步骤 02:信息检查

import mne

# ====== 打印整体信息 ======
print(raw)
# 输出示例：<Raw | sample_raw.fif | 376 ch | 1000 Hz | 277.7 s>

# ====== 详细 Info ======
print(raw.info)

# ====== 关键字段提取 ======
print(f"sampling frequency: {raw.info['sfreq']} Hz")
print(f"highpass corner:    {raw.info['highpass']} Hz")
print(f"lowpass corner:     {raw.info['lowpass']} Hz")
print(f"channel count:      {len(raw.ch_names)}")
print(f"first 10 channels:  {raw.ch_names[:10]}")
print(f"duration:           {raw.times[-1]:.2f} s")

# ====== 检查通道类型分布 ======
from collections import Counter
type_counter = Counter(raw.get_channel_types())
print(dict(type_counter))
# 期望：{'eeg': 60, 'eog': 2, 'ecg': 1, 'stim': 1} 等

# 验证 1：必备检查清单
checks = {
    '采样率 > 0': raw.info['sfreq'] > 0,
    '通道数 > 0': len(raw.ch_names) > 0,
    '有时长': raw.times[-1] > 0,
    '包含 EEG 通道': 'eeg' in raw.get_channel_types(),
}
for k, v in checks.items():
    print(f"{'✓' if v else '✗'} {k}")
assert all(checks.values()), "原始数据信息异常，请检查来源"

# 验证 2：可视化前 30 秒
raw.plot(duration=30, n_channels=30, scalings='auto')
# 人工核对：是否有异常大振幅、平坦线、漂移

# 验证 3：PSD 检查
raw.plot_psd(fmax=200)
# 期望：50 Hz / 60 Hz 附近有明显工频尖峰