.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/01_plotting/plot_3d_map_to_surface_projection.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_01_plotting_plot_3d_map_to_surface_projection.py: Making a surface plot of a 3D statistical map ============================================= In this example, we will project a 3D statistical map onto a cortical mesh using :func:`~nilearn.surface.vol_to_surf`, display a surface plot of the projected map using :func:`~nilearn.plotting.plot_surf_stat_map` with different plotting engines, and add contours of regions of interest using :func:`~nilearn.plotting.plot_surf_contours`. .. GENERATED FROM PYTHON SOURCE LINES 14-16 Get a statistical map --------------------- .. GENERATED FROM PYTHON SOURCE LINES 16-23 .. code-block:: default from nilearn import datasets motor_images = datasets.fetch_neurovault_motor_task() stat_img = motor_images.images[0] .. GENERATED FROM PYTHON SOURCE LINES 24-26 Get a cortical mesh ------------------- .. GENERATED FROM PYTHON SOURCE LINES 26-29 .. code-block:: default fsaverage = datasets.fetch_surf_fsaverage() .. GENERATED FROM PYTHON SOURCE LINES 30-32 Sample the 3D data around each node of the mesh ----------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 32-37 .. code-block:: default from nilearn import surface texture = surface.vol_to_surf(stat_img, fsaverage.pial_right) .. GENERATED FROM PYTHON SOURCE LINES 38-44 Plot the result --------------- You can visualize the texture on the surface using the function :func:`~nilearn.plotting.plot_surf_stat_map` which uses ``matplotlib`` as the default plotting engine: .. GENERATED FROM PYTHON SOURCE LINES 44-54 .. code-block:: default from nilearn import plotting fig = plotting.plot_surf_stat_map( fsaverage.infl_right, texture, hemi='right', title='Surface right hemisphere', colorbar=True, threshold=1., bg_map=fsaverage.sulc_right ) fig.show() .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_001.png :alt: Surface right hemisphere :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 55-62 Interactive plotting with Plotly -------------------------------- If you have a recent version of Nilearn (>=0.8.2), and if you have ``plotly`` installed, you can easily configure :func:`~nilearn.plotting.plot_surf_stat_map` to use ``plotly`` instead of ``matplotlib``: .. GENERATED FROM PYTHON SOURCE LINES 62-80 .. code-block:: default engine = 'plotly' # If plotly is not installed, use matplotlib try: import plotly.graph_objects as go # noqa: F401 except ImportError: engine = 'matplotlib' print(f"Using plotting engine {engine}.") fig = plotting.plot_surf_stat_map( fsaverage.infl_right, texture, hemi='right', title='Surface right hemisphere', colorbar=True, threshold=1., bg_map=fsaverage.sulc_right, engine=engine # Specify the plotting engine here ) fig.show() # Display the figure as with matplotlib figures .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Using plotting engine plotly. /home/nicolas/GitRepos/nilearn-fork/nilearn/plotting/js_plotting_utils.py:81: UserWarning: vmin cannot be chosen when cmap is symmetric warnings.warn('vmin cannot be chosen when cmap is symmetric') .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 81-88 When using ``matplolib`` as the plotting engine, a standard :class:`matplotlib.figure.Figure` is returned. With ``plotly`` as the plotting engine, a custom :class:`~nilearn.plotting.displays.PlotlySurfaceFigure` is returned which provides a similar API to the :class:`~matplotlib.figure.Figure`. For example, you can save a static version of the figure to file (this option requires to have ``kaleido`` installed): .. GENERATED FROM PYTHON SOURCE LINES 88-93 .. code-block:: default # Save the figure as we would do with a matplotlib figure # Uncomment the following line to save the previous figure to file # fig.savefig("right_hemisphere.png") .. GENERATED FROM PYTHON SOURCE LINES 94-96 Plot 3D image for comparison ---------------------------- .. GENERATED FROM PYTHON SOURCE LINES 96-103 .. code-block:: default plotting.plot_glass_brain(stat_img, display_mode='r', plot_abs=False, title='Glass brain', threshold=2.) plotting.plot_stat_map(stat_img, display_mode='x', threshold=1., cut_coords=range(0, 51, 10), title='Slices') .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_002.png :alt: plot 3d map to surface projection :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_002.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_003.png :alt: plot 3d map to surface projection :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_003.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 104-106 Use an atlas and choose regions to outline ------------------------------------------ .. GENERATED FROM PYTHON SOURCE LINES 106-122 .. code-block:: default import numpy as np destrieux_atlas = datasets.fetch_atlas_surf_destrieux() parcellation = destrieux_atlas['map_right'] # these are the regions we want to outline regions_dict = {b'G_postcentral': 'Postcentral gyrus', b'G_precentral': 'Precentral gyrus'} # get indices in atlas for these labels regions_indices = [np.where(np.array(destrieux_atlas['labels']) == region)[0][0] for region in regions_dict] labels = list(regions_dict.values()) .. GENERATED FROM PYTHON SOURCE LINES 123-125 Display outlines of the regions of interest on top of a statistical map ----------------------------------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 125-136 .. code-block:: default figure = plotting.plot_surf_stat_map(fsaverage.infl_right, texture, hemi='right', title='Surface right hemisphere', colorbar=True, threshold=1., bg_map=fsaverage.sulc_right) plotting.plot_surf_contours(fsaverage.infl_right, parcellation, labels=labels, levels=regions_indices, figure=figure, legend=True, colors=['g', 'k']) plotting.show() .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_004.png :alt: Surface right hemisphere :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_004.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 137-144 Plot with higher-resolution mesh -------------------------------- :func:`~nilearn.datasets.fetch_surf_fsaverage` takes a ``mesh`` argument which specifies whether to fetch the low-resolution ``fsaverage5`` mesh, or the high-resolution fsaverage mesh. Using ``mesh="fsaverage"`` will result in more memory usage and computation time, but finer visualizations. .. GENERATED FROM PYTHON SOURCE LINES 144-154 .. code-block:: default big_fsaverage = datasets.fetch_surf_fsaverage('fsaverage') big_texture = surface.vol_to_surf(stat_img, big_fsaverage.pial_right) plotting.plot_surf_stat_map(big_fsaverage.infl_right, big_texture, hemi='right', colorbar=True, title='Surface right hemisphere: fine mesh', threshold=1., bg_map=big_fsaverage.sulc_right) .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_005.png :alt: Surface right hemisphere: fine mesh :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_005.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none

