Error when using mne raw to get power spectrum. I want to use edf imported to mne in (A). about yasa

[raphaelvallat]

Hi @paulokanda,

Thanks for your message. You need to use np.squeeze(data) to ensure that time and data are both one-dimensional (by default data is 2D, i.e. data.shape = (n_channels, n_times)).

Hope this helps,
Thanks,
Raphael

[paulokanda]

I think that yasa is considering index as a value because

I reduced raw (from edf+) to one channel:

raw1 = raw.pick_channels(['F3'])
data = raw1.get_data() etc...

data.shape
(1, 80800)

raw_df1.head()

           time | F3

0 0 | 1.016440e-13
1 10 | -3.411143e-01
2 20 | -3.844158e-01
3 30 | -4.245883e-01
4 40 | -5.764858e-01

data
array([[ 1.01643954e-19, -3.41114305e-07, -3.84415789e-07, ...,
3.68912472e-06, 3.24150894e-06, -1.01643954e-19]])

error remains:

ValueError: x and y must have same first dimension, but have shapes (80800,) and (1, 80800)

It doesnot happen when plotting with other methods in mne.

Is it an yasa bug? Please what I'm missing? Thanks in advance.

[raphaelvallat]

Hi @paulokanda,

This is not a YASA bug since your code does not include any YASA functions. Rather, the issue is that when you use raw.get_data() with a single channel in MNE, you still end up with a two-dimensional array, even though you have only one channel. The output dimension of the array is (n_channels, n_samples). However, the time vector that we use in the matplotlib plt.plot() function is one-dimensional. The following should work:

plt.plot(time, np.squeeze(data))

Thanks,
Raphael

[paulokanda]

Thank you for your time and clear explanation.