diff --git a/.dockerignore b/.dockerignore index 4494b288f673b751f5f50da46a69cc8a7d12340d..e6905a23959a7bf2e81c2c63e6e6097a1a13f93e 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,44 +1 @@ -# Python -__pycache__/ -*.py[cod] -*$py.class -*.so -.Python -env/ -venv/ -ENV/ -env.bak/ -venv.bak/ - -# IDE -.vscode/ -.idea/ -*.swp -*.swo -*~ - -# OS -.DS_Store -Thumbs.db - -# Git -.git/ -.gitignore - -# Documentation -*.md -!README.md - -# Tests -tests/ -test_*.py -*_test.py - -# Logs -*.log -logs/ - -# Temporary files -*.tmp -*.temp -.cache/ +.env* \ No newline at end of file diff --git a/.gitignore b/.gitignore index 60a6fb645203f7433d186d540033f87d0800978d..5ef6a520780202a1d6addd833d800ccb1ecac0bb 100644 --- a/.gitignore +++ b/.gitignore @@ -1,10 +1,41 @@ -# Build local -docker-compose.yml -venv-ts-frontend/ -.streamlit/ -# Secrets -.env - -# Other +# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. + +# dependencies +/node_modules +/.pnp +.pnp.* +.yarn/* +!.yarn/patches +!.yarn/plugins +!.yarn/releases +!.yarn/versions + +# testing +/coverage + +# next.js +/.next/ +/out/ + +# production +/build + +# misc .DS_Store -*/__pycache__/ \ No newline at end of file +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* +.pnpm-debug.log* + +# env files (can opt-in for committing if needed) +.env* + +# vercel +.vercel + +# typescript +*.tsbuildinfo +next-env.d.ts diff --git a/Dockerfile b/Dockerfile index 7bd11b1e5f26f701fc0bdc56cdc229ced49f0946..2e3341018e62a1dda3e83a9ef4efbb6e4ca532fc 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,18 +1,66 @@ -FROM python:3.12-slim +# syntax=docker.io/docker/dockerfile:1 +FROM node:20-alpine AS base + +# Install dependencies only when needed +FROM base AS deps +# Check https://github.com/nodejs/docker-node/tree/b4117f9333da4138b03a546ec926ef50a31506c3#nodealpine to understand why libc6-compat might be needed. +RUN apk add --no-cache libc6-compat WORKDIR /app -RUN apt-get update && apt-get install -y \ - gcc \ - && rm -rf /var/lib/apt/lists/* +# Install dependencies based on the preferred package manager +COPY package.json yarn.lock* package-lock.json* pnpm-lock.yaml* .npmrc* ./ +RUN \ + if [ -f yarn.lock ]; then yarn --frozen-lockfile; \ + elif [ -f package-lock.json ]; then npm ci; \ + elif [ -f pnpm-lock.yaml ]; then corepack enable pnpm && pnpm i --frozen-lockfile; \ + else echo "Lockfile not found." && exit 1; \ + fi -COPY requirements.txt . -RUN pip install --no-cache-dir -r requirements.txt +# Rebuild the source code only when needed +FROM base AS builder +WORKDIR /app +COPY --from=deps /app/node_modules ./node_modules COPY . . -EXPOSE 8501 +# Next.js collects completely anonymous telemetry data about general usage. +# Learn more here: https://nextjs.org/telemetry +# Uncomment the following line in case you want to disable telemetry during the build. +# ENV NEXT_TELEMETRY_DISABLED=1 + +RUN \ + if [ -f yarn.lock ]; then yarn run build; \ + elif [ -f package-lock.json ]; then npm run build; \ + elif [ -f pnpm-lock.yaml ]; then corepack enable pnpm && pnpm run build; \ + else echo "Lockfile not found." && exit 1; \ + fi + +# Production image, copy all the files and run next +FROM base AS runner +WORKDIR /app + +ENV NODE_ENV=production +# Uncomment the following line in case you want to disable telemetry during runtime. +# ENV NEXT_TELEMETRY_DISABLED=1 + +RUN addgroup --system --gid 1001 nodejs +RUN adduser --system --uid 1001 nextjs + +COPY --from=builder /app/public ./public + +# Automatically leverage output traces to reduce image size +# https://nextjs.org/docs/advanced-features/output-file-tracing +COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./ +COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static + +USER nextjs + +EXPOSE 3000 -HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health +ENV PORT=3000 -ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"] \ No newline at end of file +# server.js is created by next build from the standalone output +# https://nextjs.org/docs/pages/api-reference/config/next-config-js/output +ENV HOSTNAME="0.0.0.0" +CMD ["node", "server.js"] \ No newline at end of file diff --git a/README.md b/README.md index 2eeecdc5823eed6af3f2da9a343c461fe51af0d0..4ff0587c3b696b868cdcd864c1529a17ad44a571 100644 --- a/README.md +++ b/README.md @@ -1,74 +1,19 @@ --- -title: TS Arena +title: TS-Arena emoji: πŸš€ colorFrom: red colorTo: red sdk: docker -app_port: 8501 -tags: -- streamlit -models: -- google/timesfm-2.0-500m-pytorch -- Maple728/TimeMoE-50M -- Salesforce/moirai-1.1-R-large -- thuml/sundial-base-128m - pinned: false +app_port: 3000 short_description: Time Series Forecasting Arena --- +# TS-Arena Frontend -# TS-Arena Streamlit Dashboard - -This is a Streamlit version of the TS-Arena Challenge Dashboard. - -## Installation - -1. Install dependencies: -```bash -pip install -r requirements.txt -``` - -2. Set up environment variables: -```bash -export X_API_URL="your_api_url_here" -export X_API_KEY="your_api_key_here" -``` - -Or create a `.env` file with: -``` -X_API_URL=your_api_url_here -X_API_KEY=your_api_key_here -``` - -## Running the App - -```bash -streamlit run app.py -``` - -The app will be available at `http://localhost:8501` - -## Features - -- **Model Ranking**: View and filter model rankings based on performance metrics (Tab 1) -- **Challenge Visualization**: Select and visualize active and completed challenges (Tab 2) -- **Time Series Selection**: Choose specific time series to analyze within a challenge -- **Interactive Plots**: Plotly charts with zoom, pan, and hover features -- **Upcoming Challenges**: View upcoming challenges in the sidebar -- **Add Model**: Information on how to participate and register your models (Tab 3) - -## Differences from Gradio Version - -Streamlit has some differences in behavior compared to Gradio: +## Concept -1. **State Management**: Streamlit uses session state and reruns the entire script on interaction -2. **Layout**: Streamlit uses `st.sidebar` for the sidebar and columns for layout -3. **Interactivity**: Dropdowns and multiselect widgets automatically trigger reruns -4. **Tabs**: Uses `st.tabs()` instead of Gradio's `gr.Tab()` +TS-Arena is a platform designed for **pre-registered forecasts into the real future**. This approach ensures rigorous, information leakage-free evaluations by comparing model predictions against data that did not exist at the time of the forecast. -## File Structure +This repository contains the backend infrastructure that powers the TS-Arena platform. It is designed to be self-hostable, allowing you to run your own instance of the benchmarking environment. -- `app.py` - Main Streamlit application -- `utils/api_client.py` - API client for fetching challenge data -- `utils/utils.py` - Utility functions for parsing durations -- `requirements.txt` - Python dependencies +For more information visit our [Git repository](https://github.com/DAG-UPB/ts-arena-backend). diff --git a/app.py b/app.py deleted file mode 100644 index 85fc5bf2cd8c1d4804fb87f54926515f205f3cee..0000000000000000000000000000000000000000 --- a/app.py +++ /dev/null @@ -1,185 +0,0 @@ -from components.challenges_tab_component import render_challenges_tab_component -from components.filter_component import render_filter_component, set_rankings_session_state -import streamlit as st -import pandas as pd -import sys -import os - -from components.challenge_list_component import render_challenge_list_component - -# Add src to path for imports -sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src')) -from utils.api_client import ChallengeStatus, DashboardAPIClient - -# Get API URL from environment variable -api_url = os.getenv('X_API_URL', '') -if api_url: - os.environ['DASHBOARD_API_URL'] = api_url - print(f"Loaded API URL from X_API_URL: {api_url}", file=sys.stderr) -else: - print("Warning: X_API_URL environment variable not set, using default", file=sys.stderr) - -# Get API key from environment variable -api_key = os.getenv('X_API_KEY', '') -if api_key: - os.environ['DASHBOARD_API_KEY'] = api_key - print(f"Loaded API key from X_API_KEY environment variable", file=sys.stderr) -else: - print("Warning: X_API_KEY environment variable not set", file=sys.stderr) - -# Initialize API client -api_client = DashboardAPIClient() - -# Page config -st.set_page_config( - page_title="TS-Arena Challenge Dashboard", - page_icon="🏟️", - layout="wide", - initial_sidebar_state="expanded" -) - -# Custom CSS to make sidebar wider -st.markdown(""" - -""", unsafe_allow_html=True) - - -# Main app -st.title("🏟️ TS-Arena – The Live-Forecasting Benchmark (Prototype)") - -# Sidebar for challenge list -with st.sidebar: - st.header("πŸ—“οΈ Upcoming") - upcoming_challenges = api_client.list_upcoming_challenges() - # Show only newest 5 challenges to reduce loading time - show_first = 5 - challenges_display = upcoming_challenges[:show_first] - render_challenge_list_component(challenges=challenges_display, api_client=api_client, challange_list_type="upcoming", show_first=5) - -# Create tabs -tab1, tab2, tab3 = st.tabs(["Model Ranking", "Challenges", "Add Model"]) - -with tab1: - with st.spinner("Loading model ranking..."): - render_filter_component(api_client=api_client, filter_type="model_ranking") - st.markdown("---") - if st.session_state.get('filtered_rankings') is None: - set_rankings_session_state(api_client=api_client) - st.rerun() - # Main content area - st.header("πŸ† Model Ranking") - - # Display rankings table from session state if available - filtered_rankings = st.session_state.get('filtered_rankings', None) - if filtered_rankings: - df_rankings = pd.concat([pd.DataFrame(df) for df in filtered_rankings], ignore_index=True) - tab_headers = list(df_rankings['time_ranges'].unique()) - tabs = st.tabs(tab_headers) - for unique_timerange, tab in zip(tab_headers, tabs): - filtered_by_time = df_rankings[df_rankings['time_ranges'] == unique_timerange].reset_index(drop=True) - with tab: - st.dataframe(filtered_by_time, use_container_width=True) - else: - st.info("No models match the selected filters") - -with tab2: - render_challenges_tab_component(api_client=api_client) - -with tab3: - st.header("πŸš€ Join the TS-Arena Benchmark!") - - st.markdown(""" - Ready to test your forecasting models against the best? Participate actively in our benchmark challenges! - Simply send us an email and we'll provide you with an API key to get started. - - ### How it works: - - Email us with your organization name and we'll send you an API key. - With this key, you can register your own models and officially participate in active competitions - once your model is registered. - """) - - col1, col2 = st.columns(2) - - with col1: - st.markdown(""" - - πŸ“§ Request API Key - - """, unsafe_allow_html=True) - - with col2: - st.markdown(""" - - ❓ Ask Questions - - """, unsafe_allow_html=True) - - st.markdown("---") - - st.markdown(""" - ### Bring the benchmark to life with your models! - - - πŸ”‘ **Personal API Key** for model registration and submission - - πŸ“Š **Access to benchmark datasets** and challenge specifications - - πŸ† **Rankings and leaderboards** showing your model's performance - - πŸ“ˆ **Detailed evaluation metrics** across multiple time series - - 🀝 **Community support** from fellow forecasting researchers - - ### Requirements: - - - Valid organization or affiliation - - Commitment to fair participation - - Adherence to benchmark guidelines - - For more information, please contact us via email! - - ### Help Us Validate Your Model Implementation: - Transparency is at the heart of our live benchmarking project. We have integrated a wide range of state-of-the-art time series forecasting models to provide the community with real-time performance insights. - To ensure that every model is evaluated under optimal conditions, **we invite the original authors and maintainers to review our implementations.** If you are a developer of one of the featured models, we would value your feedback on: - - - Model configuration and hyperparameters. - - Data preprocessing steps. - - Implementation-specific nuances. - - Our goal is to represent your work as accurately as possible. Please visit our [GitHub Repository](https://github.com/DAG-UPB/ts-arena) to review the code or open an issue for any suggested improvements. - """) - # TODO: Change link to GitHub Repository diff --git a/components/challange_card_component.py b/components/challange_card_component.py deleted file mode 100644 index f2765ff3dc38a47ec7fb9efc434b90347e787c2f..0000000000000000000000000000000000000000 --- a/components/challange_card_component.py +++ /dev/null @@ -1,196 +0,0 @@ -import sys -import streamlit as st -import time -from datetime import datetime, timezone - -from utils.api_client import ChallengeStatus -from utils.utils import duration_to_max_unit, parse_iso8601_duration, to_local - -@st.fragment(run_every="1s") -def timer_fragment(): - now = datetime.now(timezone.utc) - - st.markdown( - f""" -
- ⏱️ {now.strftime("%Y-%m-%d %H:%M:%S %Z")} -
- """, - unsafe_allow_html=True, - ) - -def render_challenge_card(challenge, api_client): - """Render a challenge card in the sidebar.""" - status = challenge.get('status', 'unknown') - desc = challenge.get('description', 'TBA') - challenge_id = str(challenge.get('challenge_id', ''))[:8] - n_series = challenge.get('n_time_series', 0) - model_count = challenge.get('model_count', 0) - forecast_horizon_interval = challenge.get('horizon', 'TBA') - context_length_interval = challenge.get('context_length', 'TBA') - - # Try to get frequency from series data for accurate parsing - frequency_iso = 'PT1H' # Default to 1 hour - forecast_horizon_from_series = None - context_length_from_series = None - - try: - challenge_id_full = challenge.get('challenge_id') - series_list = api_client.get_challenge_series(challenge_id_full) - if series_list and len(series_list) > 0: - frequency_iso = series_list[0].get('frequency', 'PT1H') - # Get forecast_horizon and context from series level (more accurate) - forecast_horizon_from_series = series_list[0].get('horizon') - except Exception as e: - print(f"DEBUG: Could not get series data for {challenge_id}: {e}", file=sys.stderr) - - # Use series-level horizon if available, otherwise fall back to challenge-level - horizon_to_parse = forecast_horizon_from_series or forecast_horizon_interval - context_to_parse = context_length_from_series or context_length_interval - - # Parse intervals with frequency - handle both string intervals and numeric values - if horizon_to_parse != 'TBA' and horizon_to_parse is not None: - if isinstance(horizon_to_parse, (int, float)): - forecast_horizon_num = int(horizon_to_parse) - elif isinstance(horizon_to_parse, str): - try: - _, horizon_seconds = parse_iso8601_duration(horizon_to_parse) - _, frequency_seconds = parse_iso8601_duration(frequency_iso) - if frequency_seconds > 0: - forecast_horizon_num = int(horizon_seconds / frequency_seconds) - else: - forecast_horizon_num = 'TBA' - except Exception as parse_e: - forecast_horizon_num = 'TBA' - else: - forecast_horizon_num = 'TBA' - else: - forecast_horizon_num = 'TBA' - - if context_to_parse != 'TBA' and context_to_parse is not None: - if isinstance(context_to_parse, (int, float)): - context_length_num = int(context_to_parse) - elif isinstance(context_to_parse, str): - try: - _, context_seconds = parse_iso8601_duration(context_to_parse) - _, frequency_seconds = parse_iso8601_duration(frequency_iso) - if frequency_seconds > 0: - context_length_num = int(context_seconds / frequency_seconds) - else: - context_length_num = 'TBA' - except Exception as parse_e: - context_length_num = 'TBA' - else: - context_length_num = 'TBA' - else: - context_length_num = 'TBA' - - # Parse frequency for display using duration_to_max_unit - frequency_display = frequency_iso - try: - freq_parts, _ = parse_iso8601_duration(frequency_iso) - frequency_display = duration_to_max_unit(freq_parts) - except Exception as e: - print(f"DEBUG: Could not parse frequency for display: {e}", file=sys.stderr) - - status_color = '#16a34a' if status == ChallengeStatus.ACTIVE.value else '#2563eb' - - # Get dates - reg_start = challenge.get('registration_start', '') - final_eval = challenge.get('end_time', '') - - dates_html = "" - if reg_start: - reg_start_iso = to_local(reg_start, "UTC").isoformat() - dates_html += f"""
- πŸ“… Registration opens: -
- - """ - if final_eval: - final_iso = str(to_local(final_eval, "UTC").isoformat()) - dates_html += f"""
- ⏰ Final Evaluation: -
- -
""" - - # Countdown Closes in & Starts in - time = None - match status: - # Time has to be in CET for JS countdown. - case ChallengeStatus.REGISTRATION.value: - time = to_local(challenge.get('registration_end', ''), "CET") - case ChallengeStatus.ACTIVE.value: - time = to_local(challenge.get('end_time', ''), "CET") - case ChallengeStatus.ANNOUNCED.value: - time = to_local(challenge.get('registration_start', ''), "CET") - case _: - pass - - markdown = f""" -
-
-
{desc}
-
{status.upper()}
-
-
ID: {challenge_id}
-
-
-
TIME SERIES
-
{n_series}
-
-
-
MODELS
-
{model_count}
-
-
-
HORIZON (STEPS x FREQ)
-
{forecast_horizon_num} x {frequency_display}
-
-
-
CONTEXT LENGTH
-
{context_length_num}
-
-
-
- {dates_html} -
-
{'Loading...'}
-
""" - return markdown - \ No newline at end of file diff --git a/components/challenge_list_component.py b/components/challenge_list_component.py deleted file mode 100644 index 945cde5cbd276521d93da6af064e46902a2dea81..0000000000000000000000000000000000000000 --- a/components/challenge_list_component.py +++ /dev/null @@ -1,86 +0,0 @@ -import streamlit as st -import streamlit.components.v1 as components -import sys - -from components.challange_card_component import render_challenge_card - - -def get_time_js_script()->str: - return """ - """ - -def render_challenge_list_component(challenges, api_client, challange_list_type: str = "ongoing", show_first: int = 5): - # Create scrollable container for active challenges - challenge_container = st.container(height="stretch") - with challenge_container: - try: - if challenges: - cards = [] - for challenge in challenges: - cards.append(render_challenge_card(challenge, api_client=api_client)) - components.html("
"+"".join(cards)+get_time_js_script()+"
", height=700, scrolling=True) - return - except Exception as e: - st.write(e) - print(f"Error loading {challange_list_type} challenges: {e}", file=sys.stderr) - if challange_list_type == "ongoing": - st.write("No active challenges") - else: - st.write("No upcoming challenges") diff --git a/components/challenges_tab_component.py b/components/challenges_tab_component.py deleted file mode 100644 index f0fd002dcebd02c92ac6a7c25c54d723f308fa7e..0000000000000000000000000000000000000000 --- a/components/challenges_tab_component.py +++ /dev/null @@ -1,545 +0,0 @@ -from datetime import datetime, timezone -import sys -import traceback -from typing import Any, Dict, List, Optional -import pandas as pd -from components.filter_models_component import render_filter_models_component -import plotly.graph_objects as go -import plotly.express as px -import numpy as np -import streamlit as st - -from components.filter_component import render_filter_component, set_challenges_session_state -from utils.api_client import ChallengeStatus, DashboardAPIClient, hash_func_dashboard_api_client -from utils.utils import duration_to_max_unit, parse_iso8601_duration - - -def get_challenge_horizon_steps_from_series(series_list): - """ - Uses the series list to determine the forecast horizon in steps. - """ - frequency_iso = series_list[0].get('frequency', 'PT1H') - horizon_iso = series_list[0].get('horizon') - return get_challenge_horizon(frequency_iso, horizon_iso) - - -def get_challenge_horizon_steps_from_challenge(challenge): - frequency_iso = challenge.get('frequency', 'PT1H') - horizon_iso = challenge.get('horizon') - return get_challenge_horizon(frequency_iso, horizon_iso) - - -def get_challenge_horizon(frequency_iso: str, horizon_iso: str) -> int: - if horizon_iso and frequency_iso: - try: - _, horizon_seconds = parse_iso8601_duration(horizon_iso) - _, frequency_seconds = parse_iso8601_duration(frequency_iso) - if frequency_seconds > 0: - steps = int(horizon_seconds / frequency_seconds) - return steps - except Exception as parse_e: - print(f"Error parsing horizon: {parse_e}", file=sys.stderr) - return -1 - - -@st.cache_data(hash_funcs={DashboardAPIClient: hash_func_dashboard_api_client}, show_spinner="Loading forecasts...") -def get_forecasts(api_client: DashboardAPIClient, challenge_id: str, series_id: int) -> Dict[str, Any]: - forecasts = api_client.get_series_forecasts(challenge_id, series_id) - forecasts = dict( - sorted(forecasts.items(), key=lambda item: item[1]["current_mase"]) - ) - return forecasts - - -def get_series_choices_for_challenge(challenge_id, api_client: DashboardAPIClient) -> List[Dict[str, Any]]: - """Get list of time series for a given challenge.""" - if not challenge_id: - return [] - - try: - # Don't try to get series for mock challenges - if str(challenge_id).startswith('mock'): - return [] - - # Get series list from API - series_list = api_client.get_challenge_series(challenge_id) - if not series_list: - return [] - - # Format series choices with ID and name - choices = [] - for series_info in series_list: - series_id = series_info.get('series_id') - series_name = series_info.get('name', f'Series {series_id}') - series_description = series_info.get('description', series_id) - choices.append({ - 'id': series_id, - 'name': series_name, - 'description': series_description, - 'display': f"{series_description} (ID: {series_id})" - }) - - return choices - except Exception as e: - print(f"Error getting series choices: {e}", file=sys.stderr) - return [] - - -@st.cache_data(show_spinner="Drawing plots...") -def make_demo_forecast_plot(forecast_horizon, challenge_desc="Demo Challenge"): - """Generate demo forecast plot with synthetic data.""" - np.random.seed(42) - - historical_len = 50 - forecast_len = int(forecast_horizon) - time = np.arange(historical_len + forecast_len) - - historical_data = 100 + 10 * np.sin(np.linspace(0, 4 * np.pi, historical_len)) + np.random.normal(0, 2, historical_len) - - fig = go.Figure() - - # Add historical data - fig.add_trace(go.Scatter( - x=time[:historical_len], - y=historical_data, - mode='lines', - name='Historical Data', - line=dict(color='black', width=3), - legendgroup='historical', - )) - - model_names = [ - "ARIMA", "Prophet", "LSTM", "XGBoost", - "Random Forest", "ETS", "Theta", "TBATS", - "Neural Prophet", "Ensemble" - ] - - colors = px.colors.qualitative.Plotly + px.colors.qualitative.Set2 - - for i, model_name in enumerate(model_names): - base_forecast = 100 + 10 * np.sin(np.linspace(4 * np.pi, 4 * np.pi + 2 * np.pi, forecast_len)) - noise = np.random.normal(0, 1 + i * 0.3, forecast_len) - trend = np.linspace(0, i * 0.5, forecast_len) - forecast = base_forecast + noise + trend - - forecast_x = np.concatenate([[time[historical_len - 1]], time[historical_len:]]) - forecast_y = np.concatenate([[historical_data[-1]], forecast]) - - fig.add_trace(go.Scatter( - x=forecast_x, - y=forecast_y, - mode='lines', - name=model_name, - line=dict(color=colors[i % len(colors)], width=2, dash='solid'), - legendgroup=f'model_{i}', - hovertemplate=f'{model_name}
Time: %{{x}}
