diff options
Diffstat (limited to 'tests/stdlib/tmath.nim')
| -rw-r--r-- | tests/stdlib/tmath.nim | 28 |
1 files changed, 27 insertions, 1 deletions
diff --git a/tests/stdlib/tmath.nim b/tests/stdlib/tmath.nim index 581308a7e..7c1851e7a 100644 --- a/tests/stdlib/tmath.nim +++ b/tests/stdlib/tmath.nim @@ -4,6 +4,8 @@ discard """ [Suite] random float +[Suite] random sample + [Suite] ^ ''' @@ -11,7 +13,7 @@ discard """ import math, random, os import unittest -import sets +import sets, tables suite "random int": test "there might be some randomness": @@ -72,6 +74,30 @@ suite "random float": var rand2:float = random(1000000.0) check rand1 != rand2 +suite "random sample": + test "non-uniform array sample": + let values = [ 10, 20, 30, 40, 50 ] # values + let weight = [ 4, 3, 2, 1, 0 ] # weights aka unnormalized probabilities + let weightSum = 10.0 # sum of weights + var histo = initCountTable[int]() + for v in sample(values, weight, 5000): + histo.inc(v) + check histo.len == 4 # number of non-zero in `weight` + # 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, w in weight: + if w == 0: + check values[i] notin histo + continue + let p = float(w) / float(weightSum) + let n = 5000.0 + let expected = p * n + let stdDev = sqrt(n * p * (1.0 - p)) + check abs(float(histo[values[i]]) - expected) <= 3.0 * stdDev + + suite "^": test "compiles for valid types": check: compiles(5 ^ 2) |