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[MAINT] Make sure only changed examples are rebuilt on PR (nilearn#4780)
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Remi-Gau authored Nov 22, 2024
1 parent 8d4b6f8 commit c10b1a5
Showing 2 changed files with 13 additions and 7 deletions.
2 changes: 1 addition & 1 deletion .github/workflows/build-docs.yml
Original file line number Diff line number Diff line change
@@ -242,7 +242,7 @@ jobs:
id: build-docs
run: |
set -o pipefail;
PATTERN=$(cat pattern.txt)
export PATTERN=$(cat pattern.txt)
tox run \
--colored yes \
--list-dependencies \
18 changes: 12 additions & 6 deletions examples/00_tutorials/plot_surface_101.py
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@@ -18,7 +18,8 @@
# brain.
#
# Practically, this means that the main difference between the two is the basic
# unit that holds the data. For volumetric images, that basic unit is a voxel,
# unit that holds the data.
# For volumetric images, that basic unit is a voxel,
# while for surface images it is a :term:`vertex`.
#
# The goal of this tutorial is to show you how to work with surface images in
@@ -44,7 +45,8 @@
# representation.
#
# For brain surfaces we typically have two meshes: one for the left hemisphere
# and one for the right hemisphere. Nilearn represents this as a
# and one for the right hemisphere.
# Nilearn represents this as a
# :class:`~nilearn.surface.PolyMesh` object with two ``parts``:
# ``left`` and ``right``.
#
@@ -97,7 +99,8 @@
# ----
#
# The data is the information stored at each :term:`vertex` of the
# :term:`mesh`. This can be anything from the thickness of the cortex to the
# :term:`mesh`.
# This can be anything from the thickness of the cortex to the
# activation level at that :term:`vertex`.
#
# For this example, let's create some random data for the vertices of the
@@ -123,7 +126,8 @@
# --------------------------
#
# The surface image can be plotted using the different functions from the
# :mod:`nilearn.plotting` module. Here we will show how to use the
# :mod:`nilearn.plotting` module.
# Here we will show how to use the
# :func:`~nilearn.plotting.view_surf` function:
from nilearn import plotting

@@ -163,7 +167,8 @@

# %%
# You will see that this creates four files in total -- two for the
# :term:`mesh` and two for the data. The files ending with ``_hemi-L.gii``
# :term:`mesh` and two for the data.
# The files ending with ``_hemi-L.gii``
# correspond to the left part and those ending with ``_hemi-R.gii`` correspond
# to the right part.

@@ -202,7 +207,8 @@
# ---------------
#
# Most things that can be done with volumetric images can also be done with
# surface images. See following examples for more details:
# surface images.
# See following examples for more details:
#
# * For plotting statistical maps on the surface, see
# :ref:`sphx_glr_auto_examples_01_plotting_plot_surf_stat_map.py`

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