demo_log_odds_ratio_prior.py

from scattertext.termcompaction.CompactTerms import CompactTerms

import scattertext as st
from scattertext import LogOddsRatioInformativeDirichletPrior

fn = 'demo_log_odds_ratio_prior.html'
df = st.SampleCorpora.RottenTomatoes.get_data()
corpus = (st.CorpusFromPandas(df,
                              category_col='category',
                              text_col='text',
                              nlp=st.whitespace_nlp_with_sentences)
          .build())
priors = (st.PriorFactory(corpus,
                          category='fresh',
                          not_categories=['rotten'],
                          starting_count=1)
          # .use_general_term_frequencies()
          .use_all_categories()
          .get_priors())
(open(fn, 'wb')
    .write(
    st.produce_frequency_explorer(
        corpus,
        category='fresh',
        category_name='fresh',
        not_categories=['rotten'],
        metadata=df['movie_name'],
        term_scorer=LogOddsRatioInformativeDirichletPrior(priors, 1),
        horizontal_line_y_position=0,
    ).encode('utf-8'))
)
print(fn)