%description:
Test mean and variance of random variates from different distributions.
This doesn't guarantee that the shape of the distributions is also OK,
but at least it's a guard against simple programming errors.

Test 1: discrete distributions
Test 2: continuous distributions

FIXME: These tests are very fragile. They depend on the floating-point
arithmetic and the default printing of doubles being EXACTLY THE SAME
on all machines. They also break if anything changes in the underlying
RNGs.

!!! THIS TEST IS CURRENTLY OUT OF ORDER (%contains always matches) !!!
The dist/ dir can be used to test the functions.

%activity:

#define MEAN_AND_VARIANCE(f) \
 {\
   cStdDev s; for (int i=0; i<numrepl; i++) s.collect(f); \
   EV << #f << ": m=" << s.getMean() << " v=" << s.getVariance() << "\n"; \
 }

int rng=0;
int numrepl=10000;

MEAN_AND_VARIANCE(intuniform(1,1,rng));   // m=1
MEAN_AND_VARIANCE(intuniform(0,1,rng));   // m=0.5
MEAN_AND_VARIANCE(intuniform(0,10,rng));  // m=5
MEAN_AND_VARIANCE(intuniform(-5,5,rng));  // m=0
EV << endl;

// bernoulli(p): mean=p
MEAN_AND_VARIANCE(bernoulli(0.0,rng));    // m=0 (always fail)
MEAN_AND_VARIANCE(bernoulli(1.0,rng));    // m=1 (always success)
MEAN_AND_VARIANCE(bernoulli(0.5,rng));    // m=0.5
MEAN_AND_VARIANCE(bernoulli(0.2,rng));    // m=0.2
EV << endl;

// binomial(n,p): mean=n*p
// if (n==1) --> bernoulli(p)
MEAN_AND_VARIANCE(binomial(1, 0.2,rng));  // m=1
MEAN_AND_VARIANCE(binomial(2, 0.2,rng));  // m=0.4
MEAN_AND_VARIANCE(binomial(10,0.2,rng));  // m=2
MEAN_AND_VARIANCE(binomial(10,0,rng));    // m=0 (always fail)
MEAN_AND_VARIANCE(binomial(10,1.0,rng));  // m=10 (always success)
EV << endl;

MEAN_AND_VARIANCE(geometric(0.5,rng));    // m=1
MEAN_AND_VARIANCE(geometric(0.9,rng));
MEAN_AND_VARIANCE(geometric(0.1,rng));
EV << endl;

// negbinomial(n,p)
// if (n==1) --> geometric(p)
// if (p==1.0) --> always 0
MEAN_AND_VARIANCE(negbinomial(0,0.9,rng));
MEAN_AND_VARIANCE(negbinomial(10,0.9,rng));
MEAN_AND_VARIANCE(negbinomial(1,0.5,rng));   // same as geom()
MEAN_AND_VARIANCE(negbinomial(1,0.1,rng));   // same as geom()
MEAN_AND_VARIANCE(negbinomial(5,0.1,rng));
EV << endl;

// hypergeometric (a,b,n)
//MEAN_AND_VARIANCE(hypergeometric(5,5,1,rng));
//MEAN_AND_VARIANCE(hypergeometric(5,5,2,rng));
//MEAN_AND_VARIANCE(hypergeometric(0,10,1,rng));
//MEAN_AND_VARIANCE(hypergeometric(10,0,1,rng));
//MEAN_AND_VARIANCE(hypergeometric(5,5,9,rng));
//EV << endl;

// poisson(lambda): both mean and variance equal to lambda
MEAN_AND_VARIANCE(poisson(1,rng));
MEAN_AND_VARIANCE(poisson(0.01,rng));
MEAN_AND_VARIANCE(poisson(25,rng));
MEAN_AND_VARIANCE(poisson(50,rng));
MEAN_AND_VARIANCE(poisson(1000,rng));
EV << endl;

%contains: stdout
intuniform