import streamlit as st
import numpy as np
import pandas as pd
import plotly.graph_objects as go

# Title of the app
st.title("Waveform Simulator for Diode Clipping Circuit")

# Sidebar for user inputs
st.sidebar.header("Circuit Parameters")
battery_voltage = st.sidebar.number_input("DC Battery Voltage (V)", min_value=-20.0, max_value=20.0, value=5.0, step=0.1)
diode_type = st.sidebar.selectbox("Diode Type", ["Germanium (Ge)", "Silicon (Si)"])
signal_type = st.sidebar.selectbox("Input Signal Type", ["AC", "DC"])

# Diode voltage drops
V_diode = 0.3 if diode_type == "Germanium (Ge)" else 0.7

# Define input voltage points for analysis
vin_points = [10, 8, 6, 5, 4, 3, 2, 1, 0.7, 0.3, 0]
if signal_type == "AC":
    vin_full = vin_points + [0] + [-x for x in vin_points[::-1]]  # Positive and negative half-cycles
else:
    vin_full = vin_points  # DC only (positive values)

# Circuit analysis function
def analyze_circuit(vin, v_bat, v_diode_drop):
    """Analyze a simple diode clipping circuit with battery bias."""
    v_out = []
    v_diode = []
    
    for v in vin:
        # Positive half-cycle or DC: Diode conducts if Vin > Vbat + Vdiode
        if v > (v_bat + v_diode_drop):
            v_o = v_bat  # Clipped at battery voltage
            v_d = v_diode_drop  # Diode forward voltage
        elif v < -v_diode_drop and signal_type == "AC":
            # Negative half-cycle: Diode conducts in reverse (idealized model)
            v_o = v  # Passes through (no clipping in this simple model)
            v_d = 0  # Diode off
        else:
            # Diode off: Vout = Vin (within battery bounds)
            v_o = v
            v_d = 0
        
        v_out.append(v_o)
        v_diode.append(v_d)
    
    return v_diode, v_out

# Perform analysis
v_diode_values, v_out_values = analyze_circuit(vin_full, battery_voltage, V_diode)

# Create table
data = {
    "V[in] (V)": vin_full,
    f"V[{diode_type[:2]}] (V)": v_diode_values,
    "V[out] (V)": v_out_values
}
df = pd.DataFrame(data)
st.subheader("Point-to-Point Analysis Table")
st.dataframe(df.style.format("{:.2f}"))

# Waveform plotting
fig = go.Figure()
fig.add_trace(go.Scatter(x=np.arange(len(vin_full)), y=vin_full, mode='lines+markers', name='V[in]', line=dict(color='blue')))
fig.add_trace(go.Scatter(x=np.arange(len(vin_full)), y=v_out_values, mode='lines+markers', name='V[out]', line=dict(color='red')))
fig.update_layout(
    title="Input and Output Waveforms",
    xaxis_title="Sample Points",
    yaxis_title="Voltage (V)",
    legend=dict(x=0, y=1),
    template="plotly_white"
)
st.plotly_chart(fig)

# Explanation
st.subheader("How It Works")
st.write(f"""
- **Input Signal**: {signal_type}. For AC, both positive and negative cycles are analyzed; for DC, only positive values are used.
- **Diode**: {diode_type} with a forward voltage drop of {V_diode}V.
- **Battery**: Clips the output at {battery_voltage}V when the diode conducts.
- **Analysis**: For each V[in], the output V[out] is calculated based on diode conduction and battery bias.
- **Waveform**: Blue line is V[in], red line is V[out].
""")