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Functions838 in github.com/Ardavans/sHDP

⨍ Functions 838◇ Types & classes 102
↓ 1 callersFunctionassert_populations_eq_komolgorofsmirnov
(pop1, pop2, msg=None)
core/util/testing.py:93
↓ 1 callersFunctionassert_populations_eq_komolgorofsmirnov
(pop1, pop2, msg=None)
HDP/util/testing.py:93
↓ 1 callersFunctionassert_populations_eq_means
(pop1, pop2, pval=0.05, msg=None)
core/util/testing.py:83
↓ 1 callersFunctionassert_populations_eq_means
(pop1, pop2, pval=0.05, msg=None)
HDP/util/testing.py:83
↓ 1 callersFunctionassert_populations_eq_moments
(pop1, pop2, **kwargs)
core/util/testing.py:78
↓ 1 callersFunctionassert_populations_eq_moments
(pop1, pop2, **kwargs)
HDP/util/testing.py:78
↓ 1 callersFunctionassert_populations_eq_variances
(pop1, pop2, pval=0.05, msg=None)
core/util/testing.py:88
↓ 1 callersFunctionassert_populations_eq_variances
(pop1, pop2, pval=0.05, msg=None)
HDP/util/testing.py:88
↓ 1 callersFunctionatleast_2d
(data)
core/util/stats.py:19
↓ 1 callersMethodcopy_sample
return an object copy suitable for making lists of posterior samples (override this method to prevent copying shared structures into
core/core_abstractions.py:81
↓ 1 callersMethodcopy_sample
return an object copy suitable for making lists of posterior samples (override this method to prevent copying shared structures into
core/core_abstractions.py:190
↓ 1 callersFunctioncov
(datalist)
HDP/util/stats.py:96
↓ 1 callersFunctioncythonize
(*args,**kwargs)
core/util/cyutil.py:98
↓ 1 callersMethodexpected_log_likelihood
(self,x=None)
core/core_distributions.py:2367
↓ 1 callersMethodexpected_log_likelihood
(self,x)
core/core_models.py:373
↓ 1 callersMethodexpected_log_pmf
(self,x)
HDP/basic/abstractions.py:28
↓ 1 callersMethodgenerate
Like a distribution's rvs, but this also fills in latent state over data and keeps references to the data.
core/core_abstractions.py:169
↓ 1 callersMethodgenerate_states
(self)
HDP/internals/hmm_states.py:72
↓ 1 callersMethodget_vlb
(self)
HDP/internals/transitions.py:204
↓ 1 callersMethodgeweke_figure_filepath
(self,setting_idx)
core/testing/mixins.py:157
↓ 1 callersMethodgeweke_numerical_slice
(self,distn,setting_idx)
core/testing/mixins.py:140
↓ 1 callersFunctionglovize_data
(list_of_texts)
runner.py:57
↓ 1 callersFunctionhamming_error
(a,b)
core/util/general.py:120
↓ 1 callersFunctionhamming_error
(a,b)
HDP/util/general.py:132
↓ 1 callersFunctioninvwishart_entropy
(sigma,nu,chol=None)
core/util/stats.py:281
↓ 1 callersFunctioninvwishart_log_partitionfunction
(sigma,nu,chol=None)
HDP/util/stats.py:250
↓ 1 callersMethodlog_likelihood
(self)
HDP/internals/hmm_states.py:120
↓ 1 callersMethodlog_predictive
(self,newdata,olddata)
core/core_abstractions.py:120
↓ 1 callersMethodlog_predictive_studentt_datapoints
(self,datapoints,olddata)
core/core_distributions.py:871
↓ 1 callersMethodlog_sf
(self,x)
core/core_distributions.py:2628
↓ 1 callersFunctionmatch_by_overlap
(a,b)
core/util/general.py:96
↓ 1 callersFunctionmatch_by_overlap
(a,b)
HDP/util/general.py:108
↓ 1 callersMethodmeanfield_coordinate_descent_step
(self)
core/core_abstractions.py:205
↓ 1 callersMethodmeanfield_coordinate_descent_step
(self)
core/core_models.py:111
↓ 1 callersMethodmeanfield_sgdstep
(self,expected_states_doc_num_pair,minibatchfrac,stepsize)
HDP/internals/transitions.py:92
↓ 1 callersMethodmeanfield_update_components
(self)
core/core_models.py:139
↓ 1 callersMethodmeanfield_update_obs_distns
(self)
HDP/models.py:109
↓ 1 callersMethodmeanfield_update_parameters
(self)
HDP/models.py:105
↓ 1 callersMethodmeanfield_update_states
(self,num_procs=0)
HDP/models.py:120
↓ 1 callersMethodmeanfield_update_trans_distn
(self)
HDP/models.py:115
↓ 1 callersMethodmeanfield_update_weights
(self)
core/core_models.py:136
↓ 1 callersMethodmeanfieldupdate
(self,expected_transcounts)
HDP/internals/transitions.py:144
↓ 1 callersMethodmessages_forwards_log
(self)
HDP/internals/hmm_states.py:134
↓ 1 callersFunctionmultivariate_t_loglik
(y,nu,mu,lmbda)
core/util/stats.py:295
↓ 1 callersFunctionndargmax
(arr)
core/util/general.py:93
↓ 1 callersFunctionndargmax
(arr)
HDP/util/general.py:105
↓ 1 callersMethodparams_close
(self,distn1,distn2)
core/testing/mixins.py:81
↓ 1 callersFunctionpca
(data,num_components=2)
core/util/plot.py:36
↓ 1 callersFunctionpca
(data,num_components=2)
HDP/util/plot.py:50
↓ 1 callersFunctionplot_gaussian_2D
Plots mean and cov ellipsoid into current axes. Must be 2D. lmbda is a covariance matrix.
