More examples

Using nifti-snapshot from shell

TBSS figures

Snapshot of an ``tbss_fill`` image

This would be the most simple, and maybe most useful way of capturing TBSS outputs. The assumption in this function is that the TBSS was ran with ENIGMA FA template as the standard.

fw=tbss_FW_tfce_corrp_tstat2_filled.nii.gz

nifti_snapshot \
  --input ${fw} \
  --tbss \
  --output_file cli_test_fw.png \
  --cmap "Blues_r" \
  --title "Significant changes in FW in group A" \
  --cbar_title 'Increased FW'

The cmap option used in nifti_snapshot is based on the matplotlib colormaps, so you could also experiment using different colormaps.

Just for your information, look here to see how tbss_filled images could be created.

Output figure looks as following.

Snapshot of two `tbss_fill` images with overlap highlight

It is uncommon to visualize two different modalities together from TBSS, but it could be useful if one wants to investigate shared or unique information contained in each modality. For example, visualizing FA maps and FAt maps together may prove helpful to investigate the effect of Freewater modeling in finding different regions detected by each modality.

fa=tbss_FA_tfce_corrp_tstat1_filled.nii.gz
fat=tbss_FAt_tfce_corrp_tstat1_filled.nii.gz

nifti_snapshot \
    --input ${fa} ${fat} \
    --tbss \
    --output_file cli_test.png \
    --cmap "Blues_r" "autumn" \
    --title "Significant changes in FA and FAt in group A" \
    --cbar_title 'Reduced' 'Reduced FAt' 'Overlap' \
    --overlap \
    --overlap_cmap "summer" \
    --overlap_alpha 0.8

As you can see in the code above, it takes in two --cmap options for each modality. And for regions that overlap between the two modalities, colormap defined through --overlap_cmap option would be used.

Calling nifti-snapshot from python

from nifti_snapshot import nifti_snapshot

fw = 'tbss_FA_tfce_corrp_tstat1_filled.nii.gz'
fw_color = 'Blues_r'

tbssFigure = nifti_snapshot.TbssFigure(
        image_files=[fw],
        output_file='docs/fw_example.png',
        cmap_list=[fw_color],
        cbar_titles=['Increased FW'],
        alpha_list=[0.8],
        title='Increased Freewater in group A',
        cbar_x=0.35, cbar_width=0.3)
tbssFigure.create_figure_one_map()

from nifti_snapshot import nifti_snapshot

fa = 'tbss_FA_tfce_corrp_tstat1_filled.nii.gz'
fat = 'tbss_FAt_tfce_corrp_tstat1_filled.nii.gz'

fa_color_1 = 'Blues_r'
fa_color_2 = 'autumn'
fa_color_overlap = 'summer'

tbssFigure = nifti_snapshot.TbssFigure(
    image_files=[fa, fat],
    output_file='docs/fa_fat_example.png',
    cmap_list=[fa_color_1, fa_color_2],
    overlap_cmap=fa_color_overlap,
    cbar_titles=[
        'Reduced FA',
        'Reduced FAt',
        'Overlap'],
    alpha_list=[1, 1, 0.8],
    title='Significant changes in FA and FAt in group A')
tbssFigure.create_figure_two_maps_and_overlap()