Added a Climate Statistics Analyzer project

Domains/ClimateAnalyzer/climate.py

@@ -0,0 +1,371 @@
+import streamlit as st
+import pandas as pd
+import numpy as np
+import plotly.express as px
+import plotly.graph_objects as go
+from datetime import datetime, timedelta
+
+# --- Configuration and Setup ---
+
+# Initialize session state for custom locations and their base data
+if 'available_locations' not in st.session_state:
+    st.session_state['available_locations'] = ["New York, USA", "Mumbai, India", "London, UK", "Sydney, Australia"]
+if 'custom_city_bases' not in st.session_state:
+    st.session_state['custom_city_bases'] = {}
+
+
+# Set Streamlit page config (using default light theme)
+st.set_page_config(
+    page_title="Climate Change Forecasting Dashboard",
+    page_icon="🌍",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Define a set of colors optimized for the default light theme
+COLOR_PRIMARY = '#1f77b4'   # Streamlit default blue
+COLOR_SECONDARY = '#ff7f0e' # Streamlit default orange (Good for temperature)
+COLOR_TERTIARY = '#2ca02c'  # Streamlit default green (Good for humidity/rainfall)
+COLOR_WIND = '#d62728'      # Streamlit default red (Good for wind speed)
+
+# Custom CSS for light mode look (primarily for font size and structure)
+st.markdown(f"""
+    <style>
+        /* Main page title font */
+        .big-font {{
+            font-size: 36px !important;
+            font-weight: bold;
+            color: {COLOR_PRIMARY}; 
+        }}
+        /* Minimal styling for metric cards in light mode for structure */
+        div[data-testid="stMetric"] {{
+            border-radius: 10px;
+            padding: 10px 15px;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1); /* Subtle shadow for lift */
+            border-left: 5px solid {COLOR_PRIMARY};
+        }}
+        /* User Profile Box */
+        .user-profile-box {{
+            padding: 10px; 
+            border: 1px solid #ccc; /* Light border */
+            border-radius: 8px; 
+            background-color: #f0f2f6; /* Very light gray background */
+            margin-bottom: 20px;
+        }}
+        .user-profile-box p, .user-profile-box small {{
+            color: #333333; /* Dark text for contrast */
+        }}
+    </style>
+    """, unsafe_allow_html=True)
+
+
+# --- Dummy Data Generation Functions ---
+
+def generate_kpi_data(location):
+    """Generates dummy KPI data based on location, dynamically checking custom city bases."""
+    # Base data for hardcoded cities
+    base_data = {
+        'New York, USA': {'temp': 25, 'rain': 10}, 
+        'Mumbai, India': {'temp': 30, 'rain': 50}, 
+        'London, UK': {'temp': 18, 'rain': 5}, 
+        'Sydney, Australia': {'temp': 22, 'rain': 15}
+    }
+
+    # Determine base temperature and rainfall
+    if location in st.session_state['custom_city_bases']:
+        custom_bases = st.session_state['custom_city_bases'][location]
+        base_temp = custom_bases['base_temp']
+        base_rain = custom_bases['base_rain']
+    else:
+        # Use hardcoded base or a safe default if not found
+        temp_data = base_data.get(location, {'temp': 20, 'rain': 15})
+        base_temp = temp_data['temp']
+        base_rain = temp_data['rain']
+
+    return {
+        'Current Temp (°C)': np.round(base_temp + np.random.uniform(-3, 3), 1),
+        'Air Quality Index (AQI)': np.random.randint(40, 120),
+        '24h Rainfall (mm)': np.round(base_rain + np.random.uniform(-5, 5), 1),
+        'Humidity (%)': np.random.randint(50, 90),
+        'Location': location
+    }
+
+def generate_time_series_data(days=365):
+    """Generates dummy time-series data for trend charts."""
