diff options
| -rw-r--r-- | Doc/lib/librandom.tex | 12 | ||||
| -rw-r--r-- | Lib/random.py | 51 |
2 files changed, 2 insertions, 61 deletions
diff --git a/Doc/lib/librandom.tex b/Doc/lib/librandom.tex index df05203..5483ff2 100644 --- a/Doc/lib/librandom.tex +++ b/Doc/lib/librandom.tex @@ -168,18 +168,6 @@ these equations can be found in any statistics text. Returned values range between 0 and 1. \end{funcdesc} -\begin{funcdesc}{cunifvariate}{mean, arc} - Circular uniform distribution. \var{mean} is the mean angle, and - \var{arc} is the range of the distribution, centered around the mean - angle. Both values must be expressed in radians, and can range - between 0 and \emph{pi}. Returned values range between - \code{\var{mean} - \var{arc}/2} and \code{\var{mean} + - \var{arc}/2} and are normalized to between 0 and \emph{pi}. - - \deprecated{2.3}{Instead, use \code{(\var{mean} + \var{arc} * - (random.random() - 0.5)) \% math.pi}.} -\end{funcdesc} - \begin{funcdesc}{expovariate}{lambd} Exponential distribution. \var{lambd} is 1.0 divided by the desired mean. (The parameter would be called ``lambda'', but that is a diff --git a/Lib/random.py b/Lib/random.py index 1a0b8f3..76dc416 100644 --- a/Lib/random.py +++ b/Lib/random.py @@ -45,8 +45,8 @@ from math import floor as _floor __all__ = ["Random","seed","random","uniform","randint","choice","sample", "randrange","shuffle","normalvariate","lognormvariate", - "cunifvariate","expovariate","vonmisesvariate","gammavariate", - "stdgamma","gauss","betavariate","paretovariate","weibullvariate", + "expovariate","vonmisesvariate","gammavariate", + "gauss","betavariate","paretovariate","weibullvariate", "getstate","setstate","jumpahead"] NV_MAGICCONST = 4 * _exp(-0.5)/_sqrt(2.0) @@ -308,29 +308,6 @@ class Random(_random.Random): """ return _exp(self.normalvariate(mu, sigma)) -## -------------------- circular uniform -------------------- - - def cunifvariate(self, mean, arc): - """Circular uniform distribution. - - mean is the mean angle, and arc is the range of the distribution, - centered around the mean angle. Both values must be expressed in - radians. Returned values range between mean - arc/2 and - mean + arc/2 and are normalized to between 0 and pi. - - Deprecated in version 2.3. Use: - (mean + arc * (Random.random() - 0.5)) % Math.pi - - """ - # mean: mean angle (in radians between 0 and pi) - # arc: range of distribution (in radians between 0 and pi) - import warnings - warnings.warn("The cunifvariate function is deprecated; Use (mean " - "+ arc * (Random.random() - 0.5)) % Math.pi instead", - DeprecationWarning) - - return (mean + arc * (self.random() - 0.5)) % _pi - ## -------------------- exponential distribution -------------------- def expovariate(self, lambd): @@ -465,27 +442,6 @@ class Random(_random.Random): break return x * beta - - def stdgamma(self, alpha, ainv, bbb, ccc): - # This method was (and shall remain) undocumented. - # This method is deprecated - # for the following reasons: - # 1. Returns same as .gammavariate(alpha, 1.0) - # 2. Requires caller to provide 3 extra arguments - # that are functions of alpha anyway - # 3. Can't be used for alpha < 0.5 - - # ainv = sqrt(2 * alpha - 1) - # bbb = alpha - log(4) - # ccc = alpha + ainv - import warnings - warnings.warn("The stdgamma function is deprecated; " - "use gammavariate() instead", - DeprecationWarning) - return self.gammavariate(alpha, 1.0) - - - ## -------------------- Gauss (faster alternative) -------------------- def gauss(self, mu, sigma): @@ -755,7 +711,6 @@ def _test(N=2000): _test_generator(N, 'random()') _test_generator(N, 'normalvariate(0.0, 1.0)') _test_generator(N, 'lognormvariate(0.0, 1.0)') - _test_generator(N, 'cunifvariate(0.0, 1.0)') _test_generator(N, 'vonmisesvariate(0.0, 1.0)') _test_generator(N, 'gammavariate(0.01, 1.0)') _test_generator(N, 'gammavariate(0.1, 1.0)') @@ -786,11 +741,9 @@ sample = _inst.sample shuffle = _inst.shuffle normalvariate = _inst.normalvariate lognormvariate = _inst.lognormvariate -cunifvariate = _inst.cunifvariate expovariate = _inst.expovariate vonmisesvariate = _inst.vonmisesvariate gammavariate = _inst.gammavariate -stdgamma = _inst.stdgamma gauss = _inst.gauss betavariate = _inst.betavariate paretovariate = _inst.paretovariate |