Update app.py

app.py

@@ -2,27 +2,27 @@
 import gradio as gr
 import requests
 import pandas as pd
+import numpy as np
 from datetime import datetime, timedelta
 import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
 
 def get_weather_data(station_id, hours=72):
     """
     Fetch weather data from NWS API
     """
-    # NWS API requires a user agent header
     headers = {
         'User-Agent': '(Weather Data Fetcher, contact@yourdomain.com)',
         'Accept': 'application/json'
     }
     
-    # First, get the station details
     station_url = f'https://api.weather.gov/stations/{station_id}'
     try:
         response = requests.get(station_url, headers=headers)
         response.raise_for_status()
         station_data = response.json()
         
-        # Get observations
         observations_url = f'https://api.weather.gov/stations/{station_id}/observations'
         params = {
             'limit': hours,
@@ -34,7 +34,6 @@ def get_weather_data(station_id, hours=72):
         
         data = response.json()
         
-        # Extract relevant information
         records = []
         for obs in data['features']:
             props = obs['properties']
@@ -44,28 +43,99 @@ def get_weather_data(station_id, hours=72):
                 'relative_humidity': props['relativeHumidity']['value'],
                 'wind_speed': props['windSpeed']['value'],
                 'wind_direction': props['windDirection']['value'],
-                'barometric_pressure': props['barometricPressure']['value']
+                'barometric_pressure': props['barometricPressure']['value'],
+                'snow_depth': props.get('snowDepth', {}).get('value'),
+                'snow_accumulation': props.get('snowfall', {}).get('value')
             }
             records.append(record)
             
         df = pd.DataFrame(records)
         df['timestamp'] = pd.to_datetime(df['timestamp'])
         
-        # Convert temperature from Celsius to Fahrenheit
-        df['temperature'] = (df['temperature'] * 9/5) + 32
+        # Convert units to imperial
+        df['temperature'] = (df['temperature'] * 9/5) + 32  # C to F
+        df['wind_speed'] = df['wind_speed'] * 2.237  # m/s to mph
+        df['snow_depth'] = df['snow_depth'] * 39.3701  # meters to inches
+        df['snow_accumulation'] = df['snow_accumulation'] * 39.3701  # meters to inches
+        
+        # Calculate cumulative snow accumulation
+        df['cumulative_snow'] = df['snow_accumulation'].fillna(0).cumsum()
         
         return df, None
         
     except requests.exceptions.RequestException as e:
         return None, f"Error fetching data: {str(e)}"
 
-def create_plot(df):
+def create_plots(df):
     """
-    Create an interactive plot using plotly
+    Create interactive plots using plotly
     """
-    fig = px.line(df, x='timestamp', y='temperature',
-                  title='Temperature Over Time',
-                  labels={'timestamp': 'Time', 'temperature': 'Temperature (°F)'})
+    # Create figure with secondary y-axis
+    fig = make_subplots(rows=3, cols=1, 
+                       subplot_titles=('Temperature Over Time', 
+                                     'Wind Speed Over Time',
+                                     'Snow Accumulation Over Time'),
+                       vertical_spacing=0.1,
+                       heights=[0.33, 0.33, 0.33])
+
+    # Add temperature trace
+    fig.add_trace(
+        go.Scatter(x=df['timestamp'], y=df['temperature'],
+                  name='Temperature', line=dict(color='red')),
+        row=1, col=1
+    )
+
+    # Add wind speed trace
+    fig.add_trace(
+        go.Scatter(x=df['timestamp'], y=df['wind_speed'],
+                  name='Wind Speed', line=dict(color='blue')),
+        row=2, col=1
+    )
+
+    # Add snow accumulation trace
+    fig.add_trace(
+        go.Scatter(x=df['timestamp'], y=df['cumulative_snow'],
+                  name='Cumulative Snow', line=dict(color='purple')),
+        row=3, col=1
+    )
+
+    # Update layout
+    fig.update_layout(
+        height=900,
+        showlegend=True,
+        title_text="Weather Conditions Over Time"
+    )
+
+    # Update axes labels
+    fig.update_yaxes(title_text="Temperature (°F)", row=1, col=1)
+    fig.update_yaxes(title_text="Wind Speed (mph)", row=2, col=1)
+    fig.update_yaxes(title_text="Snow Accumulation (inches)", row=3, col=1)
+    fig.update_xaxes(title_text="Time", row=3, col=1)
+
+    return fig
+
+def create_wind_rose(df):
+    """
+    Create a wind rose diagram
+    """
+    # Create wind direction bins
+    direction_bins = np.arange(0, 361, 45)
+    df['direction_bin'] = pd.cut(df['wind_direction'], 
+                                bins=direction_bins, 
+                                labels=['N', 'NE', 'E', 'SE', 'S', 'SW', 'W', 'NW'])
+    
+    # Calculate average wind speed for each direction
+    wind_stats = df.groupby('direction_bin')['wind_speed'].agg(['mean', 'count']).reset_index()
+    
+    # Create wind rose
+    fig = px.bar_polar(wind_stats,
+                       r="mean",
+                       theta="direction_bin",
+                       color="mean",
+                       title="Wind Rose Diagram",
+                       color_continuous_scale="blues")
+    
+    fig.update_layout(height=400)
     return fig
 
 def fetch_and_display(station_id, hours):
@@ -75,17 +145,19 @@ def fetch_and_display(station_id, hours):
     df, error = get_weather_data(station_id, hours)
     
     if error:
-        return None, error
+        return None, None, error
     
     if df is not None and not df.empty:
-        fig = create_plot(df)
-        return fig, "Data fetched successfully!"
+        time_series = create_plots(df)
+        wind_rose = create_wind_rose(df)
+        return time_series, wind_rose, "Data fetched successfully!"
     
-    return None, "No data available for the specified parameters."
+    return None, None, "No data available for the specified parameters."
 
 # Create Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Weather Data Viewer")
+    gr.Markdown("Displays temperature, wind speed, and snow accumulation data from NWS stations")
     
     with gr.Row():
         station_id = gr.Textbox(label="Station ID", value="YCTIM")
@@ -93,13 +165,17 @@ with gr.Blocks() as demo:
                          label="Hours of Data", step=1)
     
     fetch_btn = gr.Button("Fetch Data")
-    plot = gr.Plot()
+    
+    with gr.Row():
+        time_series_plot = gr.Plot()
+        wind_rose_plot = gr.Plot()
+    
     message = gr.Textbox(label="Status")
     
     fetch_btn.click(
         fn=fetch_and_display,
         inputs=[station_id, hours],
-        outputs=[plot, message]
+        outputs=[time_series_plot, wind_rose_plot, message]
     )
 
 # Launch the app