.. GENERATED FROM PYTHON SOURCE LINES 155-163 Plot multiple views of the 3D volume on a surface ------------------------------------------------- :func:`~nilearn.plotting.plot_img_on_surf` takes a statistical map and projects it onto a surface. It supports multiple choices of orientations, and can plot either one or both hemispheres. If no ``surf_mesh`` is given, :func:`~nilearn.plotting.plot_img_on_surf` projects the images onto `FreeSurfer `_\'s fsaverage5. .. GENERATED FROM PYTHON SOURCE LINES 163-170 .. code-block:: default plotting.plot_img_on_surf(stat_img, views=['lateral', 'medial'], hemispheres=['left', 'right'], colorbar=True) plotting.show() .. image-sg:: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_006.png :alt: plot 3d map to surface projection :srcset: /auto_examples/01_plotting/images/sphx_glr_plot_3d_map_to_surface_projection_006.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 171-179 3D visualization in a web browser --------------------------------- An alternative to :func:`nilearn.plotting.plot_surf_stat_map` is to use :func:`nilearn.plotting.view_surf` or :func:`nilearn.plotting.view_img_on_surf` that give more interactive visualizations in a web browser. See :ref:`interactive-surface-plotting` for more details. .. GENERATED FROM PYTHON SOURCE LINES 179-187 .. code-block:: default view = plotting.view_surf(fsaverage.infl_right, texture, threshold='90%', bg_map=fsaverage.sulc_right) # In a Jupyter notebook, if ``view`` is the output of a cell, it will # be displayed below the cell view .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 188-192 .. code-block:: default # uncomment this to open the plot in a web browser: # view.open_in_browser() .. GENERATED FROM PYTHON SOURCE LINES 193-195 We don't need to do the projection ourselves, we can use :func:`~nilearn.plotting.view_img_on_surf`: .. GENERATED FROM PYTHON SOURCE LINES 195-201 .. code-block:: default view = plotting.view_img_on_surf(stat_img, threshold='90%') # view.open_in_browser() view .. raw:: html

.. GENERATED FROM PYTHON SOURCE LINES 202-211 Impact of plot parameters on visualization ------------------------------------------ You can specify arguments to be passed on to the function :func:`nilearn.surface.vol_to_surf` using `vol_to_surf_kwargs`. This allows fine-grained control of how the input 3D image is resampled and interpolated - for example if you are viewing a volumetric atlas, you would want to avoid averaging the labels between neighboring regions. Using nearest-neighbor interpolation with zero radius will achieve this. .. GENERATED FROM PYTHON SOURCE LINES 211-223 .. code-block:: default destrieux = datasets.fetch_atlas_destrieux_2009(legacy_format=False) view = plotting.view_img_on_surf( destrieux.maps, surf_mesh="fsaverage", vol_to_surf_kwargs={"n_samples": 1, "radius": 0.0, "interpolation": "nearest"}, symmetric_cmap=False, ) # view.open_in_browser() view .. raw:: html

.. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 22.218 seconds) **Estimated memory usage:** 618 MB .. _sphx_glr_download_auto_examples_01_plotting_plot_3d_map_to_surface_projection.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/nilearn/nilearn.github.io/main?filepath=examples/auto_examples/01_plotting/plot_3d_map_to_surface_projection.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_3d_map_to_surface_projection.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_3d_map_to_surface_projection.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_