Value: %{{y:.2f}}' - )) - - upper_bound = forecast + (3 + i * 0.5) - lower_bound = forecast - (3 + i * 0.5) - - fig.add_trace(go.Scatter( - x=np.concatenate([time[historical_len:], time[historical_len:][::-1]]), - y=np.concatenate([upper_bound, lower_bound[::-1]]), - fill='toself', - fillcolor=colors[i % len(colors)], - opacity=0.15, - line=dict(width=0), - name=f'{model_name} CI', - legendgroup=f'model_{i}', - showlegend=False, - hoverinfo='skip' - )) - - fig.add_vline( - x=historical_len - 0.5, - line_dash="dash", - line_color="gray", - opacity=0.7, - annotation_text="Forecast Start", - annotation_position="top" - ) - - fig.update_layout( - title={ - 'text': f'πŸ“ˆ {challenge_desc} - Forecast Comparison ({forecast_len} steps ahead)', - 'x': 0.5, - 'xanchor': 'center', - 'font': {'size': 20, 'color': '#2c3e50'} - }, - xaxis_title='Time', - yaxis_title='Value', - hovermode='x unified', - template='plotly_white', - height=600, - font=dict(family="Arial, sans-serif", size=12), - plot_bgcolor='rgba(245, 245, 245, 0.5)', - ) - - fig.update_xaxes( - showgrid=True, - gridwidth=1, - gridcolor='lightgray', - showline=True, - linewidth=2, - linecolor='gray' - ) - - fig.update_yaxes( - showgrid=True, - gridwidth=1, - gridcolor='lightgray', - showline=True, - linewidth=2, - linecolor='gray' - ) - - return fig - - -@st.cache_data(hash_funcs={DashboardAPIClient: hash_func_dashboard_api_client}, show_spinner="Drawing plots...") -def plot_real_challenge_data(challenge: Dict[str, Any], forecast_horizon: int, api_client: DashboardAPIClient, selected_series_ids: List[int] = None, selected_readable_model_ids: List[str] = None) -> Optional[go.Figure]: - """Plot real challenge data from API with selected series and forecasts.""" - try: - challenge_id = challenge.get('challenge_id') - challenge_desc = challenge.get('description', 'Challenge') - - # Get all series for this challenge - series_list = api_client.get_challenge_series(challenge_id) - if not series_list: - return None - - # Filter series based on selection - if selected_series_ids: - series_list = [s for s in series_list if s.get('series_id') in selected_series_ids] - - if not series_list: - fig = go.Figure() - fig.add_annotation( - text="No series selected or found", - xref="paper", yref="paper", - x=0.5, y=0.5, showarrow=False, - font=dict(size=16, color="gray") - ) - return fig - - # Create figure - fig = go.Figure() - - # Color palette for models - colors = px.colors.qualitative.Plotly + px.colors.qualitative.Set2 + px.colors.qualitative.Set3 - model_color_map = {} - color_idx = 0 - - inferred_frequency = None - steps_to_show = forecast_horizon - - # Process each series - for series_idx, series_info in enumerate(series_list): - series_id = series_info.get('series_id') - series_name = series_info.get('name', f'Series {series_id}') - - # Get context data (historical) - context_df = api_client.get_challenge_data_for_series( - challenge_id, series_id, - series_info.get('context_start_time'), - series_info.get('context_end_time') - ) - - # Get actual data (test/live data) - actual_df = api_client.get_challenge_data_for_series( - challenge_id, series_id, - series_info.get('context_end_time'), - series_info.get('end_time') - ) - - # Infer frequency - if inferred_frequency is None and not context_df.empty and len(context_df) >= 2: - try: - frequency_iso = series_info.get('frequency', 'PT1H') - horizon_iso = series_info.get('horizon') or challenge.get('horizon') - - if horizon_iso and frequency_iso: - _, horizon_seconds = parse_iso8601_duration(horizon_iso) - _, frequency_seconds = parse_iso8601_duration(frequency_iso) - - if frequency_seconds > 0: - steps_to_show = int(horizon_seconds / frequency_seconds) - freq_parts, _ = parse_iso8601_duration(frequency_iso) - inferred_frequency = duration_to_max_unit(freq_parts) - except Exception as e: - print(f"Error calculating steps: {e}", file=sys.stderr) - - # Add context data (historical) - if not context_df.empty: - hist_name = "Historical Data" if len(series_list) == 1 else f"Historical - {series_name}" - fig.add_trace(go.Scatter( - x=context_df["ts"], - y=context_df["value"], - name=hist_name, - mode="lines", - line=dict(color="black", width=3), - legendgroup=f"series_{series_id}", - hovertemplate=f"{hist_name}
Time: %{{x}}
Value: %{{y}}", - )) - - # Get forecasts for this series - forecasts = get_forecasts(api_client, challenge_id, series_id) - - # Add forecasts - for model_readable_id, data in forecasts.items(): - df = data["data"] - model_label = data.get("label", model_readable_id) - if df.empty: - continue - - if not model_readable_id in selected_readable_model_ids: - continue - - if model_label not in model_color_map: - model_color_map[model_label] = colors[color_idx % len(colors)] - color_idx += 1 - - color = model_color_map[model_label] - prelim_mase = data.get('current_mase') - if prelim_mase is None: - prelim_mase = "N/A" - else: - prelim_mase = f"{prelim_mase:.2f}" - display_name = f"{model_label} - Prelim MASE: {prelim_mase}" - if len(series_list) > 1: - display_name += f" ({series_name})" - - # Connect forecast to last historical point - if not context_df.empty and not df.empty: - last_hist_ts = context_df["ts"].iloc[-1] - last_hist_val = context_df["value"].iloc[-1] - forecast_x = pd.concat([pd.Series([last_hist_ts]), df["ts"]]).reset_index(drop=True) - forecast_y = pd.concat([pd.Series([last_hist_val]), df["y"]]).reset_index(drop=True) - else: - forecast_x = df["ts"] - forecast_y = df["y"] - - fig.add_trace(go.Scatter( - x=forecast_x, - y=forecast_y, - name=display_name, - mode="lines+markers", - line=dict(color=color, width=2), - marker=dict(size=4), - legendgroup=model_label, - hovertemplate=f"{display_name}
Time: %{{x}}
Value: %{{y:.2f}}", - )) - - # Add actual data for first series only - if series_idx == 0 and not actual_df.empty: - actual_df_limited = actual_df.head(steps_to_show) - if not actual_df_limited.empty: - fig.add_trace(go.Scatter( - x=actual_df_limited["ts"], - y=actual_df_limited["value"], - name=f"Actual - {series_name}", - mode="lines", - line=dict(color="grey", width=3, dash="dot"), - marker=dict(size=6, symbol="diamond"), - legendgroup=f"series_{series_id}", - hovertemplate=f"Actual - {series_name}
Time: %{{x}}
Value: %{{y}}", - )) - - # Update layout - fig.update_layout( - xaxis_title='Time', - yaxis_title='Value', - hovermode='x unified', - template='plotly_white', - height=600, - font=dict(family="Arial, sans-serif", size=12), - plot_bgcolor='rgba(245, 245, 245, 0.5)', - ) - - fig.update_xaxes( - showgrid=True, - gridwidth=1, - gridcolor='lightgray', - showline=True, - linewidth=2, - linecolor='gray' - ) - - fig.update_yaxes( - showgrid=True, - gridwidth=1, - gridcolor='lightgray', - showline=True, - linewidth=2, - linecolor='gray' - ) - - return fig - - except Exception as e: - print(f"Error plotting real challenge data: {e}", file=sys.stderr) - traceback.print_exc() - return None - - -def render_challenges_tab_component(api_client: DashboardAPIClient): - render_filter_component(api_client=api_client, filter_type="active_challenges") - st.markdown("---") - - # Main content area - st.header("🎯 Visualize a Challenge") - - # Challenge selection - if st.session_state.get('filtered_challenges') is None: - with st.spinner("Loading active challenges..."): - now = datetime.now(timezone.utc).strftime("%Y-%m-%dT") - set_challenges_session_state( - api_client=api_client, - selected_from_date=now+ "00:00:00.000Z", - selected_to_date=now + "23:59:59.999Z", - selected_statuses=[ChallengeStatus.ACTIVE.value], - ) - st.rerun() - active_completed_challenges = st.session_state['filtered_challenges'] - challenge_options = {f"{c.get('status')} β€’ {c.get('description')}, Start Date: {datetime.strptime(c.get('start_time'), '%Y-%m-%dT%H:%M:%S.%fZ').strftime('%Y-%m-%d %H:%M:%S') if c.get('start_time') else 'N/A'} ({str(c.get('challenge_id', ''))[:8]})": c - for c in active_completed_challenges} - - if challenge_options: - selected_challenge_key = st.selectbox( - "Challenge Selection", - options=list(challenge_options.keys()), - key="challenge_select" - ) - - selected_challenge = challenge_options[selected_challenge_key] - challenge_id = str(selected_challenge.get('challenge_id', '')) - challenge_id_short = challenge_id[:8] if challenge_id != '' else '' - challenge_name = selected_challenge.get('description', 'Challenge') - - # Series selection - series_options = get_series_choices_for_challenge(challenge_id, api_client) - - # Display challenge heading - st.subheader(f"πŸ“Š {challenge_name}") - - # Get detailed challenge info - status = selected_challenge.get('status', 'unknown') - n_series = selected_challenge.get('n_time_series', 0) - model_count = selected_challenge.get('model_count', 0) - - if status == ChallengeStatus.ANNOUNCED.value: - if n_series == 0: - n_series = "tbd" - if model_count == 0: - model_count = "tbd" - - challenge_id = str(selected_challenge.get('challenge_id', ''))[:8] - - # Get frequency and calculate horizon/context in steps - frequency_iso = 'PT1H' # Default - context_length_num = 'N/A' - frequency_display = 'N/A' - - try: - challenge_id_full = selected_challenge.get('challenge_id') - series_list = api_client.get_challenge_series(challenge_id_full) - forecast_horizon_steps_num = get_challenge_horizon_steps_from_series(series_list) - if forecast_horizon_steps_num == -1: - forecast_horizon_steps_num = get_challenge_horizon_steps_from_challenge(selected_challenge) - if series_list and len(series_list) > 0: - frequency_iso = series_list[0].get('frequency', 'PT1H') - context_iso = series_list[0].get('context_length') or selected_challenge.get('context_length') - - # Parse frequency for display - try: - freq_parts, _ = parse_iso8601_duration(frequency_iso) - frequency_display = duration_to_max_unit(freq_parts) - except: - frequency_display = frequency_iso - - context_length_num = context_iso - except Exception as e: - print(f"Error getting series data for challenge info: {e}", file=sys.stderr) - - # Status color - status_color = '#16a34a' if status == ChallengeStatus.ACTIVE.value else '#2563eb' - - # Compact single-line info display matching Gradio version - st.markdown(f""" -
-
{status.upper()}
-
ID: {challenge_id}
-
-
Series: {n_series}
-
Models: {model_count}
-
Horizon: {forecast_horizon_steps_num if forecast_horizon_steps_num != -1 else 'N/A' } Steps
-
Context: {context_length_num}
-
Frequency: {frequency_display}
-
- """, unsafe_allow_html=True) - - models = api_client.list_models_for_challenge(challenge_id) - selected_series_ids, selected_readable_model_ids = render_filter_models_component(series_options, models) - - # Individual plots for each series (default) - with st.spinner("Loading individual series plots..."): - try: - challenge_id_full = selected_challenge.get('challenge_id') - - if not str(challenge_id_full).startswith('mock'): - # Get series list - series_list = api_client.get_challenge_series(challenge_id_full) - - if series_list and selected_series_ids: - # Filter to selected series - filtered_series = [s for s in series_list if s.get('series_id') in selected_series_ids] - - if filtered_series: - # Create scrollable container for individual plots - individual_plots_container = st.container(height=800) - with individual_plots_container: - for series_info in filtered_series: - series_id = series_info.get('series_id') - series_name = series_info.get('name', f'Series {series_id}') - series_desc = series_info.get('description', '') - if series_desc: - expander_title = f"πŸ“ˆ {series_desc} (ID: {series_id})" - else: - expander_title = f"πŸ“ˆ {series_name} (ID: {series_id})" - with st.expander(expander_title, expanded=True): - # Plot this individual series - fig = plot_real_challenge_data( - challenge=selected_challenge, - forecast_horizon=forecast_horizon_steps_num, - api_client=api_client, - selected_series_ids=[series_id], - selected_readable_model_ids=selected_readable_model_ids, - ) - if fig: - st.plotly_chart(fig, width="stretch") - else: - st.warning(f"Could not load data for {series_name}") - else: - st.info("No series selected") - else: - st.info("No series available or none selected") - else: - st.info("Individual series plots not available for demo data") - fig = make_demo_forecast_plot(forecast_horizon_steps_num, challenge_name) - st.plotly_chart(fig, width="stretch") - - except Exception as e: - st.error(f"Error loading individual plots: {str(e)}") - traceback.print_exc() - # Interactive features info - st.markdown(""" - **Interactive Features:** - - πŸ–±οΈ **Click legend items** to show/hide individual models - - πŸ” **Zoom** by dragging a box on the chart - - πŸ‘† **Pan** by clicking and dragging - - πŸ”„ **Reset** by double-clicking the chart - - πŸ“Š **Hover** to see exact values - """) - else: - st.info("No challenges available") \ No newline at end of file diff --git a/components/filter_component.py b/components/filter_component.py deleted file mode 100644 index 34c98827971bdd6cbc086e6f5f04fc001e9a0021..0000000000000000000000000000000000000000 --- a/components/filter_component.py +++ /dev/null @@ -1,170 +0,0 @@ -from typing import List, Optional -import streamlit as st -import pandas as pd -import sys - -from utils.api_client import ChallengeStatus, DashboardAPIClient - -# Cached function to set rankings in session state -def set_rankings_session_state( - api_client: DashboardAPIClient, - selected_domains: Optional[List[str]] = None, - selected_categories: Optional[List[str]] = None, - selected_frequencies: Optional[List[str]] = None, - selected_horizons: Optional[List[str]] = None -): - if 'filtered_rankings' not in st.session_state: - st.session_state['filtered_rankings'] = None - - filter_options = api_client.get_filter_options() - filtered_rankings = [] - for time_range in filter_options.get("time_ranges", ['All']): - loop_dict = api_client.get_filtered_rankings( - domains=selected_domains if selected_domains else None, - categories=selected_categories if selected_categories else None, - frequencies=selected_frequencies if selected_frequencies else None, - horizons=selected_horizons if selected_horizons else None, - time_range=time_range - ) - loop_dict = [{**item, "time_ranges": time_range} for item in loop_dict] - filtered_rankings.append(loop_dict) - st.session_state['filtered_rankings'] = filtered_rankings - - -def set_challenges_session_state( - api_client: DashboardAPIClient, - selected_domains: Optional[List[str]] = None, - selected_categories: Optional[List[str]] = None, - selected_frequencies: Optional[List[str]] = None, - selected_horizons: Optional[List[str]] = None, - selected_from_date: Optional[str] = None, - selected_to_date: Optional[str] = None, - selected_statuses: Optional[List[str]] = None -): - filtered_rankings = api_client.get_filtered_challenges( - domain=selected_domains if selected_domains else None, - category=selected_categories if selected_categories else None, - frequency=selected_frequencies if selected_frequencies else None, - horizon=selected_horizons if selected_horizons else None, - from_date=selected_from_date if selected_from_date else None, - to_date=selected_to_date if selected_to_date else None, - status=selected_statuses if selected_statuses else None - ) - if filtered_rankings: - st.session_state["filtered_challenges"] = filtered_rankings - else: - st.session_state["filtered_challenges"] = [] - st.info("No challenges match the selected filters") - -def render_filter_component(api_client: DashboardAPIClient, filter_type: str = "model_ranking"): - """ - Render the filter component in the Streamlit app. - - Args: - api_client: Instance of DashboardAPIClient to fetch filter options and rankings. - """ - - # Add filter section right after the header - if filter_type == "model_ranking": - st.markdown("### πŸ” Filter Model Rankings") - elif filter_type == "active_challenges": - st.markdown("### πŸ” Filter Active Challenges") - - # Get filter options from API - filter_options = api_client.get_filter_options() - - # Create columns for filters - col1, col2, col3 = st.columns(3) - col5, col6, col7, col8 = st.columns(4) - - with col1: - selected_domains = st.multiselect( - "Domain", - options=filter_options.get("domains", []), - help="Filter by domain", - key=f"domain_filter_{filter_type}" - ) - - with col2: - selected_categories = st.multiselect( - "Category", - options=filter_options.get("categories", []), - help="Filter by category", - key=f"category_filter_{filter_type}" - ) - - with col3: - selected_frequencies = st.multiselect( - "Frequency", - options=filter_options.get("frequencies", []), - help="Filter by time series frequency", - key=f"frequency_filter_{filter_type}" - ) - - with col5: - selected_horizons = st.multiselect( - "Horizon", - options=filter_options.get("horizons", []), - help="Filter by forecast horizon", - key=f"horizon_filter_{filter_type}" - ) - - # Active Challenges specific filters - selected_statuses = None - selected_from_date = None - selected_to_date = None - if filter_type == "active_challenges": - with col6: - selected_from_date = st.date_input( - "End Date From", - value="today", - help="Filter by Date", - key=f"from_date_filter_{filter_type}" - ) - selected_from_date = selected_from_date.strftime( - "%Y-%m-%dT00:00:00.000Z") - with col7: - selected_to_date = st.date_input( - "End Date To", - value='today', - help="Filter by Date", - key=f"to_date_filter_{filter_type}" - ) - selected_to_date = selected_to_date.strftime( - "%Y-%m-%dT23:59:59.999Z") - with col8: - selected_statuses = st.multiselect( - "Status", - options=[ChallengeStatus.ACTIVE.value, - ChallengeStatus.COMPLETED.value], - default=[ChallengeStatus.ACTIVE.value], - help="Filter by challenge status", - key=f"status_filter_{filter_type}" - ) - # TODO: Filter for registration start and end date - - # Apply filters button - if st.button("πŸ” Apply Filters", type="primary", key=f"apply_filters_button_{filter_type}"): - try: - if filter_type == "model_ranking": - set_rankings_session_state( - api_client, - selected_domains=selected_domains, - selected_categories=selected_categories, - selected_frequencies=selected_frequencies, - selected_horizons=selected_horizons - ) - - elif filter_type == "active_challenges": - set_challenges_session_state( - api_client, - selected_domains=selected_domains, - selected_categories=selected_categories, - selected_frequencies=selected_frequencies, - selected_horizons=selected_horizons, - selected_from_date=selected_from_date, - selected_to_date=selected_to_date, - selected_statuses=selected_statuses - ) - except Exception as e: - st.error(f"Error applying filters: {str(e)}") diff --git a/components/filter_models_component.py b/components/filter_models_component.py deleted file mode 100644 index d7501660409db2a159ec1ec6f6157deafafc6826..0000000000000000000000000000000000000000 --- a/components/filter_models_component.py +++ /dev/null @@ -1,76 +0,0 @@ -import streamlit as st - -def render_filter_models_component(series_options: list[dict], models: list[dict]): - # Select series: - if series_options: - # Default to first two series only - default_selection = [s['description'] for s in series_options[:2]] - - selected_series = st.multiselect( - "Time Series Selection", - options=[s['description'] for s in series_options], - default=default_selection, - help="Select which time series to display in the plot", - key="series_select" - ) - - # Extract series IDs from selection - selected_series_ids = [ - s['id'] for s in series_options - if s['description'] in selected_series - ] - else: - selected_series_ids = None - - # Select models: - if models: - selected_readable_model_ids = [model["readable_id"] for model in models] - max_value = [model["model_size"] for model in models if model["model_size"] is not None] - max_value = max(max_value) if max_value else 0 - # Filter size - selected_size = st.number_input( - "Model Max Size", - min_value=0, - value=max_value, - step=1, - help="Filter models by size (in million)", - key="model_size_filter" - ) - # Nones are always displayed - deselected_sizes_ids = [model["readable_id"] for model in models if model["model_size"] is not None and model["model_size"] > selected_size] - - # Filter name - selected_names = st.text_input( - "Model Name Contains", - value="", - help="Filter models by name containing this text. Multiple names can be separated by commas.", - key="model_name_filter" - ) - if selected_names.strip(",").strip() == "": - deselected_name_ids = [] - else: - deselected_name_ids = selected_readable_model_ids.copy() - for multiple in selected_names.split(","): - multiple = multiple.strip() - if multiple: - deselected_name_ids = list(set([model["readable_id"] for model in models if multiple.lower() not in model["name"].lower() and multiple.lower() != model["readable_id"].lower()]) & set(deselected_name_ids)) - - # Filter by architecture - available_architectures = list(set(model["architecture"] for model in models if model["architecture"] is not None)) - select_architecture = st.multiselect( - "Model Architecture", - options=available_architectures, - default=available_architectures, - help="Filter by model architecture", - key="model_architecture_filter" - ) - deselected_architecture_ids = [ - model["readable_id"] for model in models - if model["architecture"] not in select_architecture - ] - - # Combine filters - selected_readable_model_ids = list(set(selected_readable_model_ids) - set(deselected_sizes_ids) - set(deselected_name_ids) - set(deselected_architecture_ids)) - else: - selected_readable_model_ids = None - return selected_series_ids, selected_readable_model_ids \ No newline at end of file diff --git a/eslint.config.mjs b/eslint.config.mjs new file mode 100644 index 0000000000000000000000000000000000000000..05e726d1b4201bc8c7716d2b058279676582e8c0 --- /dev/null +++ b/eslint.config.mjs @@ -0,0 +1,18 @@ +import { defineConfig, globalIgnores } from "eslint/config"; +import nextVitals from "eslint-config-next/core-web-vitals"; +import nextTs from "eslint-config-next/typescript"; + +const eslintConfig = defineConfig([ + ...nextVitals, + ...nextTs, + // Override default ignores of eslint-config-next. + globalIgnores([ + // Default ignores of eslint-config-next: + ".next/**", + "out/**", + "build/**", + "next-env.d.ts", + ]), +]); + +export default eslintConfig; diff --git a/next.config.ts b/next.config.ts new file mode 100644 index 0000000000000000000000000000000000000000..8254d9141b6ee0f0ec7d217e768902771824dbfa --- /dev/null +++ b/next.config.ts @@ -0,0 +1,6 @@ +/** @type {import('next').NextConfig} */ +// next.config.js +module.exports = { + // ... rest of the configuration. + output: "standalone", +}; diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000000000000000000000000000000000000..82eb5e60ae6f94f8283e4b39000a8b3e34b39dcf --- /dev/null +++ b/package-lock.json @@ -0,0 +1,9267 @@ +{ + "name": "ts-arena", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "ts-arena", + "version": "0.1.0", + "dependencies": { + "@headlessui/react": "^2.2.9", + "@tanstack/react-table": "^8.21.3", + "humanize-duration": "^3.33.2", + "iso8601-duration": "^2.1.3", + "lucide-react": "^0.563.0", + "next": "16.1.1", + "plotly.js": "^3.3.1", + "react": "19.2.3", + "react-dom": 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"version": "4.0.2", + "resolved": "https://registry.npmjs.org/zod-validation-error/-/zod-validation-error-4.0.2.tgz", + "integrity": "sha512-Q6/nZLe6jxuU80qb/4uJ4t5v2VEZ44lzQjPDhYJNztRQ4wyWc6VF3D3Kb/fAuPetZQnhS3hnajCf9CsWesghLQ==", + "dev": true, + "license": "MIT", + "engines": { + "node": ">=18.0.0" + }, + "peerDependencies": { + "zod": "^3.25.0 || ^4.0.0" + } + } + } +} diff --git a/package.json b/package.json new file mode 100644 index 0000000000000000000000000000000000000000..b94dc632fce689405ba0b355eb7db7b01849c26c --- /dev/null +++ b/package.json @@ -0,0 +1,37 @@ +{ + "name": "ts-arena", + "version": "0.1.0", + "private": true, + "scripts": { + "dev": "next dev", + "build": "next build", + "start": "next start", + "lint": "eslint", + "lint:fix": "eslint --fix" + }, + "dependencies": { + "@headlessui/react": "^2.2.9", + "@tanstack/react-table": "^8.21.3", + "humanize-duration": "^3.33.2", + "iso8601-duration": "^2.1.3", + "lucide-react": "^0.563.0", + "next": "16.1.1", + "plotly.js": "^3.3.1", + "react": "19.2.3", + "react-dom": "19.2.3", + "react-plotly.js": "^2.6.0" + }, + "devDependencies": { + "@tailwindcss/postcss": "^4", + "@types/humanize-duration": "^3.27.4", + "@types/node": "^20", + "@types/plotly.js": "^3.0.9", + "@types/react": "^19", + "@types/react-dom": "^19", + "@types/react-plotly.js": "^2.6.4", + "eslint": "^9", + "eslint-config-next": "16.1.1", + "tailwindcss": "^4", + "typescript": "^5" + } +} diff --git a/postcss.config.mjs b/postcss.config.mjs new file mode 100644 index 0000000000000000000000000000000000000000..61e36849cf7cfa9f1f71b4a3964a4953e3e243d3 --- /dev/null +++ b/postcss.config.mjs @@ -0,0 +1,7 @@ +const config = { + plugins: { + "@tailwindcss/postcss": {}, + }, +}; + +export default config; diff --git a/public/file.svg b/public/file.svg new file mode 100644 index 0000000000000000000000000000000000000000..004145cddf3f9db91b57b9cb596683c8eb420862 --- /dev/null +++ b/public/file.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/public/globe.svg b/public/globe.svg new file mode 100644 index 0000000000000000000000000000000000000000..567f17b0d7c7fb662c16d4357dd74830caf2dccb --- /dev/null +++ b/public/globe.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/public/next.svg b/public/next.svg new file mode 100644 index 0000000000000000000000000000000000000000..5174b28c565c285e3e312ec5178be64fbeca8398 --- /dev/null +++ b/public/next.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/public/vercel.svg b/public/vercel.svg new file mode 100644 index 0000000000000000000000000000000000000000..77053960334e2e34dc584dea8019925c3b4ccca9 --- /dev/null +++ b/public/vercel.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/public/window.svg b/public/window.svg new file mode 100644 index 0000000000000000000000000000000000000000..b2b2a44f6ebc70c450043c05a002e7a93ba5d651 --- /dev/null +++ b/public/window.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 0049964ad2eeffec137f31848b672a4b4f85b108..0000000000000000000000000000000000000000 --- a/requirements.txt +++ /dev/null @@ -1,7 +0,0 @@ -streamlit>=1.28.0 -plotly>=5.17.0 -numpy>=1.24.0 -pandas>=2.0.0 -requests>=2.31.0 -isodate>=0.6.1 -python-dotenv>=1.0.0 diff --git a/src/app/add-model/page.tsx b/src/app/add-model/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..09bb47a66af4cbb6394a681e8c6e5d4820b38606 --- /dev/null +++ b/src/app/add-model/page.tsx @@ -0,0 +1,221 @@ +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import { Mail, Key, TrendingUp, Trophy, BarChart3, Users, CheckCircle, Github } from 'lucide-react'; + +export default function InfoPage() { + return ( +
+ + +
+

