mirror of
https://github.com/TheusHen/EEGFrontier.git
synced 2026-04-13 07:05:49 +00:00
52c98dcdfa
- Implemented mne_tools.py for converting sample records to MNE Raw format. - Created models.py to define data structures for sample, event, and error packets. - Developed pyqt_focus.py for a PyQt-based focus monitoring GUI with real-time EEG data visualization. - Added eflex_bridge.py to manage the EEG engine instance. - Introduced simulator.py to simulate EEG data packets for testing purposes. - Established a web dashboard in pendulum_web.py for live EEG data display and diagnostics. - Configured project dependencies in pyproject.toml and equirements.txt. - Added batch and PowerShell scripts for running and stopping the Reflex application. - Created xconfig.py for Reflex application configuration.
32 lines
794 B
Python
32 lines
794 B
Python
from __future__ import annotations
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from typing import Sequence
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import mne
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import numpy as np
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from .models import SampleRecord
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def samples_to_mne_raw(
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samples: Sequence[SampleRecord],
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sample_rate_hz: float,
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channel_names: Sequence[str] = ("EEG1", "EEG2", "EEG3", "EEG4"),
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) -> mne.io.BaseRaw:
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if len(samples) == 0:
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raise ValueError("No samples available to convert to MNE Raw.")
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data_uv = np.array(
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[[s.ch1_uv, s.ch2_uv, s.ch3_uv, s.ch4_uv] for s in samples],
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dtype=np.float64,
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)
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data_v = (data_uv.T) * 1e-6
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info = mne.create_info(
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ch_names=list(channel_names),
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sfreq=float(sample_rate_hz),
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ch_types=["eeg"] * len(channel_names),
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)
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raw = mne.io.RawArray(data_v, info, verbose="ERROR")
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return raw
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