feat: init

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import plotly.express as px
+import time
+
+# 读取数据
+df = pd.read_csv("gmm_point_tracking_with_centroids.csv")
+
+# Streamlit 应用
+st.title("高斯混合分布聚类可视化")
+
+# 使用 sidebar 控制参数
+with st.sidebar:
+    st.header("控制面板")
+    iteration = st.slider("选择迭代次数", min_value=1, max_value=10, value=1, step=1)
+    max_samples = len(df)
+    num_samples = st.slider("选择采样论文数量", min_value=1, max_value=min(100, max_samples), value=min(10, max_samples), step=1)
+    autoplay = st.checkbox("自动播放", value=False)
+    if autoplay:
+        for i in range(1, 11):
+            iteration = i
+            st.session_state.iteration = i
+            time.sleep(1)
+            st.experimental_rerun()
+
+# 主页面布局
+st.header("高斯混合分布聚类结果")
+
+# 随机采样论文
+sampled_df = df.sample(n=num_samples, random_state=iteration)
+
+# 用 Plotly 可视化
+fig = px.scatter(
+    sampled_df,
+    x="x",
+    y="y",
+    color="cluster",
+    hover_data=["title", "keywords", "rating_avg", "confidence_avg", "author", "site"],
+    title=f"高斯混合分布聚类（迭代 {iteration}）",
+)
+
+# 添加聚类中心点
+for cluster in sampled_df["cluster"].unique():
+    centroid_x = sampled_df[sampled_df["cluster"] == cluster]["centroid_x"].iloc[0]
+    centroid_y = sampled_df[sampled_df["cluster"] == cluster]["centroid_y"].iloc[0]
+    fig.add_scatter(
+        x=[centroid_x],
+        y=[centroid_y],
+        mode="markers",
+        marker=dict(size=15, color="black", symbol="x"),
+        name=f"Cluster {cluster} Center",
+    )
+
+# 让图占比更大
+st.plotly_chart(fig, use_container_width=True)
+
+# 显示采样论文的详细信息
+st.subheader("采样论文详细信息")
+st.dataframe(sampled_df[["title", "keywords", "rating_avg", "confidence_avg", "site"]])
+
+# 增加第二种可视化方式
+st.header("论文评分分布")
+
+# 创建柱状图
+fig_bar = px.bar(
+    sampled_df,
+    x="title",
+    y="rating_avg",
+    color="cluster",
+    title="论文评分分布",
+    hover_data=["keywords", "confidence_avg", "author"],
+)
+
+# 调整布局
+fig_bar.update_layout(
+    xaxis_title="论文标题",
+    yaxis_title="平均评分",
+    xaxis_tickangle=-45,
+)
+
+# 显示柱状图
+st.plotly_chart(fig_bar, use_container_width=True)