add prediction subpage

pages/Vorhersage.py

@@ -0,0 +1,112 @@
+import streamlit as st
+import requests
+import pandas as pd
+import pydeck as pdk
+
+# Base URL for PegelOnline API
+BASE_API_URL = "https://pegelonline.wsv.de/webservices/rest-api/v2"
+
+def fetch_forecasts(station_id):
+    """
+    Fetches the forecast data for a specific station.
+    """
+    url = f"{BASE_API_URL}/stations/{station_id}/WV/measurements.json"
+    response = requests.get(url)
+    if response.status_code == 200:
+        data = response.json()
+        # Filter only forecast data
+        forecasts = [
+            {
+                "initialized": item["initialized"],
+                "timestamp": item["timestamp"],
+                "value": item["value"],
+            }
+            for item in data if item["type"] == "forecast"
+        ]
+        return pd.DataFrame(forecasts)
+    else:
+        return pd.DataFrame()  # Return an empty DataFrame on error
+
+# Streamlit app with subpage
+def main():
+    st.title("RiverRadar - Water Level Forecasts")
+
+    st.subheader("Pegel Forecast Map")
+
+    # Input for station ID
+    station_id = st.text_input(
+        "Enter Pegel Station ID",
+        "1d26e504-7f9e-480a-b52c-5932be6549ab",  # Default value for demo
+    )
+    
+    # Fetch forecasts for the given station
+    st.write("Fetching forecast data...")
+    forecasts_df = fetch_forecasts(station_id)
+
+    if not forecasts_df.empty:
+        st.success("Forecast data loaded!")
+        
+        # Format timestamps and add as columns
+        forecasts_df["timestamp"] = pd.to_datetime(forecasts_df["timestamp"])
+        forecasts_df["hour"] = forecasts_df["timestamp"].dt.hour
+
+        # Display forecast graph
+        st.write("### Forecast Data as Interactive Graph")
+
+        # Plot the forecast data
+        if not forecasts_df.empty:
+            import altair as alt
+
+            # Create an Altair line chart
+            chart = alt.Chart(forecasts_df).mark_line(point=True).encode(
+                x=alt.X("timestamp:T", title="Time"),
+                y=alt.Y("value:Q", title="Water Level (cm)"),
+                tooltip=["timestamp:T", "value:Q"]
+            ).properties(
+                title="Water Level Predictions",
+                width=700,
+                height=400
+            )
+
+            # Display the chart
+            st.altair_chart(chart, use_container_width=True)
+        else:
+            st.warning("No forecast data available for this station.")
+
+        # Map visualization
+        st.write("### Forecast Visualization on Map")
+
+        # Dummy station location (Replace with real station data if available)
+        station_location = {
+            "latitude": 52.520008,
+            "longitude": 13.404954,  # Berlin coordinates for demo
+        }
+
+        # Create a PyDeck layer
+        layer = pdk.Layer(
+            "ScatterplotLayer",
+            data=forecasts_df,
+            get_position=[station_location["longitude"], station_location["latitude"]],
+            get_radius=2000,
+            get_color=[255, 0, 0, 140],
+            pickable=True,
+        )
+
+        # Map settings
+        view_state = pdk.ViewState(
+            latitude=station_location["latitude"],
+            longitude=station_location["longitude"],
+            zoom=6,
+            pitch=0,
+        )
+        r = pdk.Deck(
+            layers=[layer],
+            initial_view_state=view_state,
+            tooltip={"text": "Water Level: {value} cm"},
+        )
+        st.pydeck_chart(r)
+    else:
+        st.warning("No forecast data available for this station.")
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -3,3 +3,4 @@ requests
 pandas
 geopandas
 pydeck
+altair