| import mne | |
| import streamlit as st | |
| import matplotlib.pyplot as plt | |
| def preprocessing_and_plotting(raw): | |
| # Select the first channel | |
| channel = raw.ch_names[0] | |
| st.write(f"Selected channel: {channel}") | |
| # Plot the first channel | |
| fig, ax = plt.subplots() | |
| ax.plot(raw.times, raw[channel][0].T) | |
| ax.set_xlabel("Time (s)") | |
| ax.set_ylabel("Amplitude (µV)") | |
| ax.set_title(f"EEG signal of {channel}") | |
| st.pyplot(fig) | |
| def read_file(edf_file): | |
| # To read file as bytes: | |
| bytes_data = edf_file.getvalue() | |
| # Open a file named "output.bin" in the current directory in write binary mode | |
| with open('edf_file.edf', "wb") as f: | |
| # Write the bytes data to the file | |
| f.write(bytes_data) | |
| raw = mne.io.read_raw_edf('edf_file.edf') | |
| st.write(f"Loaded {edf_file.name} with {raw.info['nchan']} channels") | |
| return raw | |