Merge branch 'main' into T54A-refactoring

.github/workflows/code_quality.yml

@@ -8,9 +8,11 @@ on:
   push:
     paths:
       - '**.py'
+      - '.github/workflows/code_quality.yml'
   pull_request:
     paths:
       - '**.py'
+      - '.github/workflows/code_quality.yml'
 
 # Jobs that define the workflow
 jobs:
@@ -33,22 +35,23 @@ jobs:
     - uses: actions/cache@v3
       with:
         path: ~/.cache/pip
-        key: ${{ runner.os }}-pip-pylint
+        key: ${{ runner.os }}-pip-${{ hashFiles('setup.py') }}
         restore-keys: |
-          ${{ runner.os }}-pip-pylint
+          ${{ runner.os }}-pip-
 
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install pylint
+        pip install .[tests]
 
     - name: Analyse the code with pylint
       run: |
-        pylint --exit-zero narps_open > pylint_report_narps_open.txt
-        pylint --exit-zero tests > pylint_report_tests.txt
+        pylint --fail-under 8 --ignore-paths narps_open/pipelines/ narps_open > pylint_report_narps_open.txt
+        pylint --fail-under 8 tests > pylint_report_tests.txt
 
     - name: Archive pylint results
       uses: actions/upload-artifact@v3
+      if: failure() # Only if previous step failed
       with:
         name: pylint-reports-python
         path: |

.github/workflows/pipeline_tests.yml

@@ -47,7 +47,7 @@ jobs:
         echo "tests=$test_files" >> $GITHUB_OUTPUT
         echo "teams=$teams" >> $GITHUB_OUTPUT
 
-  # A job to identify and run the tests
+  # A job to run the tests
   pytest:
     needs: identify-tests
     runs-on: self-hosted

.github/workflows/test_changes.yml

@@ -38,7 +38,7 @@ jobs:
         echo $test_files
         echo "tests=$test_files" >> $GITHUB_OUTPUT
 
-  # A job to list the tests to be run
+  # A job to run the tests
   pytest:
     needs: identify-tests
     runs-on: self-hosted

README.md

@@ -65,3 +65,13 @@ To get the pipelines running, please follow the installation steps in [INSTALL.m
 ## Funding
 
 This project is supported by Région Bretagne (Boost MIND). 
+
+## Credits
+
+This project is developed in the Empenn team by Boris Clenet, Elodie Germani, Jeremy Lefort-Besnard and Camille Maumet with contributions by Rémi Gau.
+
+In addition, this project was presented and received contributions during the following events:
+ - OHBM Brainhack 2022 (June 2022): Elodie Germani, Arshitha Basavaraj, Trang Cao, Rémi Gau, Anna Menacher, Camille Maumet.
+ - e-ReproNim FENS NENS Cluster Brainhack: <ADD_NAMES_HERE>
+ - OHBM Brainhack 2023 (July 2023): <ADD_NAMES_HERE>
+ - ORIGAMI lab hackathon (Sept 2023): 

docs/description.md

@@ -8,7 +8,7 @@ The file `narps_open/data/description/analysis_pipelines_derived_descriptions.ts
 
 The class `TeamDescription` of module `narps_open.data.description` acts as a parser for these two files.
 
