app.py

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

def calculate_output(vin):
    v_ge = np.where(vin >= 0.3, 0.3, np.where(vin < 0, vin, 0))
    v_o = np.where((vin >= 0.3) | (vin < 0), 0, 6)
    return v_ge, v_o

def main():
    st.title("🇩🇪 Germanium Transistor Waveform Simulator")
    st.caption("Analyze clipping behavior of Ge transistor (V_Ge = 0.3V) with 6V DC supply")

    # User inputs
    amplitude = st.slider("Input Amplitude (V)", 0, 15, 10)
    time = np.linspace(0, 2*np.pi, 1000)

    # Generate input waveform
    vin = amplitude * np.sin(time)
    
    # Calculate outputs
    v_ge, v_o = calculate_output(vin)

    # Create table data
    sample_points = [10,8,6,5,4,3,2,1,0.7,0.3,0,-0.3,-0.7,-1,-2,-3,-4,-5,-6,-8,-10]
    table_data = []
    for point in sample_points:
        v_ge_val = 0.3 if point >= 0.3 else (point if point < 0 else 0)
        v_o_val = 0 if (point >= 0.3 or point < 0) else 6
        table_data.append([point, round(v_ge_val, 2), v_o_val])

    # Display results
    col1, col2 = st.columns(2)
    
    with col1:
        st.subheader("Waveforms")
        fig, ax = plt.subplots(figsize=(8, 4))
        ax.plot(time, vin, label='Input (V_in)')
        ax.plot(time, v_o, label='Output (V_o)', color='red')
        ax.set_xlabel('Time')
        ax.set_ylabel('Voltage (V)')
        ax.legend()
        ax.grid(True)
        st.pyplot(fig)

    with col2:
        st.subheader("Data Table")
        df = pd.DataFrame(table_data, columns=["V_in (V)", "V_Ge (V)", "V_o (V)"])
        st.dataframe(df.style.format({"V_Ge": "{:.2f}", "V_o": "{:.0f}"}), height=600)

    st.markdown("### Circuit Behavior Summary")
    st.write("""
    - **Positive Half Cycle (V_in ≥ 0):**
        - Clipped to 0V when input ≥ 0.3V
        - Output stays at 6V when input < 0.3V
    - **Negative Half Cycle (V_in < 0):**
        - Output always remains at 6V
    - Germanium forward voltage (V_Ge) = 0.3V
    """)

if __name__ == "__main__":
    main()