How to save plot_sensors_connectivity()?

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1

plot_sensors_connectivity()

Hi,

I have a question about plot_sensors_connectivity().

Can I save the figure somehow or/and make subplots? I don’t need 3D figure, so I just need jpg or png picture.

Thanks!

2

The function returns a Matplotlib figure instance. So something like

from mne_connectivity.viz import plot_sensors_connectivity
fig = plot_sensors_connectivity(info, con, ...)
fig.set_size_inches(desired_width, desired_height)
fig.savefig('my_figure.png')

should work. If that doesn’t work, it’s a bug, please let us know.

3

Unfortunately it’s not working:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [26], in <module>
----> 1 fig.savefig('my_figure.png')

AttributeError: 'PyVistaFigure' object has no attribute 'savefig'
4

plot_sensors_connectivity() returns a 3D scene, so saving it to disk is a little bit more complicated. Here’s a fully reproducible working example:

# %%

import mne
from mne_connectivity import spectral_connectivity_epochs
from mne.datasets import sample
from mne_connectivity.viz import plot_sensors_connectivity
import matplotlib.pyplot as plt

data_path = sample.data_path()
raw_fname = data_path / 'MEG/sample/sample_audvis_filt-0-40_raw.fif'
event_fname = data_path / 'MEG/sample/sample_audvis_filt-0-40_raw-eve.fif'

raw = mne.io.read_raw_fif(raw_fname)
raw.info['bads'] += ['MEG 2443']
picks = mne.pick_types(raw.info, meg='grad', eeg=False, stim=False, eog=True,
                       exclude='bads')

events = mne.read_events(event_fname)
event_id, tmin, tmax = 3, -0.2, 1.5  # need a long enough epoch for 5 cycles
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
                    baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6))

fmin, fmax = 4., 9.
sfreq = raw.info['sfreq']  # the sampling frequency
tmin = 0.0  # exclude the baseline period
epochs.load_data().pick_types(meg='grad')  # just keep MEG and no EOG now
con = spectral_connectivity_epochs(
    epochs, method='pli', mode='multitaper', sfreq=sfreq, fmin=fmin, fmax=fmax,
    faverage=True, tmin=tmin, mt_adaptive=False, n_jobs=1
)

# %%
# Do the actual plotting
connectivity_fig = plot_sensors_connectivity(
    epochs.info,
    con.get_data(output='dense')[:, :, 0]
)
# Take a screenshot of the 3D scene
screenshot = connectivity_fig.plotter.screenshot()

# The screenshot is just a NumPy array, so we can display it via imshow()
# and then save it to a file.
fig, ax = plt.subplots(figsize=(10, 10))
ax.imshow(screenshot, origin='upper')
ax.set_axis_off()  # Disable axis labels and ticks
fig.tight_layout()
fig.savefig('connectivity.png', dpi=150)

connectivity
connectivity1500Ă—1500 146 KB

3 Likes
5

@richard, thank you very much!

6

would it be possible to save the returned 3D scene as an interactive 3D pdf file?

7

I’m afraid this is currently not possible, sorry.!

8

Thank you for your reply.

Alternatively, it is possible to export the 3D scene as a glTF file (export_gltf — PyVista 0.37.0 documentation) and view it with an online viewer (https://gltf-viewer.donmccurdy.com/).

2 Likes
9

how did you do this? Because I have been having errors all day

10

@codZeus please open a new issue, and provide code for a minimal, reproducible example, and the error (including full traceback) you encounter when running that example in a fresh python session.

11

sure I will.

I asked a question about whitened evoked response and whitened GFP that hasn’t been answered. Do you mind helping me with that?

Thanks

12

there are lots of unanswered questions; I will get to it when I am able.