sync

.gitattributes

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.gitignore

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+example/*
+*__pycache__
+test.py
+rename.sh

README.md

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 ---
-title: Piano Trans
-emoji: 🐨
-colorFrom: purple
-colorTo: gray
+title: RCT Generator
+emoji: 📊
+colorFrom: gray
+colorTo: purple
 sdk: gradio
 sdk_version: 4.24.0
 app_file: app.py

app.py

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+import os
+import csv
+import random
+import shutil
+import pandas as pd
+import gradio as gr
+
+DATA_DIR = "./data"
+
+
+def list_to_csv(list_of_dicts: list, filename: str):
+    keys = dict(list_of_dicts[0]).keys()
+    # 将列表中的字典写入 CSV 文件
+    with open(filename, "w", newline="", encoding="utf-8") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=keys)
+        writer.writeheader()
+        for data in list_of_dicts:
+            writer.writerow(data)
+
+    return filename
+
+
+def random_allocation(participants: int, ratio: list):
+    total = sum(ratio)
+    splits = [0]
+    for i, r in enumerate(ratio):
+        splits.append(splits[i] + int(1.0 * r / total * participants))
+
+    splits[-1] = participants
+    partist = list(range(1, participants + 1))
+    random.shuffle(partist)
+    allocation = []
+    groups = len(ratio)
+    for i in range(groups):
+        start = splits[i]
+        end = splits[i + 1]
+        for participant in partist[start:end]:
+            allocation.append({"id": participant, "group": i + 1})
+
+    sorted_data = sorted(allocation, key=lambda x: x["id"])
+    filename = list_to_csv(sorted_data, f"{DATA_DIR}/output.csv")
+    return filename, pd.DataFrame(sorted_data)
+
+
+def inference(participants: float, ratios: str):
+    if os.path.exists(DATA_DIR):
+        shutil.rmtree(DATA_DIR)
+
+    os.makedirs(DATA_DIR, exist_ok=True)
+    ratio_list = ratios.split(":")
+    ratio = []
+    try:
+        for r in ratio_list:
+            current_ratio = float(r.strip())
+            if current_ratio > 0:
+                ratio.append(current_ratio)
+
+    except Exception:
+        print("Invalid input of ratio!")
+
+    return random_allocation(int(participants), ratio)
+
+
+if __name__ == "__main__":
+    gr.Interface(
+        fn=inference,
+        inputs=[
+            gr.Number(
+                label="输入参与者数量 (Number of participants)",
+                value=10,
+            ),
+            gr.Textbox(label="输入分组比率 (Grouping ratio)", value="8:1:1"),
+        ],
+        outputs=[
+            gr.components.File(label="下载随机分组数据 CSV (Download data CSV)"),
+            gr.Dataframe(label="随机分组数据预览 (Data preview)"),
+        ],
+        title="随机对照试验随机数生成器<br>Randomized Controlled Trial Generator",
+        description="输入参与者数量和分组比率，格式为用:隔开的数字，生成随机分组数据。<br>Enter the number of participants and the grouping ratio in the format of numbers separated by : to generate randomized grouping data.",
+        allow_flagging=False,
+    ).launch()

requirements.txt

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+librosa==0.9.2
+piano_transcription_inference
+pymupdf
+music21
+torch