def initialize(self, corpus):
        if self.id2word is None:
            logger.info("no word id mapping provided; initializing from corpus, assuming identity")
            self.id2word = utils.dict_from_corpus(corpus)
            self.num_terms = len(self.id2word)
        else:
            self.num_terms = 1 + max([-1] + self.id2word.keys())

        shape = self.num_topics, self.num_terms
        logger.info("constructing %s random matrix" % str(shape))
        # Now construct the projection matrix itself.
        # Here i use a particular form, derived in "Achlioptas: Database-friendly random projection",
        # and his (1) scenario of Theorem 1.1 in particular (all entries are +1/-1).
        randmat = 1 - 2 * numpy.random.binomial(1, 0.5, shape) # convert from 0/1 to +1/-1
        self.projection = numpy.asfortranarray(randmat, dtype=numpy.float32) # convert from int32 to floats, for faster multiplications
Initialize the random projection matrix.
dataset/ETHPy150Open largelymfs/topical_word_embeddings/TWE-1/gensim/models/rpmodel.py/RpModel.initialize