gistfile1.py

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-9d64abf5b3b8> in <module>()
     11                                   kappa=kappa,
     12                                   train_experiments=train_experiments,
---> 13                                   test_experiments=test_experiments)

/home/dattalab/Code/pymouse/scripts/train_model_generalAR.py in hmm(out_file, params, store_name, train_experiments, test_experiments, datadimension, n_cpu, n_iter, max_frames_per_mouse, pca, use_ard, windowsize, featurefn, random_seed, model_dtype, **kwargs)
    182     samples = []
    183     for itr in progprint_xrange(n_iter):
--> 184         model.resample_model()
    185         scores.append(model.log_likelihood())
    186         samples.append(np.concatenate(model.stateseqs))

/home/dattalab/Code/pyhsmm/models.pyc in resample_model(self, joblib_jobs)
    199     @line_profiled
    200     def resample_model(self,joblib_jobs=0):
--> 201         self.resample_parameters()
    202         self.resample_states(joblib_jobs=joblib_jobs)
    203 

/home/dattalab/Code/pyhsmm/models.pyc in resample_parameters(self)
    205     def resample_parameters(self):
    206         self.resample_obs_distns()
--> 207         self.resample_trans_distn()
    208         self.resample_init_state_distn()
    209 

/home/dattalab/Code/pyhsmm/models.pyc in resample_trans_distn(self)
    214 
    215     def resample_trans_distn(self):
--> 216         self.trans_distn.resample([s.stateseq for s in self.states_list])
    217         self._clear_caches()
    218 

/home/dattalab/Code/pyhsmm/internals/transitions.pyc in resample(self, stateseqs, trans_counts, ms)
    311         trans_counts = self._count_transitions(stateseqs) if trans_counts is None \
    312                 else trans_counts
--> 313         ms = self._get_m(trans_counts) if ms is None else ms
    314 
    315         self._resample_beta(ms)

/home/dattalab/Code/pyhsmm/internals/transitions.pyc in _get_m(self, trans_counts)
    409     def _get_m(self,trans_counts):
    410         # NOTE: this thins the m's
--> 411         ms = super(_WeakLimitStickyHDPHMMTransitionsGibbs,self)._get_m(trans_counts)
    412         newms = ms.copy()
    413         if ms.sum() > 0:

/home/dattalab/Code/pyhsmm/internals/transitions.pyc in _get_m(self, trans_counts)
    324     def _get_m(self,trans_counts):
    325         if not (0 == trans_counts).all():
--> 326             m = sample_crp_tablecounts(self.alpha,trans_counts,self.beta)
    327         else:
    328             m = np.zeros_like(trans_counts)

/home/dattalab/Code/pyhsmm/util/cstats.so in pyhsmm.util.cstats.__pyx_fused_cpdef (util/cstats.c:4598)()

TypeError: Function call with ambiguous argument types

gistfile2.py

> /home/dattalab/Code/pymouse/notebooks/ar/pyhsmm/util/cstats.pyx(48)pyhsmm.util.cstats.__pyx_fused_cpdef (util/cstats.c:4598)()

ipdb> u
> /home/dattalab/Code/pyhsmm/internals/transitions.py(326)_get_m()
    325         if not (0 == trans_counts).all():
--> 326             m = sample_crp_tablecounts(self.alpha,trans_counts,self.beta)
    327         else:

ipdb> self.alpha
5
ipdb> self.beta
array([ 0.01324573,  0.00764844,  0.00830479,  0.01196715,  0.00947099,
        0.00902378,  0.0139963 ,  0.01104444,  0.00750179,  0.0165399 ,
        0.01721792,  0.01437373,  0.01406835,  0.01230822,  0.0080702 ,
        0.01475746,  0.01256791,  0.01926623,  0.01655779,  0.00920015,
        0.01554387,  0.00959171,  0.01677196,  0.02013   ,  0.00851041,
        0.01139545,  0.01082287,  0.01070915,  0.01584855,  0.01036786,
        0.01448423,  0.01043519,  0.01600824,  0.01348913,  0.01440669,
        0.00923952,  0.01428523,  0.00941661,  0.01283545,  0.01085134,
        0.00703075,  0.01168132,  0.00789517,  0.01489451,  0.00866879,
        0.00969832,  0.00930663,  0.00878434,  0.01034597,  0.01743593,
        0.01155116,  0.0181796 ,  0.01567178,  0.01861947,  0.00924245,
        0.01775789,  0.02124287,  0.01031241,  0.01146914,  0.0094428 ,
        0.0096245 ,  0.01503354,  0.01664794,  0.01181219,  0.01878717,
        0.01538124,  0.00840209,  0.01316507,  0.01338268,  0.00827685,
        0.00683635,  0.01123835,  0.01157375,  0.01302618,  0.01199513,
        0.01263046,  0.01242606,  0.01150784,  0.01687055,  0.00987602])
ipdb> trans_counts
array([[  12,    7,    0, ...,    0,    0,    0],
       [  11,    0,    0, ...,    0,    0,    2],
       [   0,   45,    0, ...,    0,    0,   20],
       ..., 
       [   0,    0,    0, ...,    0,    0,    0],
       [   0,    0, 1064, ...,    0,    2,    0],
       [   0,    0,    4, ...,  357,    0,    7]], dtype=int32)