, squaresum float64
|
||||
for _, s := range samples {
|
||||
sum += s
|
||||
squaresum += s * s
|
||||
}
|
||||
res.mean = sum / float64(len(samples))
|
||||
res.stddev = math.Sqrt(squaresum/float64(len(samples)) - res.mean*res.mean)
|
||||
return res
|
||||
}
|
||||
|
||||
func checkSampleDistribution(t *testing.T, samples []float64, expected *statsResults) {
|
||||
t.Helper()
|
||||
actual := getStatsResults(samples)
|
||||
err := actual.checkSimilarDistribution(expected)
|
||||
if err != nil {
|
||||
t.Error(err)
|
||||
}
|
||||
}
|
||||
|
||||
func checkSampleSliceDistributions(t *testing.T, samples []float64, nslices int, expected *statsResults) {
|
||||
t.Helper()
|
||||
chunk := len(samples) / nslices
|
||||
for i := 0; i < nslices; i++ {
|
||||
low := i * chunk
|
||||
var high int
|
||||
if i == nslices-1 {
|
||||
high = len(samples) - 1
|
||||
} else {
|
||||
high = (i + 1) * chunk
|
||||
}
|
||||
checkSampleDistribution(t, samples[low:high], expected)
|
||||
}
|
||||
}
|
||||
|
||||
//
|
||||
// Normal distribution tests
|
||||
//
|
||||
|
||||
func generateNormalSamples(nsamples int, mean, stddev float64, seed uint64) []float64 {
|
||||
r := New(NewSource(seed))
|
||||
samples := make([]float64, nsamples)
|
||||
for i := range samples {
|
||||
samples[i] = r.NormFloat64()*stddev + mean
|
||||
}
|
||||
return samples
|
||||
}
|
||||
|
||||
func testNormalDistribution(t *testing.T, nsamples int, mean, stddev float64, seed uint64) {
|
||||
//fmt.Printf("testing nsamples=%v mean=%v stddev=%v seed=%v\n", nsamples, mean, stddev, seed);
|
||||
|
||||
samples := generateNormalSamples(nsamples, mean, stddev, seed)
|
||||
errorScale := max(1.0, stddev) // Error scales with stddev
|
||||
expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.08 * errorScale}
|
||||
|
||||
// Make sure that the entire set matches the expected distribution.
|
||||
checkSampleDistribution(t, samples, expected)
|
||||
|
||||
// Make sure that each half of the set matches the expected distribution.
|
||||
checkSampleSliceDistributions(t, samples, 2, expected)
|
||||
|
||||
// Make sure that each 7th of the set matches the expected distribution.
|
||||
checkSampleSliceDistributions(t, samples, 7, expected)
|
||||
}
|
||||
|
||||
// Actual tests
|
||||
|
||||
func TestStandardNormalValues(t *testing.T) {
|
||||
for _, seed := range testSeeds {
|
||||
testNormalDistribution(t, numTestSamples, 0, 1, seed)
|
||||
}
|
||||
}
|
||||
|
||||
func TestNonStandardNormalValues(t *testing.T) {
|
||||
sdmax := 1000.0
|
||||
mmax := 1000.0
|
||||
if testing.Short() {
|
||||
sdmax = 5
|
||||
mmax = 5
|
||||
}
|
||||
for sd := 0.5; sd < sdmax; sd *= 2 {
|
||||
for m := 0.5; m < mmax; m *= 2 {
|
||||
for _, seed := range testSeeds {
|
||||
testNormalDistribution(t, numTestSamples, m, sd, seed)
|
||||
if testing.Short() {
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//
|
||||
// Exponential distribution tests
|
||||
//
|
||||
|
||||
func generateExponentialSamples(nsamples int, rate float64, seed uint64) []float64 {
|
||||
r := New(NewSource(seed))
|
||||
samples := make([]float64, nsamples)
|
||||
for i := range samples {
|
||||
samples[i] = r.ExpFloat64() / rate
|
||||
}
|
||||
return samples
|
||||
}
|
||||
|
||||
func testExponentialDistribution(t *testing.T, nsamples int, rate float64, seed uint64) {
|
||||
//fmt.Printf("testing nsamples=%v rate=%v seed=%v\n", nsamples, rate, seed)
|
||||
|
||||
mean := 1 / rate
|
||||
stddev := mean
|
||||
|
||||
samples := generateExponentialSamples(nsamples, rate, seed)
|
||||
errorScale := max(1.0, 1/rate) // Error scales with the inverse of the rate
|
||||
expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.20 * errorScale}
|
||||
|
||||
// Make sure that the entire set matches the expected distribution.
