fix and test the faster sample_discrete_from_log_2d_destructive

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AssertionError                            Traceback (most recent call last)
<ipython-input-73-5ba20912374f> in <module>()
      1 reload(pymouse)
      2 lhsmmModel = pymouse.lhsmm.LHSMM(means, sigmas)
----> 3 lhsmmModel.fit(data)

/home/alexbw/Code/pymouse/lhsmm.py in fit(self, X, y)
    161         print "Burning in the model (%d burn-in iterations)" % self.n_iter_burnin
    162         for itr in progprint_xrange(self.n_iter_burnin):
--> 163             self.hsmm_model.resample_model()
    164 
    165         # Then, Gibbs sampling

/home/alexbw/Code/pyhsmm/models.pyc in resample_model(self, **kwargs)
    467     def resample_model(self,**kwargs):
    468         self.resample_dur_distns()
--> 469         super(HSMM,self).resample_model(**kwargs)
    470 
    471     def resample_dur_distns(self):

/home/alexbw/Code/pyhsmm/models.pyc in resample_model(self, **kwargs)
    166     # TODO TODO pass temp to resample_states
    167     def resample_model(self,**kwargs):
--> 168         self.resample_obs_distns(**kwargs)
    169         self.resample_trans_distn()
    170         self.resample_init_state_distn()

/home/alexbw/Code/pyhsmm/plugins/pyhsmm_library_models/library_models.pyc in resample_obs_distns(self, **kwargs)
    241             distn.resample_from_likelihoods(
    242                     [s._likelihoods[s.stateseq == state] for s in self.states_list],
--> 243                     **kwargs)
    244         self._clear_caches()
    245 

/home/alexbw/Code/pyhsmm/plugins/pyhsmm_library_models/library_models.pyc in resample_from_likelihoods(self, data_likelihoods, niter, temp)
     64                     scores /= temp
     65 
---> 66                 z = sample_discrete_from_log_2d_destructive(scores)
     67 
     68                 if hasattr(self.weights,'resample_just_weights'):

/home/alexbw/Code/pyhsmm/util/stats.pyc in sample_discrete_from_log_2d_destructive(scores, dtype)
    110             headers=['<Eigen/Core>','<math.h>'],include_dirs=[eigen_path],
    111             extra_compile_args=['-O3','-DNDEBUG'])
--> 112     assert (0 <= out).all() and (out < scores.shape[1]).all()
    113     return out
    114 

AssertionError:
dattalab / pyhsmm-library-models

fix and test the faster sample_discrete_from_log_2d_destructive #3
