[FIX] bug fix 892

demos/ds003717/code/03_stats.m

@@ -15,7 +15,7 @@
 % You can try some of the other models from the models folder.
 model_file = fullfile(cwd, 'models', 'model-defaultSESS01_smdl.json');
 
-% definte what result to see
+% define what result to see
 opt.results(1) = defaultResultsStructure();
 opt.results(1).nodeName = 'run_combine_AV';
 opt.results(1).name = 'AV';

demos/ds003717/code/04_transformation.m

@@ -6,7 +6,7 @@
 %
 % in the trial type column by the value AV
 %
-% This is an example of how to desgin a transformer
+% This is an example of how to design a transformer
 % to then use it in your bids stats model.
 % One could also use the same approach to create a transformer
 % with many more steps.

docs/poster/OHBM_2023.bib

@@ -61,7 +61,7 @@ @article{nidm_results
   doi      = {10.1038/sdata.2016.102},
   abstract = {Abstract
 
-              Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at:
+              Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publicly available at:
               http://nidm.nidash.org/specs/nidm-results.html
               .},
   language = {en},

docs/poster/paper.Rmd

@@ -81,7 +81,7 @@ neuroimaging data (see for example @esteban_fmriprep_2019).
 
 But there is no common library that, independently of the imaging modality:
 
-- can index and query data and metdata BIDS dataset (whether they are raw or
+- can index and query data and metadata BIDS dataset (whether they are raw or
   derivatives datasets)
 - helps easily create filenames that follow a BIDS pattern
 - can interact with the BIDS schema
@@ -97,7 +97,7 @@ features.
 
 ## Indexing and querying datasets
 
-When a dataset has several dozens of participants with heterogenous content in
+When a dataset has several dozens of participants with heterogeneous content in
 terms of imaging modality or acquisition parameters and with metadata for even a
 single data file potentially spread across several JSON files, it can become
 difficult to fetch the right file or piece of metadata.
@@ -115,7 +115,7 @@ BIDS schema or not, but require that they follow typical BIDS filenaming
 patterns (like those generated by fMRIprep [@esteban_fmriprep_2019] - see
 [next section](#creating-bids-valid-filenames) for more details).
 
-One notable extension was made to this filename parsing rule to accomodate
+One notable extension was made to this filename parsing rule to accommodate
 filenames that include a prefix before the standard BIDS filename (for example
 `swuasub-01_task-rest_bold.nii` with the prefix `swua`) as prefixing is such a
 common way to deal with derivatives filenames.
@@ -131,7 +131,7 @@ datatype/sub-subLabel(_entity-label)*_suffix\.ext
 
 <!-- test pseudo regex above and add link and example  -->
 
-As of this writing, the BIDS specfication supports:
+As of this writing, the BIDS specification supports:
 
 - 12 datatypes (for example: `func`, `anat`, `eeg`...)
 - 28 different entities (for example: `ses`, `task`, `acq`...)

src/stats/subject_level/convertRealignParamToTsv.m → src/IO/convertRealignParamToTsv.m

@@ -30,6 +30,12 @@
     rmInput = false;
   end
 
+  % dirty hack to fix bug 892
+  % ideally replace with a better solution if the cause of the problem gets identified.
+  if ismember(newline, rpTxtFile)
+    rpTxtFile = strrep(rpTxtFile, newline, '');
+  end
+
   content = spm_load(rpTxtFile);
 
   if ~strcmp(opt.bidsFilterFile.bold.suffix, 'bold')

tests/tests_stats/subject_level/test_convertRealignParamToTsv.m → tests/tests_preproc/utils/test_convertRealignParamToTsv.m

@@ -13,7 +13,7 @@ function test_convertRealignParamToTsv_basic()
   opt = setOptions('vislocalizer');
 
   input = fullfile(opt.dir.preproc, 'sub-01', 'ses-01', 'func', ...
-                   'rp_sub-01_ses-01_task-vislocalizer_bold.txt');
+                   sprintf('rp_sub-01_ses-01_task-vislocalizer_bold.txt\n'));
 
   opt = set_spm_2_bids_defaults(opt);