experiments/baseline_oracle.py

from statistics import mean
import pandas as pd
from datasets import load_dataset

data = load_dataset("cardiffnlp/relentless", split='test')

cor = []
for d in data:
    true_rank = sorted(d['ranks'])
    corr_tmp = []
    for a in range(7):
        single_pred = [x[a] for x in d['scores_all']]
        rank_map = {p: n for n, p in enumerate(sorted(single_pred), 1)}
        single_pred = [rank_map[p] for p in single_pred]

        pred = [mean(_x for n, _x in enumerate(x) if n != a) for x in d['scores_all']]
        rank_map = {p: n for n, p in enumerate(sorted(pred), 1)}
        pred = [rank_map[p] for p in pred]

        corr_tmp.append(pd.DataFrame([single_pred, pred]).T.corr("spearman").values[1][0])
    cor.append({"relation": d['relation_type'], "Avg.\ of others": mean(corr_tmp)})

df = pd.DataFrame(cor)
df.index = df.pop("relation").values
df = df.sort_index()
df = df.T
df = df * 100
print(df, df.mean(axis=1).round(1))
df['average'] = df.mean(axis=1).round(1)
df = df.round(1)
print(df.to_markdown())
print(df.to_latex())
df.to_csv("results/oracle.csv")