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"""
EEG Simulator Node - Generates a simulated multi-channel EEG signal
Place this file in the 'nodes' folder
"""
import numpy as np
from PyQt6 import QtGui
import cv2
import sys
import os
# --- This is the new, correct block ---
import __main__
BaseNode = __main__.BaseNode
PA_INSTANCE = getattr(__main__, "PA_INSTANCE", None)
# ------------------------------------
class EEGSimulatorNode(BaseNode):
NODE_CATEGORY = "Source"
NODE_COLOR = QtGui.QColor(40, 120, 80) # Source Green
def __init__(self, sample_rate=250.0):
super().__init__()
self.node_title = "EEG Simulator"
self.outputs = {'signal': 'signal'}
self.sample_rate = sample_rate
self.time = 0.0
# Inspired by MNE channel names
self.channels = ["Fp1", "Fp2", "C3", "C4", "O1", "O2", "T7", "T8"]
self.selected_channel = self.channels[0]
# Internal state for each channel's oscillators
self.channel_state = {}
for ch in self.channels:
self.channel_state[ch] = {
'phase': np.random.rand(4) * 2 * np.pi,
'freqs': np.array([
np.random.uniform(2, 4), # Delta
np.random.uniform(5, 8), # Theta
np.random.uniform(9, 12), # Alpha
np.random.uniform(15, 25) # Beta
]),
'amps': np.array([
np.random.uniform(0.5, 1.0),
np.random.uniform(0.2, 0.5),
np.random.uniform(0.1, 0.8), # Alpha can be strong
np.random.uniform(0.05, 0.2)
]) * 0.2 # Scale down
}
self.output_value = 0.0
self.history = np.zeros(64) # For display
def step(self):
dt = 1.0 / self.sample_rate
self.time += dt
# Get the state for the selected channel
state = self.channel_state[self.selected_channel]
# Update phases
state['phase'] += state['freqs'] * dt * 2 * np.pi
# Compute sines
sines = np.sin(state['phase'])
# Modulate alpha rhythm (make it bursty)
alpha_mod = (np.sin(self.time * 0.2 * 2 * np.pi) + 1.0) / 2.0 # Slow modulation
sines[2] *= alpha_mod
# Sum oscillators
signal = np.dot(sines, state['amps'])
# Add noise
noise = (np.random.rand() - 0.5) * 0.1
self.output_value = signal + noise
# Update display history
self.history[:-1] = self.history[1:]
self.history[-1] = self.output_value
def get_output(self, port_name):
if port_name == 'signal':
return self.output_value
return None
def get_display_image(self):
w, h = 64, 64
img = np.zeros((h, w), dtype=np.uint8)
# Normalize history from [-1, 1] to [0, h-1]
vis_data = (self.history + 1.0) / 2.0 * (h - 1)
for i in range(w - 1):
y1 = int(np.clip(vis_data[i], 0, h - 1))
y2 = int(np.clip(vis_data[i+1], 0, h - 1))
# Draw line segment
img = cv2.line(img, (i, y1), (i+1, y2), (255, 255, 255), 1)
img = np.ascontiguousarray(img)
return QtGui.QImage(img.data, w, h, w, QtGui.QImage.Format.Format_Grayscale8)
def get_config_options(self):
# Create channel options for the dropdown menu
channel_options = [(ch, ch) for ch in self.channels]
return [
("Channel", "selected_channel", self.selected_channel, channel_options)
]
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