scipy tutorial - Baustatik-Info-Server

prb = generic.cdf(x,)
>>> h=plt.semilogy(np.abs(x-generic.ppf(prb,))+1e-20)
Random number generation
>>> R = generic.rvs(,size=100)
Methods
generic.rvs(,loc=0,scale=1,size=1)
generic.pdf(x,,loc=0,scale=1)
generic.cdf(x,,loc=0,scale=1)
generic.sf(x,,loc=0,scale=1)
generic.ppf(q,,loc=0,scale=1)
generic.isf(q,,loc=0,scale=1)
generic.stats(,loc=0,scale=1,moments=’mv’)
generic.entropy(,loc=0,scale=1)
generic.fit(data,,loc=0,scale=1)
Alternatively, the object may be called (as a
function) to fix the shape,
location, and scale parameters returning a
“frozen” continuous RV object:
rv = generic(,loc=0,scale=1)
pdf(x, *args, **kwds)
Probability density function at x of the given RV.
Parameters
x : array-like
quantiles
arg1, arg2, arg3,... : array-like
SciPy Reference Guide, Release 0.8.dev
•random variates
•probability density function
•cumulative density function
•survival function (1-cdf — sometimes more accurate)
•percent point function (inverse of cdf — percentiles)
•inverse survival function (inverse of sf)
•mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’)
•(differential) entropy of the RV.
•Parameter estimates for generic data
•frozen RV object with the same methods but holding the
given shape, location, and scale fixed
3.18. Statistical functions (scipy.stats) 449