Visualization

mne.viz:

Visualization routines.

Brain(subject_id[, hemi, surf, title, ...])

Class for visualizing a brain.

ClickableImage(imdata, **kwargs)

Display an image so you can click on it and store x/y positions.

add_background_image(fig, im[, set_ratios])

Add a background image to a plot.

centers_to_edges(*arrays)

Convert center points to edges.

compare_fiff(fname_1, fname_2[, fname_out, ...])

Compare the contents of two fiff files using diff and show_fiff.

circular_layout(node_names, node_order[, ...])

Create layout arranging nodes on a circle.

iter_topography(info[, layout, on_pick, ...])

Create iterator over channel positions.

mne_analyze_colormap([limits, format])

Return a colormap similar to that used by mne_analyze.

plot_bem([subject, subjects_dir, ...])

Plot BEM contours on anatomical slices.

plot_brain_colorbar(ax, clim[, colormap, ...])

Plot a colorbar that corresponds to a brain activation map.

plot_chpi_snr(snr_dict[, axes])

Plot time-varying SNR estimates of the HPI coils.

plot_cov(cov, info[, exclude, colorbar, ...])

Plot Covariance data.

plot_channel_labels_circle(labels[, colors, ...])

Plot labels for each channel in a circle plot.

plot_csd(csd[, info, mode, colorbar, cmap, ...])

Plot CSD matrices.

plot_dipole_amplitudes(dipoles[, colors, show])

Plot the amplitude traces of a set of dipoles.

plot_dipole_locations(dipoles[, trans, ...])

Plot dipole locations.

plot_drop_log(drop_log[, threshold, ...])

Show the channel stats based on a drop_log from Epochs.

plot_epochs(epochs[, picks, scalings, ...])

Visualize epochs.

plot_epochs_psd_topomap(epochs[, bands, ...])

Plot the topomap of the power spectral density across epochs.

plot_events(events[, sfreq, first_samp, ...])

Plot events to get a visual display of the paradigm.

plot_evoked(evoked[, picks, exclude, unit, ...])

Plot evoked data using butterfly plots.

plot_evoked_image(evoked[, picks, exclude, ...])

Plot evoked data as images.

plot_evoked_topo(evoked[, layout, ...])

Plot 2D topography of evoked responses.

plot_evoked_topomap(evoked[, times, ...])

Plot topographic maps of specific time points of evoked data.

plot_evoked_joint(evoked[, times, title, ...])

Plot evoked data as butterfly plot and add topomaps for time points.

plot_evoked_field(evoked, surf_maps[, time, ...])

Plot MEG/EEG fields on head surface and helmet in 3D.

plot_evoked_white(evoked, noise_cov[, show, ...])

Plot whitened evoked response.

plot_filter(h, sfreq[, freq, gain, title, ...])

Plot properties of a filter.

plot_head_positions(pos[, mode, cmap, ...])

Plot head positions.

plot_ideal_filter(freq, gain[, axes, title, ...])

Plot an ideal filter response.

plot_compare_evokeds(evokeds[, picks, ...])

Plot evoked time courses for one or more conditions and/or channels.

plot_ica_sources(ica, inst[, picks, start, ...])

Plot estimated latent sources given the unmixing matrix.

plot_ica_components(ica[, picks, ch_type, ...])

Project mixing matrix on interpolated sensor topography.

plot_ica_properties(ica, inst[, picks, ...])

Display component properties.

plot_ica_scores(ica, scores[, exclude, ...])

Plot scores related to detected components.

plot_ica_overlay(ica, inst[, exclude, ...])

Overlay of raw and cleaned signals given the unmixing matrix.

plot_epochs_image(epochs[, picks, sigma, ...])

Plot Event Related Potential / Fields image.

plot_layout(layout[, picks, show_axes, show])

Plot the sensor positions.

plot_montage(montage[, scale_factor, ...])

Plot a montage.

plot_projs_topomap(projs, info[, cmap, ...])

Plot topographic maps of SSP projections.

plot_raw(raw[, events, duration, start, ...])

Plot raw data.

plot_raw_psd(raw[, fmin, fmax, tmin, tmax, ...])

Plot the power spectral density across channels.

plot_sensors(info[, kind, ch_type, title, ...])

Plot sensors positions.

plot_sensors_connectivity(*args, **kwargs)

Warning

DEPRECATED: Functions in the mne.connectivity sub-module have moved to a new package (mne-connectivity) and will be removed in MNE-Python version 0.25. Install the new connectivity package by running pip install mne-connectivity in a system terminal or anaconda prompt.

plot_snr_estimate(evoked, inv[, show, axes, ...])

Plot a data SNR estimate.

plot_source_estimates(stc[, subject, ...])

Plot SourceEstimate.

link_brains(brains[, time, camera, ...])

Plot multiple SourceEstimate objects with PyVista.

plot_volume_source_estimates(stc, src[, ...])

Plot Nutmeg style volumetric source estimates using nilearn.

plot_vector_source_estimates(stc[, subject, ...])

Plot VectorSourceEstimate with PySurfer.

plot_sparse_source_estimates(src, stcs[, ...])

Plot source estimates obtained with sparse solver.

plot_tfr_topomap(tfr[, tmin, tmax, fmin, ...])

Plot topographic maps of specific time-frequency intervals of TFR data.

plot_topo_image_epochs(epochs[, layout, ...])

Plot Event Related Potential / Fields image on topographies.

plot_topomap(data, pos[, vmin, vmax, cmap, ...])

Plot a topographic map as image.

plot_alignment([info, trans, subject, ...])

Plot head, sensor, and source space alignment in 3D.

snapshot_brain_montage(fig, montage[, ...])

Take a snapshot of a Mayavi Scene and project channels onto 2d coords.

plot_arrowmap(data, info_from[, info_to, ...])

Plot arrow map.

set_3d_backend(backend_name[, verbose])

Set the 3D backend for MNE.

get_3d_backend()

Return the 3D backend currently used.

use_3d_backend(backend_name)

Create a 3d visualization context using the designated backend.

set_3d_options([antialias])

Set 3D rendering options.

set_3d_view(figure[, azimuth, elevation, ...])

Configure the view of the given scene.

set_3d_title(figure, title[, size])

Configure the title of the given scene.

create_3d_figure(size[, bgcolor, ...])

Return an empty figure based on the current 3d backend.

get_brain_class()

Return the proper Brain class based on the current 3d backend.