Update src/streamlit_app.py

src/streamlit_app.py

@@ -151,3 +151,56 @@ if plot_waveform_button:
 
     except Exception as e:
         st.error(f"❌ Error: {str(e)}")
+
+spectrogram_button = st.button("Plot TP9 Spectrograms")
+
+if spectrogram_button:
+    try:
+        # Download and read CSV
+        response = requests.get(csv_url)
+        response.raise_for_status()
+        data = pd.read_csv(io.StringIO(response.text))
+        st.write(f"Loaded data with shape: {data.shape}")
+
+        # Extract timestamps and TP9
+        timestamps = data['timestamps'] if 'timestamps' in data.columns else data['TimeStamp']
+        tp10_raw = data['TP9']
+
+        # Calculate sampling rate
+        time_diffs = np.diff(timestamps)
+        average_interval = np.mean(time_diffs)
+        sampling_rate = 1 / average_interval
+
+        # Create MNE Raw object
+        info = mne.create_info(ch_names=['TP9'], sfreq=sampling_rate, ch_types='eeg')
+        raw = mne.io.RawArray(np.array([tp10_raw]), info)
+
+        # Apply bandpass filter
+        raw.filter(1, 50, fir_design='firwin')
+        tp10_filtered_mne = raw.get_data()[0]
+
+        from scipy.signal import spectrogram
+
+        # Spectrogram before filtering
+        frequencies_pre, times_pre, spectrogram_pre = spectrogram(tp10_raw, fs=sampling_rate, nperseg=256)
+        fig_spec_pre, ax_pre = plt.subplots(figsize=(10, 6))
+        p1 = ax_pre.pcolormesh(times_pre, frequencies_pre, np.log10(spectrogram_pre + 1e-10), shading='gouraud')
+        fig_spec_pre.colorbar(p1, ax=ax_pre, label='Log Power Spectral Density')
+        ax_pre.set_title('Spectrogram of TP9 (Raw)')
+        ax_pre.set_xlabel('Time (seconds)')
+        ax_pre.set_ylabel('Frequency (Hz)')
+        st.pyplot(fig_spec_pre)
+
+        # Spectrogram after filtering
+        frequencies_post, times_post, spectrogram_post = spectrogram(tp10_filtered_mne, fs=sampling_rate, nperseg=256)
+        fig_spec_post, ax_post = plt.subplots(figsize=(10, 6))
+        p2 = ax_post.pcolormesh(times_post, frequencies_post, np.log10(spectrogram_post + 1e-10), shading='gouraud')
+        fig_spec_post.colorbar(p2, ax=ax_post, label='Log Power Spectral Density')
+        ax_post.set_title('Spectrogram of TP9 (Filtered 1–50Hz)')
+        ax_post.set_xlabel('Time (seconds)')
+        ax_post.set_ylabel('Frequency (Hz)')
+        st.pyplot(fig_spec_post)
+
+    except Exception as e:
+        st.error(f"❌ Error: {str(e)}")
+