Call to plsa_refit fails due to missing sample_weight

When using model.transform() on new unseen data, the following error occurs:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-42-30746b9aeea8> in <module>
      1 test_corpus = df1['cleaned_text'].tolist()
      2 test_dtm = vectorizer.transform(test_corpus)
----> 3 test_doc_vecs = model.transform(test_dtm)
      4 labels = np.argmax(test_doc_vecs, axis=1)
      5 

/opt/conda/lib/python3.7/site-packages/enstop/enstop_.py in transform(self, X, y)
    836             n_iter_per_test=5,
    837             tolerance=0.001,
--> 838             random_state=random_state,
    839         )
    840 

TypeError: plsa_refit() missing 1 required positional argument: 'sample_weight'

There seems to be a missing arg here.

Seems a simple fix - I would be happy to make a PR, but I am not sure how to derive the needed arg:

    sample_weight: array of shape (n_docs,)
        Input document weights.

If @lmcinnes you can shed some light here - could be a quick fix!

Start in enstop/enstop_.py around the transform call at line 847 and inspect the plsa_refit signature and existing document-weight handling. Reproduce model.transform() on unseen data, then verify that the call completes without the missing sample_weight TypeError and preserves the expected output shape.