[DOC] format citation

examples/03_connectivity/plot_signal_extraction.py

@@ -260,8 +260,8 @@
 # :func:`nilearn.interfaces.fmriprep.load_confounds`, one can use a predefined
 # strategy with :func:`nilearn.interfaces.fmriprep.load_confounds_strategy`.
 # Based on the confound variables generated through :term:`fMRIPrep`, and past
-# benchmarks studies (:footcite:`Ciric2017`, :footcite:`Parker2018`): `simple`,
-# `scrubbing`, `compcor`, `ica_aroma`.
+# benchmarks studies (:footcite:t:`Ciric2017`, :footcite:t:`Parker2018`):
+# `simple`, `scrubbing`, `compcor`, `ica_aroma`.
 # The following examples shows how to use the `simple` strategy and overwrite
 # the motion default to basic.
 

examples/07_advanced/plot_beta_series.py

@@ -20,9 +20,9 @@
 in the context of :term:`functional connectivity` analyses.
 
 Two of the most well-known beta series modeling methods are
-Least Squares- All (LSA) :footcite:p:`Rissman2004` and
+Least Squares- All (LSA) (:footcite:t:`Rissman2004`) and
 Least Squares- Separate (LSS)
-:footcite:p:`Mumford2012,Turner2012`.
+(:footcite:t:`Mumford2012,Turner2012`).
 In LSA, a single :term:`GLM` is run, in which each trial of each condition of
 interest is separated out into its own condition within the design matrix.
 In LSS, each trial of each condition of interest has its own :term:`GLM`,

nilearn/connectome/connectivity_matrices.py

@@ -112,7 +112,7 @@ def _geometric_mean(matrices, init=None, max_iter=10, tol=1e-7):
 
     In case of positive numbers, this mean is the usual geometric mean.
 
-    See Algorithm 3 of :footcite:`Fletcher2007`.
+    See Algorithm 3 of :footcite:t:`Fletcher2007`.
 
     References
     ----------
@@ -387,7 +387,7 @@ class ConnectivityMeasure(BaseEstimator, TransformerMixin):
     kind : {"covariance", "correlation", "partial correlation",\
             "tangent", "precision"}, default='covariance'
         The matrix kind.
-        For the use of "tangent" see :footcite:`Varoquaux2010b`.
+        For the use of "tangent" see :footcite:t:`Varoquaux2010b`.
 
     vectorize : bool, default=False
         If True, connectivity matrices are reshaped into 1D arrays and only

nilearn/connectome/group_sparse_cov.py

@@ -30,7 +30,7 @@ def compute_alpha_max(emp_covs, n_samples):
     matrices are fully dense (i.e. minimal number of zero coefficients).
 
     The formula used in this function was derived using the same method
-    as in :footcite:`Duchi2012`.
+    as in :footcite:t:`Duchi2012`.
 
     Parameters
     ----------
@@ -148,7 +148,7 @@ def group_sparse_covariance(
     Running time is linear on max_iter, and number of subjects (len(subjects)),
     but cubic on number of features (subjects[0].shape[1]).
 
-    The present algorithm is based on :footcite:`Honorio2015`.
+    The present algorithm is based on :footcite:t:`Honorio2015`.
 
     Parameters
     ----------
@@ -502,8 +502,8 @@ def _group_sparse_covariance(
 class GroupSparseCovariance(BaseEstimator, CacheMixin):
     """Covariance and precision matrix estimator.
 
-    The model used has been introduced in :footcite:`Varoquaux2010a`, and the
-    algorithm used is based on what is described in :footcite:`Honorio2015`.
+    The model used has been introduced in :footcite:t:`Varoquaux2010a`, and the
+    algorithm used is based on what is described in :footcite:t:`Honorio2015`.
 
     Parameters
     ----------

nilearn/datasets/atlas.py

@@ -43,7 +43,7 @@ def fetch_atlas_difumo(
     256, 512, and 1024).
     These modes are optimized to represent well raw :term:`BOLD` timeseries,
     over a with range of experimental conditions.
-    See :footcite:`Dadi2020`.
+    See :footcite:t:`Dadi2020`.
 
     .. versionadded:: 0.7.1
 
@@ -169,9 +169,9 @@ def fetch_atlas_craddock_2012(
     The provided images are in MNI152 space. All images are 4D with
     shapes equal to ``(47, 56, 46, 43)``.
 
-    See :footcite:`CreativeCommons` for the licence.
+    See :footcite:t:`CreativeCommons` for the licence.
 
-    See :footcite:`Craddock2012` and :footcite:`nitrcClusterROI`
+    See :footcite:t:`Craddock2012` and :footcite:t:`nitrcClusterROI`
     for more information on this :term:`parcellation`.
 