+    dates = [datetime.now() - timedelta(days=days - i) for i in range(days)]
+    df = pd.DataFrame({
+        'Date': dates,
+        'Temperature (°C)': np.round(20 + 5 * np.sin(np.arange(days) * 2 * np.pi / 365) + np.random.normal(0, 1.5, days), 1),
+        'Rainfall (mm)': np.round(np.abs(5 + 10 * np.sin(np.arange(days) * 2 * np.pi / 365 * 2) + np.random.normal(0, 5, days)), 1),
+        'Humidity (%)': np.round(60 + 15 * np.cos(np.arange(days) * 2 * np.pi / 365) + np.random.normal(0, 5, days), 1),
+        'Wind Speed (km/h)': np.round(5 + 10 * np.random.rand(days), 1)
+    })
+    df.set_index('Date', inplace=True)
+    return df
+
+
+# --- Plotly Chart Functions ---
+
+def create_mini_line_chart(df, column, color):
+    """Creates a small Plotly line chart for KPI trends."""
+    fig = px.line(df, y=column, height=80)
+    fig.update_traces(line_color=color, line_width=2)
+    fig.update_layout(
+        margin=dict(l=0, r=0, t=5, b=5),
+        plot_bgcolor='rgba(0,0,0,0)',
+        paper_bgcolor='rgba(0,0,0,0)',
+        showlegend=False,
+        yaxis={'visible': False},
+        xaxis={'visible': False},
+        hovermode="x unified"
+    )
+    return fig
+
+def create_comparison_chart(df_comp):
+    """Creates a grouped bar chart for regional comparison."""
+    df_melt = df_comp.melt(id_vars='Location', var_name='Metric', value_name='Value')
+
+    fig = px.bar(
+        df_melt,
+        x='Location',
+        y='Value',
+        color='Metric',
+        barmode='group',
+        title='Regional KPI Comparison',
+        template='plotly_white',
+        height=550,
+        color_discrete_map={
+            'Current Temp (°C)': COLOR_SECONDARY, 
+            '24h Rainfall (mm)': COLOR_PRIMARY,
+            'Humidity (%)': COLOR_TERTIARY
+        }
+    )
+    fig.update_layout(
+        xaxis_title="Region",
+        yaxis_title="Value",
+        legend_title="Metric"
+    )
+    return fig
+
+def create_residual_chart(df_residuals):
+    """Creates a placeholder scatter plot for residuals."""
+    fig = px.scatter(
+        df_residuals,
+        x=df_residuals.index,
+        y='Residuals',
+        title='Model Residuals Scatter Plot (Placeholder)',
+        height=400,
+        template='plotly_white'
+    )
+    fig.update_traces(marker=dict(size=8, color=COLOR_SECONDARY, opacity=0.8))
+    fig.update_layout(
+        xaxis_title="Observation Index",
+        yaxis_title="Residual Value",
+        hovermode="closest"
+    )
+    return fig
+
+
+# --- Page Definitions ---
+
+def page_overview():
+    """Page 1: Overview Dashboard"""
+    st.markdown('<p class="big-font">🌿 Real-time Overview Dashboard</p>', unsafe_allow_html=True)
+    st.markdown("Monitor real-time conditions and 7-day trends for the selected location.")
+    st.info("💡 **NOTE:** All data is randomly generated for this prototype, but values are adjusted per location for demonstration.")