Join the TS-Arena Benchmark

+

+ Test your forecasting models against the best in real-time benchmark challenges +

+
+ + {/* Main CTA Section */} +
+

Get Started

+

+ Ready to test your forecasting models against the best? Participate actively in our benchmark challenges! + Simply send us an email and we'll provide you with an API key to get started. Find detailed participation instructions in our{' '} + + Git repository + . +

+ +
+ + + Request API Key + + + + Ask Questions + +
+
+ + {/* How it Works */} +
+

How it Works

+
+
+
+ 1 +
+
+

Request an API Key

+

+ Email us with your organization name and we'll send you an API key. +

+
+
+ +
+
+ 2 +
+
+

Register Your Model

+

+ Use your API key to register models for challenges in the registration phase. +

+
+
+ +
+
+ 3 +
+
+

Submit Forecasts

+

+ Obtain time-series context via our API and submit your forecasts before registration closes. +

+
+
+ +
+
+ 4 +
+
+

Track Performance

+

+ During the active phase, your model is evaluated on live data. Monitor performance on leaderboards and explore forecasts through interactive plots. +

+
+
+
+
+ + {/* Benefits Grid */} +
+

What You Get

+
+
+ +
+

Personal API Key

+

For model registration and submission

+
+
+ +
+ +
+

Benchmark Datasets

+

Access to datasets and challenge specifications

+
+
+ +
+ +
+

Rankings & Leaderboards

+

Real-time performance tracking

+
+
+ +
+ +
+

Detailed Metrics

+

Comprehensive evaluation across time series

+
+
+ +
+ +
+

Community Support

+

Connect with forecasting researchers

+
+
+
+
+ + {/* Requirements */} +
+

Requirements

+
+
+ + Valid organization or affiliation +
+
+ + Commitment to fair participation +
+
+ + Adherence to benchmark guidelines +
+
+
+ + {/* Model Validation Section */} +
+
+ +
+

Help Us Validate Model Implementations

+

+ Transparency is at the heart of our live benchmarking project. We have integrated a wide range of + state-of-the-art time series forecasting models to provide the community with real-time performance insights. +

+
+
+ +
+

+ To ensure that every model is evaluated under optimal conditions, we invite the original authors + and maintainers to review our implementations. If you are a developer of one of the featured models, + we would value your feedback on: +

+
    +
  • + β€’ + Model configuration and hyperparameters +
  • +
  • + β€’ + Data preprocessing steps +
  • +
  • + β€’ + Implementation-specific nuances +
  • +
+
+ +

+ Our goal is to represent your work as accurately as possible. Please visit our GitHub repository + to review the code or open an issue for any suggested improvements. +

+ + + + View on GitHub + +
+
+ ); +} diff --git a/src/app/api/v1/API_STRUCTURE.md b/src/app/api/v1/API_STRUCTURE.md new file mode 100644 index 0000000000000000000000000000000000000000..14c35cff7dd1a08aebe743281ed3b2914836979e --- /dev/null +++ b/src/app/api/v1/API_STRUCTURE.md @@ -0,0 +1,75 @@ +# API Structure Documentation +## Structure + +``` +/src/app/api/v1/ +β”œβ”€β”€ definitions/ +β”‚ β”œβ”€β”€ route.ts GET /api/v1/definitions +β”‚ └── [definitionId]/ +β”‚ └── rounds/ +β”‚ └── route.ts GET /api/v1/definitions/{id}/rounds +β”œβ”€β”€ rounds/ +β”‚ β”œβ”€β”€ route.ts GET /api/v1/rounds +β”‚ β”œβ”€β”€ metadata/ +β”‚ β”‚ └── route.ts GET /api/v1/rounds/metadata +β”‚ └── [roundId]/ +β”‚ β”œβ”€β”€ route.ts GET /api/v1/rounds/{id} +β”‚ β”œβ”€β”€ leaderboard/ +β”‚ β”‚ └── route.ts GET /api/v1/rounds/{id}/leaderboard +β”‚ β”œβ”€β”€ models/ +β”‚ β”‚ └── route.ts GET /api/v1/rounds/{id}/models +β”‚ └── series/ +β”‚ β”œβ”€β”€ route.ts GET /api/v1/rounds/{id}/series +β”‚ └── [seriesId]/ +β”‚ β”œβ”€β”€ data/ +β”‚ β”‚ └── route.ts GET /api/v1/rounds/{id}/series/{id}/data +β”‚ └── forecasts/ +β”‚ └── route.ts GET /api/v1/rounds/{id}/series/{id}/forecasts +└── models/ + β”œβ”€β”€ rankings/ + β”‚ └── route.ts GET /api/v1/models/rankings + β”œβ”€β”€ ranking-filters/ + β”‚ └── route.ts GET /api/v1/models/ranking-filters + └── [modelId]/ + β”œβ”€β”€ route.ts GET /api/v1/models/{id} + β”œβ”€β”€ rankings/ + β”‚ └── route.ts GET /api/v1/models/{id}/rankings + β”œβ”€β”€ series-by-definition/ + β”‚ └── route.ts GET /api/v1/models/{id}/series-by-definition + └── definitions/ + └── [definitionId]/ + └── series/ + └── [seriesId]/ + └── forecasts/ + └── route.ts GET /api/v1/models/{id}/definitions/{id}/series/{id}/forecasts +``` + +## Service Layer + +The service layer has been organized into three domain-specific files: + +### definitionService.ts +Handles challenge definition-related API calls: +- `getDefinitionRounds()` - Get rounds for a specific definition + +### roundService.ts +Handles round-related API calls: +- `getChallenges()` - List all rounds (previously called challenges) +- `getRoundsMetadata()` - Get filter metadata +- `getChallengeSeries()` - Get series for a round +- `getSeriesData()` - Get time series data +- `getSeriesForecasts()` - Get forecasts for a series +- `getRoundModels()` - Get models participating in a round + +### modelService.ts +Handles model-related API calls: +- `getFilteredRankings()` - Get model rankings with filters +- `getRankingFilters()` - Get available ranking filters +- `getModelDetails()` - Get model details +- `getModelRankings()` - Get model ranking history +- `getModelSeriesByDefinition()` - Get series grouped by definition +- `getModelSeriesForecasts()` - Get model forecasts across rounds + +## Authentication + +All API routes forward the `X-API-Key` header to the backend API for authentication. diff --git a/src/app/api/v1/definitions/[definitionId]/rounds/route.ts b/src/app/api/v1/definitions/[definitionId]/rounds/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..bc642ad6e8a7092a962044439b9baa5f0b5f896f --- /dev/null +++ b/src/app/api/v1/definitions/[definitionId]/rounds/route.ts @@ -0,0 +1,50 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ definitionId: string }> | { definitionId: string } } +) { + const resolvedParams = await Promise.resolve(params); + const { definitionId } = resolvedParams; + + if (!definitionId || definitionId === 'undefined') { + return NextResponse.json( + { error: 'Invalid definition ID' }, + { status: 400 } + ); + } + + // Forward query params to backend + const searchParams = request.nextUrl.searchParams; + const queryString = searchParams.toString(); + const url = `${API_BASE_URL}/api/v1/definitions/${definitionId}/rounds${queryString ? '?' + queryString : ''}`; + + console.log('Calling definition rounds API:', url); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch rounds for definition' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching rounds for definition:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/definitions/route.ts b/src/app/api/v1/definitions/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..db390226e8983f4ffb1fd5605798cabb9b1f30c1 --- /dev/null +++ b/src/app/api/v1/definitions/route.ts @@ -0,0 +1,35 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET() { + const url = `${API_BASE_URL}/api/v1/definitions`; + + console.log('Calling challenge definitions API:', url); + console.log('API_BASE_URL:', API_BASE_URL); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch challenge definitions' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching challenge definitions:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/models/[modelId]/definitions/[definitionId]/series/[seriesId]/forecasts/route.ts b/src/app/api/v1/models/[modelId]/definitions/[definitionId]/series/[seriesId]/forecasts/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..8a3724a8edffbf1cafc7d1b813fe86dc3605f962 --- /dev/null +++ b/src/app/api/v1/models/[modelId]/definitions/[definitionId]/series/[seriesId]/forecasts/route.ts @@ -0,0 +1,53 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ modelId: string; definitionId: string; seriesId: string }> } +) { + const { modelId, definitionId, seriesId } = await params; + + // Parse IDs as numbers for the external API + const modelIdNum = parseInt(modelId, 10); + const definitionIdNum = parseInt(definitionId, 10); + const seriesIdNum = parseInt(seriesId, 10); + + if (isNaN(modelIdNum) || isNaN(definitionIdNum) || isNaN(seriesIdNum)) { + return NextResponse.json({ error: 'Invalid model ID, definition ID, or series ID' }, { status: 400 }); + } + + // Get query parameters for date filtering + const searchParams = request.nextUrl.searchParams; + const startDate = searchParams.get('start_date'); + const endDate = searchParams.get('end_date'); + + // Build URL with query parameters + const urlParams = new URLSearchParams(); + if (startDate) urlParams.append('start_time', startDate); + if (endDate) urlParams.append('end_time', endDate); + + const queryString = urlParams.toString(); + const url = `${API_BASE_URL}/api/v1/models/${modelIdNum}/definitions/${definitionIdNum}/series/${seriesIdNum}/forecasts${queryString ? '?' + queryString : ''}`; + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + const data = await response.json(); + + if (!response.ok) { + console.error('API returned error:', data); + return NextResponse.json(data, { status: response.status }); + } + + return NextResponse.json(data); + } catch (error) { + console.error('Fetch error:', error); + return NextResponse.json({ error: 'Failed to fetch forecasts' }, { status: 500 }); + } +} diff --git a/src/app/api/v1/models/[modelId]/rankings/route.ts b/src/app/api/v1/models/[modelId]/rankings/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..499eaa095cf638602769f829869686787d792e59 --- /dev/null +++ b/src/app/api/v1/models/[modelId]/rankings/route.ts @@ -0,0 +1,43 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ modelId: string }> } +) { + const { modelId } = await params; + + + // Parse modelId as number for the external API + const modelIdNum = parseInt(modelId, 10); + + + if (isNaN(modelIdNum)) { + return NextResponse.json({ error: 'Invalid model ID' }, { status: 400 }); + } + + const url = `${API_BASE_URL}/api/v1/models/${modelIdNum}/rankings`; + + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + const data = await response.json(); + + if (!response.ok) { + console.error('API returned error:', data); + return NextResponse.json(data, { status: response.status }); + } + + return NextResponse.json(data); + } catch (error) { + console.error('Fetch error:', error); + return NextResponse.json({ error: 'Failed to fetch rankings' }, { status: 500 }); + } +} diff --git a/src/app/api/v1/models/[modelId]/route.ts b/src/app/api/v1/models/[modelId]/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..18761ea6b99ceaf275c5b955542ff043fd515376 --- /dev/null +++ b/src/app/api/v1/models/[modelId]/route.ts @@ -0,0 +1,40 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ modelId: string }> } +) { + const { modelId } = await params; + + // Parse modelId as number for the external API + const modelIdNum = parseInt(modelId, 10); + + if (isNaN(modelIdNum)) { + return NextResponse.json({ error: 'Invalid model ID' }, { status: 400 }); + } + + const url = `${API_BASE_URL}/api/v1/models/${modelIdNum}`; + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + const data = await response.json(); + + if (!response.ok) { + console.error('API returned error:', data); + return NextResponse.json(data, { status: response.status }); + } + + return NextResponse.json(data); + } catch (error) { + console.error('Fetch error:', error); + return NextResponse.json({ error: 'Failed to fetch model details' }, { status: 500 }); + } +} diff --git a/src/app/api/v1/models/[modelId]/series-by-definition/route.ts b/src/app/api/v1/models/[modelId]/series-by-definition/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..935316886c6d40933ec375bc20d398437942e869 --- /dev/null +++ b/src/app/api/v1/models/[modelId]/series-by-definition/route.ts @@ -0,0 +1,40 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ modelId: string }> } +) { + const { modelId } = await params; + + // Parse modelId as number for the external API + const modelIdNum = parseInt(modelId, 10); + + if (isNaN(modelIdNum)) { + return NextResponse.json({ error: 'Invalid model ID' }, { status: 400 }); + } + + const url = `${API_BASE_URL}/api/v1/models/${modelIdNum}/series-by-definition`; + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + const data = await response.json(); + + if (!response.ok) { + console.error('API returned error:', data); + return NextResponse.json(data, { status: response.status }); + } + + return NextResponse.json(data); + } catch (error) { + console.error('Fetch error:', error); + return NextResponse.json({ error: 'Failed to fetch series by definition' }, { status: 500 }); + } +} diff --git a/src/app/api/v1/models/ranking-filters/route.ts b/src/app/api/v1/models/ranking-filters/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..bc82838bad904c801ce09f51504e5c689f8a0008 --- /dev/null +++ b/src/app/api/v1/models/ranking-filters/route.ts @@ -0,0 +1,35 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET() { + const url = `${API_BASE_URL}/api/v1/models/ranking-filters`; + + console.log('Calling ranking filters API:', url); + console.log('API_BASE_URL:', API_BASE_URL); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch ranking filters' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching ranking filters:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/models/rankings/route.ts b/src/app/api/v1/models/rankings/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..4368f1023a28c1e2af894c16e04051581a103a14 --- /dev/null +++ b/src/app/api/v1/models/rankings/route.ts @@ -0,0 +1,28 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET(request: NextRequest) { + const searchParams = request.nextUrl.searchParams; + + const params = new URLSearchParams(); + searchParams.forEach((value, key) => { + params.append(key, value); + }); + + const url = `${API_BASE_URL}/api/v1/models/rankings${params.toString() ? '?' + params.toString() : ''}`; + + console.log('Calling external API:', url); + console.log('API_BASE_URL:', API_BASE_URL); + + // ToDo: Add error handling + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + const data = await response.json(); + return NextResponse.json(data); +} diff --git a/src/app/api/v1/rounds/[roundId]/leaderboard/route.ts b/src/app/api/v1/rounds/[roundId]/leaderboard/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..22338d4d4c276532c7ea597d73375282f21eafba --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/leaderboard/route.ts @@ -0,0 +1,47 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ roundId: string }> | { roundId: string } } +) { + const resolvedParams = await Promise.resolve(params); + const { roundId } = resolvedParams; + + if (!roundId || roundId === 'undefined') { + return NextResponse.json( + { error: 'Invalid round ID' }, + { status: 400 } + ); + } + + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}/leaderboard`; + + console.log('Calling round leaderboard API:', url); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch leaderboard' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching leaderboard:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/[roundId]/models/route.ts b/src/app/api/v1/rounds/[roundId]/models/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..7b3a574be67e893afbc90b6fc4282d588ccea971 --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/models/route.ts @@ -0,0 +1,47 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ roundId: string }> | { roundId: string } } +) { + const resolvedParams = await Promise.resolve(params); + const { roundId } = resolvedParams; + + if (!roundId || roundId === 'undefined') { + return NextResponse.json( + { error: 'Invalid round ID' }, + { status: 400 } + ); + } + + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}/models`; + + console.log('Calling round models API:', url); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch models for round' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching models for round:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/[roundId]/route.ts b/src/app/api/v1/rounds/[roundId]/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..e2273232e514e3320ffe5edbce58d9fca04a18ef --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/route.ts @@ -0,0 +1,47 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: NextRequest, + { params }: { params: Promise<{ roundId: string }> | { roundId: string } } +) { + const resolvedParams = await Promise.resolve(params); + const { roundId } = resolvedParams; + + if (!roundId || roundId === 'undefined') { + return NextResponse.json( + { error: 'Invalid round ID' }, + { status: 400 } + ); + } + + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}`; + + console.log('Calling round API:', url); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch round' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching round:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/[roundId]/series/[seriesId]/data/route.ts b/src/app/api/v1/rounds/[roundId]/series/[seriesId]/data/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..a594476466f61c2bb7d43eabf6be3bed03ea74f4 --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/series/[seriesId]/data/route.ts @@ -0,0 +1,59 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: Request, + { params }: { params: Promise<{ roundId: string; seriesId: string }> } +) { + const { roundId, seriesId } = await params; + const { searchParams } = new URL(request.url); + const startTime = searchParams.get('start_time'); + const endTime = searchParams.get('end_time'); + + console.log('Data API route - params:', { roundId, seriesId, startTime, endTime }); + + if (!startTime || !endTime) { + return NextResponse.json( + { error: 'start_time and end_time query parameters are required' }, + { status: 400 } + ); + } + + const queryParams = new URLSearchParams({ + start_time: startTime, + end_time: endTime, + }); + + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}/series/${seriesId}/data?${queryParams.toString()}`; + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + console.log('Data API response status:', response.status); + + if (!response.ok) { + const errorText = await response.text(); + console.error('Data API error response:', response.status, errorText); + return NextResponse.json( + { error: 'Failed to fetch series data', details: errorText, externalStatus: response.status }, + { status: response.status } + ); + } + + const data = await response.json(); + console.log('Data API success'); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching series data:', error); + return NextResponse.json( + { error: 'Internal server error', details: error instanceof Error ? error.message : String(error) }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/[roundId]/series/[seriesId]/forecasts/route.ts b/src/app/api/v1/rounds/[roundId]/series/[seriesId]/forecasts/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..69cb8159dde116965dde3be6a8adcc9faae9a5b6 --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/series/[seriesId]/forecasts/route.ts @@ -0,0 +1,43 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: Request, + { params }: { params: Promise<{ roundId: string; seriesId: string }> } +) { + const { roundId, seriesId } = await params; + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}/series/${seriesId}/forecasts`; + + console.log('Forecasts API route - params:', { roundId, seriesId }); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + console.log('Forecasts API response status:', response.status); + + if (!response.ok) { + const errorText = await response.text(); + console.error('Forecasts API error response:', response.status, errorText); + return NextResponse.json( + { error: 'Failed to fetch forecasts', details: errorText, externalStatus: response.status }, + { status: response.status } + ); + } + + const data = await response.json(); + console.log('Forecasts API success, data keys:', Object.keys(data)); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching forecasts:', error); + return NextResponse.json( + { error: 'Internal server error', details: error instanceof Error ? error.message : String(error) }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/[roundId]/series/route.ts b/src/app/api/v1/rounds/[roundId]/series/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..3341ca99279b09e0ab5b0d7c3d9447be52861182 --- /dev/null +++ b/src/app/api/v1/rounds/[roundId]/series/route.ts @@ -0,0 +1,38 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET( + request: Request, + { params }: { params: Promise<{ roundId: string }> } +) { + const { roundId } = await params; + const url = `${API_BASE_URL}/api/v1/rounds/${roundId}/series`; + + console.log('Calling external API:', url); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch round series' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching round series:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/metadata/route.ts b/src/app/api/v1/rounds/metadata/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..7b1ae197803721a6834dd95e106d0207aff39461 --- /dev/null +++ b/src/app/api/v1/rounds/metadata/route.ts @@ -0,0 +1,35 @@ +import { NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET() { + const url = `${API_BASE_URL}/api/v1/rounds/metadata`; + + console.log('Calling rounds metadata API:', url); + console.log('API_BASE_URL:', API_BASE_URL); + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch rounds metadata' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching rounds metadata:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/api/v1/rounds/route.ts b/src/app/api/v1/rounds/route.ts new file mode 100644 index 0000000000000000000000000000000000000000..43cd4d38292928317e846b0c57c0fe85531c3a27 --- /dev/null +++ b/src/app/api/v1/rounds/route.ts @@ -0,0 +1,57 @@ +import { NextRequest, NextResponse } from 'next/server'; + +const API_BASE_URL = process.env.NEXT_PUBLIC_DASH_BOARD_API_URL || ''; +const API_KEY = process.env.NEXT_PUBLIC_DASH_BOARD_API_KEY || ''; + +export async function GET(request: NextRequest) { + const searchParams = request.nextUrl.searchParams; + + // Build query parameters from the request + const queryParams = new URLSearchParams(); + + // Add filter parameters if they exist + const domains = searchParams.getAll('domain'); + const categories = searchParams.getAll('category'); + const frequencies = searchParams.getAll('frequency'); + const horizons = searchParams.getAll('horizon'); + const from = searchParams.get('from'); + const to = searchParams.get('to'); + const status = searchParams.get('status'); + const searchTerm = searchParams.get('search'); + + domains.forEach(d => queryParams.append('domain', d)); + categories.forEach(c => queryParams.append('category', c)); + frequencies.forEach(f => queryParams.append('frequency', f)); + horizons.forEach(h => queryParams.append('horizon', h)); + if (from) queryParams.append('from', from); + if (to) queryParams.append('to', to); + if (status && status !== 'all') queryParams.append('status', status); + if (searchTerm) queryParams.append('search', searchTerm); + + const queryString = queryParams.toString(); + const url = `${API_BASE_URL}/api/v1/rounds${queryString ? '?' + queryString : ''}`; + + try { + const response = await fetch(url, { + headers: { + 'X-API-Key': API_KEY, + } + }); + + if (!response.ok) { + return NextResponse.json( + { error: 'Failed to fetch rounds' }, + { status: response.status } + ); + } + + const data = await response.json(); + return NextResponse.json(data); + } catch (error) { + console.error('Error fetching rounds:', error); + return NextResponse.json( + { error: 'Internal server error' }, + { status: 500 } + ); + } +} diff --git a/src/app/challenges/[challengeId]/[roundId]/page.tsx b/src/app/challenges/[challengeId]/[roundId]/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..19607ec7c82518cbdef38727190f9faf6e4de65f --- /dev/null +++ b/src/app/challenges/[challengeId]/[roundId]/page.tsx @@ -0,0 +1,455 @@ +'use client'; + +import { useState, useEffect } from 'react'; +import { useParams, useRouter } from 'next/navigation'; +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import TimeSeriesChart from '@/src/components/TimeSeriesChart'; +import Link from 'next/link'; +import { Clock, ChevronRight, Info } from 'lucide-react'; + +interface RoundMetadata { + round_id: number; + name: string; + description: string; + status: string; + context_length: number; + horizon: string; + start_time: string; + end_time: string; + registration_start: string; + registration_end: string; + frequency?: string; +} + +interface LeaderboardEntry { + model_id: number; + readable_id: string; + model_name: string; + series_id: number; + series_name: string; + forecast_count: number; + mase: number | null; + rmse: number | null; + is_final: boolean; + rank: number; +} + +interface ModelRow { + model_id: number; + readable_id: string; + model_name: string; + seriesRanks: Record; + avgRank: number; +} + +export default function RoundDetail() { + const params = useParams(); + const router = useRouter(); + const challengeId = params.challengeId; + const [round, setRound] = useState(null); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + const [leaderboard, setLeaderboard] = useState([]); + const [leaderboardLoading, setLeaderboardLoading] = useState(false); + const [leaderboardPage, setLeaderboardPage] = useState(1); + const MODELS_PER_PAGE = 10; + + useEffect(() => { + const fetchRound = async () => { + // Handle params.roundId which can be string | string[] | undefined + const roundIdParam = params.roundId; + if (!roundIdParam) { + setError('Invalid round ID: undefined'); + setLoading(false); + return; + } + + const roundId = Array.isArray(roundIdParam) ? roundIdParam[0] : roundIdParam; + + try { + setLoading(true); + setError(null); + + // Fetch the round data using the rounds endpoint + const response = await fetch(`/api/v1/rounds/${roundId}`); + + if (!response.ok) { + throw new Error('Failed to fetch round data'); + } + + const data: RoundMetadata = await response.json(); + setRound(data); + } catch (err) { + setError(err instanceof Error ? err.message : 'An error occurred'); + console.error('Error fetching round:', err); + } finally { + setLoading(false); + } + }; + + fetchRound(); + }, [params.roundId]); + + // Fetch leaderboard data + useEffect(() => { + const fetchLeaderboard = async () => { + const roundIdParam = params.roundId; + if (!roundIdParam) return; + + const roundId = Array.isArray(roundIdParam) ? roundIdParam[0] : roundIdParam; + + try { + setLeaderboardLoading(true); + const response = await fetch(`/api/v1/rounds/${roundId}/leaderboard`); + + if (!response.ok) { + console.error('Failed to fetch leaderboard'); + return; + } + + const data: LeaderboardEntry[] = await response.json(); + setLeaderboard(data); + } catch (err) { + console.error('Error fetching leaderboard:', err); + } finally { + setLeaderboardLoading(false); + } + }; + + fetchLeaderboard(); + }, [params.roundId]); + + if (loading) { + return ( +
+
+
+
+
+
+
+ ); + } + + if (error || !round) { + return ( +
+
+
+