     Parameters
@@ -292,8 +292,8 @@ def fetch_atlas_destrieux_2009(
     """Download and load the Destrieux cortical \
     :term:`deterministic atlas<Deterministic atlas>` (dated 2009).
 
-    See :footcite:`Fischl2004`,
-    and :footcite:`Destrieux2009`.
+    See :footcite:t:`Fischl2004`,
+    and :footcite:t:`Destrieux2009`.
 
     .. note::
 
@@ -828,9 +828,9 @@ def _compute_symmetric_split(source, atlas_niimg, names):
 def fetch_atlas_msdl(data_dir=None, url=None, resume=True, verbose=1):
     """Download and load the MSDL brain :term:`Probabilistic atlas`.
 
-    It can be downloaded at :footcite:`atlas_msdl`, and cited
-    using :footcite:`Varoquaux2011`.
-    See also :footcite:`Varoquaux2013` for more information.
+    It can be downloaded at :footcite:t:`atlas_msdl`, and cited
+    using :footcite:t:`Varoquaux2011`.
+    See also :footcite:t:`Varoquaux2013` for more information.
 
     Parameters
     ----------
@@ -903,7 +903,7 @@ def fetch_atlas_msdl(data_dir=None, url=None, resume=True, verbose=1):
 def fetch_coords_power_2011(legacy_format=True):
     """Download and load the Power et al. brain atlas composed of 264 ROIs.
 
-    See :footcite:`Power2011`.
+    See :footcite:t:`Power2011`.
 
     Parameters
     ----------
@@ -953,7 +953,7 @@ def fetch_atlas_smith_2009(
     """Download and load the Smith :term:`ICA` and BrainMap \
     :term:`Probabilistic atlas` (2009).
 
-    See :footcite:`Smith2009b` and :footcite:`Laird2011`.
+    See :footcite:t:`Smith2009b` and :footcite:t:`Laird2011`.
 
     Parameters
     ----------
@@ -981,14 +981,14 @@ def fetch_atlas_smith_2009(
               The shape of the image is ``(91, 109, 91, 20)``.
             - 'rsn10': :obj:`str`, path to nifti file containing the
               10 well-matched maps from the 20 maps obtained as for 'rsn20',
-              as shown in :footcite:`Smith2009b`. The shape of the
+              as shown in :footcite:t:`Smith2009b`. The shape of the
               image is ``(91, 109, 91, 10)``.
             - 'bm20': :obj:`str`, path to nifti file containing the
               20-dimensional :term:`ICA`, BrainMap components.
               The shape of the image is ``(91, 109, 91, 20)``.
             - 'bm10': :obj:`str`, path to nifti file containing the
               10 well-matched maps from the 20 maps obtained as for 'bm20',
-              as shown in :footcite:`Smith2009b`. The shape of the
+              as shown in :footcite:t:`Smith2009b`. The shape of the
               image is ``(91, 109, 91, 10)``.
             - 'rsn70': :obj:`str`, path to nifti file containing the
               70-dimensional :term:`ICA`, resting-:term:`fMRI` components.
@@ -1087,8 +1087,8 @@ def fetch_atlas_yeo_2011(data_dir=None, url=None, resume=True, verbose=1):
     7 or 17 depending on the atlas version considered.
 
     For more information on this dataset's structure,
-    see :footcite:`CorticalParcellation_Yeo2011`,
-    and :footcite:`Yeo2011`.
+    see :footcite:t:`CorticalParcellation_Yeo2011`,
+    and :footcite:t:`Yeo2011`.
 
     Parameters
     ----------
@@ -1198,8 +1198,8 @@ def fetch_atlas_aal(
     (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468, PubMed).
 
     For more information on this dataset's structure,
-    see :footcite:`AAL_atlas`,
-    and :footcite:`Tzourio-Mazoyer2002`.
+    see :footcite:t:`AAL_atlas`,
+    and :footcite:t:`Tzourio-Mazoyer2002`.
 
     .. warning::
 
@@ -1346,9 +1346,9 @@ def fetch_atlas_basc_multiscale_2015(
     Multiple resolutions (number of networks) are available, among
     7, 12, 20, 36, 64, 122, 197, 325, 444. The brain parcellations
     have been generated using a method called bootstrap analysis of
-    stable clusters called as BASC :footcite:`Bellec2010`,
+    stable clusters called as BASC :footcite:t:`Bellec2010`,
     and the resolutions have been selected using a data-driven method
-    called MSTEPS :footcite:`Bellec2013`.
+    called MSTEPS :footcite:t:`Bellec2013`.
 