+
+    # Use dynamically updated list of locations
+    available_locations = st.session_state['available_locations']
+    col_loc, col_empty = st.columns([1, 3])
+    with col_loc:
+        location = st.selectbox("🌍 Select/Enter Location", available_locations)
+
+    kpi_data = generate_kpi_data(location)
+    df_trend = generate_time_series_data(days=7)
+
+    st.markdown("---")
+
+    st.subheader(f"Current Status in **{location}**")
+    col1, col2, col3, col4 = st.columns(4)
+
+    kpi_map = {
+        col1: {"label": "Current Temp (°C)", "value": kpi_data['Current Temp (°C)'], "icon": "🌡️", "trend_col": "Temperature (°C)", "color": COLOR_SECONDARY},
+        col2: {"label": "Air Quality Index (AQI)", "value": kpi_data['Air Quality Index (AQI)'], "icon": "💨", "trend_col": "Wind Speed (km/h)", "color": COLOR_WIND},
+        col3: {"label": "24h Rainfall (mm)", "value": kpi_data['24h Rainfall (mm)'], "icon": "💧", "trend_col": "Rainfall (mm)", "color": COLOR_PRIMARY},
+        col4: {"label": "Humidity (%)", "value": kpi_data['Humidity (%)'], "icon": "💧", "trend_col": "Humidity (%)", "color": COLOR_TERTIARY},
+    }
+
+    for col, data in kpi_map.items():
+        with col:
+            st.metric(label=f"{data['icon']} {data['label']}", value=data['value'])
+            st.caption("Last 7-Day Trend")
+            st.plotly_chart(create_mini_line_chart(df_trend, data['trend_col'], data['color']), use_container_width=True)
+
+    st.markdown("---")
+
+
+def page_comparison():
+    """Page 2: Regional Comparison"""
+    st.markdown('<p class="big-font">🌐 Regional Comparison</p>', unsafe_allow_html=True)
+    st.markdown("Compare current climate metrics across different geographical locations.")
+
+    # Use dynamically updated list of locations
+    available_locations = st.session_state['available_locations']
+
+    selected_locations = st.multiselect(
+        "Select Locations for Comparison",
+        options=available_locations,
+        default=available_locations
+    )
+
+    if not selected_locations:
+        st.warning("Please select at least one location for comparison.")
+        return
+
+    st.markdown("---")
+
+    comparison_data = [generate_kpi_data(loc) for loc in selected_locations]
+    df_comparison = pd.DataFrame(comparison_data).drop(columns=['Air Quality Index (AQI)'])
+
+    st.subheader("Current Condition Metrics by Region")
+    st.plotly_chart(create_comparison_chart(df_comparison), use_container_width=True)
+
+    st.markdown("---")
+
+    st.subheader("Comparison Table")
+    st.dataframe(df_comparison.set_index('Location'), use_container_width=True)
+
+
+def page_model_performance():
+    """Page 3: Model Performance (Placeholder)"""
+    st.markdown('<p class="big-font">📊 Model Performance Metrics</p>', unsafe_allow_html=True)
+    st.markdown("An overview of the forecasting model's accuracy and performance indicators.")
+
+    mae = round(np.random.uniform(1.5, 3.5), 2)
+    rmse = round(np.random.uniform(2.0, 4.5), 2)
+    r2 = round(np.random.uniform(0.85, 0.95), 2)
+
+    st.markdown("---")
+
+    st.subheader("Key Accuracy Metrics")
+    col1, col2, col3 = st.columns(3)
+
+    col1.metric("Mean Absolute Error (MAE)", f"{mae} °C", delta=f"-{round(mae*0.1, 2)}", delta_color="inverse")
+    col2.metric("Root Mean Square Error (RMSE)", f"{rmse} °C", delta=f"-{round(rmse*0.15, 2)}", delta_color="inverse")
+    col3.metric("R-squared ($R^2$)", f"{r2}", delta=f"+{round(r2*0.01, 2)}", delta_color="normal")
+
+    st.markdown("---")
+
+    st.subheader("Model Residuals Analysis")
+    df_residuals = pd.DataFrame({
+        'Residuals': np.random.normal(0, 2, 100),
+        'Index': np.arange(100)
+    }).set_index('Index')
+
+    st.plotly_chart(create_residual_chart(df_residuals), use_container_width=True)
+
+
+def page_customization():
+    """Page 4: Customization - Add New City"""
+    st.markdown('<p class="big-font">✨ Custom City Configuration</p>', unsafe_allow_html=True)
+    st.markdown("Add a new city to the dashboard for real-time monitoring and comparison.")
+
+    st.markdown("---")
+    st.subheader("Add New City")
+
+    new_city = st.text_input("Enter City Name and Country (e.g., Tokyo, Japan)")
+
+    # Simple input fields for dummy base data
+    st.subheader("Define Base Climate Profile (For Dummy Data Generation)")
+    st.caption("These values set the average conditions the dashboard will generate data around.")
