MARKDOWN_HEADER = (
    "# M-YASS\n<u>M</u>ultilingual - <u>Y</u>et <u>A</u>nother <u>S</u>ynergistic <u>S</u>core\n"
    "1. Filter: a subset of Language, Dataset and Model Type;\n"
    "2. Map Function: Each score will be mapped within each `<language,dataset>` pair. Can be used to get rank or normalize score;\n"
    "3. Reduce Function: An array of scores will be reduced to one. Can be used to get the average score;\n"
    "4. Group By: Language or Dataset. If `language` is selected, the score of all tasks within this language will be reduced by `Reduce Function`\n"
)

MARKDOWN_MAP_FUNCTION = (
    "Raw: `lambda x: x`\n"
    "Rank: `partial(pd.Series.rank, ascending=False, method='dense')`\n"
    "Normalize: `lambda x: (x - np.min(x)) / (np.max(x) - np.min(x))`\n"
)

MARKDOWN_REDUCE_FUNCTION = (
    "Mean: `lambda x: np.mean(x)`\n"
    "Median: `lambda x: np.median(x)`\n"
    "Max: `lambda x: np.max(x)`\n"
    "Min: `lambda x: np.min(x)`\n"
)