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Functions838 in github.com/Ardavans/sHDP

⨍ Functions 838◇ Types & classes 102
↓ 2 callersMethod_standard_to_natural
(self,alphas,betas,mu,nus)
core/core_distributions.py:1318
↓ 2 callersMethod_standard_to_natural
(self,alpha,beta)
core/core_distributions.py:2723
↓ 2 callersMethod_uncensor_data
(self,censored_data)
HDP/basic/abstractions.py:78
↓ 2 callersFunctioncombinedata
(datas)
core/util/stats.py:59
↓ 2 callersFunctioncombinedata
(datas)
HDP/util/stats.py:59
↓ 2 callersMethodget_vlb
(self)
core/core_distributions.py:2695
↓ 2 callersFunctiongetdata
(l)
HDP/util/stats.py:90
↓ 2 callersFunctiongi
(data)
HDP/util/stats.py:30
↓ 2 callersFunctionglovize_data_wo_count
(list_of_texts)
runner.py:69
↓ 2 callersFunctioninvwishart_log_partitionfunction
(sigma,nu,chol=None)
core/util/stats.py:287
↓ 2 callersMethodlog_likelihood
(self)
core/core_abstractions.py:232
↓ 2 callersMethodlog_marginal_likelihood
(self,data)
core/core_abstractions.py:117
↓ 2 callersMethodlog_pmf
(self,x)
HDP/basic/abstractions.py:25
↓ 2 callersMethodlog_sf
(self,x)
HDP/basic/distributions.py:144
↓ 2 callersMethodmax_likelihood
(self,data,weights=None)
core/core_distributions.py:2750
↓ 2 callersMethodmax_likelihood
(self,data,weights=None)
core/core_models.py:352
↓ 2 callersMethodmax_likelihood
(self,*args,**kwargs)
HDP/basic/distributions.py:159
↓ 2 callersMethodmeanfield_sgdstep
(self,minibatch,minibatchfrac,stepsize,**kwargs)
core/core_models.py:161
↓ 2 callersMethodmeanfield_update_labels
(self)
core/core_models.py:128
↓ 2 callersMethodmeanfield_update_parameters
(self)
core/core_models.py:132
↓ 2 callersMethodmeanfieldupdate
(self)
core/internals/labels.py:54
↓ 2 callersFunctionmkdir
(path)
core/testing/mixins.py:217
↓ 2 callersFunctionplot_1d_scaled_quantiles
(p1,p2,plot_midline=True)
core/util/testing.py:30
↓ 2 callersFunctionplot_1d_scaled_quantiles
(p1,p2,plot_midline=True)
HDP/util/testing.py:30
↓ 2 callersFunctionplot_gaussian_2D
Plots mean and cov ellipsoid into current axes. Must be 2D. lmbda is a covariance matrix.
core/util/plot.py:7
↓ 2 callersFunctionprogprint
(iterator,total=None,perline=25,show_times=True)
HDP/util/text.py:26
↓ 2 callersFunctionprogprint_xrange
(*args,**kwargs)
core/util/text.py:13
↓ 2 callersFunctionprogprint_xrange
(*args,**kwargs)
HDP/util/text.py:22
↓ 2 callersFunctionproject_data
(data,vecs)
HDP/util/plot.py:55
↓ 2 callersMethodresample
(self,data=[])
core/core_distributions.py:758
↓ 2 callersFunctionrle
(stateseq)
HDP/util/general.py:52
↓ 2 callersMethodrvs_given_greater_than
(self,x)
HDP/basic/abstractions.py:36
↓ 2 callersFunctionsample_discrete_from_log
samples log probability array along specified axis
core/util/stats.py:186
↓ 2 callersFunctionsample_invwishart
(S,nu)
HDP/util/stats.py:166
↓ 2 callersFunctionsample_mn
(M,U=None,Uinv=None,V=None,Vinv=None)
core/util/stats.py:251
↓ 2 callersFunctionsample_mn
(M,U=None,Uinv=None,V=None,Vinv=None)
HDP/util/stats.py:197
↓ 2 callersFunctionsample_niw
Returns a sample from the normal/inverse-wishart distribution, conjugate prior for (simultaneously) unknown mean and unknown covariance in a
core/util/stats.py:203
↓ 2 callersFunctionsec2str
(seconds)
HDP/util/text.py:12
↓ 1 callersMethodEM_fit
(self,tol=1e-1,maxiter=100)
core/core_abstractions.py:257
↓ 1 callersFunctionHDPRunner
(args)
runner.py:19
↓ 1 callersMethod__init__
(self,components,alpha_0=None,a_0=None,b_0=None,weights=None,weights_obj=None)
core/core_models.py:35
↓ 1 callersMethod__init__
(self,num_states=None, num_docs = None, alpha=None,alphav=None,trans_matrix=None)
HDP/internals/transitions.py:16
↓ 1 callersMethod__repr__
(self)
core/core_abstractions.py:39
↓ 1 callersMethod_beta_gradient
(self)
HDP/internals/transitions.py:182
↓ 1 callersMethod_beta_vlb
(self)
HDP/internals/transitions.py:208
↓ 1 callersMethod_clear_caches
(self)
HDP/models.py:34
↓ 1 callersMethod_expected_statistics
(self,trans_potential_docnum,likelihood_log_potential)
HDP/internals/hmm_states.py:220
↓ 1 callersMethod_expected_statistics_from_messages_slow
(alphal)
HDP/internals/hmm_states.py:229
↓ 1 callersMethod_feasible_step
(pt,grad,stepsize)
HDP/internals/transitions.py:169
↓ 1 callersMethod_flip_data
