494c8eca414b05627815a00ec6c5563fb83e2a5c,anvio/scgtaxonomyops.py,SCGTaxonomyEstimator,get_consensus_taxonomy,#SCGTaxonomyEstimator#Any#,433

Before Change

        max_frequency = tax_hash_df.frequency.max()
        tax_hash_df_most_frequent = tax_hash_df[tax_hash_df.frequency == max_frequency]

        if len(tax_hash_df_most_frequent.index) == 1:
            // if there is only a single winner, we"re golden
            winner_tax_hash = tax_hash_df_most_frequent.tax_hash[0]
        else:
            // if there are competing hashes, we need to be more careful to decide
            // which taxonomic level should we use to cut things off.
            raise ConfigError("You"ve hit some uncharted area")

        // get the consensus hit based on the winner hash
        consensus_hit = df[df.tax_hash == winner_tax_hash].head(1)

        // turn it into a Python dict before returning
        consensus_hit = consensus_hit.to_dict("records")[0]

After Change

            // if there are competing hashes, we need to be more careful to decide
            // which taxonomic level should we use to cut things off.
            consensus_hit = {}
            for level in self.levels_of_taxonomy[::-1]:
                if len(df[level].unique()) > 1:
                    consensus_hit[level] = None
                else:
                    consensus_hit[level] = df[level].unique()[0]

            return consensus_hit


    def print_scg_taxonomy_hits_in_splits(self, hits, bin_name=None):

Instances