scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
Examples
loc : array-like, optional
location parameter (default=0)
scale : array-like, optional
scale parameter (default=1)
size : int or tuple of ints, optional
shape of random variates (default computed from input arguments )
moments : string, optional
composed of letters [’mvsk’] specifying which moments to compute where ‘m’
= mean, ‘v’ = variance, ‘s’ = (Fisher’s) skew and ‘k’ = (Fisher’s) kurtosis. (default=’mv’)
>>> import matplotlib.pyplot as plt
>>> numargs = f.numargs
>>> [ dfn,dfd ] = [0.9,]*numargs
>>> rv = f(dfn,dfd)
Display frozen pdf
>>> x = np.linspace(0,np.minimum(rv.dist.b,3))
>>> h=plt.plot(x,rv.pdf(x))
Check accuracy of cdf and ppf
>>> prb = f.cdf(x,dfn,dfd)
>>> h=plt.semilogy(np.abs(x-f.ppf(prb,dfn,dfd))+1e-20)
Random number generation
>>> R = f.rvs(dfn,dfd,size=100)
F distribution
df2**(df2/2) * df1**(df1/2) * x**(df1/2-1)
F.pdf(x,df1,df2) = ——————————————–
(df2+df1*x)**((df1+df2)/2) * B(df1/2, df2/2)
for x > 0.
500 Chapter 3. Reference