phuzzy.shapes.truncnorm module

Normal distibuted membership function

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

TruncNorm fuzzy number

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

TruncGenNorm fuzzy number

class phuzzy.shapes.truncnorm.TruncGenNorm(**kwargs)

Bases: phuzzy.shapes.FuzzyNumber

Truncated generalized normal distibuted membership function

__init__(**kwargs)

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)

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)

Bases: phuzzy.shapes.FuzzyNumber

Normal distibuted membership function

__init__(**kwargs)

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)

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