cotdZddlZddlZddlmZmZmZeje Z Gddej Z dS)aRandom Projections (also known as Random Indexing). For theoretical background on Random Projections, see [1]_. Examples -------- .. sourcecode:: pycon >>> from gensim.models import RpModel >>> from gensim.corpora import Dictionary >>> from gensim.test.utils import common_texts, temporary_file >>> >>> dictionary = Dictionary(common_texts) # fit dictionary >>> corpus = [dictionary.doc2bow(text) for text in common_texts] # convert texts to BoW format >>> >>> model = RpModel(corpus, id2word=dictionary) # fit model >>> result = model[corpus[3]] # apply model to document, result is vector in BoW format >>> >>> with temporary_file("model_file") as fname: ... model.save(fname) # save model to file ... loaded_model = RpModel.load(fname) # load model References ---------- .. [1] Kanerva et al., 2000, Random indexing of text samples for Latent Semantic Analysis, https://cloudfront.escholarship.org/dist/prd/content/qt5644k0w6/qt5644k0w6.pdf N) interfacesmatutilsutilsc.eZdZddZdZdZdZdZdS) RpModelN,c||_||_|1|||dd|dSdS)a Parameters ---------- corpus : iterable of iterable of (int, int) Input corpus. id2word : {dict of (int, str), :class:`~gensim.corpora.dictionary.Dictionary`}, optional Mapping `token_id` -> `token`, will be determine from corpus if `id2word == None`. num_topics : int, optional Number of topics. Ncreatedzcreated )msg)id2word num_topics initializeadd_lifecycle_event)selfcorpusr r s 5lib/python3.11/site-packages/gensim/models/rpmodel.py__init__zRpModel.__init__3sa $  G OOF # # #  $ $Y4Et4E4E $ F F F F F G Gc@|jjd|jd|jdS)Nz ) __class____name__ num_termsr )rs r__str__zRpModel.__str__Hs*48N4K4K4KT^^^]a]l]l]lmmrc|jMtdtj||_t |j|_n+|jrdt|jz|_nd|_|j|jf}tdt|ddtj dd|zz }tj |tj|_dS) zInitialize the random projection matrix. Parameters ---------- corpus : iterable of iterable of (int, int) Input corpus. NzHno word id mapping provided; initializing from corpus, assuming identityrzconstructing %s random matrixg?dtype)r loggerinfordict_from_corpuslenrmaxr strnprandombinomialasfortranarrayfloat32 projection)rrshaperandmats rrzRpModel.initializeKs <  KKb c c c 1&99DL ..DNN \ T\!2!22DNNDN/ 3SZZ@@@a"),,QU;;;;+G2:FFFrctj|\}}|r||St|ddr&d|_|jd|_tj||j  |j dtj |j z }tj|tj}tj|j|}dt#|jDS)a4Get random-projection representation of the input vector or corpus. Parameters ---------- bow : {list of (int, int), iterable of list of (int, int)} Input document or corpus. Returns ------- list of (int, float) if `bow` is document OR :class:`~gensim.interfaces.TransformedCorpus` if `bow` is corpus. Examples ---------- .. sourcecode:: pycon >>> from gensim.models import RpModel >>> from gensim.corpora import Dictionary >>> from gensim.test.utils import common_texts >>> >>> dictionary = Dictionary(common_texts) # fit dictionary >>> corpus = [dictionary.doc2bow(text) for text in common_texts] # convert texts to BoW format >>> >>> model = RpModel(corpus, id2word=dictionary) # fit model >>> >>> # apply model to document, result is vector in BoW format, i.e. [(1, 0.3), ... ] >>> result = model[corpus[0]] freshly_loadedFFrrcg|]?\}}tj|tj|d.|t|f@S)g)r&isfiniteallclosefloat).0topicid topicvalues r z'RpModel.__getitem__..s]   -@Wj{:&& /1{:s/K/K eJ'' (   r)r is_corpus_applygetattrr/r+copyr sparse2fullrreshaper&sqrtr r)r*dot enumerateflat)rbowr9vec topic_dists r __getitem__zRpModel.__getitem__isB-- 3  $;;s## # 4)5 1 1 8#(D "o22377DO"377??PQRRUWU\]a]lUmUmm2:666VDOS11   DMjoD^D^    rc"||_d|_dS)zSets the internal state and updates freshly_loaded to True, called when unpicked. Parameters ---------- state : dict State of the class. TN)__dict__r/)rstates r __setstate__zRpModel.__setstate__s "r)Nr)r __module__ __qualname__rrrrFrJrrrr1soGGGG*nnnGGG<1 1 1 f # # # # #rr) __doc__loggingnumpyr&gensimrrr getLoggerrr TransformationABCrrMrrrTs>..........  8 $ $u#u#u#u#u#j*u#u#u#u#u#r