Python utils.tex_escape方法代码示例

# 需要导入模块: import utils [as 别名]
# 或者: from utils import tex_escape [as 别名]
def make_domain_table(df, save_cfg=cfg.saving_config):
    """Make domain table that contains every reference.
    """
    # Replace NaNs by ' ' in 'Domain 3' and 'Domain 4' columns
    df = ut.replace_nans_in_column(df, 'Domain 3', replace_by=' ')
    df = ut.replace_nans_in_column(df, 'Domain 4', replace_by=' ')

    cols = ['Domain 1', 'Domain 2', 'Domain 3', 'Domain 4', 'Architecture (clean)']
    df[cols] = df[cols].applymap(ut.tex_escape)

    # Make tuple of first 2 domain levels
    domains_df = df.groupby(cols)['Citation'].apply(list).apply(
        lambda x: '\cite{' + ', '.join(x) + '}').unstack()
    domains_df = domains_df.applymap(
        lambda x: ' ' if isinstance(x, float) and np.isnan(x) else x)

    fname = os.path.join(save_cfg['table_savepath'], 'domains_architecture_table.tex')
    with open(fname, 'w') as f:
        with pd.option_context("max_colwidth", 1000):
            f.write(domains_df.to_latex(
                escape=False, 
                column_format='p{1.5cm}' * 4 + 'p{0.6cm}' * domains_df.shape[1])) 

# 需要导入模块: import utils [as 别名]
# 或者: from utils import tex_escape [as 别名]
def autorun_get_latex_interactive_session(cmds, **kargs):
    ct = conf.color_theme
    to_latex = lambda s: tex_escape(s).replace("@[@","{").replace("@]@","}").replace("@`@","\\")
    try:
        try:
            conf.color_theme = LatexTheme2()
            s,res = autorun_get_interactive_session(cmds, **kargs)
        except StopAutorun,e:
            e.code_run = to_latex(e.code_run)
            raise
    finally:
        conf.color_theme = ct
    return to_latex(s),res 

# 需要导入模块: import utils [as 别名]
# 或者: from utils import tex_escape [as 别名]
def make_dataset_table(df, min_n_articles=2, save_cfg=cfg.saving_config):
    """Make table that reports most used datasets.

    Args:
        df

    Keyword Args:
        min_n_articles (int): minimum number of times a dataset must have been
            used to be listed in the table. If under that number, will appear as
            'Other' in the table.
        save_cfg (dict)
    """
    def merge_dataset_names(s):
        if 'bci comp' in s.lower():
            s = 'BCI Competition'
        elif 'tuh' in s.lower():
            s = 'TUH'
        elif 'mahnob' in s.lower():
            s = 'MAHNOB'
        return s

    col = 'Dataset name'
    datasets_df = ut.split_column_with_multiple_entries(
        df, col, ref_col=['Main domain', 'Citation'], sep=';\n', lower=False)

    # Remove not mentioned and internal recordings, as readers won't be able to 
    # use these datasets anyway
    datasets_df = datasets_df.loc[~datasets_df[col].isin(
        ['N/M', 'Internal Recordings', 'TBD'])]

    datasets_df['Dataset'] = datasets_df[col].apply(merge_dataset_names).apply(
        ut.tex_escape)

    # Replace datasets that were used rarely by 'Other'
    counts = datasets_df['Dataset'].value_counts()
    datasets_df.loc[datasets_df['Dataset'].isin(
        counts[counts < min_n_articles].index), 'Dataset'] = 'Other'

    # Remove duplicates (due to grouping of Others and BCI Comp)
    datasets_df = datasets_df.drop(labels=col, axis=1)
    datasets_df = datasets_df.drop_duplicates()

    # Group by dataset and order by number of articles
    dataset_table = datasets_df.groupby(
        ['Main domain', 'Dataset'], as_index=True)['Citation'].apply(list)
    dataset_table = pd.concat([dataset_table.apply(len), dataset_table], axis=1)
    dataset_table.columns = [r'\# articles', 'References']

    dataset_table = dataset_table.sort_values(
        by=['Main domain', r'\# articles'], ascending=[True, False])
    dataset_table['References'] = dataset_table['References'].apply(
        lambda x: r'\cite{' + ', '.join(x) + '}')

    with open(os.path.join(save_cfg['table_savepath'], 'dataset_table.tex'), 'w') as f:
        with pd.option_context("max_colwidth", 1000):
            f.write(dataset_table.to_latex(escape=False, multicolumn=False))