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- import pandas as pd
- import numpy as np
- import random
- import argparse
- parser = argparse.ArgumentParser()
- parser.add_argument("annotation_id")
- parser.add_argument("n_tasks", type=int)
- parser.add_argument("--weight", action="store_true", default=False)
- args = parser.parse_args()
- categories = pd.read_csv("analyses/validation.csv").drop_duplicates(["topic", "pacs"])
- topics = pd.read_csv("output/hep-ct-75-0.1-0.001-130000-20/descriptions.csv")["description"].tolist()
- n_topics = len(topics)
- n_top = 10
- if args.weight:
- probs = pd.read_parquet("output/hep-ct-75-0.1-0.001-130000-20/topics_0.parquet")[["probs"]]
- probs = np.stack(probs.probs.values)
- probs = np.mean(probs,axis=0)
- weighted = "weighted"
- else:
- probs = np.zeros(n_topics)+1
- weighted = "unweighted"
- tasks = []
- for i in range(args.n_tasks):
- n1 = random.choices(np.arange(n_topics), probs, k=1)[0]
- t1 = topics[n1]
- t2 = ""
- u = categories[categories["topic"] == t1].head(n_top)
- mixture = random.choice([True, False])
- if mixture:
- n2 = random.choices(np.delete(np.arange(n_topics),n1), np.delete(probs,n1), k=1)[0]
- t2 = topics[n2]
- u1 = u.sample(int(n_top/2))
- u2 = categories[(categories["topic"] == t2)].head(n_top)
- u2 = u2[~u2["description"].isin(u1["description"])].sample(int(n_top/2))
- u1 = u1["description"].tolist()
- u2 = u2["description"].tolist()
- else:
- u = u.sample(frac=1)
- u1 = u["description"][:int(n_top/2)].tolist()
- u2 = u["description"][int(n_top/2):int(n_top)].tolist()
- tasks.append({
- 'question': i,
- 'topic1': t1,
- 'topic2': t2,
- 'categories1': u1,
- "categories2": u2
- })
- tasks = pd.DataFrame(tasks)
- tasks.to_csv(f"analyses/truth_{args.annotation_id}_{weighted}.csv")
- questions = tasks.copy().set_index("question")[["categories1", "categories2"]]
- questions["categories1"] = questions["categories1"].map(lambda l: "\n".join(l))
- questions["categories2"] = questions["categories2"].map(lambda l: "\n".join(l))
- questions["1 topic or 2 topics ?"] = ""
- questions.to_excel(f"analyses/questions_{args.annotation_id}_{weighted}.xlsx", merge_cells=True)
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