Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,99 @@
-import altair as alt
+import os
+import io
 import numpy as np
 import pandas as pd
+import matplotlib.pyplot as plt
+import mne
+from mne.channels import make_dig_montage
+from matplotlib.animation import FuncAnimation
+import requests
 import streamlit as st
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# Set page config
+st.set_page_config(page_title="Muse EEG Topomap Viewer", layout="centered")
+
+def plot_eeg_topomap_muse_from_csv(csv_url, save_path_animation=None, save_directory=None,
+                                   show_names=False, start_time=0.05, end_time=1, step_size=0.1):
+    response = requests.get(csv_url)
+    if response.status_code != 200:
+        raise RuntimeError(f"Failed to download CSV from {csv_url}")
+    data = pd.read_csv(io.StringIO(response.text))
+    st.write(f"Loaded data with shape: {data.shape}")
+
+    muse_channels = ['AF7', 'AF8', 'TP9', 'TP10']
+    if not all(ch in data.columns for ch in muse_channels):
+        raise ValueError(f"The dataset must contain the following channels: {muse_channels}")
+
+    eeg_data = data[muse_channels].values.T
+
+    muse_positions = {
+        'AF7': [-0.05, 0.085, 0],
+        'AF8': [0.05, 0.085, 0],
+        'TP9': [-0.08, -0.04, 0],
+        'TP10': [0.08, -0.04, 0]
+    }
+    for ch in muse_positions:
+        muse_positions[ch][0] += np.random.normal(0, 0.0001)
+        muse_positions[ch][1] += np.random.normal(0, 0.0001)
+
+    montage = make_dig_montage(ch_pos=muse_positions, coord_frame='head')
+
+    if 'TimeStamp' in data.columns:
+        timestamps = data['TimeStamp']
+    elif 'timestamps' in data.columns:
+        timestamps = data['timestamps']
+    else:
+        raise ValueError("CSV must contain a 'TimeStamp' or 'timestamps' column")
+
+    time_diffs = np.diff(timestamps)
+    average_interval = np.mean(time_diffs)
+    sfreq = 1 / average_interval
+
+    info = mne.create_info(ch_names=muse_channels, sfreq=sfreq, ch_types='eeg')
+    evoked = mne.EvokedArray(eeg_data, info)
+    evoked.set_montage(montage)
+
+    times = np.arange(start_time, end_time, step_size)
+    if len(times) == 0:
+        raise ValueError("Not enough time range selected for topomap animation.")
+
+    if save_path_animation:
+        if save_directory:
+            os.makedirs(save_directory, exist_ok=True)
+            save_path_animation = os.path.join(save_directory, save_path_animation)
+
+        fig, ax = plt.subplots()
+
+        def update(frame):
+            ax.clear()
+            evoked.plot_topomap([times[frame]], ch_type='eeg', time_unit='s',
+                                axes=ax, colorbar=False, show=False)
+
+        anim = FuncAnimation(fig, update, frames=range(len(times)), interval=200)
+        anim.save(save_path_animation, writer='pillow')
+        plt.close(fig)
+
+        return save_path_animation
+    else:
+        return None
+
+# Streamlit UI
+st.title("🧠 Muse EEG Topomap Animation from CSV")
+
+default_url = "https://raw.githubusercontent.com/garenasd945/EEG_muse2/refs/heads/master/dataset/original_data/subjecta-relaxed-1.csv"
+csv_url = st.text_input("CSV URL", value=default_url)
+generate_button = st.button("Generate Topomap Animation")
+
+if generate_button:
+    try:
+        gif_path = plot_eeg_topomap_muse_from_csv(
+            csv_url,
+            save_path_animation="eeg_topomap_animation.gif",
+            save_directory="animations",
+            show_names=True
+        )
+        if gif_path:
+            st.image(gif_path, caption="EEG Topomap Animation")
+    except Exception as e:
+        st.error(f"❌ Error: {str(e)}")
+#update