-You can also use the command-line tool as so. Option `-t` is for the team id, option `-d` allows to print only one of the sub parts of the description among : `general`, `exclusions`, `preprocessing`, `analysis`, and `categorized_for_analysis`.
+You can use the command-line tool as so. Option `-t` is for the team id, option `-d` allows to print only one of the sub parts of the description among : `general`, `exclusions`, `preprocessing`, `analysis`, and `categorized_for_analysis`. Options `--json` and `--md` allow to choose the export format you prefer between JSON and Markdown.
 
 ```bash
 python narps_open/data/description -h
@@ -21,8 +21,25 @@ python narps_open/data/description -h
 #   -t TEAM, --team TEAM  the team ID
 #   -d {general,exclusions,preprocessing,analysis,categorized_for_analysis,derived}, --dictionary {general,exclusions,preprocessing,analysis,categorized_for_analysis,derived}
 #                         the sub dictionary of team description
+#  --json                output team description as JSON
+#  --md                  output team description as Markdown
 
-python narps_open/data/description -t 2T6S -d general
+python narps_open/data/description -t 2T6S --json
+# {
+#     "general.teamID": "2T6S",
+#     "general.NV_collection_link": "https://neurovault.org/collections/4881/",
+#     "general.results_comments": "NA",
+#     "general.preregistered": "No",
+#     "general.link_preregistration_form": "We did not pre-register our analysis.",
+#     "general.regions_definition": "We employed the pre-hypothesized brain regions (vmPFC, vSTR, and amygdala) from Barta, McGuire, and Kable (2010, Neuroimage). Specific MNI coordinates are:\nvmPFC: x = 2, y = 46, z = -8\nleft vSTR: x = -12, y = 12, z = -6, right vSTR = x = 12, y = 10, z = -6\n(right) Amygdala: x = 24, y = -4, z = -18",
+#     "general.softwares": "SPM12 , \nfmriprep 1.1.4",
+#     "exclusions.n_participants": "108",
+#     "exclusions.exclusions_details": "We did not exclude any participant in the analysis",
+#     "preprocessing.used_fmriprep_data": "Yes",
+#     "preprocessing.preprocessing_order": "We used the provided preprocessed data by fMRIPprep 1.1.4 (Esteban, Markiewicz, et al. (2018); Esteban, Blair, et al. (2018); RRID:SCR_016216), which is based on Nipype 1.1.1 (Gorgolewski et al. (2011); Gorgolewski et al. (2018); RRID:SCR_002502) and we additionally conducted a spatial smoothing using the provided preprocessed data set and SPM12. Here, we attach the preprocessing steps described in the provided data set. \nAnatomical data preprocessing\nThe T1-weighted (T1w) image was corrected for intensity non-uniformity (INU) using N4BiasFieldCorrection (Tustison et al. 2010, ANTs 2.2.0), and used as T1w-reference throughout the workflow. The T1w-reference was then skull-stripped using antsBrainExtraction.sh (ANTs 2.2.0), using OASIS as target template. Brain surfaces we
+# ...
+
+python narps_open/data/description -t 2T6S -d general --json
 # {
 #    "teamID": "2T6S",
 #    "NV_collection_link": "https://neurovault.org/collections/4881/",
@@ -33,6 +50,30 @@ python narps_open/data/description -t 2T6S -d general
 #    "softwares": "SPM12 , \nfmriprep 1.1.4",
 #    "general_comments": "NA"
 # }
+
+python narps_open/data/description -t 2T6S --md
+# # NARPS team description : 2T6S
+# ## General
+# * `teamID` : 2T6S
+# * `NV_collection_link` : https://neurovault.org/collections/4881/
+# * `results_comments` : NA
+# * `preregistered` : No
+# * `link_preregistration_form` : We did not pre-register our analysis.
+# * `regions_definition` : We employed the pre-hypothesized brain regions (vmPFC, vSTR, and amygdala) from Barta, McGuire, and Kable (2010, Neuroimage). Specific MNI coordinates are:
+# vmPFC: x = 2, y = 46, z = -8
+# left vSTR: x = -12, y = 12, z = -6, right vSTR = x = 12, y = 10, z = -6
+# (right) Amygdala: x = 24, y = -4, z = -18
+# * `softwares` : SPM12 , 
+# fmriprep 1.1.4
+# * `general_comments` : NA
+# ## Exclusions
+# * `n_participants` : 108
+# * `exclusions_details` : We did not exclude any participant in the analysis
+# ## Preprocessing
+# * `used_fmriprep_data` : Yes
+# * `preprocessing_order` : We used the provided preprocessed data by fMRIPprep 1.1.4 (Esteban, Markiewicz, et al. (2018); Esteban, Blair, et al. (2018); RRID:SCR_016216), which is based on Nipype 1.1.1 (Gorgolewski et al. (2011); Gorgolewski et al. (2018); RRID:SCR_002502) and we additionally conducted a spatial smoothing using the provided preprocessed data set and SPM12. Here, we attach the preprocessing steps described in the provided data set. 
+# Anatomical data preprocessing
+# ...
 ```
 
 Of course the `narps_open.data.description` module is accessible programmatically, here is an example on how to use it:

docs/status.md

@@ -36,7 +36,7 @@ print(pipeline_info['status'])
 report.markdown() # Returns a string containing the markdown
 ```
 
-You can also use the command-line tool as so. Option `-t` is for the team id, option `-d` allows to print only one of the sub parts of the description among : `general`, `exclusions`, `preprocessing`, `analysis`, and `categorized_for_analysis`.
+You can also use the command-line tool as so.
 
