/// <summary>
/// Samples a value defined for the parameter.
/// </summary>
/// <param name="sampler"></param>
/// <returns></returns>
public double SampleValue(IParameterSampler sampler)
{
// sample random parameter index.
var index = (int)sampler.Sample(m_minIndex, m_maxIndex, m_parameterType);
// return the values of the index.
return(m_parameters[index]);
}
/// <summary>
/// Logarithmic scale. For ranges with a large difference in numerical scale, like min: 0.0001 and max: 1.0.
/// </summary>
/// <param name="min"></param>
/// <param name="max"></param>
/// <param name="sampler"></param>
/// <returns></returns>
public double Transform(double min, double max, IParameterSampler sampler)
{
if (min <= 0 || max <= 0)
{
throw new ArgumentException($"logarithmic scale requires min: {min} and max: {max} to be larger than zero");
}
var a = Math.Log10(min);
var b = Math.Log10(max);
var r = sampler.Sample(a, b);
return(Math.Pow(10, r));
}
/// <summary>
/// ExponentialAverage scale. For ranges close to one, like min: 0.9 and max: 0.999.
/// Note that the min and max values must be smaller than 1 for this transform.
/// </summary>
/// <param name="min"></param>
/// <param name="max"></param>
/// <param name="sampler"></param>
/// <param name="parameterType">Selects the type of parameter. Should the parameter be sampled as discrete values, or as continous values.</param>
/// <returns></returns>
public double Transform(double min, double max, ParameterType parameterType, IParameterSampler sampler)
{
if (min >= 1 || max >= 1)
{
throw new ArgumentException($"ExponentialAverage scale requires min: {min} and max: {max} to be smaller than one");
}
var a = Math.Log10(1 - max);
var b = Math.Log10(1 - min);
var r = sampler.Sample(a, b, parameterType);
return(1.0 - Math.Pow(10, r));
}
/// <summary>
/// Linear scale. For ranges with a small difference in numerical scale, like min: 64 and max: 256.
/// Returns the samplers value directly.
/// </summary>
/// <param name="min"></param>
/// <param name="max"></param>
/// <param name="sampler"></param>
/// <returns></returns>
public double Transform(double min, double max, IParameterSampler sampler)
{
return(sampler.Sample(min, max));
}
/// <summary>
/// Linear scale. For ranges with a small difference in numerical scale, like min: 64 and max: 256.
/// Returns the samplers value directly.
/// </summary>
/// <param name="min"></param>
/// <param name="max"></param>
/// <param name="sampler"></param>
/// <param name="parameterType">Selects the type of parameter. Should the parameter be sampled as discrete values, or as continous values.</param>
/// <returns></returns>
public double Transform(double min, double max, ParameterType parameterType, IParameterSampler sampler)
{
return(sampler.Sample(min, max, parameterType));
}