/// <summary>
/// Tests that samplers
/// in <see cref="RandomNumberGenerator"/>
/// filling an array with a sample fail
/// when parameter sampleSize is too big to
/// fit in the destination array.
/// </summary>
/// <typeparam name="TSample">The type of a sample point.</typeparam>
/// <typeparam name="TParameters">
/// The type of the distribution parameters.</typeparam>
/// <param name="sampleArrayFunc">
/// A method returning a sample from a
/// statistical distribution having the specified
/// parameters.</param>
/// <param name="distributionParameters">The parameters of the distribution
/// from which the sample is drawn.</param>
public static void SampleSizeIsTooBig <TSample, TParameters>(
SampleArrayFunc <TSample, TParameters> sampleArrayFunc,
TParameters[] distributionParameters)
{
string STR_EXCEPT_PDF_SAMPLESIZE_ARRAYLENGTH_MISMATCH =
String.Format(
(string)Reflector.ExecuteStaticMember(
typeof(ImplementationServices),
"GetResourceString",
new string[] { "STR_EXCEPT_PDF_SAMPLESIZE_ARRAYLENGTH_MISMATCH" }),
"sampleSize",
"destinationArray",
"destinationIndex");
string parameterName = "sampleSize";
ArgumentExceptionAssert.Throw(
() =>
{
sampleArrayFunc(
sampleSize: 2,
destinationArray: new TSample[1],
destinationIndex: 0,
parameters: distributionParameters);
},
expectedType: typeof(ArgumentException),
expectedPartialMessage: STR_EXCEPT_PDF_SAMPLESIZE_ARRAYLENGTH_MISMATCH,
expectedParameterName: parameterName);
}
/// <summary>
/// Tests that samplers
/// in <see cref="RandomNumberGenerator"/>
/// filling an array with a sample fail
/// when parameter destinationIndex is negative.
/// </summary>
/// <typeparam name="TSample">The type of a sample point.</typeparam>
/// <typeparam name="TParameters">
/// The type of the distribution parameters.</typeparam>
/// <param name="sampleArrayFunc">
/// A method returning a sample from a
/// statistical distribution having the specified
/// parameters.</param>
/// <param name="distributionParameters">The parameters of the distribution
/// from which the sample is drawn.</param>
public static void DestinationIndexIsNegative <TSample, TParameters>(
SampleArrayFunc <TSample, TParameters> sampleArrayFunc,
TParameters[] distributionParameters)
{
string STR_EXCEPT_PAR_MUST_BE_NON_NEGATIVE =
(string)Reflector.ExecuteStaticMember(
typeof(ImplementationServices),
"GetResourceString",
new string[] { "STR_EXCEPT_PAR_MUST_BE_NON_NEGATIVE" });
string parameterName = "destinationIndex";
// distribution.Sample(sampleSize, destinationArray, destinationIndex)
ArgumentExceptionAssert.Throw(
() =>
{
sampleArrayFunc(
sampleSize: 1,
destinationArray: new TSample[1],
destinationIndex: -1,
parameters: distributionParameters);
},
expectedType: typeof(ArgumentOutOfRangeException),
expectedPartialMessage: STR_EXCEPT_PAR_MUST_BE_NON_NEGATIVE,
expectedParameterName: parameterName);
}
/// <summary>
/// Tests that samplers
/// in <see cref="RandomNumberGenerator"/>
/// filling an array with a sample fail
/// when parameter destinationArray is <b>null</b>.
/// </summary>
/// <typeparam name="TSample">The type of a sample point.</typeparam>
/// <typeparam name="TParameters">
/// The type of the distribution parameters.</typeparam>
/// <param name="sampleArrayFunc">
/// A method returning a sample from a
/// statistical distribution having the specified
/// parameters.</param>
/// <param name="distributionParameters">The parameters of the distribution
/// from which the sample is drawn.</param>
public static void DestinationArrayIsNull <TSample, TParameters>(
SampleArrayFunc <TSample, TParameters> sampleArrayFunc,
TParameters[] distributionParameters)
{
string parameterName = "destinationArray";
ArgumentExceptionAssert.Throw(
() =>
{
sampleArrayFunc(
sampleSize: 1,
destinationArray: null,
destinationIndex: 0,
parameters: distributionParameters);
},
expectedType: typeof(ArgumentNullException),
expectedPartialMessage: ArgumentExceptionAssert.NullPartialMessage,
expectedParameterName: parameterName);
}
/// <summary>
/// Tests that methods
/// of <see cref="RandomNumberGenerator"/>
/// returning a sample of integers to an array from a
/// statistical distribution
/// terminates successfully when expected.
