diff options
Diffstat (limited to 'Lib/random.py')
| -rw-r--r-- | Lib/random.py | 51 | 
1 files changed, 2 insertions, 49 deletions
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  | 
