Update src/streamlit_app.py

src/streamlit_app.py

@@ -9,6 +9,7 @@ from matplotlib.animation import FuncAnimation
 import requests
 import streamlit as st
 import tempfile
+from scipy.signal import welch
 
 # Set page config
 st.set_page_config(page_title="Muse EEG Topomap Viewer", layout="centered")
@@ -204,3 +205,39 @@ if spectrogram_button:
     except Exception as e:
         st.error(f"❌ Error: {str(e)}")
 
+# Function to compute band power
+def bandpower(data, sf, band, window_sec=None):
+    band = np.asarray(band)
+    low, high = band
+
+    if window_sec is not None:
+        nperseg = int(window_sec * sf)
+    else:
+        nperseg = None
+
+    freqs, psd = welch(data, sf, nperseg=nperseg)
+    idx_band = np.logical_and(freqs >= low, freqs <= high)
+    return np.trapz(psd[idx_band], freqs[idx_band])
+
+# Button to calculate and plot band powers
+if st.button("Show Band Power Chart (TP9)"):
+    # Define bands
+    bands = {
+        "Delta (1–4 Hz)": (1, 4),
+        "Theta (4–8 Hz)": (4, 8),
+        "Alpha (8–12 Hz)": (8, 12),
+        "Beta (12–30 Hz)": (12, 30),
+        "Gamma (30–50 Hz)": (30, 50)
+    }
+
+    # Compute power for each band
+    powers = [bandpower(tp10_filtered_mne, sampling_rate, b) for b in bands.values()]
+
+    # Plot
+    fig, ax = plt.subplots()
+    ax.bar(bands.keys(), powers, color='skyblue')
+    ax.set_title("Band Power - TP9")
+    ax.set_ylabel("Power")
+    ax.tick_params(axis='x', rotation=45)
+    st.pyplot(fig)
+