Error

+

{error || 'Round not found'}

+
+ +
+
+ ); + } + + return ( +
+
+ + +
+
+
+

+ {round.name || `Round ${params.roundId}`} +

+ {round.description && ( +

{round.description}

+ )} +
+ {round.status && ( + + {round.status.charAt(0).toUpperCase() + round.status.slice(1)} + + )} +
+
+ + {/* Registration Banner */} + {round.status === 'registration' && ( + +
+ +
+

+ Registration is open β€” submit your forecasts by{' '} + + {round.registration_end + ? new Date(round.registration_end).toLocaleDateString('en-US', { + weekday: 'long', + year: 'numeric', + month: 'long', + day: 'numeric', + hour: '2-digit', + minute: '2-digit' + }) + : 'the registration deadline'} + +

+
+ +
+ + )} + + {/* Leaderboard Section */} +
+
+

Round Leaderboard

+

Model rankings per series based on MASE score

+
+ + {round.status === 'registration' ? ( +
+ +

No leaderboard data available yet

+

The leaderboard will be available once the round begins.

+
+ ) : leaderboardLoading ? ( +
+
+ Loading leaderboard... +
+ ) : leaderboard.length > 0 ? ( + (() => { + // Get unique series IDs and build a map of series_id to series_name + const seriesIds = [...new Set(leaderboard.map(entry => entry.series_id))].sort((a, b) => a - b); + const seriesNameMap = new Map(); + leaderboard.forEach(entry => { + if (!seriesNameMap.has(entry.series_id)) { + seriesNameMap.set(entry.series_id, entry.series_name); + } + }); + + // Group data by model + const modelMap = new Map(); + leaderboard.forEach(entry => { + if (!modelMap.has(entry.model_id)) { + modelMap.set(entry.model_id, { + model_id: entry.model_id, + readable_id: entry.readable_id, + model_name: entry.model_name, + seriesRanks: {}, + avgRank: 0 + }); + } + const model = modelMap.get(entry.model_id)!; + model.seriesRanks[entry.series_id] = { rank: entry.rank, mase: entry.mase }; + }); + + // Calculate average rank and sort + const modelRows = Array.from(modelMap.values()).map(model => { + const ranks = Object.values(model.seriesRanks).map(r => r.rank); + model.avgRank = ranks.length > 0 ? ranks.reduce((sum, r) => sum + r, 0) / ranks.length : Infinity; + return model; + }).sort((a, b) => a.avgRank - b.avgRank); + + // Pagination + const totalModels = modelRows.length; + const totalPages = Math.ceil(totalModels / MODELS_PER_PAGE); + const startIndex = (leaderboardPage - 1) * MODELS_PER_PAGE; + const paginatedModels = modelRows.slice(startIndex, startIndex + MODELS_PER_PAGE); + + return ( +
+
+ + + + + + {seriesIds.map(seriesId => ( + + ))} + + + + {paginatedModels.map((model) => ( + + + + {seriesIds.map(seriesId => { + const rankData = model.seriesRanks[seriesId]; + if (!rankData) { + return ( + + ); + } + return ( + + ); + })} + + ))} + +
+ Model + + Avg Rank + +
+ {(seriesNameMap.get(seriesId) || `Series ${seriesId}`).replace(/[_-]/g, ' ')} +
+
+ + {model.model_name} + +

{model.readable_id}

+
+ {model.avgRank.toFixed(2)} + + - + + + {rankData.rank} + +
+
+ + {/* Pagination Controls */} + {totalPages > 1 && ( +
+
+ Showing {startIndex + 1} to {Math.min(startIndex + MODELS_PER_PAGE, totalModels)} of {totalModels} models +
+
+ + +
+ {Array.from({ length: totalPages }, (_, i) => i + 1).map((page) => { + const showPage = + page === 1 || + page === totalPages || + (page >= leaderboardPage - 1 && page <= leaderboardPage + 1); + + const showEllipsis = + (page === 2 && leaderboardPage > 3) || + (page === totalPages - 1 && leaderboardPage < totalPages - 2); + + if (!showPage && !showEllipsis) return null; + + if (showEllipsis) { + return ( + + ... + + ); + } + + return ( + + ); + })} +
+ + +
+
+ )} +
+ ); + })() + ) : ( +
+ No leaderboard data available for this round +
+ )} +
+ + {/* Time Series Chart Section */} + {round.status === 'registration' ? ( +
+
+

Time Series Data

+
+
+ +

Series data not yet available

+

The time series will be revealed once the round starts.

+
+
+ ) : ( + + )} +
+
+ ); +} diff --git a/src/app/challenges/[challengeId]/page.tsx b/src/app/challenges/[challengeId]/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..dbd49a713e01633e2398e776726e23104a03b9c2 --- /dev/null +++ b/src/app/challenges/[challengeId]/page.tsx @@ -0,0 +1,750 @@ +'use client'; + +import { useState, useEffect, useMemo, useCallback } from 'react'; +import { useParams, useRouter } from 'next/navigation'; +import { Info } from 'lucide-react'; +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import RankingsTable from '@/src/components/RankingsTable'; +import type { ChallengeDefinition, DefinitionRound, PaginationInfo } from '@/src/types/challenge'; +import { getFilteredRankings, type RankingsResponse } from '@/src/services/modelService'; +import { getDefinitionRounds } from '@/src/services/definitionService'; +import Link from 'next/link'; +import { ChevronDown, ChevronRight } from 'lucide-react'; + +export default function ChallengeDefinitionDetail() { + const params = useParams(); + const router = useRouter(); + const [definition, setDefinition] = useState(null); + const [rankings, setRankings] = useState(null); + const [selectedCalculationDate, setSelectedCalculationDate] = useState( + new Date().toISOString().split('T')[0] + ); + const [loading, setLoading] = useState(true); + const [rankingsLoading, setRankingsLoading] = useState(false); + const [rankingsPage, setRankingsPage] = useState(1); + const [roundsData, setRoundsData] = useState>({}); + const [roundsLoading, setRoundsLoading] = useState>({}); + const [expandedStatuses, setExpandedStatuses] = useState>({ + active: true, + registration: true, + completed: false, + cancelled: false, + }); + const [error, setError] = useState(null); + + const ROUNDS_PER_PAGE = 10; + const STATUSES = ['active', 'registration', 'completed', 'cancelled']; + + useEffect(() => { + const fetchDefinition = async () => { + try { + setLoading(true); + const response = await fetch('/api/v1/definitions'); + + if (!response.ok) { + throw new Error('Failed to fetch challenge definitions'); + } + + const data: ChallengeDefinition[] = await response.json(); + const found = data.find(d => d.id === Number(params.challengeId)); + + if (!found) { + setError('Challenge definition not found'); + } else { + setDefinition(found); + } + } catch (err) { + setError(err instanceof Error ? err.message : 'An error occurred'); + console.error('Error fetching challenge definition:', err); + } finally { + setLoading(false); + } + }; + + if (params.challengeId) { + fetchDefinition(); + } + }, [params.challengeId]); + + // Fetch rankings for the definition + useEffect(() => { + const fetchRankings = async () => { + if (!definition || !definition.id) return; + + try { + setRankingsLoading(true); + const filters: any = { + definition_id: definition.id, + limit: 100 + }; + if (selectedCalculationDate) { + filters.calculation_date = selectedCalculationDate; + } + const rankingsData = await getFilteredRankings(filters); + setRankings(rankingsData); + } catch (err) { + console.error('Error fetching rankings:', err); + } finally { + setRankingsLoading(false); + } + }; + + fetchRankings(); + }, [definition, selectedCalculationDate]); + + // Reset to page 1 when calculation date changes + useEffect(() => { + setRankingsPage(1); + }, [selectedCalculationDate]); + + // Fetch rounds for the definition (per status with pagination) + const fetchRoundsForStatus = useCallback(async (status: string, page: number = 1) => { + if (!definition || !definition.id) return; + + const ROUNDS_PER_PAGE = 10; + + try { + setRoundsLoading(prev => ({ ...prev, [status]: true })); + const response = await getDefinitionRounds(definition.id, { + page, + pageSize: ROUNDS_PER_PAGE, + status, + }); + setRoundsData(prev => ({ + ...prev, + [status]: { + rounds: response.items, + pagination: response.pagination, + }, + })); + } catch (err) { + console.error(`Error fetching ${status} rounds:`, err); + } finally { + setRoundsLoading(prev => ({ ...prev, [status]: false })); + } + }, [definition]); + + // Initial fetch of rounds for all statuses + useEffect(() => { + if (!definition || !definition.id) return; + + STATUSES.forEach(status => { + fetchRoundsForStatus(status, 1); + }); + }, [definition, fetchRoundsForStatus]); + + const handlePageChange = (status: string, page: number) => { + fetchRoundsForStatus(status, page); + }; + + // Rankings pagination calculations + const RANKINGS_PER_PAGE = 10; + const totalRankings = rankings?.rankings.length || 0; + const totalRankingsPages = Math.ceil(totalRankings / RANKINGS_PER_PAGE); + const startRankingIndex = (rankingsPage - 1) * RANKINGS_PER_PAGE; + const endRankingIndex = startRankingIndex + RANKINGS_PER_PAGE; + const paginatedRankings = rankings?.rankings.slice(startRankingIndex, endRankingIndex) || []; + + const toggleStatus = (status: string) => { + setExpandedStatuses(prev => ({ + ...prev, + [status]: !prev[status] + })); + }; + + const getStatusConfig = (status: string) => { + const configs: Record = { + registration: { + label: 'Registration', + color: 'text-yellow-800', + bgColor: 'bg-yellow-50', + borderColor: 'border-yellow-200' + }, + active: { + label: 'Active', + color: 'text-green-800', + bgColor: 'bg-green-50', + borderColor: 'border-green-200' + }, + completed: { + label: 'Completed', + color: 'text-blue-800', + bgColor: 'bg-blue-50', + borderColor: 'border-blue-200' + }, + cancelled: { + label: 'Cancelled', + color: 'text-gray-800', + bgColor: 'bg-gray-50', + borderColor: 'border-gray-200' + } + }; + return configs[status] || { + label: status.charAt(0).toUpperCase() + status.slice(1), + color: 'text-gray-800', + bgColor: 'bg-gray-50', + borderColor: 'border-gray-200' + }; + }; + + // Get statuses that have data + const statusesWithData = useMemo(() => { + return STATUSES.filter(status => { + const data = roundsData[status]; + return data && data.pagination && data.pagination.total_items > 0; + }); + }, [roundsData]); + + if (loading) { + return ( +
+
+
Loading challenge definition...
+
+
+ ); + } + + if (error || !definition) { + return ( +
+
+

Error

+

{error || 'Challenge definition not found'}

+
+ +
+ ); + } + + return ( +
+ + +
+
+
+
+

{definition.name}

+

ID: {definition.id}

+
+
+
+ +
+
+
+

Description

+

{definition.description}

+
+ +
+
+

Schedule Information

+
+
+
Schedule ID
+
+ {definition.schedule_id} +
+
+
+
Frequency
+
+ {definition.frequency} +
+
+
+
Horizon
+
+ {definition.horizon} +
+
+ {(definition.next_registration_start || definition.next_registration_end) && ( +
+
Next Registration Period
+ {definition.next_registration_start && ( +
+ Opens:{' '} + + {new Date(definition.next_registration_start).toLocaleDateString('en-US', { + weekday: 'short', + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit' + })} + +
+ )} + {definition.next_registration_end && ( +
+ Closes:{' '} + + {new Date(definition.next_registration_end).toLocaleDateString('en-US', { + weekday: 'short', + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit' + })} + +
+ )} +
+ )} +
+
+ +
+

Configuration

+
+
+
Context Length
+
+ {definition.context_length} +
+
+ {definition.domain && ( +
+
Domain
+
+ {definition.domain} +
+
+ )} + {definition.subdomain && ( +
+
Subdomain
+
+ {definition.subdomain} +
+
+ )} +
+
+
+
+
+
+ + {/* Rankings Section */} + {definition && ( +
+
+

Model Rankings

+ + {/* Calculation Date Filter */} +
+ +
+ +
+
Calculation Date
+
+ Sets the cutoff date for model evaluation. Use this to view rankings as they appeared on a specific date. All models are ranked based on their performance up to this date. +
+
+
+ setSelectedCalculationDate(e.target.value)} + className="px-2 py-1 text-xs bg-white border border-gray-200 rounded text-gray-600 hover:border-gray-300 focus:outline-none focus:border-blue-400 focus:ring-1 focus:ring-blue-400" + /> +
+
+ + {rankingsLoading ? ( +
+ Loading rankings... +
+ ) : rankings && rankings.rankings.length > 0 ? ( + <> + + + {/* Rankings Pagination */} + {totalRankingsPages > 1 && ( +
+
+ Showing {startRankingIndex + 1} to {Math.min(endRankingIndex, totalRankings)} of {totalRankings} models +
+
+ + +
+ {Array.from({ length: totalRankingsPages }, (_, i) => i + 1).map((page) => { + const showPage = + page === 1 || + page === totalRankingsPages || + (page >= rankingsPage - 1 && page <= rankingsPage + 1); + + const showEllipsis = + (page === 2 && rankingsPage > 3) || + (page === totalRankingsPages - 1 && rankingsPage < totalRankingsPages - 2); + + if (!showPage && !showEllipsis) return null; + + if (showEllipsis) { + return ( + + ... + + ); + } + + return ( + + ); + })} +
+ + +
+
+ )} + + ) : ( +
+ No rankings available +
+ )} +
+ )} + + {/* Rounds Section */} + {definition && ( +
+
+

Challenge Rounds

+

+ All rounds associated with this challenge definition, grouped by status +

+
+ +
+ {STATUSES.map((status) => { + const statusData = roundsData[status]; + const config = getStatusConfig(status); + const isExpanded = expandedStatuses[status]; + const isLoading = roundsLoading[status]; + const rounds = statusData?.rounds || []; + const pagination = statusData?.pagination; + const totalRounds = pagination?.total_items || 0; + const currentPage = pagination?.page || 1; + const totalPages = pagination?.total_pages || 1; + + return ( +
+ {/* Status Header */} + + + {/* Expandable Content */} + {isExpanded && ( +
+ {isLoading ? ( +
+
+
+ Loading rounds... +
+
+ ) : totalRounds === 0 ? ( +
+ No rounds available for this status +
+ ) : ( + <> + + + + + + + + + + + + + + + + + + {rounds.map((round, roundIndex) => { + return ( + + + + + + + + + + + + + + )})} + +
+ Name + + Description + + Registration + + Start Time + + End Time + + Context Length + + Frequency + + Horizon + + Domains + + Categories + + Subcategories +
+ + {round.name} + + + {round.description} + +
{new Date(round.registration_start).toLocaleDateString('en-US', { + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit', + })}
+
to
+
{new Date(round.registration_end).toLocaleDateString('en-US', { + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit', + })}
+
+ {new Date(round.start_time).toLocaleDateString('en-US', { + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit', + })} + + {new Date(round.end_time).toLocaleDateString('en-US', { + year: 'numeric', + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit', + })} + + {round.context_length} + + {round.frequency} + + {round.horizon} + +
+ {round.domains && round.domains.length > 0 ? ( + round.domains.map((domain, idx) => ( + + {domain} + + )) + ) : ( + - + )} +
+
+
+ {round.categories && round.categories.length > 0 ? ( + round.categories.map((category, idx) => ( + + {category} + + )) + ) : ( + - + )} +
+
+
+ {round.subcategories && round.subcategories.length > 0 ? ( + round.subcategories.map((subcategory, idx) => ( + + {subcategory} + + )) + ) : ( + - + )} +
+
+ + {/* Pagination Controls */} + {totalPages > 1 && ( +
+
+ Showing {((currentPage - 1) * ROUNDS_PER_PAGE) + 1} to {Math.min(currentPage * ROUNDS_PER_PAGE, totalRounds)} of {totalRounds} rounds +
+
+ + +
+ {Array.from({ length: totalPages }, (_, i) => i + 1).map((page) => { + const showPage = + page === 1 || + page === totalPages || + (page >= currentPage - 1 && page <= currentPage + 1); + + const showEllipsis = + (page === 2 && currentPage > 3) || + (page === totalPages - 1 && currentPage < totalPages - 2); + + if (!showPage && !showEllipsis) return null; + + if (showEllipsis) { + return ( + + ... + + ); + } + + return ( + + ); + })} +
+ + +
+
+ )} + + )} +
+ )} +
+ ); + })} +
+
+ )} +
+ ); +} diff --git a/src/app/challenges/page.tsx b/src/app/challenges/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..0cde416bfd0801baadf3d894d1c8ecf4e29507d5 --- /dev/null +++ b/src/app/challenges/page.tsx @@ -0,0 +1,254 @@ +'use client'; + +import { useState, useEffect, useMemo } from 'react'; +import Link from 'next/link'; +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import type { ChallengeDefinition } from '@/src/types/challenge'; + +type GroupByOption = 'none' | 'frequency' | 'horizon' | 'domain' | 'subdomain'; + + +export default function ChallengeDefinitions() { + const [definitions, setDefinitions] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + const [groupBy, setGroupBy] = useState('none'); + + useEffect(() => { + const fetchDefinitions = async () => { + try { + setLoading(true); + const response = await fetch('/api/v1/definitions'); + + if (!response.ok) { + throw new Error('Failed to fetch challenges'); + } + + const data = await response.json(); + setDefinitions(data); + } catch (err) { + setError(err instanceof Error ? err.message : 'An error occurred'); + console.error('Error fetching challenges:', err); + } finally { + setLoading(false); + } + }; + + fetchDefinitions(); + }, []); + + const groupedDefinitions = useMemo(() => { + if (groupBy === 'none') { + return { 'All Challenges': [...definitions] }; + } + + const groups: Record = {}; + + definitions.forEach((def) => { + let key: string; + + switch (groupBy) { + case 'frequency': + key = def.frequency || 'No Frequency'; + break; + case 'horizon': + key = def.horizon || 'No Horizon'; + break; + case 'domain': + key = def.domain || 'No Domain'; + break; + case 'subdomain': + key = def.subdomain || 'No Subdomain'; + break; + default: + key = 'Other'; + } + + if (!groups[key]) { + groups[key] = []; + } + groups[key].push(def); + }); + + // Sort groups so "No X" entries appear last + const sortedGroups: Record = {}; + const sortedKeys = Object.keys(groups).sort((a, b) => { + const aIsNo = a.startsWith('No '); + const bIsNo = b.startsWith('No '); + + if (aIsNo && !bIsNo) return 1; + if (!aIsNo && bIsNo) return -1; + return a.localeCompare(b); + }); + + sortedKeys.forEach(key => { + sortedGroups[key] = groups[key]; + }); + + return sortedGroups; + }, [definitions, groupBy]); + + if (loading) { + return ( +
+
+
Loading challenges...
+
+
+ ); + } + + if (error) { + return ( +
+
+

