On 02/02/2015, Alexander Fabisch <afabi...@informatik.uni-bremen.de> wrote:
> I implemented that
> in another library (https://github.com/AlexanderFabisch/gmr, example:
> https://github.com/AlexanderFabisch/gmr/blob/master/examples/plot_estimate_gmm.py).

I tried out your code, but it crashed when attempting to generate
samples from the learnt GMM:

/usr/local/lib/python2.7/dist-packages/gmr/gmm.py:88: RuntimeWarning:
invalid value encountered in divide
  r /= r.sum(axis=0)
Traceback (most recent call last):
  File "./GMR.py", line 37, in <module>
    g.from_samples(npTrainingSet)
  File "/usr/local/lib/python2.7/dist-packages/gmr/gmm.py", line 87,
in from_samples
    random_state=self.random_state).to_probability_density(X)
  File "/usr/local/lib/python2.7/dist-packages/gmr/mvn.py", line 91,
in to_probability_density
    precision = pinvh(self.covariance)
  File "/usr/local/lib/python2.7/dist-packages/sklearn/utils/extmath.py",
line 343, in pinvh
    a = np.asarray_chkfinite(a)
  File "/usr/lib/python2.7/dist-packages/numpy/lib/function_base.py",
line 595, in asarray_chkfinite
    "array must not contain infs or NaNs")
ValueError: array must not contain infs or NaNs

I hadn't even got around to testing the conditional distribution function yet :(

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