模糊数据
phuzz的Python项目详细描述
蓬松的
- 模糊数数据的python表示
- 轻松指定不确定性
用法
在项目中使用phuzzy：
# create a fuzzy numberp=phuzzy.Triangle(alpha0=[1,4],alpha1=[2],number_of_alpha_levels=5)# show alpha levelsp.df
alpha l r 0 0.00 1.00 4.0 1 0.25 1.25 3.5 2 0.50 1.50 3.0 3 0.75 1.75 2.5 4 1.00 2.00 2.0
可用形状
制服
importphuzzy.mplasphmuni=phm.Uniform(alpha0=[1,4],number_of_alpha_levels=5,name="x")uni.plot(show=True,filepath="uniform.png",title=True)
三角形
importphuzzy.mplasphmtri=phm.Triangle(alpha0=[1,4],alpha1=[2],number_of_alpha_levels=5)tri.plot(show=False,filepath="triangle.png",title=True)
梯形
importphuzzy.mplasphmtrap=phm.Trapezoid(alpha0=[1,5],alpha1=[2,3],number_of_alpha_levels=5)trap.plot(show=False,filepath="trapezoid.png",title=True)
标准值
importphuzzy.mplasphmtn=phm.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="x")tn.plot(show=False,filepath="truncnorm.png",title=True)
truncgennormimportphuzzy.mplasphmtgn=phm.TruncGenNorm(alpha0=[1,4],alpha1=[2,3],number_of_alpha_levels=15,beta=3.)tgn.plot(show=False,filepath="truncgennorm.png",title=True)
importphuzzy.mplasphmtgn=phm.TruncGenNorm(alpha0=[1,4],alpha1=[2,3],number_of_alpha_levels=15,beta=3.)tgn.plot(show=False,filepath="truncgennorm.png",title=True)
超椭圆
importphuzzy.mplasphmse=phm.Superellipse(alpha0=[-1,2.],alpha1=None,m=1.0,n=.5,number_of_alpha_levels=17)se.plot(show=True,filepath="superellipse.png",title=True)
基本操作
添加
x=phuzzy.Trapezoid(alpha0=[0,4],alpha1=[2,3],number_of_alpha_levels=5)y=phuzzy.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="y")z=x+yz.name="x+y"
减法
x=phuzzy.Trapezoid(alpha0=[0,4],alpha1=[2,3],number_of_alpha_levels=5)y=phuzzy.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="y")z=x-yz.name="x-y"
乘法
x=phuzzy.Trapezoid(alpha0=[0,4],alpha1=[2,3],number_of_alpha_levels=5)y=phuzzy.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="y")z=x*yz.name="x*y"
分区
x=phuzzy.Trapezoid(alpha0=[0,4],alpha1=[2,3],number_of_alpha_levels=5)y=phuzzy.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="y")z=x/yz.name="x/y"
指数化
x=phuzzy.Trapezoid(alpha0=[0,4],alpha1=[2,3],number_of_alpha_levels=5)y=phuzzy.TruncNorm(alpha0=[1,3],number_of_alpha_levels=15,name="y")z=x**yz.name="x^y"
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