Error loading challenges

+

{error}

+
+
+ ); + } + + return ( +
+ +
+

Challenges

+

+ Available challenges and their configurations +

+
+ +
+ + +
+ +
+ {Object.entries(groupedDefinitions).map(([groupName, groupDefs]) => ( +
+ {groupBy !== 'none' && ( +

+ {groupName} + + ({groupDefs.length} {groupDefs.length === 1 ? 'challenge' : 'challenges'}) + +

+ )} + +
+ {groupDefs.map((definition) => ( + +
+
+

+ {definition.name} +

+
+ +

{definition.description}

+ +
+ +
+ Frequency: + + {definition.frequency} + +
+ +
+ Horizon: + + {definition.horizon} + +
+ +
+ Context Length: + + {definition.context_length} + +
+ + {definition.domain && ( +
+ Domain: + + {definition.domain} + +
+ )} + + {definition.subdomain && ( +
+ Subdomain: + + {definition.subdomain} + +
+ )} + + {(definition.next_registration_start || definition.next_registration_end) && ( +
+
Next Registration:
+ {definition.next_registration_start && ( +
+ Opens: {new Date(definition.next_registration_start).toLocaleDateString('en-US', { + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit' + })} +
+ )} + {definition.next_registration_end && ( +
+ Closes: {new Date(definition.next_registration_end).toLocaleDateString('en-US', { + month: 'short', + day: 'numeric', + hour: '2-digit', + minute: '2-digit' + })} +
+ )} +
+ )} +
+
+ +
+ ID: {definition.id} +
+ + ))} +
+
+ ))} +
+ + {definitions.length === 0 && ( +
+

No challenges available

+
+ )} +
+ ); +} diff --git a/src/app/globals.css b/src/app/globals.css new file mode 100644 index 0000000000000000000000000000000000000000..010bcdc9fc199f1636dbf89dcd470a5d5148a9e4 --- /dev/null +++ b/src/app/globals.css @@ -0,0 +1,31 @@ +@import "tailwindcss"; + +:root { + --background: #ffffff; + --foreground: #171717; +} + +@theme inline { + --color-background: var(--background); + --color-foreground: var(--foreground); + --font-sans: var(--font-geist-sans); + --font-mono: var(--font-geist-mono); +} + +@media (prefers-color-scheme: dark) { + :root { + --background: #0a0a0a; + --foreground: #ededed; + } +} + +body { + background: var(--background); + color: var(--foreground); + font-family: Arial, Helvetica, sans-serif; + overflow-x: hidden; +} + +html { + overflow-x: hidden; +} diff --git a/src/app/layout.tsx b/src/app/layout.tsx new file mode 100644 index 0000000000000000000000000000000000000000..54bfba8bc58155a61eb91e01f806fb4767ab8b4b --- /dev/null +++ b/src/app/layout.tsx @@ -0,0 +1,40 @@ +import type { Metadata } from "next"; +import { Geist, Geist_Mono } from "next/font/google"; +import "./globals.css"; +import Navigation from "@/src/components/Navigation"; + +const geistSans = Geist({ + variable: "--font-geist-sans", + subsets: ["latin"], +}); + +const geistMono = Geist_Mono({ + variable: "--font-geist-mono", + subsets: ["latin"], +}); + +export const metadata: Metadata = { + title: "TS-Arena", + description: "Time Series Forecasting Arena - Browse challenges and visualize time series data", + // TODO: Change icon + icons: { + icon: '/file.svg', + }, +}; + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + + + {children} + + + ); +} diff --git a/src/app/models/[modelId]/page.tsx b/src/app/models/[modelId]/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..0cb9856ad31c7054de0746e4cabe2e92255a296d --- /dev/null +++ b/src/app/models/[modelId]/page.tsx @@ -0,0 +1,161 @@ +'use client'; + +import { useState, useEffect } from 'react'; +import { useParams } from 'next/navigation'; +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import ModelPerformanceCharts from '@/src/components/ModelPerformanceCharts'; +import ModelSeriesList from '@/src/components/ModelSeriesList'; +import { getModelRankings, ModelDetailRankings, getModelSeriesByDefinition, ModelSeriesByDefinition, getModelDetails, ModelDetails } from '@/src/services/modelService'; + +export default function ModelDetailPage() { + const params = useParams(); + const modelId = params.modelId as string; + + const [modelDetails, setModelDetails] = useState(null); + const [rankingsData, setRankingsData] = useState(null); + const [seriesData, setSeriesData] = useState(null); + const [loading, setLoading] = useState(true); + + useEffect(() => { + if (!modelId) { + setLoading(false); + return; + } + + const fetchData = async () => { + setLoading(true); + try { + const [details, rankings, series] = await Promise.all([ + getModelDetails(modelId), + getModelRankings(modelId), + getModelSeriesByDefinition(modelId) + ]); + setModelDetails(details); + setRankingsData(rankings); + setSeriesData(series); + } catch (error) { + console.error('Error fetching model data:', error); + } finally { + setLoading(false); + } + }; + + fetchData(); + }, [modelId]); + + return ( +
+
+ + +
+

Model Details

+ + {loading ? ( +
+
Loading model details...
+
+ ) : modelDetails ? ( +
+
+ +
{modelDetails.name}
+
+ +
+ +
{modelDetails.readable_id}
+
+ +
+ +
{modelDetails.model_family}
+
+ +
+ +
{modelDetails.model_size.toLocaleString()} parameters
+
+ +
+ +
{modelDetails.hosting}
+
+ +
+ +
{modelDetails.architecture}
+
+ +
+ +
{modelDetails.pretraining_data}
+
+ +
+ +
+ {new Date(modelDetails.publishing_date).toLocaleDateString()} +
+
+
+ ) : ( +
+
Failed to load model details.
+
+ )} +
+ +
+

Performance by Challenge

+ {loading ? ( +
+
Loading rankings...
+
+ ) : rankingsData ? ( + + ) : ( +
+
Failed to load rankings data.
+
+ )} +
+ +
+ {loading ? ( +
+
Loading series data...
+
+ ) : seriesData ? ( + + ) : ( +
+
Failed to load series data.
+
+ )} +
+
+
+ ); +} diff --git a/src/app/page.tsx b/src/app/page.tsx new file mode 100644 index 0000000000000000000000000000000000000000..7dfdad67a375338f96d9bbc75cc1d3711e31a935 --- /dev/null +++ b/src/app/page.tsx @@ -0,0 +1,272 @@ +'use client'; + +import { useState, useEffect } from 'react'; +import { Info } from 'lucide-react'; +import Breadcrumbs from '@/src/components/Breadcrumbs'; +import RankingsTable from '@/src/components/RankingsTable'; +import TimeSeriesChart from '@/src/components/TimeSeriesChart'; +import { getFilteredRankings, getRankingFilters, ModelRanking, FilterOptions, ChallengeDefinition } from '@/src/services/modelService'; +import { getDefinitionRounds } from '@/src/services/definitionService'; + +const DEFINITION_ID = 226; +const SERIES_ID = 1371; + +interface RankingsData { + overall: ModelRanking[]; + byDefinition: Record; + byFrequencyHorizon: Record; +} + +export default function Home() { + const [filterOptions, setFilterOptions] = useState({ + definitions: [], + frequency_horizons: [], + }); + const [rankingsData, setRankingsData] = useState({ + overall: [], + byDefinition: {}, + byFrequencyHorizon: {}, + }); + const [selectedCalculationDate, setSelectedCalculationDate] = useState( + new Date().toISOString().split('T')[0] + ); + const [loading, setLoading] = useState(true); + const [isMounted, setIsMounted] = useState(false); + const [oldestActiveRound, setOldestActiveRound] = useState(null); + const [roundLoading, setRoundLoading] = useState(true); + + // Format frequency_horizon for display (e.g., "00:15:00::1 day" -> "15min / 1 day") + const formatFrequencyHorizon = (fh: string) => { + const parts = fh.split('::'); + if (parts.length !== 2) return fh; + + const [freq, horizon] = parts; + const freqMatch = freq.match(/(\d+):(\d+):(\d+)/); + let freqStr = freq; + if (freqMatch) { + const hours = parseInt(freqMatch[1]); + const mins = parseInt(freqMatch[2]); + if (hours > 0) { + freqStr = `${hours}h`; + } else if (mins > 0) { + freqStr = `${mins}min`; + } + } + + return `${freqStr} / ${horizon}`; + }; + + useEffect(() => { + setIsMounted(true); + return () => setIsMounted(false); + }, []); + + // Fetch oldest active round for definition 226 + useEffect(() => { + const fetchOldestActiveRound = async () => { + try { + setRoundLoading(true); + const response = await getDefinitionRounds(DEFINITION_ID, { status: 'active' }); + + if (response.items && response.items.length > 0) { + // Sort by start_time to get the oldest + const sorted = [...response.items].sort((a, b) => + new Date(a.start_time).getTime() - new Date(b.start_time).getTime() + ); + setOldestActiveRound(sorted[0]); + } + } catch (error) { + console.error('Error fetching active rounds:', error); + } finally { + setRoundLoading(false); + } + }; + + fetchOldestActiveRound(); + }, []); + + useEffect(() => { + if (!isMounted) return; + + const fetchAllData = async () => { + try { + setLoading(true); + + // First fetch filter options + const options = await getRankingFilters(); + setFilterOptions(options); + + // Build base filters + const baseFilters: any = { limit: 100 }; + if (selectedCalculationDate) { + baseFilters.calculation_date = selectedCalculationDate; + } + + // Fetch overall rankings (no definition/frequency filters) + const overallResponse = await getFilteredRankings(baseFilters); + + // Fetch rankings for each definition (limit concurrency) + const byDefinitionPromises = options.definitions.map(async (def: ChallengeDefinition) => { + const response = await getFilteredRankings({ + ...baseFilters, + definition_id: def.id, + }); + return { id: def.id, rankings: response.rankings }; + }); + + // Fetch rankings for each frequency/horizon (limit concurrency) + const byFrequencyHorizonPromises = options.frequency_horizons.map(async (fh: string) => { + const response = await getFilteredRankings({ + ...baseFilters, + frequency_horizon: fh, + }); + return { fh, rankings: response.rankings }; + }); + + // Process in batches to avoid overwhelming the browser + const definitionResults = await Promise.all(byDefinitionPromises); + const frequencyHorizonResults = await Promise.all(byFrequencyHorizonPromises); + + const byDefinition: Record = {}; + definitionResults.forEach(({ id, rankings }) => { + byDefinition[id] = rankings; + }); + + const byFrequencyHorizon: Record = {}; + frequencyHorizonResults.forEach(({ fh, rankings }) => { + byFrequencyHorizon[fh] = rankings; + }); + + setRankingsData({ + overall: overallResponse.rankings, + byDefinition, + byFrequencyHorizon, + }); + } catch (error) { + console.error('Error fetching rankings:', error); + } finally { + setLoading(false); + } + }; + + fetchAllData(); + }, [selectedCalculationDate, isMounted]); + + if (loading) { + return ( +
+
+ +

+ TS-Arena Model Rankings +

+
+
Loading rankings...
+
+
+
+ ); + } + + return ( +
+
+ +
+

+ TS-Arena Model Rankings +

+
+ + {/* Time Series Chart Section */} + {roundLoading ? ( +
+
+
+ Loading time series data... +
+
+ ) : oldestActiveRound ? ( +
+ +
+ ) : ( +
+

No active rounds available at the moment.

+
+ )} + + {/* Overall Rankings (Full Table) */} +
+
+

Overall Rankings

+ + {/* Calculation Date Filter */} +
+ +
+ +
+
Calculation Date
+
+ Sets the cutoff date for model evaluation. Use this to view rankings as they appeared on a specific date. All models are ranked based on their performance up to this date. +
+
+
+ setSelectedCalculationDate(e.target.value)} + className="px-2 py-1 text-xs bg-white border border-gray-200 rounded text-gray-600 hover:border-gray-300 focus:outline-none focus:border-blue-400 focus:ring-1 focus:ring-blue-400" + /> +
+
+ +
+ + {/* Rankings by Challenge Definition */} +
+

Rankings by Challenge

+
+ {filterOptions.definitions.map((def) => ( + + ))} +
+
+ + {/* Rankings by Frequency/Horizon */} +
+

Rankings by Frequency / Horizon

+
+ {filterOptions.frequency_horizons.map((fh) => ( + + ))} +
+
+
+
+ ); +} diff --git a/src/components/Breadcrumbs.tsx b/src/components/Breadcrumbs.tsx new file mode 100644 index 0000000000000000000000000000000000000000..0e30b9f0e92bbecf9b8f594ccda98cdfdf5f5083 --- /dev/null +++ b/src/components/Breadcrumbs.tsx @@ -0,0 +1,84 @@ +'use client'; + +import Link from 'next/link'; +import { usePathname } from 'next/navigation'; +import { ChevronRight } from 'lucide-react'; + +interface BreadcrumbItem { + label: string; + href: string; +} + +interface BreadcrumbsProps { + items?: BreadcrumbItem[]; +} + +export default function Breadcrumbs({ items }: BreadcrumbsProps) { + const pathname = usePathname(); + + // Generate breadcrumbs from path if not provided + const breadcrumbs = items || generateBreadcrumbsFromPath(pathname); + + if (breadcrumbs.length === 0) { + return null; + } + + return ( + + ); +} + +function generateBreadcrumbsFromPath(pathname: string): BreadcrumbItem[] { + const paths = pathname.split('/').filter(Boolean); + const breadcrumbs: BreadcrumbItem[] = []; + + let currentPath = ''; + paths.forEach((path, index) => { + currentPath += `/${path}`; + + // Create readable labels + let label = path + .split('-') + .map(word => word.charAt(0).toUpperCase() + word.slice(1)) + .join(' '); + + // Special handling for specific routes + if (path === 'challenges') { + label = 'Challenges'; + } else if (path === 'add-model') { + label = 'Add Model'; + } else if (!isNaN(Number(path))) { + // If it's a number (ID), keep it as is + label = `#${path}`; + } + + breadcrumbs.push({ + label, + href: currentPath, + }); + }); + + return breadcrumbs; +} diff --git a/src/components/ChallengeList.tsx b/src/components/ChallengeList.tsx new file mode 100644 index 0000000000000000000000000000000000000000..69380f5d2342b0d4f801fc7a8dbb8fd8c704a1f9 --- /dev/null +++ b/src/components/ChallengeList.tsx @@ -0,0 +1,67 @@ +'use client'; + +import type { Challenge } from '@/src/types/challenge'; + +interface ChallengeListProps { + challenges: Challenge[]; + selectedChallengeId?: number; + onSelectChallenge: (challengeId: number) => void; +} + +export default function ChallengeList({ + challenges, + selectedChallengeId, + onSelectChallenge +}: ChallengeListProps) { + + return ( +
+ {/* Challenge List */} +
+ {challenges.length === 0 ? ( +
+ No challenges found matching your filters. +
+ ) : ( + challenges.map((challenge) => ( + + )) + )} +
+
+ ); +} diff --git a/src/components/FilterPanel.tsx b/src/components/FilterPanel.tsx new file mode 100644 index 0000000000000000000000000000000000000000..dbcdc29a4219465420d48e39966adcd50133f1ee --- /dev/null +++ b/src/components/FilterPanel.tsx @@ -0,0 +1,227 @@ +'use client'; + +import { Listbox, ListboxButton, Label, ListboxOption, ListboxOptions } from '@headlessui/react'; + +export interface RoundsFilterOptions { + domains: string[]; + categories: string[]; + subcategories: string[]; + frequencies: string[]; + horizons: string[]; +} + +interface FilterPanelProps { + filterOptions: RoundsFilterOptions; + selectedDomains: string[]; + selectedCategories: string[]; + selectedFrequencies: string[]; + selectedHorizons: string[]; + status?: 'active' | 'completed' | 'all'; + endDateFrom?: string; + endDateTo?: string; + searchTerm?: string; + onDomainsChange: (domains: string[]) => void; + onCategoriesChange: (categories: string[]) => void; + onFrequenciesChange: (frequencies: string[]) => void; + onHorizonsChange: (horizons: string[]) => void; + onStatusChange: (status: 'active' | 'completed' | 'all') => void; + onEndDateFromChange: (date: string) => void; + onEndDateToChange: (date: string) => void; + onSearchTermChange: (searchTerm: string) => void; + onClearFilters: () => void; +} + +interface MultiSelectProps { + label: string; + options: string[]; + selected: string[]; + onChange: (values: string[]) => void; +} + +function MultiSelect({ label, options, selected, onChange }: MultiSelectProps) { + const handleRemove = (value: string, e: React.MouseEvent) => { + e.stopPropagation(); + onChange(selected.filter((v) => v !== value)); + }; + + const handleSelect = (values: string[]) => { + onChange(values); + }; + + return ( + +
+ + + + {selected.length > 0 ? ( +
+ {selected.map((item) => ( + + {item} + handleRemove(item, e)} + > + Γ— + + + ))} +
+ ) : ( + Select {label.toLowerCase()}... + )} +
+ + + {options.map((option) => ( + + {option} + + ))} + +
+
+ ); +} + +export default function FilterPanel({ + filterOptions, + selectedDomains, + selectedCategories, + selectedFrequencies, + selectedHorizons, + status, + endDateFrom, + endDateTo, + searchTerm, + onDomainsChange, + onCategoriesChange, + onFrequenciesChange, + onHorizonsChange, + onStatusChange, + onEndDateFromChange, + onEndDateToChange, + onSearchTermChange, + onClearFilters, +}: FilterPanelProps) { + return ( +
+
+

Filters

+ +
+ +
+ {/* Status and Search in same row */} +
+
+ + +
+ +
+ + onSearchTermChange(e.target.value)} + className="w-full px-3 py-2 border border-gray-300 rounded-md focus:outline-none focus:border-blue-500 focus:ring-1 focus:ring-blue-500" + /> +
+
+ + {/* Multi-select filters */} +
+ + + + + + + +
+ + {/* Date Range Filters */} +
+

