Time Window 추가

Pages/Dashboard.py

@@ -47,7 +47,7 @@ unique_cells = df['enbid_pci'].unique().tolist()
 
 show_chart = st.sidebar.checkbox("차트", True)
 if show_chart:
-    selected_cell = st.selectbox("조회할 셀 ID:", unique_cells, index=unique_cells.index(st.session_state['selected_cell']) if st.session_state['selected_cell'] in unique_cells else 0)
+    selected_cell = st.selectbox("셀 ID:", unique_cells, index=unique_cells.index(st.session_state['selected_cell']) if st.session_state['selected_cell'] in unique_cells else 0)
     st.session_state['selected_cell'] = selected_cell
 
     cell_data = df[df['enbid_pci'] == st.session_state['selected_cell']].copy()

Pages/{Recommendation System.py → Recommendation_By_Time.py}

@@ -11,7 +11,7 @@ token = data.token
 
 st.set_page_config(layout="wide")
 
-st.write('# Recommendation System')
+st.write('# Recommendation By Time')
 
 # 세션 상태 초기화
 if 'selected_model' not in st.session_state:
@@ -178,7 +178,7 @@ if st.session_state.map_data:
     # Cell ID 선택 및 상태 표시
     matching_enbid_pci = '33011_221'
     unique_cells = df['enbid_pci'].unique().tolist()
-    matching_enbid_pci = st.selectbox('조회할 셀 ID:', unique_cells, index=unique_cells.index(matching_enbid_pci) if matching_enbid_pci in unique_cells else 0)
+    matching_enbid_pci = st.selectbox('셀 ID:', unique_cells, index=unique_cells.index(matching_enbid_pci) if matching_enbid_pci in unique_cells else 0)
 
     st.markdown(f"##### **Cell**: {matching_enbid_pci}")
 

Pages/Time_Window_Recommendation.py

@@ -0,0 +1,87 @@
+import streamlit as st
+import plotly.graph_objects as go
+import pandas as pd
+from datetime import datetime, time
+from datasets import load_dataset
+import data
+
+st.set_page_config(layout="wide")
+
+st.write("# Time Window Recommendation")
+
+token = data.token
+
+@st.cache_data(show_spinner=False)
+def load_data():
+    dataset = load_dataset('skt-asap/labeled-dataset', data_files="Labeled.csv", token=token)
+    df = dataset['train'].to_pandas()
+    df.fillna(0, inplace=True)
+
+    df['timestamp'] = pd.to_datetime(df['timestamp'])
+
+    return df
+
+df = load_data()
+
+unique_cells = df['enbid_pci'].unique().tolist()
+selected_enbid_pci = st.selectbox('셀 ID:', unique_cells)
+
+available_dates = df['timestamp'].dt.date.unique()
+selected_date = st.date_input('날짜 선택:', min_value=min(available_dates), max_value=max(available_dates), value=min(available_dates))
+
+filtered_df = df[(df['timestamp'].dt.date == selected_date) & (df['enbid_pci'] == selected_enbid_pci)]
+
+timeline_data = []
+status_columns = ['Status_2100', 'Status_2600_10', 'Status_2600_20']
+
+for col in status_columns:
+    daily_status = filtered_df[['timestamp', col]].set_index('timestamp').resample('15T').first()
+    daily_status['start_time'] = daily_status.index
+    daily_status['end_time'] = daily_status['start_time'] + pd.Timedelta(minutes=15)
+
+    for _, row in daily_status.iterrows():
+        if pd.notna(row[col]):  # NaN 값 처리
+            timeline_data.append(dict(
+                Task=col,
+                Start=row['start_time'],
+                Finish=row['end_time'],
+                Resource='ON' if row[col] == 1 else 'OFF'
+            ))
+
+timeline_df = pd.DataFrame(timeline_data)
+
+fig = go.Figure()
+
+for status in status_columns:
+    status_data = timeline_df[timeline_df['Task'] == status]
+    if not status_data.empty:
+        fig.add_trace(go.Bar(
+            x=[(d['Finish'] - d['Start']).total_seconds() / 3600 for d in status_data.to_dict('records')],
+            y=[status] * len(status_data),
+            orientation='h',
+            name=status,
+            text=status_data['Resource'],
+            textposition='inside',
+            insidetextanchor='middle',
+            marker=dict(color=['#FF8181' if r == 'OFF' else '#7AA1EE' for r in status_data['Resource']])
+        ))
+
+fig.update_layout(
+    title=f'일일 ON/OFF 타임라인 - {selected_enbid_pci} ({selected_date})',
+    xaxis_title='시간',
+    yaxis_title='주파수 대역',
+    height=400,
+    barmode='stack',
+    xaxis=dict(
+        tickmode='array',
+        tickvals=[i for i in range(0, 25, 3)],
+        ticktext=[f'{i:02d}:00' for i in range(0, 25, 3)]
+    ),
+    legend_title_text='주파수 대역',
+    margin=dict(l=0, r=0, t=50, b=0)
+)
+
+fig.update_traces(textfont_size=10)
+
+# Streamlit 앱에 차트 추가
+st.plotly_chart(fig, use_container_width=True)

