codespell: config, action + some typo fixups (#2958)

.codespellrc

@@ -0,0 +1,6 @@
+[codespell]
+skip = .git,*.pdf,*.svg,*.html,dataset_description.json
+# te - TE
+# Weill - name
+# reson - Reson. abbreviation in citation
+ignore-words-list = te,weill,reson

.github/workflows/contrib.yml

@@ -47,3 +47,13 @@ jobs:
         run: |
           python -m black --diff --color --check wrapper
           python -m isort --diff --color --check wrapper
+  
+  codespell:
+    name: Check for spelling errors
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Codespell
+        uses: codespell-project/actions-codespell@v1

CHANGES.rst

@@ -506,7 +506,7 @@ This release also includes some maintenance changes handling old versions of sof
 Bug-fix release in the 20.1.x series.
 
 * FIX: Dependency conflict between *NiWorkflows* and *TemplateFlow* (#2269)
-* FIX: More targetted *TemplateFlow* queries to work with all later releases (#2268)
+* FIX: More targeted *TemplateFlow* queries to work with all later releases (#2268)
 * MAINT: Update dependency pinnings including ``niworkflows~=1.2.9`` and three minimal bug-fixes.
 
 20.1.2 (September 04, 2020)
@@ -1498,7 +1498,7 @@ With thanks to @mgxd and @naveau for contributions.
 ---------------------------
 * FIX: Pin niworkflows-0.2.4 to fix (#868).
 * FIX: Roll back run/task groupings after BIDS query (#918).
-  Groupings for the multi-echo extension will be reenabled soon.
+  Groupings for the multi-echo extension will be re-enabled soon.
 
 1.0.2 (2nd of January 2018)
 ---------------------------

docs/installation.rst

@@ -39,7 +39,7 @@ of containerized execution drawn from the BIDS-Apps protocols.
 For detailed information of containerized execution of *NiPreps*, please visit the corresponding
 `Docker <https://www.nipreps.org/apps/docker/>`__
 or `Singularity <https://www.nipreps.org/apps/singularity/>`__ subsections.
-The *NiPreps* portal also containes
+The *NiPreps* portal also contains
 `extended details of execution with the Docker wrapper <https://www.nipreps.org/apps/docker/#running-a-niprep-with-a-lightweight-wrapper>`__.
 
 Manually Prepared Environment (Python 3.8+)

docs/workflows.rst

@@ -431,7 +431,7 @@ original space.
 All volumes in the :abbr:`BOLD (blood-oxygen level-dependent)` series are
 resampled in their native space by concatenating the mappings found in previous
 correction workflows (:abbr:`HMC (head-motion correction)` and
-:abbr:`SDC (susceptibility-derived distortion correction)` if excecuted)
+:abbr:`SDC (susceptibility-derived distortion correction)` if executed)
 for a one-shot interpolation process.
 Interpolation uses a Lanczos kernel.
 

fmriprep/cli/parser.py

@@ -572,7 +572,7 @@ def _slice_time_ref(value, parser):
         dest="verbose_count",
         action="count",
         default=0,
-        help="Increases log verbosity for each occurence, debug level is -vvv",
+        help="Increases log verbosity for each occurrence, debug level is -vvv",
     )
     g_other.add_argument(
         "-w",

fmriprep/config.py

@@ -28,7 +28,7 @@
 each run and subject is left under
 ``<fmriprep_dir>/sub-<participant_id>/log/<run_unique_id>/fmriprep.toml``.
 Settings are stored using :abbr:`ToML (Tom's Markup Language)`.
-The module has a :py:func:`~fmriprep.config.to_filename` function to allow writting out
+The module has a :py:func:`~fmriprep.config.to_filename` function to allow writing out
 the settings to hard disk in *ToML* format, which looks like:
 
 .. literalinclude:: ../fmriprep/data/tests/config.toml
@@ -644,7 +644,7 @@ def _set_ants_seed():
 
 
 def _set_numpy_seed():
-    """NumPy's random seed is independant from Python's `random` module"""
+    """NumPy's random seed is independent from Python's `random` module"""
     import numpy as np
 
     val = random.randint(1, 65536)

fmriprep/data/reports-spec.yml

@@ -86,7 +86,7 @@ sections:
     subtitle: Alignment between the anatomical reference of the fieldmap and the target EPI (debug mode)
   - bids: {datatype: figures, desc: fieldmap, suffix: bold}
     caption: Estimated fieldmap, as reconstructed on the target BOLD run space to allow
-      the assessment of its alignement with the distorted data.
+      the assessment of its alignment with the distorted data.
       The anatomical reference is the fieldmap's reference moved into the target EPI's grid through
       the estimated transformation.
       In other words, this plot should be equivalent to that of the 

fmriprep/interfaces/confounds.py

@@ -343,7 +343,7 @@ def camel_to_snake(name):
         return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
 
     def _adjust_indices(left_df, right_df):
-        # This forces missing values to appear at the beggining of the DataFrame
+        # This forces missing values to appear at the beginning of the DataFrame
         # instead of the end
         index_diff = len(left_df.index) - len(right_df.index)
         if index_diff > 0:

fmriprep/workflows/base.py

@@ -409,7 +409,7 @@ def init_single_subject_wf(subject_id: str):
                 f"{[e.method for e in fmap_estimators]}."
             )
 
-    # Append the functional section to the existing anatomical exerpt
+    # Append the functional section to the existing anatomical excerpt
     # That way we do not need to stream down the number of bold datasets
     func_pre_desc = """
 Functional data preprocessing

fmriprep/workflows/bold/t2s.py

@@ -126,7 +126,7 @@ def init_t2s_reporting_wf(name: str = 't2s_reporting_wf'):
     r"""
     Generate T2\*-map reports.
 
-    This workflow generates a histogram of esimated T2\* values (in seconds) in the
+    This workflow generates a histogram of estimated T2\* values (in seconds) in the
     cortical and subcortical gray matter mask.
 
     Parameters

long_description.rst

@@ -15,7 +15,7 @@ fMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessin
 workflow, which can help ensure the validity of inference and the interpretability
 of results.
 
-The workflow is based on `Nipype <https://nipype.readthedocs.io>`_ and encompases a large
+The workflow is based on `Nipype <https://nipype.readthedocs.io>`_ and encompasses a large
 set of tools from well-known neuroimaging packages, including
 `FSL <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>`_,
 `ANTs <https://stnava.github.io/ANTs/>`_,