+    col1, col2 = st.columns(2)
+    with col1:
+        base_temp = st.number_input("Base Average Temperature (°C)", min_value=-50, max_value=50, value=25)
+    with col2:
+        base_rain = st.number_input("Base 24h Rainfall (mm)", min_value=0, max_value=100, value=15)
+
+    if st.button("Add City to Dashboard", use_container_width=True, key="add_city_btn"):
+        city_name = new_city.strip()
+        if city_name and city_name not in st.session_state['available_locations']:
+
+            # Store base data for the new city
+            st.session_state['custom_city_bases'][city_name] = {
+                'base_temp': base_temp,
+                'base_rain': base_rain
+            }
+
+            st.session_state['available_locations'].append(city_name)
+            st.success(f"City **{city_name}** added successfully! Check the Overview and Comparison tabs.")
+        elif city_name and city_name in st.session_state['available_locations']:
+            st.warning(f"City **{city_name}** is already on the list.")
+        else:
+            st.error("Please enter a valid city name.")
+
+    st.markdown("---")
+
+    st.subheader("Currently Monitored Locations")
+    st.info(", ".join(st.session_state['available_locations']))
+
+
+def page_settings():
+    """Page 5: Settings (Kept simple)"""
+    st.markdown('<p class="big-font">⚙️ Settings</p>', unsafe_allow_html=True)
+    st.markdown("Customize your dashboard experience here.")
+
+    st.markdown("---")
+
+    st.subheader("Data & Units")
+    unit_choice = st.radio("🌡️ **Temperature Units**", ('°C (Celsius)', '°F (Fahrenheit)'))
+    st.info(f"The dashboard is currently displaying data in **{unit_choice.split(' ')[0]}**.")
+
+    st.markdown("---")
+
+    st.subheader("Data Management")
+    st.button("📦 **Download Configuration File** (Placeholder)")
+    st.button("🔄 **Reset Dashboard to Default** (Placeholder)")
+
+
+# --- Main Application Logic ---
+
+# 1. Sidebar Navigation & User Profile
+with st.sidebar:
+    st.image("https://upload.wikimedia.org/wikipedia/commons/thumb/e/ef/Globe_icon_-_blue.svg/512px-Globe_icon_-_blue.svg.png", width=50) 
+    st.markdown("# 🌍 Climate Forecaster")
+    st.markdown("---")
+
+    # 👤 User Information Details Sidebar (Light Mode Styling)
+    st.markdown("## 👤 User Profile")
+    st.markdown(f"""
+        <div class="user-profile-box">
+            <p style="color: #333333; font-weight: bold;">John Doe</p>
+            <small style="color: #666666;">Analyst @ Global Climate Init.</small><br>
+            <small style="color: #666666;">ID: JDOE-4903A</small>
+        </div>
+    """, unsafe_allow_html=True)
+    st.slider("Notification Level", 0, 10, 5, help="Set the sensitivity for anomaly alerts.")
+    st.button("⚙️ Manage Account Settings", use_container_width=True)
+
+    st.markdown("---")
+
+    # 🧭 Navigation
+    st.markdown("## 🧭 Navigation")
+    pages = {
+        "🌿 Overview Dashboard": page_overview,
+        "🌐 Regional Comparison": page_comparison, 
+        "📊 Model Performance": page_model_performance,
+        "✨ Customization": page_customization, # Added new page
+        "⚙️ Settings": page_settings,
+    }
+
+    # Ensure selection defaults to the first available page if the old one was selected
+    default_index = 0
+    if "selection" in st.session_state and st.session_state.selection not in pages.keys():
+        st.session_state.selection = list(pages.keys())[default_index]
+
+    selection = st.radio("Select View", list(pages.keys()), index=default_index, key="selection")
+    st.markdown("---")
+    st.caption("Prototype built with Streamlit & Plotly.")
+
+
+# 2. Execute selected page function
+pages[selection]()