nireports.reportlets.mosaic module

Base components to generate mosaic-like reportlets.

nireports.reportlets.mosaic.plot_mosaic(img, out_file=None, ncols=8, title=None, overlay_mask=None, bbox_mask_file=None, only_plot_noise=False, annotate=True, vmin=None, vmax=None, cmap='Greys_r', plot_sagittal=False, fig=None, maxrows=16, views=('axial', 'sagittal', None))

Plot a mosaic of 2D cuts.

nireports.reportlets.mosaic.plot_registration(anat_nii, div_id, plot_params=None, order=('z', 'x', 'y'), cuts=None, estimate_brightness=False, label=None, contour=None, compress='auto', dismiss_affine=False)

Plots the foreground and background views Default order is: axial, coronal, sagittal

nireports.reportlets.mosaic.plot_segmentation(anat_file, segmentation, out_file, **kwargs)

Plot a segmentation (from MRIQC).

nireports.reportlets.mosaic.plot_segs(image_nii, seg_niis, out_file, bbox_nii=None, masked=False, colors=None, compress='auto', **plot_params)

Generate a static mosaic with ROIs represented by their delimiting contour.

Plot segmentation as contours over the image (e.g. anatomical). seg_niis should be a list of files. mask_nii helps determine the cut coordinates. plot_params will be passed on to nilearn plot_* functions. If seg_niis is a list of size one, it behaves as if it was plotting the mask.

nireports.reportlets.mosaic.plot_slice(dslice, spacing=None, cmap='Greys_r', label=None, ax=None, vmax=None, vmin=None, annotate=None)

nireports.reportlets.mosaic.plot_slice_tern(dslice, prev=None, post=None, spacing=None, cmap='Greys_r', label=None, ax=None, vmax=None, vmin=None)

nireports.reportlets.mosaic.plot_spikes(in_file, in_fft, spikes_list, cols=3, labelfmt='t={0:.3f}s (z={1:d})', out_file=None)

Plot a mosaic enhancing EM spikes.