End Date Range

+
+
+ + onEndDateFromChange(e.target.value)} + className="w-full px-3 py-2 border border-gray-300 rounded-md text-sm focus:outline-none focus:border-blue-500 focus:ring-1 focus:ring-blue-500" + /> +
+
+ + onEndDateToChange(e.target.value)} + className="w-full px-3 py-2 border border-gray-300 rounded-md text-sm focus:outline-none focus:border-blue-500 focus:ring-1 focus:ring-blue-500" + /> +
+
+
+
+
+ ); +} diff --git a/src/components/ModelPerformanceCharts.tsx b/src/components/ModelPerformanceCharts.tsx new file mode 100644 index 0000000000000000000000000000000000000000..0fbac19c1e9567c6376c1f0c9b7443cf3d29ad17 --- /dev/null +++ b/src/components/ModelPerformanceCharts.tsx @@ -0,0 +1,195 @@ +'use client'; + +import { useState } from 'react'; +import Link from 'next/link'; +import dynamic from 'next/dynamic'; +import { DefinitionRankingWithHistory } from '@/src/services/modelService'; +import { ChevronDown, ChevronRight } from 'lucide-react'; + +const Plot = dynamic(() => import('react-plotly.js'), { ssr: false }); + +interface ModelPerformanceChartsProps { + definitionRankings: DefinitionRankingWithHistory[]; +} + +export default function ModelPerformanceCharts({ definitionRankings }: ModelPerformanceChartsProps) { + const [expandedDefinitions, setExpandedDefinitions] = useState>({}); + + const toggleDefinition = (definitionId: number) => { + setExpandedDefinitions(prev => ({ + ...prev, + [definitionId]: !prev[definitionId] + })); + }; + + if (!definitionRankings || definitionRankings.length === 0) { + return ( +
+ No ranking data available for this model. +
+ ); + } + + return ( +
+ {definitionRankings.map((definition) => { + const isExpanded = expandedDefinitions[definition.definition_id]; + const dailyRankings = definition.daily_rankings || []; + + // Sort rankings by date + const sortedRankings = [...dailyRankings].sort((a, b) => + new Date(a.calculation_date).getTime() - new Date(b.calculation_date).getTime() + ); + + // Prepare data for Plotly + const dates = sortedRankings.map(r => r.calculation_date); + const eloScores = sortedRankings.map(r => r.elo_score); + const eloUpper = sortedRankings.map(r => r.elo_ci_upper); + const eloLower = sortedRankings.map(r => r.elo_ci_lower); + const ranks = sortedRankings.map(r => r.rank_position); + + return ( +
+ + + {isExpanded && sortedRankings.length > 0 && ( +
+ Date: %{x}
' + + 'ELO Score: %{y:.1f}
' + + 'Rank: #%{customdata}
' + + '', + }, + ] as any} + layout={{ + title: 'ELO Score Over Time', + xaxis: { + title: 'Date', + gridcolor: '#e5e7eb', + showgrid: true, + }, + yaxis: { + title: 'ELO Score', + gridcolor: '#e5e7eb', + showgrid: true, + range: [0, Math.max(...eloUpper, ...eloScores, ...eloLower) * 1.05], + }, + hovermode: 'closest', + showlegend: true, + legend: { + x: 0, + y: 1, + bgcolor: 'rgba(255, 255, 255, 0.8)', + }, + margin: { l: 60, r: 40, t: 50, b: 60 }, + paper_bgcolor: 'white', + plot_bgcolor: 'white', + } as any} + config={{ + responsive: true, + displayModeBar: true, + displaylogo: false, + modeBarButtonsToRemove: ['lasso2d', 'select2d'], + }} + style={{ width: '100%', height: '400px' }} + /> + + {/* Current stats */} +
+
+
Current Rank
+
+ #{sortedRankings[sortedRankings.length - 1].rank_position} +
+
+
+
Current ELO
+
+ {sortedRankings[sortedRankings.length - 1].elo_score.toFixed(1)} +
+
+
+
95% CI
+
+ [{sortedRankings[sortedRankings.length - 1].elo_ci_lower.toFixed(0)}, {sortedRankings[sortedRankings.length - 1].elo_ci_upper.toFixed(0)}] +
+
+
+
+ )} + + {isExpanded && sortedRankings.length === 0 && ( +
+ No ranking history available for this challenge. +
+ )} +
+ ); + })} +
+ ); +} + diff --git a/src/components/ModelRankingsTable.tsx b/src/components/ModelRankingsTable.tsx new file mode 100644 index 0000000000000000000000000000000000000000..047db9ec981037f93ad06af6835d29187e996933 --- /dev/null +++ b/src/components/ModelRankingsTable.tsx @@ -0,0 +1,130 @@ +'use client'; + +import { useState } from 'react'; +import Link from 'next/link'; +import { DefinitionRanking, TimeRangeRanking } from '@/src/services/modelService'; + +interface ModelRankingsTableProps { + definitionRankings: DefinitionRanking[]; +} + +const timeRanges = [ + { key: 'rankings_7d', label: '7 Days' }, + { key: 'rankings_30d', label: '30 Days' }, + { key: 'rankings_90d', label: '90 Days' }, + { key: 'rankings_365d', label: '365 Days' }, +] as const; + +function RankingCell({ ranking }: { ranking?: TimeRangeRanking }) { + if (!ranking) { + return ( + + N/A + + ); + } + + return ( + +
+
+ Rank {ranking.rank} / {ranking.total_models} +
+
+ Rounds: {ranking.rounds_participated} +
+
+ Avg MASE: {ranking.avg_mase !== null ? ranking.avg_mase.toFixed(3) : 'N/A'} +
+ {ranking.stddev_mase !== null && ( +
+ StdDev: {ranking.stddev_mase.toFixed(3)} +
+ )} +
+ ELO: {ranking.elo_score !== null && ranking.elo_score !== undefined ? ranking.elo_score.toFixed(0) : 'NaN'} +
+
+ + ); +} + +export default function ModelRankingsTable({ definitionRankings }: ModelRankingsTableProps) { + const [isExpanded, setIsExpanded] = useState(true); + + console.log('ModelRankingsTable - definitionRankings:', definitionRankings); + console.log('ModelRankingsTable - type:', typeof definitionRankings); + console.log('ModelRankingsTable - is array:', Array.isArray(definitionRankings)); + + if (!definitionRankings || definitionRankings.length === 0) { + return ( +
+ No ranking data available for this model. +
+ ); + } + + return ( +
+ + + {isExpanded && ( +
+ + + + + {timeRanges.map((timeRange) => ( + + ))} + + + + + {definitionRankings.map((definition) => ( + + + {timeRanges.map((timeRange) => ( + + ))} + + + ))} + +
+ Challenge Definition + + {timeRange.label} + + Actions +
+
{definition.definition_name}
+
+ + Go to Challenge + +
+
+ )} +
+ ); +} diff --git a/src/components/ModelSeriesList.tsx b/src/components/ModelSeriesList.tsx new file mode 100644 index 0000000000000000000000000000000000000000..864e32d2c9d370f3a392a72e57ed44f5cf3111a0 --- /dev/null +++ b/src/components/ModelSeriesList.tsx @@ -0,0 +1,431 @@ +'use client'; + +import React, { useState } from 'react'; +import dynamic from 'next/dynamic'; +import type { PlotParams } from 'react-plotly.js'; +import { DefinitionWithSeries, getModelSeriesForecasts } from '@/src/services/modelService'; +import { ModelSeriesForecastsResponse } from '../types/challenge'; +import { ChevronDown, ChevronUp } from 'lucide-react'; + +// Dynamically import Plotly to avoid SSR issues +const Plot = dynamic(() => import('react-plotly.js'), { ssr: false }); + +interface ModelSeriesListProps { + definitions: DefinitionWithSeries[]; + modelId: string; +} + +interface ExpandedSeriesData { + loading: boolean; + error?: string; + data?: ModelSeriesForecastsResponse; +} + +export default function ModelSeriesList({ definitions, modelId }: ModelSeriesListProps) { + const [expandedDefinitions, setExpandedDefinitions] = useState>(() => { + // Initialize with the first definition expanded + if (definitions && definitions.length > 0) { + return new Set([definitions[0].definition_id]); + } + return new Set(); + }); + + const [expandedSeries, setExpandedSeries] = useState>(new Set()); + const [seriesData, setSeriesData] = useState>(new Map()); + const [dateFilters, setDateFilters] = useState>(new Map()); + const [pendingDateFilters, setPendingDateFilters] = useState>(new Map()); + + const toggleDefinition = (definitionId: number) => { + setExpandedDefinitions(prev => { + const newSet = new Set(prev); + if (newSet.has(definitionId)) { + newSet.delete(definitionId); + } else { + newSet.add(definitionId); + } + return newSet; + }); + }; + + const fetchSeriesData = async (seriesId: number, definitionId: number, startDate?: string, endDate?: string) => { + setSeriesData(prev => new Map(prev).set(seriesId, { loading: true })); + + try { + const data = await getModelSeriesForecasts(modelId, definitionId, seriesId, startDate, endDate); + const roundsWithForecasts = data.rounds.filter(r => r.forecast_exists && r.forecasts && r.forecasts.length > 0); + console.log(`Series ${seriesId} (${data.series_name}):`, { + totalRounds: data.rounds.length, + roundsWithForecasts: roundsWithForecasts.length, + rounds: roundsWithForecasts.map(r => ({ + id: r.round_id, + name: r.round_name, + points: r.forecasts?.length || 0, + forecasts: r.forecasts + })) + }); + setSeriesData(prev => new Map(prev).set(seriesId, { loading: false, data })); + } catch (error) { + console.error('Error fetching forecasts:', error); + setSeriesData(prev => new Map(prev).set(seriesId, { + loading: false, + error: 'Failed to load forecast data' + })); + } + }; + + const toggleSeries = async (seriesId: number, definitionId: number) => { + const isExpanding = !expandedSeries.has(seriesId); + + setExpandedSeries(prev => { + const newSet = new Set(prev); + if (newSet.has(seriesId)) { + newSet.delete(seriesId); + } else { + newSet.add(seriesId); + } + return newSet; + }); + + // If expanding and we don't have data yet, fetch it + if (isExpanding && !seriesData.has(seriesId)) { + let filters = dateFilters.get(seriesId); + + // Set default start date to 30 days ago if not already set + if (!filters?.startDate) { + const defaultStartDate = new Date(); + defaultStartDate.setDate(defaultStartDate.getDate() - 30); + const startDateStr = defaultStartDate.toISOString().split('T')[0]; + + filters = { ...filters, startDate: startDateStr }; + setDateFilters(prev => new Map(prev).set(seriesId, filters!)); + } + + await fetchSeriesData(seriesId, definitionId, filters?.startDate, filters?.endDate); + } + }; + + const handleDateChange = (seriesId: number, type: 'start' | 'end', value: string) => { + const currentFilters = pendingDateFilters.get(seriesId) || dateFilters.get(seriesId) || {}; + const newFilters = { + ...currentFilters, + [type === 'start' ? 'startDate' : 'endDate']: value + }; + + setPendingDateFilters(prev => new Map(prev).set(seriesId, newFilters)); + }; + + const applyDateFilters = async (seriesId: number, definitionId: number) => { + const pending = pendingDateFilters.get(seriesId); + if (pending) { + setDateFilters(prev => new Map(prev).set(seriesId, pending)); + setPendingDateFilters(prev => { + const newMap = new Map(prev); + newMap.delete(seriesId); + return newMap; + }); + await fetchSeriesData(seriesId, definitionId, pending.startDate, pending.endDate); + } + }; + + const renderPlot = (seriesId: number) => { + const data = seriesData.get(seriesId); + const filters = dateFilters.get(seriesId); + + if (!data) return null; + + if (data.loading) { + return ( +
+
+
+ ); + } + + if (data.error) { + return ( +
+

{data.error}

+
+ ); + } + + if (!data.data) return null; + + // Prepare plot data from rounds - keep colors per round but display as continuous timeline + const traces: any[] = []; + const colors = ['#3b82f6', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6', '#ec4899', '#06b6d4', '#84cc16']; + + // Filter and sort rounds by their start time to display chronologically + const roundsWithForecasts = data.data.rounds + .filter(round => round.forecast_exists && round.forecasts && round.forecasts.length > 0) + .sort((a, b) => new Date(a.start_time).getTime() - new Date(b.start_time).getTime()); + + // Add ground truth trace if available + if (data.data.ground_truth && data.data.ground_truth.length > 0) { + traces.push({ + x: data.data.ground_truth.map(p => p.ts), + y: data.data.ground_truth.map(p => p.value), + type: 'scatter', + mode: 'lines', + name: 'Ground Truth', + line: { width: 2, color: '#000000', dash: 'solid' }, + marker: { size: 4 }, + }); + } + + roundsWithForecasts.forEach((round, idx) => { + const forecastPoints = round.forecasts!; + const color = colors[idx % colors.length]; + + // Main forecast line for this round + traces.push({ + x: forecastPoints.map(p => p.ts), + y: forecastPoints.map(p => p.y), + type: 'scatter', + mode: 'lines', + name: round.round_name, + line: { width: 2, color: color }, + marker: { size: 3 }, + }); + }); + + if (traces.length === 0) { + return ( +
+ No forecast data available for this series. +
+ ); + } + + // Calculate the maximum date from all forecast data + let maxDate: Date | undefined = undefined; + for (const round of roundsWithForecasts) { + if (round.forecasts) { + for (const point of round.forecasts) { + const pointDate = new Date(point.ts); + if (!maxDate || pointDate > maxDate) { + maxDate = pointDate; + } + } + } + } + + // Use calculated maxDate if endDate filter is not set + const effectiveEndDate = filters?.endDate || (maxDate ? maxDate.toISOString().split('T')[0] : undefined); + + const xAxisRange = (filters?.startDate || effectiveEndDate) ? [ + filters?.startDate, + effectiveEndDate + ] : undefined; + + console.log(`X-axis range for series ${seriesId}:`, { + from: filters?.startDate, + to: filters?.endDate, + effectiveEndDate, + maxDateFromData: maxDate ? maxDate.toISOString() : null, + range: xAxisRange + }); + + const layout: Partial = { + title: { text: data.data.series_name }, + xaxis: { + title: { text: 'Time' }, + type: 'date', + range: xAxisRange, + }, + yaxis: { + title: { text: 'Value' }, + }, + hovermode: 'closest', + showlegend: true, + legend: { + x: 1.02, + y: 1, + xanchor: 'left', + yanchor: 'top', + }, + margin: { l: 60, r: 200, t: 60, b: 60 }, + autosize: true, + }; + + const config: PlotParams['config'] = { + responsive: true, + displayModeBar: true, + displaylogo: false, + modeBarButtonsToRemove: ['lasso2d', 'select2d'], + }; + + return ( +
+ +
+ ); + }; + + if (!definitions || definitions.length === 0) { + return ( +
+ No series data available for this model. +
+ ); + } + + return ( +
+ + +
+ + + + + + + + + + + {definitions.map((definition) => { + const isExpanded = expandedDefinitions.has(definition.definition_id); + const totalRounds = definition.series.reduce((sum, s) => sum + s.rounds_participated, 0); + + return ( + + + + + + + + + {isExpanded && definition.series.map((series) => { + const isSeriesExpanded = expandedSeries.has(series.series_id); + + return ( + + + + + + + + + {isSeriesExpanded && ( + + + + )} + + ); + })} + + ); + })} + +
+ Challenge Definition + + Series Count + + Total Rounds + + Details +
+
{definition.definition_name}
+
+ {definition.series.length} + + {totalRounds} + + +
+
+ └─ + +
+
+ β€” + + {series.rounds_participated} + + +
+
+
+ + + +
+ {renderPlot(series.series_id)} +
+
+
+
+ ); +} diff --git a/src/components/Navigation.tsx b/src/components/Navigation.tsx new file mode 100644 index 0000000000000000000000000000000000000000..420c6257b2d90e217ffeecb7f59828b057d7b3f3 --- /dev/null +++ b/src/components/Navigation.tsx @@ -0,0 +1,48 @@ +'use client'; + +import Link from 'next/link'; +import { usePathname } from 'next/navigation'; + +export default function Navigation() { + const pathname = usePathname(); + + const navItems = [ + { href: '/', label: 'Rankings' }, + { href: '/challenges', label: 'Challenges' }, + { href: '/add-model', label: 'Add Model' }, + ]; + + return ( + + ); +} diff --git a/src/components/RankingsTable.tsx b/src/components/RankingsTable.tsx new file mode 100644 index 0000000000000000000000000000000000000000..4bbc0a36c5c52f2e42afc5ee30ad2c1d073962ad --- /dev/null +++ b/src/components/RankingsTable.tsx @@ -0,0 +1,330 @@ +'use client'; + +import { useMemo } from 'react'; +import { useRouter } from 'next/navigation'; +import { + useReactTable, + getCoreRowModel, + getSortedRowModel, + getFilteredRowModel, + ColumnDef, + flexRender, + SortDirection, +} from '@tanstack/react-table'; +import { ModelRanking } from '@/src/services/modelService'; + +interface RankingsTableProps { + rankings: ModelRanking[]; + compact?: boolean; + title?: string; + limit?: number; + definitionId?: number; +} + +// Text search filter component +function TextSearchFilter({ column }: { column: any }) { + const filterValue = (column.getFilterValue() as string) || ''; + + return ( +
e.stopPropagation()} className="mt-1"> + column.setFilterValue(e.target.value || undefined)} + placeholder="Search..." + className="w-full px-2 py-1.5 text-xs border border-gray-300 rounded focus:outline-none focus:border-blue-500 focus:ring-1 focus:ring-blue-500" + /> +
+ ); +} + +// Numeric max filter component +function NumberMaxFilter({ column }: { column: any }) { + const filterValue = (column.getFilterValue() as number) || ''; + + return ( +
e.stopPropagation()} className="mt-1"> + column.setFilterValue(e.target.value ? Number(e.target.value) : undefined)} + placeholder="Max (M)..." + className="w-full px-2 py-1.5 text-xs border border-gray-300 rounded focus:outline-none focus:border-blue-500 focus:ring-1 focus:ring-blue-500" + /> +
+ ); +} + +export default function RankingsTable({ + rankings, + compact = false, + title, + limit, + definitionId, +}: RankingsTableProps) { + const router = useRouter(); + + const handleRowClick = (modelId: string, modelName: string) => { + router.push(`/models/${modelId}`); + }; + + // Apply limit if specified + const displayedRankings = limit ? rankings.slice(0, limit) : rankings; + + const fullColumns = useMemo[]>( + () => [ + { + accessorKey: 'rank_position', + header: 'Rank', + cell: (info) => ( + {info.getValue() as number} + ), + }, + { + accessorKey: 'model_name', + header: 'Model Name', + cell: (info) => ( + {info.getValue() as string} + ), + }, + { + accessorKey: 'elo_score', + header: 'ELO Score', + cell: (info) => { + const row = info.row.original; + return ( +
+ {row.elo_score.toFixed(1)} +
+ +{row.elo_ci_upper_diff.toFixed(1)}/-{row.elo_ci_lower_diff.toFixed(1)} +
+
+ ); + }, + }, + { + accessorKey: 'mase_avg', + header: 'Avg MASE', + cell: (info) => { + const row = info.row.original; + return ( +
+ {row.mase_avg.toFixed(3)} +
+ Β±{row.mase_std.toFixed(3)} +
+
+ ); + }, + }, + { + accessorKey: 'n_evaluations', + header: 'Evaluations', + cell: (info) => ( + {(info.getValue() as number).toLocaleString()} + ), + }, + { + accessorKey: 'n_matches', + header: 'Matches', + cell: (info) => ( + {(info.getValue() as number).toLocaleString()} + ), + }, + { + accessorKey: 'readable_id', + header: 'Model ID', + cell: (info) => ( + {info.getValue() as string} + ), + }, + { + accessorKey: 'organization_name', + header: 'Organization', + cell: (info) => info.getValue() as string, + }, + { + accessorKey: 'architecture', + header: 'Architecture', + cell: (info) => ( + {(info.getValue() as string) || 'N/A'} + ), + }, + { + accessorKey: 'model_size', + header: 'Model Size', + filterFn: (row, columnId, filterValue) => { + const value = row.getValue(columnId) as number; + if (!filterValue) return true; + return value <= filterValue; + }, + cell: (info) => { + const size = info.getValue() as number; + return ( + + {size ? `${size.toLocaleString()}M` : 'N/A'} + + ); + }, + }, + ], + [] + ); + + const compactColumns = useMemo[]>( + () => [ + { + accessorKey: 'rank_position', + header: 'Rank', + cell: (info) => ( + {info.getValue() as number} + ), + }, + { + accessorKey: 'model_name', + header: 'Model Name', + cell: (info) => ( + {info.getValue() as string} + ), + }, + { + accessorKey: 'elo_score', + header: 'ELO Score', + cell: (info) => { + const row = info.row.original; + return ( +
+ {row.elo_score.toFixed(1)} +
+ +{row.elo_ci_upper_diff.toFixed(1)}/-{row.elo_ci_lower_diff.toFixed(1)} +
+
+ ); + }, + }, + { + accessorKey: 'mase_avg', + header: 'Avg MASE', + cell: (info) => { + const row = info.row.original; + return ( +
+ {row.mase_avg.toFixed(3)} +
+ Β±{row.mase_std.toFixed(3)} +
+
+ ); + }, + }, + ], + [] + ); + + const columns = compact ? compactColumns : fullColumns; + + const table = useReactTable({ + data: displayedRankings ?? [], + columns, + getCoreRowModel: getCoreRowModel(), + getSortedRowModel: getSortedRowModel(), + getFilteredRowModel: getFilteredRowModel(), + initialState: { + sorting: [ + { + id: 'rank_position', + desc: false, + }, + ], + }, + }); + + const getSortIcon = (isSorted: false | SortDirection) => { + if (!isSorted) { + return ↕; + } + return {isSorted === 'asc' ? '↑' : '↓'}; + }; + + return ( +
+ {title && ( +
+ {definitionId ? ( +