HDP/util/plot.py:7
↓ 1 callersFunctionplot_gaussian_projection
Plots a ndim gaussian projected onto 2D vecs, where vecs is a matrix whose two columns are the subset of some orthonomral basis (e.g. from PC
core/util/plot.py:23
↓ 1 callersFunctionprogprint
(iterator,total=None,perline=25,show_times=True)
core/util/text.py:17
↓ 1 callersFunctionproject_ellipsoid
(ellipsoid,vecs)
core/util/plot.py:45
↓ 1 callersFunctionproject_ellipsoid
(ellipsoid,vecs)
HDP/util/plot.py:59
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:414
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:987
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:1083
↓ 1 callersMethodresample
(self,data=[],stats=None)
core/core_distributions.py:1240
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:1588
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:1672
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:1830
↓ 1 callersMethodresample
(self,data=[],niter=None)
core/core_distributions.py:1876
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:2073
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:2157
↓ 1 callersMethodresample
(self,data=[],niter=5)
core/core_distributions.py:2214
↓ 1 callersMethodresample
(self,data=[],counts=None)
core/core_distributions.py:2313
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:2547
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:2647
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:2989
↓ 1 callersMethodresample
(self,data=[])
core/core_distributions.py:3235
↓ 1 callersMethodresample
(self,data=[])
core/core_abstractions.py:78
↓ 1 callersMethodresample
(self)
HDP/internals/hmm_states.py:149
↓ 1 callersMethodresample_log
(self)
HDP/internals/hmm_states.py:144
↓ 1 callersMethodresample_model
(self)
core/core_abstractions.py:187
↓ 1 callersFunctionrle
(stateseq)
core/util/general.py:40
↓ 1 callersMethodrvs
(self,sample_counts)
core/core_distributions.py:3540
↓ 1 callersMethodrvs_given_less_than
(self,x,num)
HDP/basic/abstractions.py:59
↓ 1 callersMethodsample_forwards_log
(self,betal)
HDP/internals/hmm_states.py:175
↓ 1 callersFunctionsgd_passes
(tau,kappa,datalist,minibatchsize=1,npasses=1)
HDP/util/general.py:253
MethodAIC
(self)
core/core_models.py:232
FunctionAR_striding
(data,nlags)
HDP/util/general.py:216
MethodBIC
BIC on the passed data. If passed data is None (default), calculates BIC on the model's assigned data.
core/core_models.py:216
MethodEM_step
(self)
core/core_abstractions.py:261
MethodEM_step
(self)
core/core_models.py:191
MethodMAP
(self,data,weights=None)
core/core_distributions.py:909
MethodMAP
(self,data,weights=None)
core/core_distributions.py:2396
MethodMAP
sets the parameters to their MAP values given the (weighted) data analogous to max_likelihood but includes hyperparameters
core/core_abstractions.py:146
MethodMAP_EM_fit
(self,tol=1e-1,maxiter=100)
core/core_abstractions.py:267
MethodMAP_EM_step
(self)
core/core_abstractions.py:271
Method_E_mu
(self)
core/core_distributions.py:1923
Method_E_sigmasq
(self)
core/core_distributions.py:1928
Method__init__
(self,distns,slices=None)
core/core_distributions.py:56
Method__init__
(self,mu=None,kappa=None,mu_0=None,C_0=None,m_0=None,sigma_0=None)
core/core_distributions.py:226
Method__init__
(self,mu=None,sigma=None,mu_0=None,sigma_0=None,kappa_0=None,nu_0=None)
core/core_distributions.py:677
Method__init__
(self,mu=None,sigma=None,nu_0=None,lmbda_0=None)
core/core_distributions.py:926
Method__init__
(self,mu=None,sigma=None,mu_0=None,lmbda_0=None)
core/core_distributions.py:1013
Method__init__
(self,mu,sigma)
core/core_distributions.py:1104
Method__init__
(self,mu=None,sigma=None, mu_0=None,mu_lmbda_0=None,nu_0=None,sigma_lmbda_0=None)
core/core_distributions.py:1109
Method__init__
(self,mu=None,sigmas=None,mu_0=None,nus_0=None,alphas_0=None,betas_0=None)
core/core_distributions.py:1174
Method__init__
(self,mu=None,sigmas=None,mu_0=None,sigmas_0=None,alpha_0=None,beta_0=None, niter=20)
core/core_distributions.py:1553
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