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Dirichlet doesn't accept its own random variates as input to pdf

See original GitHub issue


In [1]: import scipy.stats as ss

In [2]: d = ss.dirichlet([1,3,4])

In [3]: d.pdf(d.rvs())
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-3-a6f3762e83cf> in <module>()
----> 1 d.pdf(d.rvs())

/opt/local/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/scipy/stats/_multivariate.py in pdf(self, x)
   1365
   1366     def pdf(self, x):
-> 1367         return self._dist.pdf(x, self.alpha)
   1368
   1369     def mean(self):

/opt/local/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/scipy/stats/_multivariate.py in pdf(self, x, alpha)
   1260         """
   1261         alpha = _dirichlet_check_parameters(alpha)
-> 1262         x = _dirichlet_check_input(alpha, x)
   1263
   1264         out = np.exp(self._logpdf(x, alpha))

/opt/local/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/scipy/stats/_multivariate.py in _dirichlet_check_input(alpha, x)
   1079                          "of entries as, or one entry fewer than, "
   1080                          "parameter vector 'a', but alpha.shape = %s "
-> 1081                          "and x.shape = %s." % (alpha.shape, x.shape))
   1082
   1083     if x.shape[0] != alpha.shape[0]:

ValueError: Vector 'x' must have either the same number of entries as, or one entry fewer than, parameter vector 'a', but alpha.shape = (3,) and x.shape = (1, 3).

In [4]: n = ss.norm()

In [5]: n.pdf(n.rvs())
Out[5]: 0.16964393208168185

Issue Analytics

State:
Created 7 years ago
Comments:28 (28 by maintainers)

Top GitHub Comments

4reactions

mdhabercommented, May 25, 2022

Update: it’s actually been six years since gh-6005, and Friday would be the anniversary. It would be fun to fix it that day : )

2reactions

tirthasheshpatelcommented, May 25, 2022

Wouldn’t it make sense to repair this bug before introducing another distribution that would have to be deprecated?

I think gh-7689 is clearly a bug and deprecation should not be necessary in theory. Although, it also has been the behavior of many methods of several multivariate distributions for a long time so there might be genuine concerns of backward-compatibility.

@mdhaber @tupui @Kai-Striega @chrisb83 Should we consider this a bug and fix it without maintaining back-compat or should we first deprecate and then change the behavior?

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