// 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"
	"math"
	"os"
	"runtime"
	"strings"
	"testing"
	"testing/iotest"
)

const (
	numTestSamples = 10000
)

type statsResults struct {
	mean        float64
	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) })
	}
}