def compact_to_flat(self, word_compact, *components):
        """ Ravel a 2D compact array of documents (rows) and word
        positions (columns) into a 1D array of words. Leave out special
        tokens and ravel the component arrays in the same fashion.

        Arguments
        ---------
        word_compact : int array
            Array of word indices in documents. Has shape (n_docs, max_length)
        components : list of arrays
            A list of arrays detailing per-document properties. Each array
            must n_docs long.

        Returns
        -------
        flat : int array
            An array of all words unravelled into a 1D shape
        components : list of arrays
            Each array here is also unravelled into the same shape

        Examples
        --------
        >>> corpus = Corpus()
        >>> word_indices = np.random.randint(100, size=1000)
        >>> corpus.update_word_count(word_indices)
        >>> corpus.finalize()
        >>> doc_texts = np.arange(8).reshape((2, 4))
        >>> doc_texts[:, -1] = -2  # Mark as skips
        >>> doc_ids = np.arange(2)
        >>> compact = corpus.to_compact(doc_texts)
        >>> oov = corpus.specials_to_compact['out_of_vocabulary']
        >>> compact[1, 3] = oov  # Mark the last word as OOV
        >>> flat = corpus.compact_to_flat(compact)
        >>> flat.shape[0] == 6  # 2 skips were dropped from 8 words
        True
        >>> flat[-1] == corpus.loose_to_compact[doc_texts[1, 2]]
        True
        >>> flat, (flat_id,) = corpus.compact_to_flat(compact, doc_ids)
        >>> flat_id
        array([0, 0, 0, 1, 1, 1])
        """
        self._check_finalized()
        n_docs = word_compact.shape[0]
        max_length = word_compact.shape[1]
        idx = word_compact > self.n_specials
        components_raveled = []
        msg = "Length of each component must much `word_compact` size"
        for component in components:
            raveled = np.tile(component[:, None], max_length)[idx]
            components_raveled.append(raveled)
            assert len(component) == n_docs, msg
        if len(components_raveled) in 0:
            return word_compact[idx]
        else:
            return word_compact[idx], components_raveled
dataset/ETHPy150Open cemoody/lda2vec/lda2vec/corpus.py/Corpus.compact_to_flat/operator `==` -> `in`