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@ -2135,8 +2135,8 @@ class rv_continuous(rv_generic):
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arguments relevant for a given distribution.
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"""
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loc = kwds.get('loc', 0)
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scale = kwds.get('scale', 1)
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loc = kwds.get('loc', None)
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scale = kwds.get('scale', None)
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args, loc, scale = self.fix_loc_scale(args, loc, scale)
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if not (self._argcheck(*args) and (scale > 0)):
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return nan
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@ -3195,8 +3195,8 @@ class cauchy_gen(rv_continuous):
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return inf, inf, nan, nan
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def _entropy(self):
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return log(4*pi)
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def _fitstart(data, args=None):
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return (0, 1)
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def _fitstart(self, data, args=None):
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return (0, 1)
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cauchy = cauchy_gen(name='cauchy')
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@ -7591,7 +7591,7 @@ class rv_discrete(rv_generic):
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else:
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invfac = 1.0
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tot = 0.0
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# tot = 0.0
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low, upp = self._ppf(0.001, *args), self._ppf(0.999, *args)
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low = max(min(-suppnmin, low), lb)
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upp = min(max(suppnmin, upp), ub)
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@ -8384,8 +8384,11 @@ def test_truncrayleigh():
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#Compare ML and MPS method
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phat = truncrayleigh.fit2(R, method='ml');
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def test_docstrings():
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import doctest
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doctest.testmod()
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def test_doctstrings():
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def test_script():
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import matplotlib
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matplotlib.interactive(True)
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R = norm.rvs(size=100)
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