|
||||
checkSampleDistribution(t, samples, expected)
|
||||
|
||||
// Make sure that each half of the set matches the expected distribution.
|
||||
checkSampleSliceDistributions(t, samples, 2, expected)
|
||||
|
||||
// Make sure that each 7th of the set matches the expected distribution.
|
||||
checkSampleSliceDistributions(t, samples, 7, expected)
|
||||
}
|
||||
|
||||
// Actual tests
|
||||
|
||||
func TestStandardExponentialValues(t *testing.T) {
|
||||
for _, seed := range testSeeds {
|
||||
testExponentialDistribution(t, numTestSamples, 1, seed)
|
||||
}
|
||||
}
|
||||
|
||||
func TestNonStandardExponentialValues(t *testing.T) {
|
||||
for rate := 0.05; rate < 10; rate *= 2 {
|
||||
for _, seed := range testSeeds {
|
||||
testExponentialDistribution(t, numTestSamples, rate, seed)
|
||||
if testing.Short() {
|
||||
break
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// compareUint32Slices returns the first index where the two slices
|
||||
// disagree, or <0 if the lengths are the same and all elements
|
||||
// are identical.
|
||||
func compareUint32Slices(s1, s2 []uint32) int {
|
||||
if len(s1) != len(s2) {
|
||||
if len(s1) > len(s2) {
|
||||
return len(s2) + 1
|
||||
}
|
||||
return len(s1) + 1
|
||||
}
|
||||
for i := range s1 {
|
||||
if s1[i] != s2[i] {
|
||||
return i
|
||||
}
|
||||
}
|
||||
return -1
|
||||
}
|
||||
|
||||
// compareFloat32Slices returns the first index where the two slices
|
||||
// disagree, or <0 if the lengths are the same and all elements
|
||||
// are identical.
|
||||
func compareFloat32Slices(s1, s2 []float32) int {
|
||||
if len(s1) != len(s2) {
|
||||
if len(s1) > len(s2) {
|
||||
return len(s2) + 1
|
||||
}
|
||||
return len(s1) + 1
|
||||
}
|
||||
for i := range s1 {
|
||||
if !nearEqual(float64(s1[i]), float64(s2[i]), 0, 1e-7) {
|
||||
return i
|
||||
}
|
||||
}
|
||||
return -1
|
||||
}
|
||||
|
||||
func hasSlowFloatingPoint() bool {
|
||||
switch runtime.GOARCH {
|
||||
case "arm":
|
||||
return os.Getenv("GOARM") == "5" || strings.HasSuffix(os.Getenv("GOARM"), ",softfloat")
|
||||
case "mips", "mipsle", "mips64", "mips64le":
|
||||
// Be conservative and assume that all mips boards
|
||||
// have emulated floating point.
|
||||
// TODO: detect what it actually has.
|
||||
return true
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func TestFloat32(t *testing.T) {
|
||||
// For issue 6721, the problem came after 7533753 calls, so check 10e6.
|
||||
num := int(10e6)
|
||||
// But do the full amount only on builders (not locally).
|
||||
// But ARM5 floating point emulation is slow (Issue 10749), so
|
||||
// do less for that builder:
|
||||
if testing.Short() && hasSlowFloatingPoint() { // TODO: (testenv.Builder() == "" || hasSlowFloatingPoint())
|
||||
num /= 100 // 1.72 seconds instead of 172 seconds
|
||||
}
|
||||
|
||||
r := New(NewSource(1))
|
||||
for ct := 0; ct < num; ct++ {
|
||||
f := r.Float32()
|
||||
if f >= 1 {
|
||||
t.Fatal("Float32() should be in range [0,1). ct:", ct, "f:", f)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func testReadUniformity(t *testing.T, n int, seed uint64) {
|
||||
r := New(NewSource(seed))
|
||||
buf := make([]byte, n)
|
||||
nRead, err := r.Read(buf)
|
||||
if err != nil {
|
||||
t.Errorf("Read err %v", err)
|
||||
}
|
||||
if nRead != n {
|
||||
t.Errorf("Read returned unexpected n; %d != %d", nRead, n)
|
||||
}
|
||||
|
||||
// Expect a uniform distribution of byte values, which lie in [0, 255].