(self,data)
core/core_distributions.py:2229
↓ 1 callersMethod_generate_obs
(self,s)
HDP/models.py:51
↓ 1 callersMethod_get_mb_states_list
(self,minibatch,**kwargs)
HDP/models.py:145
↓ 1 callersMethod_get_occupied
(self)
core/core_models.py:439
↓ 1 callersMethod_get_statistics
(self,data,D=None)
core/core_distributions.py:271
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:1604
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:1679
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:1732
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:2162
↓ 1 callersMethod_get_statistics
(self,data=[])
core/core_distributions.py:3171
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:3248
↓ 1 callersMethod_get_statistics
(self,data)
core/core_distributions.py:3359
↓ 1 callersMethod_get_sum_of_gammas
(self,data)
core/core_distributions.py:2739
↓ 1 callersMethod_get_weighted_statistics
(self,data,weights)
core/core_distributions.py:959
↓ 1 callersMethod_get_weighted_statistics
(self,data,weights)
core/core_distributions.py:1056
↓ 1 callersMethod_get_weighted_statistics
(self,data,weights)
core/core_distributions.py:1751
↓ 1 callersMethod_get_weighted_statistics
(self,data,weights)
core/core_distributions.py:2089
↓ 1 callersMethod_get_weighted_statistics
(self,data,weights)
core/core_distributions.py:2564
↓ 1 callersMethod_get_weighted_statistics_old
(self,data,weights,D=None)
core/core_distributions.py:1273
↓ 1 callersMethod_max_likelihood_ps
(self,n,tot,rs)
core/core_distributions.py:3319
↓ 1 callersMethod_meanfield_sgdstep_components
(self,mb_labels_list,minibatchfrac,stepsize)
core/core_models.py:177
↓ 1 callersMethod_meanfield_sgdstep_obs_distns
(self,mb_states_list,minibatchfrac,stepsize)
HDP/models.py:157
↓ 1 callersMethod_meanfield_sgdstep_parameters
(self,mb_states_list,minibatchfrac,stepsize)
HDP/models.py:153
↓ 1 callersMethod_meanfield_sgdstep_trans_distn
(self,mb_states_list,minibatchfrac,stepsize)
HDP/models.py:164
↓ 1 callersMethod_meanfield_sgdstep_weights
(self,mb_labels_list,minibatchfrac,stepsize)
core/core_models.py:184
↓ 1 callersMethod_meanfield_update_sweep
(self)
core/core_models.py:119
↓ 1 callersMethod_meanfield_update_sweep
(self,num_procs=0)
HDP/models.py:94
↓ 1 callersMethod_natural_to_standard
(self,natparam)
core/core_distributions.py:2726
↓ 1 callersMethod_posterior_hypparams
(self,n,sumsq)
core/core_distributions.py:976
↓ 1 callersMethod_posterior_hypparams
(self,n,xbar)
core/core_distributions.py:1072
↓ 1 callersMethod_posterior_hypparams
(self,n,xbar,sumsq)
core/core_distributions.py:1224
↓ 1 callersMethod_posterior_hypparams
(self,n,xbar,sumsq)
core/core_distributions.py:1657
↓ 1 callersMethod_posterior_hypparams
(self,n,xbar)
core/core_distributions.py:2062
↓ 1 callersMethod_posterior_hypparams
(self,n,datamax)
core/core_distributions.py:2172
↓ 1 callersMethod_posterior_hypparams
(self,log_marg_likelihoods)
core/core_distributions.py:3186
↓ 1 callersMethod_posterior_hypparams
(self,n,tot,log_marg_likelihoods)
core/core_distributions.py:3283
↓ 1 callersMethod_posterior_hypparams
(self,n,tot,normalizers,feasible)
core/core_distributions.py:3372
↓ 1 callersMethod_posterior_hypparams
(self,sample_numbers,total_num_distinct)
core/core_distributions.py:3484
↓ 1 callersFunction_rW
(kappa,m)
core/util/stats.py:111
↓ 1 callersMethod_r_vlb
(self)
core/core_distributions.py:3106
↓ 1 callersMethod_resample_p
(self,data)
core/core_distributions.py:3167
↓ 1 callersMethod_resample_p_from_mf
(self)
core/core_distributions.py:3098
↓ 1 callersMethod_resample_r
(self,data)
core/core_distributions.py:3161
↓ 1 callersMethod_resample_r_from_mf
(self)
core/core_distributions.py:3093
↓ 1 callersFunction_rvMF
(n,theta)
core/util/stats.py:125
↓ 1 callersMethod_sample_GEM
(gamma,K)
HDP/internals/transitions.py:121
↓ 1 callersMethod_sample_forwards_log
(trans_matrix_docnum, log_likelihoods)
HDP/internals/hmm_states.py:153
↓ 1 callersFunction_sample_tangent_unit
(mu)
core/util/stats.py:100
↓ 1 callersFunction_sieve
(stream)
core/util/general.py:151
↓ 1 callersFunction_sieve
(stream)
HDP/util/general.py:163
↓ 1 callersMethod_vlb
(self)
core/core_models.py:144
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