discard """ joinable: false # to avoid messing with global rand state matrix: "--mm:refc; --mm:orc; --backend:js --jsbigint64:off -d:nimStringHash2; --backend:js --jsbigint64:on" """ import std/[assertions, formatfloat] import std/[random, math, stats, sets, tables] import std/private/jsutils when not defined(js): import std/os randomize(233) proc main() = var occur: array[1000, int] for i in 0..100_000: let x = rand(high(occur)) inc occur[x] doAssert max(occur) <= 140 and min(occur) >= 60 # gives some slack var a = [0, 1] shuffle(a) doAssert a in [[0,1], [1,0]] doAssert rand(0) == 0 when not defined(nimscript): doAssert sample("a") == 'a' when compileOption("rangeChecks") and not defined(nimscript): doAssertRaises(RangeDefect): discard rand(-1) doAssertRaises(RangeDefect): discard rand(-1.0) # don't use causes integer overflow doAssert compiles(rand[int](low(int) .. high(int))) main() block: when not defined(js): doAssert almostEqual(rand(12.5), 7.355175342026979) doAssert almostEqual(rand(2233.3322), 499.342386778917) type DiceRoll = range[0..6] when not defined(js): doAssert rand(DiceRoll).int == 3 else: doAssert rand(DiceRoll).int == 6 var rs: RunningStat for j in 1..5: for i in 1 .. 100_000: rs.push(gauss()) doAssert abs(rs.mean-0) < 0.08, $rs.mean doAssert abs(rs.standardDeviation()-1.0) < 0.1 let bounds = [3.5, 5.0] for a in [rs.max, -rs.min]: doAssert a >= bounds[0] and a <= bounds[1] rs.clear() block: type DiceRoll = range[3..6] var flag = false for i in 0..<100: if rand(5.DiceRoll) < 3: flag = true doAssert flag # because of: rand(max: int): int block: # random int block: # there might be some randomness var set = initHashSet[int](128) for i in 1..1000: incl(set, rand(high(int))) doAssert len(set) == 1000 block: # single number bounds work var rand: int for i in 1..1000: rand = rand(1000) doAssert rand <= 1000 doAssert rand >= 0 block: # slice bounds work var rand: int for i in 1..1000: rand = rand(100..1000) doAssert rand <= 1000 doAssert rand >= 100 block: # again gives new numbers var rand1 = rand(1000000) when not (defined(js) or defined(nimscript)): os.sleep(200) var rand2 = rand(1000000) doAssert rand1 != rand2 block: # random float block: # there might be some randomness var set = initHashSet[float](128) for i in 1..100: incl(set, rand(1.0)) doAssert len(set) == 100 block: # single number bounds work var rand: float for i in 1..1000: rand = rand(1000.0) doAssert rand <= 1000.0 doAssert rand >= 0.0 block: # slice bounds work var rand: float for i in 1..1000: rand = rand(100.0..1000.0) doAssert rand <= 1000.0 doAssert rand >= 100.0 block: # again gives new numbers var rand1: float = rand(1000000.0) when not (defined(js) or defined(nimscript)): os.sleep(200) var rand2: float = rand(1000000.0) doAssert rand1 != rand2 block: # random sample block: # "non-uniform array sample unnormalized int CDF let values = [10, 20, 30, 40, 50] # values let counts = [4, 3, 2, 1, 0] # weights aka unnormalized probabilities var histo = initCountTable[int]() let cdf = counts.cumsummed # unnormalized CDF for i in 0 ..< 5000: histo.inc(sample(values, cdf)) doAssert histo.len == 4 # number of non-zero in `counts` # Any one bin is a binomial random var for n samples, each with prob p of # adding a count to k; E[k]=p*n, Var k=p*(1-p)*n, approximately Normal for # big n. So, P(abs(k - p*n)/sqrt(p*(1-p)*n))>3.0) =~ 0.0027, while # P(wholeTestFails) =~ 1 - P(binPasses)^4 =~ 1 - (1-0.0027)^4 =~ 0.01. for i, c in counts: if c == 0: doAssert values[i] notin histo continue let p = float(c) / float(cdf[^1]) let n = 5000.0 let expected = p * n let stdDev = sqrt(n * p * (1.0 - p)) doAssert abs(float(histo[values[i]]) - expected) <= 3.0 * stdDev block: # non-uniform array sample normalized float CDF let values = [10, 20, 30, 40, 50] # values let counts = [0.4, 0.3, 0.2, 0.1, 0] # probabilities var histo = initCountTable[int]() let cdf = counts.cumsummed # normalized CDF for i in 0 ..< 5000: histo.inc(sample(values, cdf)) doAssert histo.len == 4 # number of non-zero in ``counts`` for i, c in counts: if c == 0: doAssert values[i] notin histo continue let p = float(c) / float(cdf[^1]) let n = 5000.0 let expected = p * n let stdDev = sqrt(n * p * (1.0 - p)) # NOTE: like unnormalized int CDF test, P(wholeTestFails) =~ 0.01. doAssert abs(float(histo[values[i]]) - expected) <= 3.0 * stdDev block: # 0 is a valid seed var r = initRand(0) doAssert r.rand(1.0) != r.rand(1.0) r = initRand(10) doAssert r.rand(1.0) != r.rand(1.0) # changing the seed changes the sequence var r1 = initRand(123) var r2 = initRand(124) doAssert r1.rand(1.0) != r2.rand(1.0) block: # bug #17467 let n = 1000 for i in -n .. n: var r = initRand(i) let x = r.rand(1.0) doAssert x > 1e-4, $(x, i) # This used to fail for each i in 0..<26844, i.e. the 1st produced value # was predictable and < 1e-4, skewing distributions. block: # bug #16360, Natural overload var r = initRand() template test(a) = let a2 = a block: let a3 = r.rand(a2) doAssert a3 <= a2 doAssert a3.type is a2.type block: let a3 = rand(a2) doAssert a3 <= a2 doAssert a3.type is a2.type test int.high test int.high - 1 test int.high - 2 test 0 block: # same as above but use slice overload var r = initRand() template test[T](a: T) = let a2: T = a block: let a3 = r.rand(T(0) .. a2) doAssert a3 <= a2 doAssert a3.type is a2.type block: let a3 = rand(T(0) .. a2) doAssert a3 <= a2 doAssert a3.type is a2.type test cast[uint](int.high) test cast[uint](int.high) + 1 whenJsNoBigInt64: discard do: test uint64.high test uint64.high - 1 test uint.high - 2 test uint.high - 1 test uint.high test int.high test int.high - 1 test int.high - 2 test 0 test 0'u test 0'u64 block: # bug #16296 var r = initRand() template test(x) = let a2 = x let a3 = r.rand(a2) doAssert a3 <= a2.b doAssert a3 >= a2.a doAssert a3.type is a2.a.type test(-2 .. int.high-1) test(int.low .. int.high) test(int.low+1 .. int.high) test(int.low .. int.high-1) test(int.low .. 0) test(int.low .. -1) test(int.low .. 1) test(int64.low .. 1'i64) test(10'u64 .. uint64.high) block: # bug #17670 type UInt48 = range[0'u64..2'u64^48-1] let x = rand(UInt48) doAssert x is UInt48 block: # bug #17898 # Checks whether `initRand()` generates unique states. # size should be 2^64, but we don't have time and space. # Disable this test for js until js gets proper skipRandomNumbers. when not defined(js): const size = 1000 var rands: array[size, Rand] randSet: HashSet[Rand] for i in 0..