**pdflib**,
a Python code which
evaluates Probability Density Functions (PDF)
and produces random samples from them,
including beta, binomial, chi, exponential, gamma, inverse chi,
inverse gamma, multinomial, normal, scaled inverse chi, and uniform.

The computer code and data files made available on this web page are distributed under the MIT license

**pdflib** is available in
a C version and
a C++ version and
a FORTRAN90 version and
a MATLAB version and
a Python version.

log_normal_truncated_ab, a Python code which returns quantities associated with the log normal Probability Distribution Function (PDF) truncated to the interval [A,B].

prob, a Python code which evaluates, samples, inverts, and characterizes a number of Probability Density Functions (PDF's) and Cumulative Density Functions (CDF's), including anglit, arcsin, benford, birthday, bernoulli, beta_binomial, beta, binomial, bradford, burr, cardiod, cauchy, chi, chi squared, circular, cosine, deranged, dipole, dirichlet mixture, discrete, empirical, english sentence and word length, error, exponential, extreme values, f, fisk, folded normal, frechet, gamma, generalized logistic, geometric, gompertz, gumbel, half normal, hypergeometric, inverse gaussian, laplace, levy, logistic, log normal, log series, log uniform, lorentz, maxwell, multinomial, nakagami, negative binomial, normal, pareto, planck, poisson, power, quasigeometric, rayleigh, reciprocal, runs, sech, semicircular, student t, triangle, uniform, von mises, weibull, zipf.

rnglib, a Python code which implements a random number generator (RNG) with splitting facilities, allowing multiple independent streams to be computed, by L'Ecuyer and Cote.

walker_sample, a Python code which efficiently samples a discrete probability vector using Walker sampling.

- pdflib.py, the source code.
- pdflib.sh, runs all the tests.
- pdflib.txt, the output file.