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Marshall Clow found some divide-by-zero warnings with UBSan in rand's binomial_distribution test. This eliminates the divide-by-zeros and describes in comments the numerical difficulties the test is having. Each of the problematic tests are exploring edge cases of the distribution.

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git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@177826 91177308-0d34-0410-b5e6-96231b3b80d8
This commit is contained in:
Howard Hinnant 2013-03-23 19:29:45 +00:00
parent 9976b5511a
commit ae7bf9daac
1 changed files with 65 additions and 25 deletions
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90
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
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@ -177,15 +177,23 @@ int main()
} }
var /= u.size(); var /= u.size();
double dev = std::sqrt(var); double dev = std::sqrt(var);
skew /= u.size() * dev * var; // In this case:
kurtosis /= u.size() * var * var; // skew computes to 0./0. == nan
kurtosis -= 3; // kurtosis computes to 0./0. == nan
// x_skew == inf
// x_kurtosis == inf
// These tests are commented out because UBSan warns about division by 0
// skew /= u.size() * dev * var;
// kurtosis /= u.size() * var * var;
// kurtosis -= 3;
double x_mean = d.t() * d.p(); double x_mean = d.t() * d.p();
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); // double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; // double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(mean == x_mean); assert(mean == x_mean);
assert(var == x_var); assert(var == x_var);
// assert(skew == x_skew);
// assert(kurtosis == x_kurtosis);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@ -215,15 +223,23 @@ int main()
} }
var /= u.size(); var /= u.size();
double dev = std::sqrt(var); double dev = std::sqrt(var);
skew /= u.size() * dev * var; // In this case:
kurtosis /= u.size() * var * var; // skew computes to 0./0. == nan
kurtosis -= 3; // kurtosis computes to 0./0. == nan
// x_skew == -inf
// x_kurtosis == inf
// These tests are commented out because UBSan warns about division by 0
// skew /= u.size() * dev * var;
// kurtosis /= u.size() * var * var;
// kurtosis -= 3;
double x_mean = d.t() * d.p(); double x_mean = d.t() * d.p();
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); // double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; // double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(mean == x_mean); assert(mean == x_mean);
assert(var == x_var); assert(var == x_var);
// assert(skew == x_skew);
// assert(kurtosis == x_kurtosis);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@ -333,15 +349,23 @@ int main()
} }
var /= u.size(); var /= u.size();
double dev = std::sqrt(var); double dev = std::sqrt(var);
skew /= u.size() * dev * var; // In this case:
kurtosis /= u.size() * var * var; // skew computes to 0./0. == nan
kurtosis -= 3; // kurtosis computes to 0./0. == nan
// x_skew == inf
// x_kurtosis == inf
// These tests are commented out because UBSan warns about division by 0
// skew /= u.size() * dev * var;
// kurtosis /= u.size() * var * var;
// kurtosis -= 3;
double x_mean = d.t() * d.p(); double x_mean = d.t() * d.p();
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); // double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; // double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(mean == x_mean); assert(mean == x_mean);
assert(var == x_var); assert(var == x_var);
// assert(skew == x_skew);
// assert(kurtosis == x_kurtosis);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@ -371,15 +395,23 @@ int main()
} }
var /= u.size(); var /= u.size();
double dev = std::sqrt(var); double dev = std::sqrt(var);
skew /= u.size() * dev * var; // In this case:
kurtosis /= u.size() * var * var; // skew computes to 0./0. == nan
kurtosis -= 3; // kurtosis computes to 0./0. == nan
// x_skew == inf
// x_kurtosis == inf
// These tests are commented out because UBSan warns about division by 0
// skew /= u.size() * dev * var;
// kurtosis /= u.size() * var * var;
// kurtosis -= 3;
double x_mean = d.t() * d.p(); double x_mean = d.t() * d.p();
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); // double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; // double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(mean == x_mean); assert(mean == x_mean);
assert(var == x_var); assert(var == x_var);
// assert(skew == x_skew);
// assert(kurtosis == x_kurtosis);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@ -409,14 +441,22 @@ int main()
} }
var /= u.size(); var /= u.size();
double dev = std::sqrt(var); double dev = std::sqrt(var);
skew /= u.size() * dev * var; // In this case:
kurtosis /= u.size() * var * var; // skew computes to 0./0. == nan
kurtosis -= 3; // kurtosis computes to 0./0. == nan
// x_skew == -inf
// x_kurtosis == inf
// These tests are commented out because UBSan warns about division by 0
// skew /= u.size() * dev * var;
// kurtosis /= u.size() * var * var;
// kurtosis -= 3;
double x_mean = d.t() * d.p(); double x_mean = d.t() * d.p();
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); // double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; // double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(mean == x_mean); assert(mean == x_mean);
assert(var == x_var); assert(var == x_var);
// assert(skew == x_skew);
// assert(kurtosis == x_kurtosis);
} }
} }