|
||||
var (
|
||||
mean = 255.0 / 2
|
||||
stddev = 256.0 / math.Sqrt(12.0)
|
||||
errorScale = stddev / math.Sqrt(float64(n))
|
||||
)
|
||||
|
||||
expected := &statsResults{mean, stddev, 0.10 * errorScale, 0.08 * errorScale}
|
||||
|
||||
// Cast bytes as floats to use the common distribution-validity checks.
|
||||
samples := make([]float64, n)
|
||||
for i, val := range buf {
|
||||
samples[i] = float64(val)
|
||||
}
|
||||
// Make sure that the entire set matches the expected distribution.
|
||||
checkSampleDistribution(t, samples, expected)
|
||||
}
|
||||
|
||||
func TestReadUniformity(t *testing.T) {
|
||||
testBufferSizes := []int{
|
||||
2, 4, 7, 64, 1024, 1 << 16, 1 << 20,
|
||||
}
|
||||
for _, seed := range testSeeds {
|
||||
for _, n := range testBufferSizes {
|
||||
testReadUniformity(t, n, seed)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestReadEmpty(t *testing.T) {
|
||||
r := New(NewSource(1))
|
||||
buf := make([]byte, 0)
|
||||
n, err := r.Read(buf)
|
||||
if err != nil {
|
||||
t.Errorf("Read err into empty buffer; %v", err)
|
||||
}
|
||||
if n != 0 {
|
||||
t.Errorf("Read into empty buffer returned unexpected n of %d", n)
|
||||
}
|
||||
}
|
||||
|
||||
func TestReadByOneByte(t *testing.T) {
|
||||
r := New(NewSource(1))
|
||||
b1 := make([]byte, 100)
|
||||
_, err := io.ReadFull(iotest.OneByteReader(r), b1)
|
||||
if err != nil {
|
||||
t.Errorf("read by one byte: %v", err)
|
||||
}
|
||||
r = New(NewSource(1))
|
||||
b2 := make([]byte, 100)
|
||||
_, err = r.Read(b2)
|
||||
if err != nil {
|
||||
t.Errorf("read: %v", err)
|
||||
}
|
||||
if !bytes.Equal(b1, b2) {
|
||||
t.Errorf("read by one byte vs single read:\n%x\n%x", b1, b2)
|
||||
}
|
||||
}
|
||||
|
||||
func TestReadSeedReset(t *testing.T) {
|
||||
r := New(NewSource(42))
|
||||
b1 := make([]byte, 128)
|
||||
_, err := r.Read(b1)
|
||||
if err != nil {
|
||||
t.Errorf("read: %v", err)
|
||||
}
|
||||
r.Seed(42)
|
||||
b2 := make([]byte, 128)
|
||||
_, err = r.Read(b2)
|
||||
if err != nil {
|
||||
t.Errorf("read: %v", err)
|
||||
}
|
||||
if !bytes.Equal(b1, b2) {
|
||||
t.Errorf("mismatch after re-seed:\n%x\n%x", b1, b2)
|
||||
}
|
||||
}
|
||||
|
||||
func TestShuffleSmall(t *testing.T) {
|
||||
// Check that Shuffle allows n=0 and n=1, but that swap is never called for them.
|
||||
r := New(NewSource(1))
|
||||
for n := 0; n <= 1; n++ {
|
||||
r.Shuffle(n, func(i, j int) { t.Fatalf("swap called, n=%d i=%d j=%d", n, i, j) })
|
||||
}
|
||||
}
|
||||
@@ -1 +0,0 @@
|
||||
checks = ["inherit", "-U1000"]
|
||||
Reference in New Issue
Block a user