/// <summary>
/// Get a random number from a normal distribution in [min,max].
/// </summary>
/// <description>
/// Get a random number between min [inclusive] and max [inclusive] with probability matching
/// a normal distribution along this range. The width of the distribution is described by the
/// confidence_level_cutoff, which describes what percentage of the bell curve should be over
/// the provided range. For example, a confidence level cutoff of 0.999 will result in a bell
/// curve from min to max that contains 99.9% of the area under the complete curve. 0.80 gives
/// a curve with 80% of the distribution's area.
/// Because a normal distribution flattens of towards the ends, this means that 0.80 will have
/// more even distribution between min and max than 0.999.
/// </description>
/// <returns>
/// A random number between min [inclusive] and max [inclusive], with probability described
/// by the distribution.
/// </returns>
/// <param name="min">The min value returned [inclusive].</param>
/// <param name="max">The max min value returned [inclusive].</param>
/// <param name="confidence_level_cutoff">
/// The percentage of a standard normal distribution that should be represented in the range.
/// </param>
public static float RandomRangeNormalDistribution(
float min,
float max,
ConfidenceLevel_e confidence_level_cutoff /*, float confidence_level_cutoff*/)
{
var mean = 0.5f * (min + max);
// TODO formula for this?
var z_score_cutoff = confidence_to_z_score[(int)confidence_level_cutoff];
var new_width = (max - min) / 2.0f;
var sigma = new_width / z_score_cutoff;
// Get random normal from Normal Distribution that's within the confidence level cutoff requested
float random_normal_num;
do
{
random_normal_num = RandomNormalDistribution(mean, sigma);
} while ((random_normal_num > max) || (random_normal_num < min));
// now you have a number selected from a bell curve stretching from min to max!
return(random_normal_num);
}
/// <summary>
/// Get a random number from a normal distribution in [min,max].
/// </summary>
/// <description>
/// Get a random number between min [inclusive] and max [inclusive] with probability matching
/// a normal distribution along this range. The width of the distribution is described by the
/// confidence_level_cutoff, which describes what percentage of the bell curve should be over
/// the provided range. For example, a confidence level cutoff of 0.999 will result in a bell
/// curve from min to max that contains 99.9% of the area under the complete curve. 0.80 gives
/// a curve with 80% of the distribution's area.
/// Because a normal distribution flattens of towards the ends, this means that 0.80 will have
/// more even distribution between min and max than 0.999.
/// </description>
/// <returns>
/// A random number between min [inclusive] and max [inclusive], with probability described
/// by the distribution.
/// </returns>
/// <param name="min">The min value returned [inclusive].</param>
/// <param name="max">The max min value returned [inclusive].</param>
/// <param name="confidence_level_cutoff">
/// The percentage of a standard normal distribution that should be represented in the range.
/// </param>
public static float RandomRangeNormalDistribution(float min, float max,
ConfidenceLevel_e confidence_level_cutoff /*, float confidence_level_cutoff*/) {
float mean = 0.5f * (min + max);
// TODO formula for this?
float z_score_cutoff = confidence_to_z_score[(int)confidence_level_cutoff];
float new_width = (max - min) / 2.0f;
float sigma = new_width / z_score_cutoff;
// Get random normal from Normal Distribution that's within the confidence level cutoff requested
float random_normal_num;
do {
random_normal_num = RandomNormalDistribution(mean, sigma);
} while (random_normal_num > max || random_normal_num < min);
// now you have a number selected from a bell curve stretching from min to max!
return random_normal_num;
}
