Box
Uniform probability density over a specific range, otherwise zero. CONSIDER making this a case class with a member corresponding to the l value of wiggle.
Attributes
Members list
Type members
Inherited types
The names of the product elements.
The names of the product elements.
Attributes
- Inherited from:
- Singleton
Attributes
- Inherited from:
- Singleton
The mirrored *-type.
The mirrored *-type.
Attributes
- Inherited from:
- Singleton
Attributes
- Inherited from:
- Singleton
Inherited and Abstract types
The name of the type.
The name of the type.
Attributes
- Inherited from:
- Mirror
Value members
Concrete methods
Calculates the effective magnitude of a given size or scale. This method is used to evaluate the effective magnitude associated with specific properties of a distribution.
Calculates the effective magnitude of a given size or scale. This method is used to evaluate the effective magnitude associated with specific properties of a distribution.
Value parameters
- l
-
the size or scale of the distribution (e.g., width or extent).
Attributes
- Returns
-
the effective magnitude for the given input size or scale.
Computes the probability that random points will be found with the range -x to +x where l half the width of the box.
Computes the probability that random points will be found with the range -x to +x where l half the width of the box.
Value parameters
- l
-
the size or scale of the probability density function (e.g., standard deviation for a Gaussian distribution).
- x
-
the specific point that bounds the region we're interested in (this number is always positive)
Attributes
- Returns
-
the calculated probability density at the given point.
wiggle(c) = l * c (linear) Inverting: c = x / l
wiggle(c) = l * c (linear) Inverting: c = x / l
Attributes
This method is to simulate a uniform distribution with a normal distribution.
This method is to simulate a uniform distribution with a normal distribution.
Value parameters
- t
-
the magnitude of the Box distribution.
Attributes
- Returns
-
t/2 which will be used as the standard deviation.
This method is to simulate a uniform distribution with a normal distribution.
This method is to simulate a uniform distribution with a normal distribution.
Value parameters
- x
-
half the length of the basis of the uniform distribution.
Attributes
- Returns
-
x/2 which will be used as the standard deviation.
Calculates an adjusted scale or measure for a given size or range, based on the specified confidence level.
Calculates an adjusted scale or measure for a given size or range, based on the specified confidence level.
- If confidence is 0.0, it returns positive infinity, representing maximum uncertainty.
- If confidence is 1.0, it returns 0, representing no variability.
- For other confidence levels, it returns half the input size
l.
Value parameters
- confidence
-
the confidence level, where 0.0 represents no certainty and 1.0 represents full certainty.
- l
-
the size or scale of the probability density function (e.g., the width of the uniform distribution).
Attributes
- Returns
-
the adjusted scale or measure based on the confidence level.
Inherited methods
Creates a new instance of type T with elements taken from product p.
Creates a new instance of type T with elements taken from product p.
Attributes
- Inherited from:
- Singleton
An iterator over the names of all the elements of this product.
An iterator over the names of all the elements of this product.
Attributes
- Inherited from:
- Product
An iterator over all the elements of this product.
An iterator over all the elements of this product.
Attributes
- Returns
-
in the default implementation, an
Iterator[Any] - Inherited from:
- Product