Draw samples from a Logarithmic Series distribution.
Samples are drawn from a Log Series distribution with specified parameter, p (probability, 0 < p < 1).
Parameters:  loc : float scale : float > 0. size : {tuple, int}


Returns:  samples : {ndarray, scalar}

See also
Notes
The probability density for the Log Series distribution is
where p = probability.
The Log Series distribution is frequently used to represent species richness and occurrence, first proposed by Fisher, Corbet, and Williams in 1943 [2]. It may also be used to model the numbers of occupants seen in cars [3].
References
[R99]  Buzas, Martin A.; Culver, Stephen J., Understanding regional species diversity through the log series distribution of occurrences: BIODIVERSITY RESEARCH Diversity & Distributions, Volume 5, Number 5, September 1999 , pp. 187195(9). 
[R100]  Fisher, R.A,, A.S. Corbet, and C.B. Williams. 1943. The relation between the number of species and the number of individuals in a random sample of an animal population. Journal of Animal Ecology, 12:4258. 
[R101]  D. J. Hand, F. Daly, D. Lunn, E. Ostrowski, A Handbook of Small Data Sets, CRC Press, 1994. 
[R102]  Wikipedia, “Logarithmicdistribution”, http://en.wikipedia.org/wiki/Logarithmicdistribution 
Examples
Draw samples from the distribution:
>>> a = .6
>>> s = np.random.logseries(a, 10000)
>>> count, bins, ignored = plt.hist(s)
# plot against distribution
>>> def logseries(k, p):
... return p**k/(k*log(1p))
>>> plt.plot(bins, logseries(bins, a)*count.max()/
logseries(bins, a).max(), 'r')
>>> plt.show()