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_connectivity_circle(con, node_names[, …])

Visualize connectivity as a circular graph.

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

Plot Covariance data.

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(info, con[, …])

Visualize the sensor connectivity in 3D.

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 backend for MNE.

get_3d_backend()

Return the 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.