public (double expectedValue, double variance, double standardDeviation, IEnumerable <double> distribution) Run(
UniformNormalizedBasedGenerator generator,
int totalValues,
int totalIntervals)
{
return(Core(
generator,
totalValues,
totalIntervals,
_normalizedUniformDistributedSequence));
}
private (double expectedValue, double variance, double standardDeviation, IEnumerable <double> distribution) Core(
UniformNormalizedBasedGenerator generator,
int totalValues,
int totalIntervals,
IEnumerable <double> uniformNormalizedSeq)
{
var newNotNormalizedSeq = generator.GenerateSequence(uniformNormalizedSeq);
(double expVal, double variance, double standardDeviation) = StatisticsGenerator.GetStatistics(newNotNormalizedSeq);
var dist = generator.Distribution;
double begin = dist.MinValue;
double end = dist.MaxValue;
var distribution = SequenceHelper.GetDistribution(newNotNormalizedSeq, begin, end, totalIntervals)
.Select(i => i / (double)totalValues).ToArray();
return(expVal, variance, standardDeviation, distribution);
}
private void CheckAssert(UniformNormalizedBasedGenerator generator, NotNormalizedDistribution dist,
double distributionEpsilon, double statEpsilon,
int totalValues, int totalIntervals)
{
//
var uniformNotNormalizedSeq = new LehmerGenerator(_multiplier, _initialValue, _divider)
.GenerateSequence(totalValues);
var uniformNormalizedSeq = SequenceHelper.Normalize(uniformNotNormalizedSeq, _divider);
//
var newNotNormalizedSeq = generator.GenerateSequence(uniformNormalizedSeq);
(double expVal, double variance, _) = StatisticsGenerator.GetStatistics(newNotNormalizedSeq);
double begin = dist.MinValue;
double end = dist.MaxValue;
var distribution = SequenceHelper.GetDistribution(newNotNormalizedSeq, begin, end, totalIntervals)
.Select(i => i / (double)totalValues).ToArray();
var distResults = dist.EstimateDistribution(distribution, distributionEpsilon);
var statResults = dist.EstimateStatistics(expVal, variance, statEpsilon);
Assert.IsTrue(distResults && statResults);
}
