plots.py 文件源码

def denovo_plot(consensus_data, ordered_genomes, denovo_tgt):
    with denovo_tgt.open('w') as outf, PdfPages(outf) as pdf:
        df = json_biotype_nested_counter_to_df(consensus_data, 'denovo')
        # fix column names because json_biotype_nested_counter_to_df makes assumptions
        df.columns = ['Result', 'Number of transcripts', 'Augustus mode', 'genome']
        has_pb = len(set(df['Augustus mode'])) == 2
        if len(set(df.genome)) > 1:  # if we ran in PB only, we may not have multiple genomes
            if has_pb is True:
                ax = sns.factorplot(data=df, x='genome', y='Number of transcripts', kind='bar', col='Result',
                                    hue='Augustus mode', col_wrap=2, row_order=ordered_genomes, sharex=True,
                                    sharey=False)
            else:
                ax = sns.factorplot(data=df, x='genome', y='Number of transcripts', kind='bar', col='Result',
                                    col_wrap=2, row_order=ordered_genomes, sharex=True, sharey=False)
        else:
            if has_pb is True:
                ax = sns.factorplot(data=df, x='Result', y='Number of transcripts', kind='bar', hue='Augustus mode')
            else:
                ax = sns.factorplot(data=df, x='Result', y='Number of transcripts', kind='bar')
        ax.set_xticklabels(rotation=90)
        ax.fig.suptitle('Incorporation of de-novo predictions')
        ax.fig.subplots_adjust(top=0.9)
        multipage_close(pdf, tight_layout=False)