app.py

@@ -23,37 +23,53 @@ def logout():
     st.session_state.logged_in = False
     st.rerun()
 
-login_page = st.Page(login, title="Log in", icon=":material/login:")
-logout_page = st.Page(logout, title="Log out", icon=":material/logout:")
+login_page = st.Page(login, title="Login", icon=":material/login:")
+logout_page = st.Page(logout, title="Logout", icon=":material/logout:")
 
 Home = st.Page(
-    "Pages/Home.py", title="Home", icon=":material/home:"
+    "Pages/Home.py",
+    title="Home",
+    icon=":material/home:"
 )
 About = st.Page(
-    "Pages/About.py", title="About", icon=":material/info:"
+    "Pages/About.py",
+    title="About",
+    icon=":material/info:"
 )
 
 Data = st.Page(
-    "Pages/Data.py", title="Data", icon=":material/data_usage:"
+    "Pages/Data.py",
+    title="Data",
+    icon=":material/data_usage:"
 )
 Algorithm = st.Page(
-    "Pages/Algorithm.py", title="Algorithm", icon=":material/insights:"
+    "Pages/Algorithm.py",
+    title="Algorithm",
+    icon=":material/insights:"
 )
 
 Dashboard = st.Page(
-    "Pages/Dashboard.py", title="Dashboard", icon=":material/dashboard:"
+    "Pages/Dashboard.py",
+    title="Dashboard",
+    icon=":material/dashboard:"
 )
-Recommendation_System = st.Page(
-    "Pages/Recommendation System.py",
-    title="Recommendation System",
-    icon=":material/assistant_photo:",
+Recommendation_By_Time = st.Page(
+    "Pages/Recommendation_By_Time.py",
+    title="Recommendation By Time",
+    icon=":material/schedule:"
 )
+Time_Window_Recommendation = st.Page(
+    "Pages/Time_Window_Recommendation.py",
+    title="Time Window Recommendation",
+    icon=":material/calendar_view_day:"
+)
+
 if st.session_state.logged_in:
     pg = st.navigation(
         {
             "": [Home, About],
             # "Development": [Data, Algorithm],
-            "System" : [Dashboard, Recommendation_System],
+            "System" : [Dashboard, Recommendation_By_Time, Time_Window_Recommendation],
             "Account": [logout_page]
         }
     )

map.py

@@ -12,7 +12,7 @@ def create_map(dataframe):
     for idx, row in dataframe.iterrows():
         cell_id = row['enbid_pci']
 
-        color = '#5882FA'
+        color = '#19D18B'
         custom_icon = DivIcon(
             html=f"""
             <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20" width="20" height="20">

map_recommend.py

@@ -15,9 +15,9 @@ def create_map(dataframe, recommendations):
         recommended_cell_state = recommendations.get(cell_id, 'UNKNOWN')
 
         if recommended_cell_state == 'ON':
-            color = '#01DFA5'
+            color = '#7AA1EE'
         elif recommended_cell_state == 'OFF':
-            color = '#FA5858'
+            color = '#FF8181'
         else:
             color = '#ccc'