router.push(`/challenges/${definitionId}`)} + > + {title} +

+ ) : ( +

{title}

+ )} +
+ )} +
+ + + {table.getHeaderGroups().map((headerGroup) => ( + + {headerGroup.headers.map((header) => { + const columnId = header.column.id; + const showTextFilter = !compact && (columnId === 'model_name' || columnId === 'readable_id'); + const showNumberMaxFilter = !compact && columnId === 'model_size'; + + return ( + + ); + })} + + ))} + + + {table.getRowModel().rows.map((row) => ( + handleRowClick(String(row.original.model_id), row.original.model_name)} + > + {row.getVisibleCells().map((cell) => ( + + ))} + + ))} + +
+
+ {flexRender( + header.column.columnDef.header, + header.getContext() + )} + {header.column.getCanSort() && + getSortIcon(header.column.getIsSorted())} +
+ + {showTextFilter && } + {showNumberMaxFilter && } +
+ {flexRender(cell.column.columnDef.cell, cell.getContext())} +
+
+ + {table.getRowModel().rows.length === 0 && ( +
+ No rankings found. +
+ )} +
+ ); +} diff --git a/src/components/TimeSeriesChart.tsx b/src/components/TimeSeriesChart.tsx new file mode 100644 index 0000000000000000000000000000000000000000..373c5247ef1a279f455d514d5dcea87526e0ab15 --- /dev/null +++ b/src/components/TimeSeriesChart.tsx @@ -0,0 +1,689 @@ +'use client'; + +import { useEffect, useState, useCallback } from 'react'; +import dynamic from 'next/dynamic'; +import Link from 'next/link'; +import type { PlotParams } from 'react-plotly.js'; +import type { ForecastsResponse, ForecastData, Model } from '@/src/types/challenge'; +import { getChallengeSeries, getSeriesData, getSeriesForecasts, getRoundModels } from '@/src/services/roundService'; +import humanizeDuration from 'humanize-duration'; +import { parse, toSeconds } from 'iso8601-duration'; + + +// Dynamically import Plotly to avoid SSR issues +const Plot = dynamic(() => import('react-plotly.js'), { ssr: false }); + +// Convert ISO 8601 duration to human-readable format +function formatFrequency(freq: string | undefined): string { + if (!freq) return 'N/A'; + + try { + // Parse ISO 8601 duration string (e.g., "PT3M" for 3 minutes) + const duration = parse(freq); + + // Convert to seconds, then to milliseconds + const seconds = toSeconds(duration); + const milliseconds = seconds * 1000; + + // Use humanize-duration to format + return humanizeDuration(milliseconds, { + largest: 2, + round: true, + conjunction: ' and ', + serialComma: false + }); + } catch (error) { + // If parsing fails, return the original string + console.warn(`Failed to parse frequency "${freq}":`, error); + return freq; + } +} + +interface SeriesDataItem { + contextData: any[]; + testData: any[]; + series_id: number; + series_name: string; + forecasts?: ForecastsResponse; + forecastsLoading?: boolean; + forecastsError?: string; +} + +interface TimeSeriesChartProps { + challengeId: number; + challengeName: string; + challengeDescription?: string; + startDate?: string; + endDate?: string; + frequency?: string; + horizon?: string; + seriesId?: number; + on_title_page?: boolean; + definitionId?: number; + status?: string; +} + +export default function TimeSeriesChart({ challengeId, challengeName, challengeDescription, startDate, endDate, frequency, horizon, seriesId, on_title_page = false, definitionId, status }: TimeSeriesChartProps) { + const [seriesData, setSeriesData] = useState([]); + const [loading, setLoading] = useState(true); + const [error, setError] = useState(null); + const [expandedSeries, setExpandedSeries] = useState>(new Set()); + + // Forecast filter state + const [maxSizeFilter, setMaxSizeFilter] = useState(''); + const [architectureFilter, setArchitectureFilter] = useState(''); + const [modelSearchFilter, setModelSearchFilter] = useState(''); + + // Models data + const [models, setModels] = useState([]); + const [modelsLoading, setModelsLoading] = useState(true); + + // Function to load data and forecasts for a specific series + const loadForecastsForSeries = useCallback(async (seriesId: number) => { + // Check if data is already loaded or loading + setSeriesData(prev => { + const series = prev.find(s => s.series_id === seriesId); + if (!series || (series.forecasts && series.contextData?.length > 0)) { + return prev; + } + + // Mark as loading + return prev.map(s => + s.series_id === seriesId + ? { ...s, forecastsLoading: true, forecastsError: undefined } + : s + ); + }); + + try { + // Get the series metadata to fetch context and test data + const series = await getChallengeSeries(challengeId); + const currentSeries = series.find(s => s.series_id === seriesId); + + if (!currentSeries) { + throw new Error(`Series ${seriesId} not found`); + } + + const startTime = currentSeries.context_start_time; + const endTimeContext = currentSeries.context_end_time; + const endTimeTest = currentSeries.end_time; + + if (!startTime || !endTimeContext || !endTimeTest) { + throw new Error(`Missing time range for series ${seriesId}`); + } + + // Load context data, test data, and forecasts in parallel + const [dataContext, dataTest, forecasts] = await Promise.all([ + getSeriesData(challengeId, seriesId, startTime, endTimeContext), + getSeriesData(challengeId, seriesId, endTimeContext, endTimeTest), + getSeriesForecasts(challengeId, seriesId) + ]); + + const modelCount = forecasts?.forecasts ? Object.keys(forecasts.forecasts).length : 0; + console.log(`βœ“ Loaded ${dataContext.data?.length || 0} context data points for series ${seriesId}`); + console.log(`βœ“ Loaded ${dataTest.data?.length || 0} test data points for series ${seriesId}`); + console.log(`βœ“ Loaded ${modelCount} forecast models for series ${seriesId}`); + + // Update with loaded data and forecasts + setSeriesData(prev => prev.map(s => + s.series_id === seriesId + ? { + ...s, + contextData: dataContext.data, + testData: dataTest.data, + forecasts, + forecastsLoading: false + } + : s + )); + } catch (err) { + console.error(`Failed to fetch data for series ${seriesId}:`, err); + setSeriesData(prev => prev.map(s => + s.series_id === seriesId + ? { ...s, forecastsLoading: false, forecastsError: 'Failed to load data' } + : s + )); + } + }, [challengeId]); + + const toggleSeries = (seriesId: number) => { + setExpandedSeries(prev => { + const newSet = new Set(prev); + if (newSet.has(seriesId)) { + newSet.delete(seriesId); + } else { + newSet.add(seriesId); + // Load forecasts when expanding + loadForecastsForSeries(seriesId); + } + return newSet; + }); + }; + + // Fetch models for the challenge + useEffect(() => { + async function fetchModels() { + try { + setModelsLoading(true); + const modelsData = await getRoundModels(challengeId); + + // API returns models as a direct array + const modelsList = Array.isArray(modelsData) ? modelsData : []; + setModels(modelsList); + } catch (err) { + console.error('Failed to fetch models:', err); + setModels([]); + } finally { + setModelsLoading(false); + } + } + fetchModels(); + }, [challengeId]); + + useEffect(() => { + async function fetchData() { + try { + setLoading(true); + setError(null); + + // Fetch all series for this challenge + const series = await getChallengeSeries(challengeId); + console.log(`Fetched ${series.length} series for challenge ${challengeId}`); + + // Filter by seriesId if provided + const filteredSeries = seriesId + ? series.filter(s => s.series_id === seriesId) + : series; + + if (seriesId && filteredSeries.length === 0) { + console.warn(`Series ${seriesId} not found in challenge ${challengeId}`); + } + + // Create series items with metadata only (data will be loaded on demand) + const validData = filteredSeries.map((s) => ({ + contextData: [], + testData: [], + series_id: s.series_id, + series_name: s.name, + forecasts: undefined, + forecastsLoading: false, + forecastsError: undefined + } as SeriesDataItem)); + + setSeriesData(validData); + + // Expand the first series by default and load its data + if (validData.length > 0) { + const firstSeriesId = validData[0].series_id; + setExpandedSeries(new Set([firstSeriesId])); + // Load data and forecasts for the first series + loadForecastsForSeries(firstSeriesId); + } + } catch (err) { + setError(err instanceof Error ? err.message : 'Failed to load time series data'); + } finally { + setLoading(false); + } + } + + fetchData(); + }, [challengeId, loadForecastsForSeries, seriesId]); + + if (loading) { + return ( +
+
+
+ ); + } + + if (error) { + return ( +
+

Error loading time series data

+

{error}

+
+ ); + } + + if (seriesData.length === 0) { + return ( +
+ No time series data available for this challenge. +
+ ); + } + + // Filter forecasts based on user input by matching with models + const filterForecasts = (forecasts: Record) => { + + const filtered = Object.entries(forecasts).filter(([modelName, forecastData]) => { + // Find the matching model from the models list + const model = models.find(m => { + const match1 = m.name === modelName; + const match2 = m.readable_id === forecastData.model_id; + const match3 = m.readable_id === modelName; + return match1 || match2 || match3; + }); + + if (!model) { + console.log(' ❌ NO MODEL FOUND'); + return false; + } + + // Filter by max_size - use model data if available + if (maxSizeFilter) { + const filterValue = parseFloat(maxSizeFilter); + if (!isNaN(filterValue)) { + if (model.model_size !== undefined && model.model_size > filterValue) { + return false; + } + } + } + + // Filter by architecture - use model data if available + if (architectureFilter) { + if (model.architecture) { + if (!model.architecture.toLowerCase().includes(architectureFilter.toLowerCase())) { + return false; + } + } else { + return false; + } + } + + // Filter by model name/ID search + if (modelSearchFilter) { + const searchLower = modelSearchFilter.toLowerCase(); + const modelIdMatch = model.readable_id?.toLowerCase() === searchLower; + const modelNameMatch = model.name?.toLowerCase().includes(searchLower); + if (!modelIdMatch && !modelNameMatch) { + return false; + } + } + + return true; + }).reduce((acc, [key, value]) => { + acc[key] = value; + return acc; + }, {} as Record); + return filtered; + }; + + // Get unique architectures and max sizes for filter options from models data + const getFilterOptions = () => { + const architectures = new Set(); + const maxSizes = new Set(); + + models.forEach(model => { + if (model.architecture) architectures.add(model.architecture); + if (model.model_size !== undefined) maxSizes.add(model.model_size); + }); + + return { + architectures: Array.from(architectures).sort(), + maxSizes: Array.from(maxSizes).sort((a, b) => a - b) + }; + }; + + const filterOptions = getFilterOptions(); + + const config: PlotParams['config'] = { + responsive: true, + displayModeBar: true, + displaylogo: false, + modeBarButtonsToRemove: ['lasso2d', 'select2d'], + }; + + return ( +
+
+ {on_title_page && definitionId ? ( + +

+ {challengeName} +

+ + ) : ( +

{challengeName}

+ )} + {!on_title_page && ( + <> + {challengeDescription && ( +

{challengeDescription}

+ )} +
+
+
+

Status

+

+ {status || 'N/A'} +

+
+
+

ID

+

{challengeId}

+
+
+

Series

+

{seriesData.length}

+
+
+

Models

+

+ {seriesData.length > 0 && seriesData[0].forecasts?.forecasts + ? Object.keys(seriesData[0].forecasts.forecasts).length + : 0} +

+
+
+

Context

+

+ {seriesData.length > 0 && seriesData[0].contextData?.length + ? seriesData[0].contextData.length + : 'N/A'} +

+
+
+

Frequency

+

+ {formatFrequency(frequency)} +

+
+
+

Horizon

+

+ {horizon || 'N/A'} +

+
+
+

Start

+

+ {startDate ? new Date(startDate).toLocaleDateString() : 'N/A'} +

+
+
+

End

+

+ {endDate ? new Date(endDate).toLocaleDateString() : 'N/A'} +

+
+
+
+ + )} + + {/* Forecast Filters */} + {!on_title_page && ( +
+

Filter Forecasts

+
+
+ {/* Model Search */} +
+ + setModelSearchFilter(e.target.value)} + className="w-full px-3 py-2 text-sm border border-gray-300 rounded-md focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent" + /> +
+ + {/* Max Size Filter */} +
+ + setMaxSizeFilter(e.target.value)} + className="w-full px-3 py-2 text-sm border border-gray-300 rounded-md focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent" + /> + {filterOptions.maxSizes.length > 0 && ( +

+ Available: {filterOptions.maxSizes.join(', ')} +

+ )} +
+ + {/* Architecture Filter */} +
+ + +
+
+ + {/* Clear Filters Button */} + {(maxSizeFilter || architectureFilter || modelSearchFilter) && ( +
+ +
+ )} +
+
+ )} +
+
{seriesData.map((series: any) => { + // Prepare traces for context and test data + const traces: any[] = []; + + // Context data trace (solid colored line) + if (series.contextData && series.contextData.length > 0) { + traces.push({ + x: series.contextData.map((d: any) => d.ts), + y: series.contextData.map((d: any) => d.value), + type: 'scatter', + mode: 'lines', + name: 'Historical Data', + line: { width: 2, color: '#2563eb' }, + marker: { size: 4 }, + legendgroup: 'actual', + legendgrouptitle: { text: 'Actual Data' }, + }); + } + + // Test data trace (grey dotted line) + if (series.testData && series.testData.length > 0) { + traces.push({ + x: series.testData.map((d: any) => d.ts), + y: series.testData.map((d: any) => d.value), + type: 'scatter', + mode: 'lines', + name: `Actual ${series.series_name || series.series_id}`, + line: { width: 2, color: '#6b7280', dash: 'dot' }, + legendgroup: 'actual', + }); + } + + // Add forecast traces for each model + if (series.forecasts?.forecasts) { + const colors = ['#dc2626', '#16a34a', '#9333ea', '#ea580c', '#0891b2', '#ca8a04']; + + // Get the last context data point to connect forecasts + const lastActualPoint = series.contextData && series.contextData.length > 0 + ? series.contextData[series.contextData.length - 1] + : null; + + // Apply filters to forecasts + const filteredForecasts = filterForecasts(series.forecasts.forecasts); + + // Sort models by MASE (ascending - best first) + const modelEntries = Object.entries(filteredForecasts) + .map(([modelName, forecastData]: [string, ForecastData]) => ({ + modelName, + forecastData, + label: forecastData?.label, + mase: forecastData?.current_mase + })) + .sort((a, b) => { + // Handle undefined/null MASE values - put them at the end + if (a.mase === undefined || a.mase === null) return 1; + if (b.mase === undefined || b.mase === null) return -1; + return a.mase - b.mase; + }); + + let visibleForecastCount = 0; + + modelEntries.forEach(({ modelName, forecastData, label, mase }, idx) => { + const dataArray = forecastData?.data; + if (Array.isArray(dataArray) && dataArray.length > 0 && lastActualPoint) { + const displayName = mase !== undefined && mase !== null + ? `${label} (MASE: ${typeof mase === 'number' ? mase.toFixed(3) : mase})` + : label; + + // Prepend the last actual point to connect the forecast line + const connectedX = [lastActualPoint.ts, ...dataArray.map((d: any) => d.ts)]; + const connectedY = [lastActualPoint.value, ...dataArray.map((d: any) => d.y)]; + + // Show only the best 5 forecasts by default + const isVisible = visibleForecastCount < 3; + visibleForecastCount++; + + traces.push({ + x: connectedX, + y: connectedY, + type: 'scatter', + mode: 'lines', + name: displayName, + line: { width: 2, dash: 'dash', color: colors[idx % colors.length] }, + visible: isVisible ? true : 'legendonly', + }); + } + }); + } + + const plotData: PlotParams['data'] = traces; + + const layout: PlotParams['layout'] = { + title: { + text: series.series_name || `Series ${series.series_id}`, + font: { size: 16 }, + }, + xaxis: { + title: { text: 'Time' }, + showgrid: true, + type: 'date', + domain: [0, 0.82], + }, + yaxis: { + title: { text: 'Value' }, + showgrid: true, + }, + hovermode: 'closest', + showlegend: true, + legend: { + orientation: 'v', + yanchor: 'top', + y: 1, + xanchor: 'left', + x: 0.85, + font: { size: 10 }, + bgcolor: 'rgba(255, 255, 255, 0.95)', + bordercolor: '#E5E7EB', + borderwidth: 1, + }, + autosize: true, + margin: { l: 60, r: 20, t: 60, b: 50 }, + }; + + const isExpanded = expandedSeries.has(series.series_id); + + return ( +
+ + {isExpanded && ( +
+ {series.forecastsLoading && ( +
+
+

Loading forecasts...

