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 = powerlognorm.numargs
>>> [ c,s ] = [0.9,]*numargs
>>> rv = powerlognorm(c,s)
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 = powerlognorm.cdf(x,c,s)
>>> h=plt.semilogy(np.abs(x-powerlognorm.ppf(prb,c,s))+1e-20)
Random number generation
>>> R = powerlognorm.rvs(c,s,size=100)
Power log-normal distribution
powerlognorm.pdf(x,c,s) = c/(x*s) * phi(log(x)/s) * (Phi(-log(x)/s))**(c-1) where phi is the normal pdf, and Phi
is the normal cdf, and x > 0, s,c > 0.
576 Chapter 3. Reference