     Note that two versions of the template are available, 'sym' or 'asym'.
     The 'asym' type contains brain images that have been registered in the
@@ -1485,7 +1485,7 @@ def fetch_coords_dosenbach_2010(ordered_regions=True, legacy_format=True):
     These ROIs cover much of the cerebral cortex
     and cerebellum and are assigned to 6 networks.
 
-    See :footcite:`Dosenbach2010`.
+    See :footcite:t:`Dosenbach2010`.
 
     Parameters
     ----------
@@ -1554,7 +1554,7 @@ def fetch_coords_seitzman_2018(ordered_regions=True, legacy_format=True):
     Visual) and have a regional label (cortexL, cortexR, cerebellum, thalamus,
     hippocampus, basalGanglia, amygdala, cortexMid).
 
-    See :footcite:`Seitzman2020`.
+    See :footcite:t:`Seitzman2020`.
 
     .. versionadded:: 0.5.1
 
@@ -1640,7 +1640,7 @@ def fetch_atlas_allen_2011(data_dir=None, url=None, resume=True, verbose=1):
     """Download and return file names for the Allen and MIALAB :term:`ICA` \
     :term:`Probabilistic atlas` (dated 2011).
 
-    See :footcite:`Allen2011`.
+    See :footcite:t:`Allen2011`.
 
     The provided images are in MNI152 space.
 
@@ -1660,7 +1660,7 @@ def fetch_atlas_allen_2011(data_dir=None, url=None, resume=True, verbose=1):
           T-maps of all 75 unthresholded components. The image has
           shape ``(53, 63, 46, 75)``.
         - 'rsn28': :obj:`str`, path to nifti file containing the
-          T-maps of 28 RSNs included in :footcite:`Allen2011`.
+          T-maps of 28 RSNs included in :footcite:t:`Allen2011`.
           The image has shape ``(53, 63, 46, 28)``.
         - 'networks': :obj:`list` of :obj:`list` of :obj:`str`, list
           containing the names for the 28 RSNs.
@@ -1742,7 +1742,7 @@ def fetch_atlas_surf_destrieux(
     """Download and load Destrieux et al, 2010 cortical \
     :term:`Deterministic atlas`.
 
-    See :footcite:`Destrieux2010`.
+    See :footcite:t:`Destrieux2010`.
 
     This atlas returns 76 labels per hemisphere based on sulco-gryal patterns
     as distributed with Freesurfer in fsaverage5 surface space.
@@ -1885,9 +1885,9 @@ def _download_talairach(talairach_dir, verbose):
 def fetch_atlas_talairach(level_name, data_dir=None, verbose=1):
     """Download the Talairach :term:`Deterministic atlas`.
 
-    For more information, see :footcite:`talairach_atlas`,
-    :footcite:`Lancaster2000`,
-    and :footcite:`Lancaster1997`.
+    For more information, see :footcite:t:`talairach_atlas`,
+    :footcite:t:`Lancaster2000`,
+    and :footcite:t:`Lancaster1997`.
 
     .. versionadded:: 0.4.0
 
@@ -1938,7 +1938,7 @@ def fetch_atlas_pauli_2017(version="prob", data_dir=None, verbose=1):
     """Download the Pauli et al. (2017) atlas.
 
     This atlas has 12 subcortical nodes in total. See
-    :footcite:`pauli_atlas` and :footcite:`Pauli2018`.
+    :footcite:t:`pauli_atlas` and :footcite:t:`Pauli2018`.
 
     Parameters
     ----------
@@ -2040,9 +2040,9 @@ def fetch_atlas_schaefer_2018(
     This function returns a :term:`Deterministic atlas`, and the provided
     images are in MNI152 space.
 
-    For more information on this dataset, see :footcite:`schaefer_atlas`,
-    :footcite:`Schaefer2017`,
-    and :footcite:`Yeo2011`.
+    For more information on this dataset, see :footcite:t:`schaefer_atlas`,
+    :footcite:t:`Schaefer2017`,
+    and :footcite:t:`Yeo2011`.
 
     Parameters
     ----------

nilearn/datasets/func.py

@@ -56,7 +56,7 @@ def fetch_haxby(
 ):
     """Download and loads complete haxby dataset.
 
-    See :footcite:`Haxby2001`.
+    See :footcite:t:`Haxby2001`.
 
     Parameters
     ----------
@@ -268,7 +268,7 @@ def adhd_ids():
 def fetch_adhd(n_subjects=30, data_dir=None, url=None, resume=True, verbose=1):
     """Download and load the ADHD :term:`resting-state` dataset.
 
-    See :footcite:`ADHDdataset`.
+    See :footcite:t:`ADHDdataset`.
 