+
+ )} + {series.forecastsError && !series.forecastsLoading && ( +
+

Warning

+

{series.forecastsError}

+ +
+ )} + +
+ )} +
+ ); + })} +
+
+ ); +} diff --git a/src/services/definitionService.ts b/src/services/definitionService.ts new file mode 100644 index 0000000000000000000000000000000000000000..c159587dba01f0293748dee8916d45c977f2c9ce --- /dev/null +++ b/src/services/definitionService.ts @@ -0,0 +1,14 @@ +export async function getDefinitionRounds( + definitionId: number, + options?: { page?: number; pageSize?: number; status?: string } +): Promise { + const params = new URLSearchParams(); + if (options?.page) params.append('page', options.page.toString()); + if (options?.pageSize) params.append('page_size', options.pageSize.toString()); + if (options?.status) params.append('status', options.status); + + const url = `/api/v1/definitions/${definitionId}/rounds${params.toString() ? '?' + params.toString() : ''}`; + + const response = await fetch(url); + return response.json(); +} diff --git a/src/services/modelService.ts b/src/services/modelService.ts new file mode 100644 index 0000000000000000000000000000000000000000..395874a57644fd2bab7355da55155432f9e5d275 --- /dev/null +++ b/src/services/modelService.ts @@ -0,0 +1,176 @@ +export interface RankingFilters { + definition_id?: number; + frequency_horizon?: string; + calculation_date?: string; + limit?: number; +} + +export interface ModelRanking { + model_id: number; + model_name: string; + readable_id: string; + username: string; + organization_name: string; + architecture?: string; + model_size?: number; + elo_score: number; + elo_ci_lower: number; + elo_ci_upper: number; + elo_ci_lower_diff: number; + elo_ci_upper_diff: number; + n_matches: number; + n_bootstraps: number; + rank_position: number; + mase_avg: number; + mase_std: number; + n_evaluations: number; + calculated_at: string; + calculation_date: string; +} + +export interface RankingsResponse { + rankings: ModelRanking[]; + filters_applied: Record; +} + +export interface ChallengeDefinition { + id: number; + name: string; +} + +export interface FilterOptions { + definitions: ChallengeDefinition[]; + frequency_horizons: string[]; +} + +export interface TimeRangeRanking { + rank: number; + total_models: number; + rounds_participated: number; + avg_mase: number | null; + stddev_mase: number | null; + min_mase: number | null; + max_mase: number | null; + elo_score: number | null; +} + +export interface DefinitionRanking { + definition_id: number; + definition_name: string; + rankings_7d?: TimeRangeRanking; + rankings_30d?: TimeRangeRanking; + rankings_90d?: TimeRangeRanking; + rankings_365d?: TimeRangeRanking; +} + +export interface DailyRanking { + calculation_date: string; + elo_score: number; + elo_ci_lower: number; + elo_ci_upper: number; + rank_position: number; +} + +export interface DefinitionRankingWithHistory { + definition_id: number; + definition_name: string; + daily_rankings: DailyRanking[]; +} + +export interface ModelDetails { + readable_id: string; + name: string; + model_family: string; + model_size: number; + hosting: string; + architecture: string; + pretraining_data: string; + publishing_date: string; +} + +export interface ModelDetailRankings { + model_id: number; + model_name: string; + definition_rankings: DefinitionRankingWithHistory[]; +} + +export interface SeriesInfo { + series_id: number; + series_name: string; + series_unique_id: string; + rounds_participated: number; +} + +export interface DefinitionWithSeries { + definition_id: number; + definition_name: string; + series: SeriesInfo[]; +} + +export interface ModelSeriesByDefinition { + model_id: number; + model_readable_id: string; + model_name: string; + definitions: DefinitionWithSeries[]; +} + +export async function getFilteredRankings(filters: RankingFilters = {}): Promise { + const params = new URLSearchParams(); + + if (filters.definition_id) params.append('definition_id', filters.definition_id.toString()); + if (filters.frequency_horizon) params.append('frequency_horizon', filters.frequency_horizon); + if (filters.calculation_date) params.append('calculation_date', filters.calculation_date); + if (filters.limit) params.append('limit', filters.limit.toString()); + + const url = `/api/v1/models/rankings${params.toString() ? '?' + params.toString() : ''}`; + + const response = await fetch(url); + return response.json(); +} + +export async function getRankingFilters(): Promise { + const url = '/api/v1/models/ranking-filters'; + + const response = await fetch(url); + return response.json(); +} + +export async function getModelDetails(modelId: string): Promise { + const url = `/api/v1/models/${modelId}`; + + const response = await fetch(url); + const data = await response.json(); + return Array.isArray(data) ? data[0] : data; +} + +export async function getModelRankings(modelId: string): Promise { + const url = `/api/v1/models/${modelId}/rankings`; + + const response = await fetch(url); + return response.json(); +} + +export async function getModelSeriesByDefinition(modelId: string): Promise { + const url = `/api/v1/models/${modelId}/series-by-definition`; + + const response = await fetch(url); + return response.json(); +} + +export async function getModelSeriesForecasts( + modelId: string, + definitionId: number, + seriesId: number, + startDate?: string, + endDate?: string +): Promise { + const params = new URLSearchParams(); + if (startDate) params.append('start_date', startDate); + if (endDate) params.append('end_date', endDate); + + const queryString = params.toString(); + const url = `/api/v1/models/${modelId}/definitions/${definitionId}/series/${seriesId}/forecasts${queryString ? '?' + queryString : ''}`; + + const response = await fetch(url); + return response.json(); +} diff --git a/src/services/roundService.ts b/src/services/roundService.ts new file mode 100644 index 0000000000000000000000000000000000000000..7019e3ecd2ba12004ee00564c1719b0fdeed7bbd --- /dev/null +++ b/src/services/roundService.ts @@ -0,0 +1,125 @@ +import type { Challenge, ChallengeSeries, TimeSeriesData, ForecastsResponse, ModelsResponse } from '@/src/types/challenge'; + +export interface ChallengeApiFilters { + domains?: string[]; + categories?: string[]; + frequencies?: string[]; + horizons?: string[]; + endDateFrom?: string; + endDateTo?: string; + status?: string; + searchTerm?: string; +} + +export async function getChallenges(filters?: ChallengeApiFilters): Promise { + const params = new URLSearchParams(); + + if (filters) { + // Add array filters + filters.domains?.forEach(d => params.append('domain', d)); + filters.categories?.forEach(c => params.append('category', c)); + filters.frequencies?.forEach(f => params.append('frequency', f)); + filters.horizons?.forEach(h => params.append('horizon', h)); + + // Add date filters - convert to ISO format + if (filters.endDateFrom) { + const fromDate = new Date(filters.endDateFrom); + params.append('from', fromDate.toISOString()); + } + if (filters.endDateTo) { + const toDate = new Date(filters.endDateTo); + // Set to end of day for 'to' date + toDate.setHours(23, 59, 59, 999); + params.append('to', toDate.toISOString()); + } + + // Add status filter + if (filters.status && filters.status !== 'all') params.append('status', filters.status); + + // Add search term + if (filters.searchTerm) params.append('search', filters.searchTerm); + } + + const queryString = params.toString(); + const url = `/api/v1/rounds${queryString ? '?' + queryString : ''}`; + + console.log('Fetching challenges with filters:', url); + + const response = await fetch(url); + if (!response.ok) { + throw new Error('Failed to fetch challenges'); + } + return response.json(); +} + +export async function getRoundsMetadata(): Promise<{ + domains: string[]; + categories: string[]; + frequencies: string[]; + horizons: string[]; + statuses: string[]; + subcategories: string[]; +}> { + const response = await fetch('/api/v1/rounds/metadata'); + if (!response.ok) { + throw new Error('Failed to fetch rounds metadata'); + } + return response.json(); +} + +export async function getChallengeSeries(roundId: number): Promise { + const response = await fetch(`/api/v1/rounds/${roundId}/series`); + if (!response.ok) { + throw new Error('Failed to fetch round series'); + } + return response.json(); +} + +export async function getSeriesData( + roundId: number, + seriesId: number, + startTime: string, + endTime: string +): Promise { + const params = new URLSearchParams({ + start_time: startTime, + end_time: endTime, + }); + const url = `/api/v1/rounds/${roundId}/series/${seriesId}/data?${params.toString()}`; + console.log('getSeriesData calling:', url); + const response = await fetch(url); + if (!response.ok) { + const errorText = await response.text(); + console.error('getSeriesData failed:', response.status, errorText); + throw new Error('Failed to fetch series data'); + } + return response.json(); +} + +export async function getSeriesForecasts( + roundId: number, + seriesId: number +): Promise { + const url = `/api/v1/rounds/${roundId}/series/${seriesId}/forecasts`; + console.log('getSeriesForecasts calling:', url); + const response = await fetch(url); + if (!response.ok) { + const errorText = await response.text(); + console.error('getSeriesForecasts failed:', response.status, errorText); + throw new Error('Failed to fetch forecasts'); + } + return response.json(); +} + +export async function getRoundModels( + roundId: number +): Promise { + const url = `/api/v1/rounds/${roundId}/models`; + const response = await fetch(url); + if (!response.ok) { + const errorText = await response.text(); + console.error('getRoundModels failed:', response.status, errorText); + throw new Error('Failed to fetch models'); + } + return response.json(); +} diff --git a/src/types/challenge.ts b/src/types/challenge.ts new file mode 100644 index 0000000000000000000000000000000000000000..173440ce90fcb68af292b170d014831ecd067d37 --- /dev/null +++ b/src/types/challenge.ts @@ -0,0 +1,178 @@ +export interface Challenge { + challenge_id: number; + name: string | null; + status: string; + start_time: string | null; + end_time: string | null; + description: string | null; + n_time_series: number; + registration_start?: string | null; + registration_end?: string | null; + context_length?: any; + horizon?: string | null; + created_at?: string | null; + model_count?: number | null; + forecast_count?: number | null; + domains?: string[] | null; + categories?: string[] | null; + subcategories?: string[] | null; + frequency?: string | null; +} + +export interface ChallengeSeries { + series_id: number; + name: string | null; + description: string | null; + frequency: string | null; + horizon: any; + endpoint_prefix: string | null; + start_time: string | null; + end_time: string | null; + registration_start: string | null; + registration_end: string | null; + context_start_time: string | null; + context_end_time: string | null; + domain: string | null; + category: string | null; + subcategory: string | null; +} + +export interface TimeSeriesDataPoint { + ts: string; + value: number; +} + +export interface TimeSeriesData { + data: TimeSeriesDataPoint[]; +} + +export interface ChallengeFilters { + status?: 'active' | 'completed' | 'all'; + searchTerm?: string; + domains?: string[]; + categories?: string[]; + frequencies?: string[]; + horizons?: string[]; + endDateFrom?: string; + endDateTo?: string; + challengeId?: string; +} + +export interface ForecastDataPoint { + ts: string; + y: number; + ci?: any; +} + +export interface ForecastData { + data: ForecastDataPoint[]; + label: string; + current_mase?: number; + model_id?: string; + model_size?: number; + architecture?: string; +} + +export interface ForecastsResponse { + forecasts: { + [modelName: string]: ForecastData; + }; +} + +export interface Model { + readable_id: string; + name: string; + model_size?: number; + architecture?: string; + description?: string; + created_at?: string; +} + +export interface ModelsResponse { + models: Model[]; +} + +export interface ChallengeDefinition { + schedule_id: string; + name: string; + description: string; + domain: string | null; + subdomain: string | null; + context_length: number; + horizon: string; + frequency: string; + id: number; + next_registration_start?: string | null; + next_registration_end?: string | null; +} + +export interface ModelSeriesForecastPoint { + ts: string; + y: number; + ci?: { + "0.025"?: number; + "0.975"?: number; + [key: string]: number | undefined; + }; +} + +export interface ModelSeriesRound { + round_id: number; + round_name: string; + start_time: string; + end_time: string; + series_in_round: boolean; + forecast_exists: boolean; + forecasts: ModelSeriesForecastPoint[] | null; +} + +export interface GroundTruthPoint { + ts: string; + value: number; +} + +export interface ModelSeriesForecastsResponse { + model_id: number; + model_readable_id: string; + model_name: string; + definition_id: number; + definition_name: string; + series_id: number; + series_name: string; + rounds: ModelSeriesRound[]; + ground_truth?: GroundTruthPoint[]; +} + +export interface DefinitionRound { + id: number; + round_name: string; + name: string; + description: string; + status: string; + registration_start: string; + registration_end: string; + start_time: string; + end_time: string; + context_length: number; + horizon: string; + frequency: string; + model_count?: number; + forecast_count?: number; + domains: string[] | null; + categories: string[] | null; + subcategories: string[] | null; +} + +export interface PaginationInfo { + page: number; + page_size: number; + total_items: number; + total_pages: number; + has_next: boolean; + has_previous: boolean; +} + +export interface DefinitionRoundsResponse { + items: DefinitionRound[]; + pagination: PaginationInfo; +} diff --git a/tsconfig.json b/tsconfig.json new file mode 100644 index 0000000000000000000000000000000000000000..3a13f90a773b0facb675bf5b1a8239c8f33d36f5 --- /dev/null +++ b/tsconfig.json @@ -0,0 +1,34 @@ +{ + "compilerOptions": { + "target": "ES2017", + "lib": ["dom", "dom.iterable", "esnext"], + "allowJs": true, + "skipLibCheck": true, + "strict": true, + "noEmit": true, + "esModuleInterop": true, + "module": "esnext", + "moduleResolution": "bundler", + "resolveJsonModule": true, + "isolatedModules": true, + "jsx": "react-jsx", + "incremental": true, + "plugins": [ + { + "name": "next" + } + ], + "paths": { + "@/*": ["./*"] + } + }, + "include": [ + "next-env.d.ts", + "**/*.ts", + "**/*.tsx", + ".next/types/**/*.ts", + ".next/dev/types/**/*.ts", + "**/*.mts" + ], + "exclude": ["node_modules"] +} diff --git a/utils/__init__.py b/utils/__init__.py deleted file mode 100644 index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000 diff --git a/utils/api_client.py b/utils/api_client.py deleted file mode 100644 index 46652fe52787e604960c44eaef6a83b70377f720..0000000000000000000000000000000000000000 --- a/utils/api_client.py +++ /dev/null @@ -1,341 +0,0 @@ -import os -import sys -from enum import Enum -from typing import List, Dict, Any, Optional, Tuple -from datetime import datetime, timedelta -import pandas as pd -import requests - -class ChallengeStatus(Enum): - ACTIVE = "active" - COMPLETED = "completed" - REGISTRATION = "registration" - ANNOUNCED = "announced" - - -class DashboardAPIClient: - """API Client fΓΌr dashboard-api.""" - - def __init__(self): - self._api_url = os.getenv("DASHBOARD_API_URL") - self.api_key = os.getenv("DASHBOARD_API_KEY") - - # Remove trailing slash - if self._api_url.endswith("/"): - self._api_url = self._api_url[:-1] - - print(f"DEBUG: API URL: {self._api_url}", file=sys.stderr) - print(f"DEBUG: API Key configured: {'Yes' if self.api_key else 'No'}", file=sys.stderr) - - self.headers = { - "X-API-Key": self.api_key, - "Content-Type": "application/json" - } - self.timeout = 30 # seconds - - @property - def api_url(self) -> str: - """Property for compatibility with caching functions.""" - return self._api_url - - @property - def database_url(self) -> str: - """Backward compatibility property for cache keys.""" - return self._api_url - - def _get(self, endpoint: str, params: Optional[Dict[str, Any]] = None) -> Any: - """Make GET request to API.""" - url = f"{self._api_url}{endpoint}" - try: - print(f"DEBUG: GET {url} with params: {params}", file=sys.stderr) - response = requests.get(url, headers=self.headers, params=params, timeout=self.timeout) - response.raise_for_status() - return response.json() - except requests.exceptions.RequestException as e: - print(f"ERROR: API request failed: {e}", file=sys.stderr) - raise - - # Challenges - def list_challenges(self) -> List[Dict[str, Any]]: - """List all challenges including aggregates (models/forecasts).""" - print("DEBUG: Calling list_challenges", file=sys.stderr) - try: - data = self._get("/api/v1/challenges") - print(f"DEBUG: list_challenges found {len(data)} challenges.", file=sys.stderr) - if data: - print("DEBUG: Challenges retrieved:", file=sys.stderr) - for r in data: - print(f" - ID: {r.get('challenge_id', 'N/A')}, Status: {r.get('status', 'N/A')}, Desc: {r.get('description', 'N/A')}", file=sys.stderr) - return data - except Exception as e: - print(f"ERROR: in list_challenges: {e}", file=sys.stderr) - return [] - - def list_completed_challenges_in_range(self, since: datetime) -> List[Dict[str, Any]]: - """List completed challenges whose end_time >= since.""" - params = { - "status": ChallengeStatus.COMPLETED.value, - "from": since.isoformat() - } - try: - return self._get("/api/v1/challenges", params=params) - except Exception as e: - print(f"ERROR: in list_completed_challenges_in_range: {e}", file=sys.stderr) - return [] - - def list_active_challenges(self) -> List[Dict[str, Any]]: - """Active challenges with status 'registration' and 'announced'.""" - print("DEBUG: Calling list_active_challenges", file=sys.stderr) - try: - params = {"status": f"{ChallengeStatus.ACTIVE.value}"} - data = self._get("/api/v1/challenges", params=params) - print(f"DEBUG: list_active_challenges found {len(data)} challenges.", file=sys.stderr) - if data: - print("DEBUG: Active challenges retrieved:", file=sys.stderr) - for r in data: - print(f" - ID: {r.get('challenge_id', 'N/A')}, Status: {r.get('status', 'N/A')}, Desc: {r.get('description', 'N/A')}", file=sys.stderr) - return data - except Exception as e: - print(f"ERROR: in list_active_challenges: {e}", file=sys.stderr) - return [] - - def list_upcoming_challenges(self) -> List[Dict[str, Any]]: - """Upcoming challenges with status 'registration' and 'announced'.""" - print("DEBUG: Calling list_upcoming_challenges", file=sys.stderr) - try: - params = {"status": f"{ChallengeStatus.REGISTRATION.value},{ChallengeStatus.ANNOUNCED.value}"} - data = self._get("/api/v1/challenges", params=params) - print(f"DEBUG: list_upcoming_challenges found {len(data)} challenges.", file=sys.stderr) - if data: - print("DEBUG: Upcoming challenges retrieved:", file=sys.stderr) - for r in data: - print(f" - ID: {r.get('challenge_id', 'N/A')}, Status: {r.get('status', 'N/A')}, Desc: {r.get('description', 'N/A')}", file=sys.stderr) - return data - except Exception as e: - print(f"ERROR: in list_upcoming_challenges: {e}", file=sys.stderr) - return [] - - def get_challenge_meta(self, challenge_id: str) -> Optional[Dict[str, Any]]: - """Get metadata for a challenge.""" - try: - return self._get(f"/api/v1/challenges/{challenge_id}") - except requests.exceptions.HTTPError as e: - if e.response.status_code == 404: - return None - raise - except Exception as e: - print(f"ERROR: in get_challenge_meta: {e}", file=sys.stderr) - return None - - def get_challenge_series(self, challenge_id: str) -> List[Dict[str, Any]]: - """Time series for a challenge.""" - try: - return self._get(f"/api/v1/challenges/{challenge_id}/series") - except Exception as e: - print(f"ERROR: in get_challenge_series: {e}", file=sys.stderr) - return [] - - def get_filtered_challenges( - self, - status: Optional[str|List[str]]=None, - from_date: Optional[str]=None, - to_date: Optional[str]=None, - frequency: Optional[str|List[str]]=None, - domain: Optional[str|List[str]]=None, - category: Optional[str|List[str]]=None, - horizon: Optional[str|List[str]]=None, - ) -> List[Dict[str, Any]]: - """Get challenges filtered by various criteria.""" - try: - str_status = ",".join(status) if isinstance(status, list) else status - str_frequency = ",".join(frequency) if isinstance(frequency, list) else frequency - str_domain = ",".join(domain) if isinstance(domain, list) else domain - str_category = ",".join(category) if isinstance(category, list) else category - str_horizon = ",".join(horizon) if isinstance(horizon, list) else horizon - params = { - "status": str_status, - "from": from_date, - "to": to_date, - "frequency": str_frequency, - "domain": str_domain, - "category": str_category, - "horizon": str_horizon - } - return self._get("/api/v1/challenges", params=params) - except Exception as e: - print(f"ERROR: in get_filtered_challenges: {e}", file=sys.stderr) - return [] - - def get_challenge_data_for_series( - self, challenge_id: int, series_id: int, start_time, end_time - ) -> pd.DataFrame: - """Get all relevant data for a series in a challenge for plotting.""" - try: - # Handle both datetime objects and string timestamps - if isinstance(start_time, str): - start_time_str = start_time - elif hasattr(start_time, 'isoformat'): - start_time_str = start_time.isoformat() - else: - start_time_str = str(start_time) - - if isinstance(end_time, str): - end_time_str = end_time - elif hasattr(end_time, 'isoformat'): - end_time_str = end_time.isoformat() - else: - end_time_str = str(end_time) - - params = { - "start_time": start_time_str, - "end_time": end_time_str - } - data = self._get(f"/api/v1/challenges/{challenge_id}/series/{series_id}/data", params=params) - - # Convert to DataFrame - if "data" in data and data["data"]: - df = pd.DataFrame(data["data"]) - df["ts"] = pd.to_datetime(df["ts"], utc=False) - return df - else: - return pd.DataFrame(columns=["ts", "value"]) - except Exception as e: - print(f"ERROR: in get_challenge_data_for_series: {e}", file=sys.stderr) - return pd.DataFrame(columns=["ts", "value"]) - - def get_series_forecasts(self, challenge_id: str, series_id: int) -> Dict[str, Dict[str, pd.DataFrame|str]]: - """Return, per forecast (model/version), the data points as a DataFrame.""" - try: - data = self._get(f"/api/v1/challenges/{challenge_id}/series/{series_id}/forecasts") - - # Convert to Dict[str, DataFrame] - result = {} - if "forecasts" in data: - for model_readable_id, forecast_data in data["forecasts"].items(): - if forecast_data: - df = pd.DataFrame(forecast_data["data"]) - df["ts"] = pd.to_datetime(df["ts"], utc=False) - result[model_readable_id] = {"data": df, "label": forecast_data.get("label", ""), "current_mase": forecast_data.get("current_mase", "")} - return result - except Exception as e: - print(f"ERROR: in get_series_forecasts: {e}", file=sys.stderr) - return {} - - def list_models_for_challenge(self, challenge_id: str) -> List[str]: - """List all unique models for a given challenge.""" - try: - return self._get(f"/api/v1/challenges/{challenge_id}/models") - except Exception as e: - print(f"ERROR: in list_models_for_challenge: {e}", file=sys.stderr) - return [] - - @staticmethod - def granularity_to_timedelta(granularity: Optional[str]) -> timedelta: - """Convert granularity string to timedelta.""" - g = (granularity or "hour").lower() - if "15" in g: - return timedelta(minutes=15) - if g.startswith("h"): - return timedelta(hours=1) - if g.startswith("d"): - return timedelta(days=1) - return timedelta(hours=1) - - def get_global_rankings(self) -> Tuple[Dict[str, List[Dict[str, Any]]], Dict[str, Optional[datetime]]]: - """Compute global model rankings. - - Returns a tuple (results, ranges) where `results` maps a range label to a list of - dict rows (model_name, n_completed, avg_mase) and `ranges` maps the - same labels to the lower-bound datetime. - """ - try: - data = self._get("/api/v1/models/rankings") - - # Reconstruct ranges from response - now = datetime.utcnow() - ranges: Dict[str, Optional[datetime]] = { - "Last 7 days": now - timedelta(days=7), - "Last 30 days": now - timedelta(days=30), - "Last 90 days": now - timedelta(days=90), - "Last 365 days": now - timedelta(days=365), - } - - results = data.get("ranges", {}) - return results, ranges - except Exception as e: - print(f"ERROR: in get_global_rankings: {e}", file=sys.stderr) - return {}, {} - - def get_filter_options(self) -> Dict[str, List[str]]: - """Get available filter options for rankings. - - GET /api/v1/models/rankings-filters (without parameters) - Returns dict with keys: domains, categories, subcategories, frequencies, horizons, time_ranges - """ - try: - # Call the endpoint without any parameters to get filter options - data = self._get("/api/v1/models/ranking-filters") - print(f"DEBUG: get_filter_options raw response: {data}", file=sys.stderr) - print(f"DEBUG: Response type: {type(data)}", file=sys.stderr) - - # Validate that we got the expected structure - if isinstance(data, dict): - expected_keys = ["domains", "categories", "frequencies", "horizons", "time_ranges"] - for key in expected_keys: - if key in data: - print(f"DEBUG: {key} = {data[key]}", file=sys.stderr) - else: - print(f"WARNING: Missing key '{key}' in API response", file=sys.stderr) - - return data - else: - print(f"ERROR: Unexpected data format from filter-rankings: {type(data)}", file=sys.stderr) - return { - "domains": [], - "categories": [], - "frequencies": [], - "horizons": [], - "time_ranges": [] - } - except Exception as e: - print(f"ERROR: in get_filter_options: {e}", file=sys.stderr) - import traceback - traceback.print_exc() - return { - "domains": [], - "categories": [], - "frequencies": [], - "horizons": [], - "time_ranges": [] - } - - def get_filtered_rankings( - self, - domains: Optional[List[str]] = None, - categories: Optional[List[str]] = None, - frequencies: Optional[List[str]] = None, - horizons: Optional[List[str]] = None, - time_range: Optional[str] = None - ) -> List[Dict[str, Any]]: - """Get filtered model rankings.""" - try: - params = {} - if domains: - params["domain"] = ",".join(domains) - if categories: - params["category"] = ",".join(categories) - if frequencies: - params["frequency"] = ",".join(frequencies) - if horizons: - params["horizon"] = ",".join(horizons) - if time_range: - params["time_range"] = time_range - - data = self._get("/api/v1/models/rankings", params=params) - return data.get("rankings", []) - except Exception as e: - print(f"ERROR: in get_filtered_rankings: {e}", file=sys.stderr) - return [] - -def hash_func_dashboard_api_client(obj: DashboardAPIClient) -> int: - return 1 \ No newline at end of file diff --git a/utils/utils.py b/utils/utils.py deleted file mode 100644 index ad60ad8f921c855cca04dad67c75a93d00ea97a6..0000000000000000000000000000000000000000 --- a/utils/utils.py +++ /dev/null @@ -1,217 +0,0 @@ -import pandas as pd -import re -import sys -from datetime import datetime, timezone -from typing import Any, Dict, List, Optional -from zoneinfo import ZoneInfo - -from utils.api_client import ChallengeStatus, DashboardAPIClient - - -def parse_iso8601_duration(duration): - """ - Parse an ISO 8601 duration string (e.g., 'P3Y6M4DT12H30M5S') - into a dictionary and total seconds. - """ - # Regex pattern for ISO 8601 durations - pattern = re.compile( - r'^P' # starts with 'P' - r'(?:(?P\d+)Y)?' # years - r'(?:(?P\d+)M)?' # months (in date part) - r'(?:(?P\d+)W)?' # weeks - r'(?:(?P\d+)D)?' # days - r'(?:T' # start of time part - r'(?:(?P\d+)H)?' # hours - r'(?:(?P\d+)M)?' # minutes - r'(?:(?P\d+)S)?' # seconds - r')?$' # end of string - ) - - match = pattern.match(duration) - if not match: - raise ValueError(f"Invalid ISO 8601 duration: {duration}") - - parts = {k: int(v) if v else 0 for k, v in match.groupdict().items()} - - # Approximate conversions - SECONDS_IN = { - 'years': 365 * 24 * 3600, # 1 year β‰ˆ 365 days - 'months': 30 * 24 * 3600, # 1 month β‰ˆ 30 days - 'weeks': 7 * 24 * 3600, - 'days': 24 * 3600, - 'hours': 3600, - 'minutes': 60, - 'seconds': 1, - } - - total_seconds = sum(parts[k] * SECONDS_IN[k] for k in parts) - - return parts, total_seconds - -def seconds_to_hours(seconds): - """ - Convert seconds to hours. - - Args: - seconds: Number of seconds (int or float) - - Returns: - float: Number of hours - """ - return seconds / 3600 - -def duration_to_max_unit(parts_dict): - """ - Convert a duration dictionary (from parse_iso8601_duration) to a single unit value. - Returns the duration in the smallest unit specified in the original duration. - - For example: - - 23 hours --> "23 Hours" - - 1 day 2 hours --> "26 Hours" (hours is smaller unit) - - 2 days --> "2 Days" - - 1 week 3 days --> "10 Days" (days is smaller unit) - - 7 days --> "1 Week" (only days specified, can be converted to weeks) - - 168 hours --> "168 Hours" (keep as hours since that was the original unit) - - Args: - parts_dict: Dictionary from parse_iso8601_duration with keys: years, months, weeks, days, hours, minutes, seconds - - Returns: - str: Formatted string like "23 Hours" or "2 Days" - """ - # Conversion factors to seconds - SECONDS_IN = { - 'years': 365 * 24 * 3600, - 'months': 30 * 24 * 3600, - 'weeks': 7 * 24 * 3600, - 'days': 24 * 3600, - 'hours': 3600, - 'minutes': 60, - 'seconds': 1, - } - - # Calculate total seconds - total_seconds = sum(parts_dict.get(k, 0) * SECONDS_IN[k] for k in SECONDS_IN) - - if total_seconds == 0: - return "0 Seconds" - - # Unit mappings (key, singular, plural, divisor) - UNIT_MAP = [ - ('years', 'Year', 'Years', 365 * 24 * 3600), - ('months', 'Month', 'Months', 30 * 24 * 3600), - ('weeks', 'Week', 'Weeks', 7 * 24 * 3600), - ('days', 'Day', 'Days', 24 * 3600), - ('hours', 'Hour', 'Hours', 3600), - ('minutes', 'Minute', 'Minutes', 60), - ('seconds', 'Second', 'Seconds', 1), - ] - - # Find the smallest unit that was actually used in the original duration - target_unit = None - for key, singular, plural, divisor in reversed(UNIT_MAP): # Start from smallest - if parts_dict.get(key, 0) > 0: - target_unit = (key, singular, plural, divisor) - break - - # If we found a target unit, convert to that unit - if target_unit: - key, singular, plural, divisor = target_unit - value = total_seconds // divisor - unit_name = singular if value == 1 else plural - return f"{value} {unit_name}" - - # Fallback: use seconds - return f"{total_seconds} Seconds" - -def to_local(dt_val: Any, tz_name: str) -> Optional[datetime]: - if dt_val is None: - return None - try: - tz = ZoneInfo(tz_name) - except Exception: - tz = ZoneInfo("UTC") - # Normalize input to aware datetime - if isinstance(dt_val, pd.Timestamp): - dt = dt_val.to_pydatetime() - elif isinstance(dt_val, datetime): - dt = dt_val - else: - try: - ts = pd.to_datetime(dt_val, utc=True) - dt = ts.to_pydatetime() - except Exception: - return None - if dt.tzinfo is None: - dt = dt.replace(tzinfo=timezone.utc) - try: - return dt.astimezone(tz) - except Exception: - return None - -def get_active_challenges_list(api_client:DashboardAPIClient) -> List[Dict[str, Any]]: - """Get list of active and completed challenges.""" - try: - challenges = api_client.list_active_challenges() - - - # If no challenges from API, return mock data - if not challenges: - print("No challenges from API, using mock data", file=sys.stderr) - challenges = [ - { - 'challenge_id': 'mock-001', - 'status': ChallengeStatus.ACTIVE.value, - 'description': 'Electricity Load Forecasting', - 'n_time_series': 370, - 'model_count': 5, - 'horizon': 24, - 'context_length': 168, - 'granularity': 'hourly', - 'registration_start': '2025-10-01T00:00:00Z', - 'final_evaluation_at': '2025-12-31T23:59:59Z' - }, - { - 'challenge_id': 'mock-002', - 'status': ChallengeStatus.ACTIVE.value, - 'description': 'Weather Prediction Challenge', - 'n_time_series': 50, - 'model_count': 8, - 'horizon': 48, - 'context_length': 336, - 'granularity': 'hourly', - 'registration_start': '2025-09-15T00:00:00Z', - 'final_evaluation_at': '2025-11-30T23:59:59Z' - }, - { - 'challenge_id': 'mock-003', - 'status': ChallengeStatus.COMPLETED.value, - 'description': 'Retail Sales Forecasting', - 'n_time_series': 100, - 'model_count': 12, - 'horizon': 7, - 'context_length': 56, - 'granularity': 'daily', - 'registration_start': '2025-08-01T00:00:00Z', - 'final_evaluation_at': '2025-09-30T23:59:59Z' - } - ] - - return challenges - except Exception as e: - print(f"Error fetching challenges: {e}", file=sys.stderr) - # Return mock data on error - return [ - { - 'challenge_id': 'mock-001', - 'status': ChallengeStatus.ACTIVE.value, - 'description': 'Electricity Load Forecasting', - 'n_time_series': 370, - 'model_count': 5, - 'horizon': 24, - 'context_length': 168, - 'granularity': 'hourly', - 'registration_start': '2025-10-01T00:00:00Z', - 'final_evaluation_at': '2025-12-31T23:59:59Z' - } - ] \ No newline at end of file