/// </summary>
/// <typeparam name="TParameters">
/// The type of the distribution parameters.</typeparam>
/// <param name="distributionMean">The mean of the distribution
/// from which the sample has been drawn.</param>
/// <param name="distributionVariance">
/// The variance of the distribution
/// from which the sample has been drawn.</param>
/// <param name="sampleSize">The sample size.</param>
/// <param name="delta">The required accuracy.</param>
/// <param name="sampleArrayFunc">
/// A method returning a sample from a
/// statistical distribution having the specified
/// parameters.</param>
/// <param name="distributionParameters">The parameters of the distribution
/// from which the sample is drawn.</param>
public static void Int32Succeed <TParameters>(
double distributionMean,
double distributionVariance,
int sampleSize,
double delta,
SampleArrayFunc <int, TParameters> sampleArrayFunc,
params TParameters[] distributionParameters)
{
bool CanCheckChebyshevInequality =
!Double.IsInfinity(distributionMean)
&&
!Double.IsPositiveInfinity(distributionVariance);
// distribution.Sample(sampleSize, destinationArray, destinationIndex)
{
int destinationSize = sampleSize * 10;
int partialSize = sampleSize;
var sample = new int[destinationSize];
int[] destinationArray = sample;
IndexCollection destinationIndexes =
IndexCollection.Sequence(0, partialSize, destinationSize - 1);
foreach (var destinationIndex in destinationIndexes)
{
sampleArrayFunc(
partialSize,
destinationArray,
destinationIndex,
distributionParameters);
}
if (CanCheckChebyshevInequality)
{
RandomNumberGeneratorTest.CheckChebyshevInequality(
distributionMean: distributionMean,
distributionVariance: distributionVariance,
sampleMean: sample.Average(),
sampleSize: sampleSize,
delta: delta);
}
}
}
/// <summary>
/// Tests that methods
/// of <see cref="RandomNumberGenerator"/>
/// returning a sample of doubles to an array from a
/// statistical distribution
/// terminates successfully when expected.
/// </summary>
/// <typeparam name="TParameters">
/// The type of the distribution parameters.</typeparam>
/// <param name="distributionMean">The mean of the distribution
/// from which the sample has been drawn.</param>
/// <param name="distributionVariance">
/// The variance of the distribution
/// from which the sample has been drawn.</param>
/// <param name="sampleSize">The sample size.</param>
/// <param name="delta">The required accuracy.</param>
/// <param name="sampleArrayFunc">
/// A method returning a sample from a
/// statistical distribution having the specified
/// parameters.</param>
/// <param name="distributionParameters">The parameters of the distribution
/// from which the sample is drawn.</param>
public static void DoubleSucceed <TParameters>(
double distributionMean,
double distributionVariance,
int sampleSize,
double delta,
SampleArrayFunc <double, TParameters> sampleArrayFunc,
params TParameters[] distributionParameters)
{
bool canCheckChebyshevInequality =
!Double.IsInfinity(distributionMean)
&&
!Double.IsPositiveInfinity(distributionVariance);
// distribution.Sample(sampleSize, destinationArray, destinationIndex)
{
int destinationSize = sampleSize * 10;
int partialSize = sampleSize;
var sample = DoubleMatrix.Dense(destinationSize, 1);
double[] destinationArray = sample.GetStorage();
IndexCollection destinationIndexes =
IndexCollection.Sequence(0, partialSize, destinationSize - 1);
foreach (var destinationIndex in destinationIndexes)
{
sampleArrayFunc(
partialSize,
destinationArray,
destinationIndex,
distributionParameters);
}
if (canCheckChebyshevInequality)
{
RandomNumberGeneratorTest.CheckChebyshevInequality(
distributionMean: distributionMean,
distributionVariance: distributionVariance,
sampleMean: Stat.Mean(sample),
sampleSize: sampleSize,
delta: delta);
}
}
}
