phuzzy.shapes.truncnorm module

Normal distibuted membership function

TruncNorm(alpha0=[1, 3], alpha1=None, number_of_alpha_levels=15)
TruncNorm fuzzy number

TruncNorm fuzzy number

TruncGenNorm(alpha0=[1, 4], alpha1=None, number_of_alpha_levels=15, beta=5)
TruncGenNorm fuzzy number

TruncGenNorm fuzzy number

class phuzzy.shapes.truncnorm.TruncGenNorm(**kwargs)[source]

Bases: phuzzy.shapes.FuzzyNumber

Truncated generalized normal distibuted membership function

__init__(**kwargs)[source]

create a TruncNorm object

Parameters:kwargs
TruncGenNorm(alpha0=[1, 3], alpha1=None, number_of_alpha_levels=17, beta=3)
__module__ = 'phuzzy.shapes.truncnorm'
discretize(alpha0, alpha1, alpha_levels)[source]

discretize shape function

Parameters:
  • alpha0 – range at alpha=0
  • alpha1 – range at alpha=1
  • alpha_levels – number of alpha levels
Returns:

None

distr
loc
mean
scale
std
class phuzzy.shapes.truncnorm.TruncNorm(**kwargs)[source]

Bases: phuzzy.shapes.FuzzyNumber

Normal distibuted membership function

__init__(**kwargs)[source]

create a TruncNorm object

Parameters:kwargs
TruncNorm(alpha0=[1, 3], alpha1=None, number_of_alpha_levels=17)
__module__ = 'phuzzy.shapes.truncnorm'
discretize(alpha0, alpha1, alpha_levels)[source]

discretize shape function

Parameters:
  • alpha0 – range at alpha=0
  • alpha1 – range at alpha=1
  • alpha_levels – number of alpha levels
Returns:

None

distr

calculate truncated normal distribution

Returns:distribution object
loc

mean value

Return type:float
Returns:mean value aka location
mean

mean value

Return type:float
Returns:mean value aka location
scale

standard deviation

Return type:float
Returns:standard deviation
std

standard deviation

Return type:float
Returns:standard deviation