     Parameters
     ----------
@@ -422,7 +422,7 @@ def miyawaki2008_file_mask():
 def fetch_miyawaki2008(data_dir=None, url=None, resume=True, verbose=1):
     """Download and loads Miyawaki et al. 2008 dataset (153MB).
 
-    See :footcite:`Miyawaki2008`.
+    See :footcite:t:`Miyawaki2008`.
 
     Parameters
     ----------
@@ -557,11 +557,11 @@ def fetch_localizer_contrasts(
     Functional Localizer page."
     (see https://osf.io/vhtf6/)
 
-    You may cite :footcite:`Papadopoulos-Orfanos2017`
+    You may cite :footcite:t:`Papadopoulos-Orfanos2017`
     when using this dataset.
 
     Scientific results obtained using this dataset are described
-    in :footcite:`Pinel2007`.
+    in :footcite:t:`Pinel2007`.
 
     Parameters
     ----------
@@ -1026,7 +1026,7 @@ def fetch_abide_pcp(
     Fetch the Autism Brain Imaging Data Exchange (ABIDE) dataset wrt criteria
     that can be passed as parameter. Note that this is the preprocessed
     version of ABIDE provided by the preprocess connectome projects (PCP).
-    See :footcite:`Nielsen2013`.
+    See :footcite:t:`Nielsen2013`.
 
     Parameters
     ----------
@@ -1348,7 +1348,7 @@ def fetch_mixed_gambles(
 ):
     """Fetch Jimura "mixed gambles" dataset.
 
-    See :footcite:`Jimura2012`.
+    See :footcite:t:`Jimura2012`.
 
     Parameters
     ----------
@@ -1431,9 +1431,9 @@ def fetch_megatrawls_netmats(
     The network matrices are estimated from functional connectivity
     datasets of 461 subjects. Full technical details in references.
 
-    More information available in :footcite:`Smith2015b`,
-    :footcite:`Smith2015a`, :footcite:`Filippini2009`,
-    :footcite:`Smith2014`, and :footcite:`Reilly2009`.
+    More information available in :footcite:t:`Smith2015b`,
+    :footcite:t:`Smith2015a`, :footcite:t:`Filippini2009`,
+    :footcite:t:`Smith2014`, and :footcite:t:`Reilly2009`.
 
     Parameters
     ----------
@@ -1664,9 +1664,9 @@ def fetch_surf_nki_enhanced(
     """Download and load the NKI enhanced :term:`resting-state` dataset, \
     preprocessed and projected to the fsaverage5 space surface.
 
-    See :footcite:`Nooner2012`.
+    See :footcite:t:`Nooner2012`.
 
-    Direct download link :footcite:`NKIdataset`.
+    Direct download link :footcite:t:`NKIdataset`.
 
     .. versionadded:: 0.3
 
@@ -1958,7 +1958,7 @@ def fetch_development_fmri(
     with a repetition time (TR) of 2 secs.
     The origin of the data is coming from OpenNeuro. See Notes below.
 
-    Please cite :footcite:`Richardson2018`
+    Please cite :footcite:t:`Richardson2018`
     if you are using this dataset.
 
     .. versionadded:: 0.5.2
@@ -2763,7 +2763,7 @@ def fetch_spm_auditory(
 ):
     """Fetch :term:`SPM` auditory single-subject data.
 
-    See :footcite:`spm_auditory`.
+    See :footcite:t:`spm_auditory`.
 
     Parameters
     ----------
@@ -2952,7 +2952,7 @@ def fetch_spm_multimodal_fmri(
 ):
     """Fetcher for Multi-modal Face Dataset.
 
-    See :footcite:`spm_multiface`.
+    See :footcite:t:`spm_multiface`.
 
     Parameters
     ----------

nilearn/datasets/neurovault.py

@@ -2466,8 +2466,8 @@ def fetch_neurovault(
     skimmed through the whole database or until an (optional) maximum
     number of images to fetch has been reached.
 
-    For more information, see :footcite:`Gorgolewski2015`,
-    and :footcite:`Yarkoni2011`.
+    For more information, see :footcite:t:`Gorgolewski2015`,
+    and :footcite:t:`Yarkoni2011`.
 
     Parameters
     ----------
@@ -2692,8 +2692,8 @@ def fetch_neurovault_ids(
     This is the fast way to get the data from the server if we already
     know which images or collections we want.
 
-    For more information, see :footcite:`Gorgolewski2015`,
-    and :footcite:`Yarkoni2011`.
+    For more information, see :footcite:t:`Gorgolewski2015`,
+    and :footcite:t:`Yarkoni2011`.
 
     Parameters
     ----------