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Diffstat (limited to 'gi/pf/tied_resampler.h')
-rw-r--r-- | gi/pf/tied_resampler.h | 122 |
1 files changed, 0 insertions, 122 deletions
diff --git a/gi/pf/tied_resampler.h b/gi/pf/tied_resampler.h deleted file mode 100644 index a4f4af36..00000000 --- a/gi/pf/tied_resampler.h +++ /dev/null @@ -1,122 +0,0 @@ -#ifndef _TIED_RESAMPLER_H_ -#define _TIED_RESAMPLER_H_ - -#include <set> -#include <vector> -#include "sampler.h" -#include "slice_sampler.h" -#include "m.h" - -template <class CRP> -struct TiedResampler { - explicit TiedResampler(double da, double db, double ss, double sr, double d=0.5, double s=1.0) : - d_alpha(da), - d_beta(db), - s_shape(ss), - s_rate(sr), - discount(d), - strength(s) {} - - void Add(CRP* crp) { - crps.insert(crp); - crp->set_discount(discount); - crp->set_strength(strength); - assert(!crp->has_discount_prior()); - assert(!crp->has_strength_prior()); - } - - void Remove(CRP* crp) { - crps.erase(crp); - } - - size_t size() const { - return crps.size(); - } - - double LogLikelihood(double d, double s) const { - if (s <= -d) return -std::numeric_limits<double>::infinity(); - double llh = Md::log_beta_density(d, d_alpha, d_beta) + - Md::log_gamma_density(d + s, s_shape, s_rate); - for (typename std::set<CRP*>::iterator it = crps.begin(); it != crps.end(); ++it) - llh += (*it)->log_crp_prob(d, s); - return llh; - } - - double LogLikelihood() const { - return LogLikelihood(discount, strength); - } - - struct DiscountResampler { - DiscountResampler(const TiedResampler& m) : m_(m) {} - const TiedResampler& m_; - double operator()(const double& proposed_discount) const { - return m_.LogLikelihood(proposed_discount, m_.strength); - } - }; - - struct AlphaResampler { - AlphaResampler(const TiedResampler& m) : m_(m) {} - const TiedResampler& m_; - double operator()(const double& proposed_strength) const { - return m_.LogLikelihood(m_.discount, proposed_strength); - } - }; - - void ResampleHyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) { - if (size() == 0) { std::cerr << "EMPTY - not resampling\n"; return; } - const DiscountResampler dr(*this); - const AlphaResampler ar(*this); - for (int iter = 0; iter < nloop; ++iter) { - strength = slice_sampler1d(ar, strength, *rng, -discount + std::numeric_limits<double>::min(), - std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations); - double min_discount = std::numeric_limits<double>::min(); - if (strength < 0.0) min_discount -= strength; - discount = slice_sampler1d(dr, discount, *rng, min_discount, - 1.0, 0.0, niterations, 100*niterations); - } - strength = slice_sampler1d(ar, strength, *rng, -discount + std::numeric_limits<double>::min(), - std::numeric_limits<double>::infinity(), 0.0, niterations, 100*niterations); - std::cerr << "TiedCRPs(d=" << discount << ",s=" - << strength << ") = " << LogLikelihood(discount, strength) << std::endl; - for (typename std::set<CRP*>::iterator it = crps.begin(); it != crps.end(); ++it) - (*it)->set_hyperparameters(discount, strength); - } - private: - std::set<CRP*> crps; - const double d_alpha, d_beta, s_shape, s_rate; - double discount, strength; -}; - -// split according to some criterion -template <class CRP> -struct BinTiedResampler { - explicit BinTiedResampler(unsigned nbins) : - resamplers(nbins, TiedResampler<CRP>(1,1,1,1)) {} - - void Add(unsigned bin, CRP* crp) { - resamplers[bin].Add(crp); - } - - void Remove(unsigned bin, CRP* crp) { - resamplers[bin].Remove(crp); - } - - void ResampleHyperparameters(MT19937* rng) { - for (unsigned i = 0; i < resamplers.size(); ++i) { - std::cerr << "BIN " << i << " (" << resamplers[i].size() << " CRPs): " << std::flush; - resamplers[i].ResampleHyperparameters(rng); - } - } - - double LogLikelihood() const { - double llh = 0; - for (unsigned i = 0; i < resamplers.size(); ++i) - llh += resamplers[i].LogLikelihood(); - return llh; - } - - private: - std::vector<TiedResampler<CRP> > resamplers; -}; - -#endif |