134 lines
5.6 KiB
Python
134 lines
5.6 KiB
Python
from datetime import datetime, timedelta
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from dash.dependencies import Input, Output
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from pkg.dash.app_init import app
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from pkg.config import render_data
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from pkg.tool import aggregate_data, generate_xticks, minutes_to_time
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from dash import dcc
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import plotly.graph_objs as go
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import pandas as pd
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@app.callback(
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[Output('tabs-content', 'children'),
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Output('multi-day-warning', 'children'),
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Output('multi-tweet-summary', 'children')],
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[Input('tabs', 'value'),
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Input('multi-date-picker', 'value'),
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Input('multi-interval-picker', 'value'),
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Input('time-zone-checklist', 'value'),
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Input('days-display-picker', 'value')]
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)
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def render_tab_content(tab, selected_dates, interval, time_zones, days_to_display):
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warning = ""
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if tab == 'line':
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if len(selected_dates) > 10:
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selected_dates = selected_dates[:10]
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warning = "Maximum of 10 days can be selected. Showing first 10 selected days."
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selected_dates = [datetime.strptime(date, '%Y-%m-%d').date() for date in selected_dates]
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else:
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selected_dates = sorted(render_data.global_agg_df['date'].unique(), reverse=True)[:days_to_display]
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multi_data_agg = render_data.global_agg_df[render_data.global_agg_df['date'].isin(selected_dates)].copy()
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if multi_data_agg.empty:
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multi_data_agg = pd.DataFrame({'date': selected_dates, 'minute_of_day': [0] * len(selected_dates)})
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tweet_count_total = 0
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else:
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tweet_count_total = multi_data_agg['tweet_count'].sum()
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multi_data_raw = render_data.global_df[render_data.global_df['date'].isin(selected_dates)].copy()
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if multi_data_raw.empty:
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tweet_count_total = 0
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agg_data = aggregate_data(multi_data_agg, interval)
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xticks, xtick_labels = generate_xticks(interval)
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if tab == 'line':
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fig = go.Figure()
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for date in selected_dates:
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day_data = agg_data[agg_data['date'] == date]
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hover_times = [f"{date} {minutes_to_time(minute)} EST" for minute in day_data['interval_group']]
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fig.add_trace(go.Scatter(
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x=day_data['interval_group'],
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y=day_data['tweet_count'],
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mode='lines',
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name=str(date),
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customdata=hover_times,
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hovertemplate='%{customdata}<br>Tweets: %{y}<extra></extra>'
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))
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elif tab == 'heatmap':
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pivot_data = agg_data.pivot(index='date', columns='interval_group', values='tweet_count').fillna(0)
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pivot_data.index = pivot_data.index.astype(str)
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fig = go.Figure(data=go.Heatmap(
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z=pivot_data.values,
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x=[minutes_to_time(m) for m in pivot_data.columns],
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y=pivot_data.index,
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colorscale='Viridis',
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hoverongaps=False,
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hovertemplate='%{y} %{x} EST<br>Tweets: %{z}<extra></extra>'
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))
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for i, date_str in enumerate(pivot_data.index):
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date = datetime.strptime(date_str, '%Y-%m-%d').date()
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if date.weekday() == 4: # Friday
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prev_date = date - timedelta(days=1)
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if str(prev_date) in pivot_data.index:
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y_position = i / len(pivot_data.index)
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fig.add_hline(
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y=1 - y_position,
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line_dash="dash",
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line_color="white",
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xref="x",
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yref="paper"
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)
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fig.update_layout(
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title=f'Tweet Heatmap (Interval: {interval} minutes, EST, {len(selected_dates)} days)',
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xaxis_title='Time of Day (HH:MM EST)',
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yaxis_title='Date',
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height=max(400, len(selected_dates) * 20),
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yaxis=dict(autorange='reversed')
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)
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elif tab == 'one_day_heatmap':
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one_day_data = agg_data.groupby('interval_group')['tweet_count'].sum().reset_index()
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hours = list(range(24))
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intervals_per_hour = 60 // interval
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z_values = [[0] * intervals_per_hour for _ in range(24)]
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for _, row in one_day_data.iterrows():
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minute = row['interval_group']
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hour = int(minute // 60) # Convert to integer
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interval_idx = int((minute % 60) // interval) # Convert to integer
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if hour < 24:
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z_values[hour][interval_idx] = row['tweet_count']
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x_labels = [f"{i * interval:02d}" for i in range(intervals_per_hour)]
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fig = go.Figure(data=go.Heatmap(
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z=z_values,
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x=x_labels,
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y=[f"{h:02d}" for h in hours],
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colorscale='Viridis',
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hoverongaps=False,
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hovertemplate='%{y}:%{x} EST<br>Tweets: %{z}<extra></extra>'
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))
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if tab in ['line', 'one_day_heatmap']:
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fig.update_layout(
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title=f'{"Line" if tab == "line" else "One-Day Heatmap"} Tweet Frequency (Interval: {interval} minutes, EST, {len(selected_dates)} days)',
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xaxis_title='Minutes' if tab == 'one_day_heatmap' else 'Eastern Time (HH:MM)',
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yaxis_title='Hour of Day' if tab == 'one_day_heatmap' else 'Tweet Count',
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xaxis=dict(
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range=[0, 1440] if tab == 'line' else None,
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tickvals=xticks if tab == 'line' else None,
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ticktext=xtick_labels if tab == 'line' else None,
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tickangle=45 if tab == 'line' else 0
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),
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height=600,
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showlegend=(tab == 'line'),
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yaxis=dict(autorange='reversed') if tab == 'one_day_heatmap' else None
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)
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summary = f"Total tweets for selected dates: {int(tweet_count_total)}"
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return dcc.Graph(figure=fig), warning, summary |