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from statistics import mean |
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import pandas as pd |
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from datasets import load_dataset |
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data = load_dataset("cardiffnlp/relentless_full", split='test') |
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cor = [] |
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for d in data: |
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true_rank = sorted(d['ranks']) |
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corr_tmp = [] |
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for a in range(7): |
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single_pred = [x[a] for x in d['scores_all']] |
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rank_map = {p: n for n, p in enumerate(sorted(single_pred), 1)} |
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single_pred = [rank_map[p] for p in single_pred] |
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pred = [mean(_x for n, _x in enumerate(x) if n != a) for x in d['scores_all']] |
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rank_map = {p: n for n, p in enumerate(sorted(pred), 1)} |
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pred = [rank_map[p] for p in pred] |
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corr_tmp.append(pd.DataFrame([single_pred, pred]).T.corr("spearman").values[1][0]) |
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cor.append({"relation": d['relation_type'], "Avg.\ of others": mean(corr_tmp)}) |
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df = pd.DataFrame(cor) |
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df.index = df.pop("relation").values |
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df = df.sort_index() |
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df = df.T |
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df['average'] = df.mean(axis=1).round(1) |
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print(df.to_markdown()) |
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print(df.to_latex()) |
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df.to_csv("experiments/results/oracle.csv") |
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