import gradio as gr
import numpy as np
import matplotlib.pyplot as plt

def calculate_and_plot(t1, a1, t2, a2):
    try:
        # الحسابات الأساسية
        k = np.log(a1 / a2) / (t2 - t1)
        a0 = a1 / np.exp(-k * t1)
        tia = a0 / k

        result = f"""
        ### ✅ Results
        - **A₀ (initial activity):** {a0:.2f} MBq  
        - **k (washout rate):** {k:.5f} / hour  
        - **TIA:** {tia:.2f} MBq·h  
        """

        # إنشاء نقاط الرسم
        t_points = np.linspace(0, max(t2 + 40, 200), 100)
        a_points = a0 * np.exp(-k * t_points)

        # رسم المنحنى باستخدام matplotlib
        fig, ax = plt.subplots(figsize=(6, 4))
        ax.plot(t_points, a_points, label="Fitted Curve", color='blue')
        ax.scatter([t1, t2], [a1, a2], color='red', label="Input Points")
        ax.set_xlabel("Time (hours)")
        ax.set_ylabel("Activity (MBq)")
        ax.set_title("Mono-Exponential Washout Curve")
        ax.grid(True)
        ax.legend()
        plt.tight_layout()

        return result, fig

    except Exception:
        return "⚠️ Error: Please check your inputs.", None

with gr.Blocks() as demo:
    gr.Markdown("# ⚛️ Lu-177 Dosimetry Tool\nEstimate Time-Integrated Activity (TIA) from Two SPECT Time Points")

    with gr.Row():
        t1 = gr.Number(label="Time Point 1 (hours)", value=20)
        a1 = gr.Number(label="Activity at Time 1 (MBq)", value=12)

    with gr.Row():
        t2 = gr.Number(label="Time Point 2 (hours)", value=60)
        a2 = gr.Number(label="Activity at Time 2 (MBq)", value=4)

    output_text = gr.Markdown()
    output_plot = gr.Plot()
    button = gr.Button("Calculate & Plot TIA")

    button.click(fn=calculate_and_plot, inputs=[t1, a1, t2, a2], outputs=[output_text, output_plot])

    gr.Markdown("""
    ---
    ### ℹ️ What Is This Tool?

    This open-source calculator estimates **Time-Integrated Activity (TIA)** for patients receiving **Lutetium-177 PSMA therapy** for metastatic prostate cancer.  
    It uses **two post-treatment SPECT/CT time points** to fit a simplified **mono-exponential washout model**, helping clinicians perform dose calculations with minimal imaging.

    ---
    ### ⚙️ How It Works

    You enter two scan times (hours) and their corresponding measured activity (MBq).  
    The tool automatically:

    - Fits an exponential time–activity curve  
    - Calculates the washout rate (_k_)  
    - Estimates initial activity (_A₀_)  
    - Computes **TIA = A₀ / k**, which can be used in absorbed dose estimation

    ---
    ### 🧠 Scientific Basis

    Model used:

    > A(t) = A₀ · exp(–k · t)  
    > TIA = A₀ / k

    This approach is ideal for organs with regular clearance kinetics (e.g., kidneys) or tumors with predictable washout, and is based on principles used in MIRD dosimetry and EANM guidelines.

    ---
    """)

demo.launch()