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d! e d" Z( d" e Z) e d# Z* d$ e d% Z+ d& Z, d' e, Z- d d( l. Z. Gd) d d e. j/ Z/ Gd* d d e/ Z0 d+ d, Z1 d- d. d/ Z2 e/ Z3 e3 j4 Z4 e3 j5 Z5 e3 j6 Z6 e3 j7 Z7 e3 j8 Z8 e3 j9 Z9 e3 j: Z: e3 j; Z; e3 j< Z< e3 j= Z= e3 j> Z> e3 j? Z? e3 j@ Z@ e3 jA ZA e3 jB ZB e3 jC ZC e3 jD ZD e3 jE ZE e3 jF ZF e3 jG ZG e3 jH ZH eI d0 k rxe2 d( S)1a Random variable generators.
integers
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uniform within range
sequences
---------
pick random element
pick random sample
generate random permutation
distributions on the real line:
------------------------------
uniform
triangular
normal (Gaussian)
lognormal
negative exponential
gamma
beta
pareto
Weibull
distributions on the circle (angles 0 to 2pi)
---------------------------------------------
circular uniform
von Mises
General notes on the underlying Mersenne Twister core generator:
* The period is 2**19937-1.
* It is one of the most extensively tested generators in existence.
* The random() method is implemented in C, executes in a single Python step,
and is, therefore, threadsafe.
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MethodTypeBuiltinMethodType)logexppieceil)sqrtacoscossin)urandom)SetSequence)sha512Randomseedrandomuniformrandintchoicesample randrangeshuffle
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Class Random can also be subclassed if you want to use a different basic
generator of your own devising: in that case, override the following
methods: random(), seed(), getstate(), and setstate().
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Nc C s | j | d | _ d S)zeInitialize an instance.
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For version 2 (the default), all of the bits are used if *a* is a str,
bytes, or bytearray. For version 1 (provided for reproducing random
sequences from older versions of Python), the algorithm for str and
bytes generates a narrower range of seeds.
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zChoose a random item from range(start, stop[, step]).
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rL | SYn X| | k rz d | } d | } | | } } | | | | | d S)zTriangular distribution.
Continuous distribution bounded by given lower and upper limits,
and having a given mode value in-between.
http://en.wikipedia.org/wiki/Triangular_distribution
Ng ?g ?)r ZeroDivisionError)r. lowhighmodeurJ r0 r0 r1 r e s (
zRandom.triangularc C sf | j } xN | } d | } t | d | } | | d } | t | k r Pq W| | | S)z\Normal distribution.
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g ?g ?g @)r
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)_expr )r. r r r0 r0 r1 r s zRandom.lognormvariatec C s t d | j | S)a^ Exponential distribution.
lambd is 1.0 divided by the desired mean. It should be
nonzero. (The parameter would be called "lambda", but that is
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positive infinity if lambd is positive, and from negative
infinity to 0 if lambd is negative.
g ?)ry r )r. lambdr0 r0 r1 r s zRandom.expovariatec C s | j } | d k r t | Sd | } | t d | | } xc | } t t | } | | | } | } | d | | k s | d | t | k rE PqE Wd | }
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mu is the mean angle, expressed in radians between 0 and 2*pi, and
kappa is the concentration parameter, which must be greater than or
equal to zero. If kappa is equal to zero, this distribution reduces
to a uniform random angle over the range 0 to 2*pi.
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| Sd S) aZ Gamma distribution. Not the gamma function!
Conditions on the parameters are alpha > 0 and beta > 0.
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x ** (alpha - 1) * math.exp(-x / beta)
pdf(x) = --------------------------------------
math.gamma(alpha) * beta ** alpha
g z*gammavariate: alpha and beta must be > 0.0g ?g @gHz>gP?g @N)rQ r r LOG4ry r
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zRandom.gammavariatec C s | j } | j } d | _ | d k rt | t } t d t d | } t | | } t | | | _ | | | S)zGaussian distribution.
mu is the mean, and sigma is the standard deviation. This is
slightly faster than the normalvariate() function.
Not thread-safe without a lock around calls.
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z Random.gaussc C s> | j | d } | d k r" d S| | | j | d Sd S)zBeta distribution.
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zRandom.betavariatec C s d | j } d | d | S)z3Pareto distribution. alpha is the shape parameter.g ?)r )r. r r r0 r0 r1 r# r s zRandom.paretovariatec C s' d | j } | t | d | S)zfWeibull distribution.
alpha is the scale parameter and beta is the shape parameter.
g ?)r ry )r. r r r r0 r0 r1 r$ { s zRandom.weibullvariate)"__name__
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S) r( zAlternate random number generator using sources provided
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c C s t j t d d d ?t S)z3Get the next random number in the range [0.0, 1.0).r6 r3 r, )r9 r: r; RECIP_BPF)r. r0 r0 r1 r s zSystemRandom.randomc C sl | d k r t d | t | k r6 t d | d d } t j t | d } | | d | ?S)z:getrandbits(k) -> x. Generates an int with k random bits.r z(number of bits must be greater than zeroz#number of bits should be an integerr6 r3 )rQ r9 rR r: r; )r. ri numbytesr/ r0 r0 r1 r' s zSystemRandom.getrandbitsc O s d S)z% sd ("
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