Visualization¶
Visualization routines.
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Class for visualizing a brain. |
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Display an image so you can click on it and store x/y positions. |
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Add a background image to a plot. |
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Convert center points to edges. |
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Compare the contents of two fiff files using diff and show_fiff. |
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Create layout arranging nodes on a circle. |
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Create iterator over channel positions. |
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Return a colormap similar to that used by mne_analyze. |
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Plot BEM contours on anatomical slices. |
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Plot a colorbar that corresponds to a brain activation map. |
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Visualize connectivity as a circular graph. |
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Plot Covariance data. |
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Plot CSD matrices. |
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Plot the amplitude traces of a set of dipoles. |
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Plot dipole locations. |
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Show the channel stats based on a drop_log from Epochs. |
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Visualize epochs. |
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Plot the topomap of the power spectral density across epochs. |
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Plot events to get a visual display of the paradigm. |
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Plot evoked data using butterfly plots. |
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Plot evoked data as images. |
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Plot 2D topography of evoked responses. |
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Plot topographic maps of specific time points of evoked data. |
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Plot evoked data as butterfly plot and add topomaps for time points. |
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Plot MEG/EEG fields on head surface and helmet in 3D. |
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Plot whitened evoked response. |
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Plot properties of a filter. |
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Plot head positions. |
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Plot an ideal filter response. |
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Plot evoked time courses for one or more conditions and/or channels. |
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Plot estimated latent sources given the unmixing matrix. |
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Project mixing matrix on interpolated sensor topography. |
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Display component properties. |
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Plot scores related to detected components. |
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Overlay of raw and cleaned signals given the unmixing matrix. |
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Plot Event Related Potential / Fields image. |
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Plot the sensor positions. |
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Plot a montage. |
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Plot topographic maps of SSP projections. |
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Plot raw data. |
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Plot the power spectral density across channels. |
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Plot sensors positions. |
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Visualize the sensor connectivity in 3D. |
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Plot a data SNR estimate. |
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Plot SourceEstimate. |
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Plot multiple SourceEstimate objects with PyVista. |
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Plot Nutmeg style volumetric source estimates using nilearn. |
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Plot VectorSourceEstimate with PySurfer. |
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Plot source estimates obtained with sparse solver. |
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Plot topographic maps of specific time-frequency intervals of TFR data. |
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Plot Event Related Potential / Fields image on topographies. |
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Plot a topographic map as image. |
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Plot head, sensor, and source space alignment in 3D. |
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Take a snapshot of a Mayavi Scene and project channels onto 2d coords. |
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Plot arrow map. |
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Set the backend for MNE. |
Return the backend currently used. |
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Create a 3d visualization context using the designated backend. |
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Set 3D rendering options. |
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Configure the view of the given scene. |
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Configure the title of the given scene. |
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Return an empty figure based on the current 3d backend. |
Return the proper Brain class based on the current 3d backend. |