st_app.py

import streamlit as st
import pandas as pd
import xgboost as xgb
import os

# Must be the first Streamlit command
st.set_page_config(
   page_title="BASED",
   page_icon="🌊",
   layout="wide",
   initial_sidebar_state="expanded",
)

try:
    # Load model directly with XGBoost
    model = xgb.Booster()
    model.load_model("based_us_sans_trampush_early_stopping_combat_overfitting.ubj")
except Exception as e:
    st.error(f"Error loading model: {str(e)}")
    st.stop()

def predict(slope, discharge, width):
    """
    Function for making predictions using the XGBoost model.
    """
    # Prepare the input features for prediction
    input_data = pd.DataFrame({
        'width': [width], 
        'slope': [slope], 
        'discharge': [discharge]
    }, dtype=float)
    
    # Convert to DMatrix for prediction
    dmat = xgb.DMatrix(input_data)
    
    # Make prediction
    prediction = model.predict(dmat)
    
    return {"depth": float(prediction[0])}

def main():
    st.title("🌊 Boost-Assisted Stream Estimator for Depth (BASED)")

    st.sidebar.title("Input Values")
    
    # Add help text for each input
    slope_help = """Channel slope [m/m]. Valid range: 1e-6 to 0.1
    • Typical lowland rivers: 0.0001-0.001
    • Mountain streams: 0.001-0.02
    """
    discharge_help = """Water discharge [m³/s]. Valid range: 0.1 to 100,000
    • Small streams: 0.1-10
    • Medium rivers: 10-1,000
    • Large rivers: 1,000-100,000
    """
    width_help = """Channel width [m]. Valid range: 1 to 10,000
    • Small streams: 1-10
    • Medium rivers: 10-100
    • Large rivers: 100-1,000+
    """
    
    slope = st.sidebar.text_input(
        "Slope [m/m]:", "0.0001",
        help=slope_help
    )
    discharge = st.sidebar.text_input(
        "Discharge [m³/s]:", "400",
        help=discharge_help
    )
    width = st.sidebar.text_input(
        "Width [m]:", "250",
        help=width_help
    )

    # Add typical ranges info box
    with st.sidebar.expander("ℹ️ About Input Ranges"):
        st.markdown("""
        **Typical Ranges by River Type:**
        
        *Mountain Streams*
        - Slope: 0.001-0.02
        - Width: 1-20m
        - Discharge: 0.1-50 m³/s
        
        *Meandering Rivers*
        - Slope: 0.0001-0.001
        - Width: 20-200m
        - Discharge: 50-1000 m³/s
        
        *Large Rivers*
        - Slope: 0.00001-0.0001
        - Width: 200-2000m
        - Discharge: 1000-100000 m³/s
        """)

    if slope and discharge and width:
        try:
            slope = float(slope)
            discharge = float(discharge)
            width = float(width)

            prediction = predict(slope, discharge, width)
            depth = prediction["depth"]

            # Add confidence information
            st.metric("Predicted Depth", f"{depth:.2f} m")
            st.metric("Width/Depth Ratio", f"{width/depth:.2f}")
            

        except ValueError:
            st.error("Please enter valid numeric values for all inputs.")

    st.subheader("📊 Model Performance")
    st.markdown("- **MAE:** 33 cm\n- **RMSE:** 102 cm\n- **R²:** 0.89\n- **MAPE:** 20%")
    st.image("img/BASED_validation.png", caption="BASED Validation Results", use_container_width=True)
    st.caption("Image source: Gearon, J.H. et al. Rules of river avulsion change downstream. Nature 634, 91–95 (2024). https://doi.org/10.1038/s41586-024-07964-2")
    
    st.subheader("ℹ️ Model Information")
    st.markdown("""
    **Version:** 1.0.0
    
    **Citation:**
    ```
    Gearon, James H. (2024). Boost-Assisted Stream Estimator for Depth (BASED) [Computer software]. Version 1.0.0. https://github.com/JakeGearon/based-api
    ```
    
    **Description:** BASED is an XGBoost regressor designed for predicting channel depth using channel width, slope, and discharge.
    """)

    st.markdown("---")
    st.subheader("⚠️ Disclaimer")
    st.markdown("""
    BASED is provided for informational and research purposes only. Do not use these predictions as the sole basis for critical decisions. 
    Always consult qualified professionals and conduct proper field measurements. The creators are not responsible for consequences arising 
    from the use or misuse of this tool.
    """)

if __name__ == "__main__":
    main()