 ```bash
 python narps_open/utils/status -h

narps_open/data/description/__init__.py

@@ -5,6 +5,7 @@
 
 from os.path import join
 from csv import DictReader
+from json import dumps
 from importlib_resources import files
 
 class TeamDescription(dict):
@@ -25,6 +26,9 @@ def __init__(self, team_id):
         self.team_id = team_id
         self._load()
 
+    def __str__(self):
+        return dumps(self, indent = 4)
+
     @property
     def general(self) -> dict:
         """ Getter for the sub dictionary general """
@@ -55,6 +59,35 @@ def derived(self) -> dict:
         """ Getter for the sub dictionary containing derived team description """
         return self._get_sub_dict('derived')
 
+    def markdown(self):
+        """ Return the team description as a string formatted in markdown """
+        return_string = f'# NARPS team description : {self.team_id}\n'
+
+        dictionaries = [
+            self.general,
+            self.exclusions,
+            self.preprocessing,
+            self.analysis,
+            self.categorized_for_analysis,
+            self.derived
+            ]
+
+        names = [
+            'General',
+            'Exclusions',
+            'Preprocessing',
+            'Analysis',
+            'Categorized for analysis',
+            'Derived'
+            ]
+
+        for dictionary, name in zip(dictionaries, names):
+            return_string += f'## {name}\n'
+            for key in dictionary:
+                return_string += f'* `{key}` : {dictionary[key]}\n'
+
+        return return_string
+
     def _get_sub_dict(self, key_first_part:str) -> dict:
         """ Return a sub-dictionary of self, with keys that contain key_first_part.
             The first part of the keys are removed, e.g.:

narps_open/data/description/__main__.py

@@ -22,22 +22,32 @@
         'derived'
         ],
     help='the sub dictionary of team description')
+formats = parser.add_mutually_exclusive_group(required = False)
+formats.add_argument('--json', action='store_true', help='output team description as JSON')
+formats.add_argument('--md', action='store_true', help='output team description as Markdown')
 arguments = parser.parse_args()
 
 # Initialize a TeamDescription
 information = TeamDescription(team_id = arguments.team)
 
-if arguments.dictionary == 'general':
-    print(dumps(information.general, indent = 4))
-elif arguments.dictionary == 'exclusions':
-    print(dumps(information.exclusions, indent = 4))
-elif arguments.dictionary == 'preprocessing':
-    print(dumps(information.preprocessing, indent = 4))
-elif arguments.dictionary == 'analysis':
-    print(dumps(information.analysis, indent = 4))
-elif arguments.dictionary == 'categorized_for_analysis':
-    print(dumps(information.categorized_for_analysis, indent = 4))
-elif arguments.dictionary == 'derived':
-    print(dumps(information.derived, indent = 4))
+# Output description
+if arguments.md and arguments.dictionary is not None:
+    print('Sub dictionaries cannot be exported as Markdown yet.')
+    print('Print the whole description instead.')
+elif arguments.md:
+    print(information.markdown())
 else:
-    print(dumps(information, indent = 4))
+    if arguments.dictionary == 'general':
+        print(dumps(information.general, indent = 4))
+    elif arguments.dictionary == 'exclusions':
+        print(dumps(information.exclusions, indent = 4))
+    elif arguments.dictionary == 'preprocessing':
+        print(dumps(information.preprocessing, indent = 4))
+    elif arguments.dictionary == 'analysis':
+        print(dumps(information.analysis, indent = 4))
+    elif arguments.dictionary == 'categorized_for_analysis':
+        print(dumps(information.categorized_for_analysis, indent = 4))
+    elif arguments.dictionary == 'derived':
+        print(dumps(information.derived, indent = 4))
+    else:
+        print(dumps(information, indent = 4))

narps_open/pipelines/__init__.py

@@ -62,7 +62,7 @@
     'O6R6': None,
     'P5F3': None,
     'Q58J': None,
-    'Q6O0': None,
+    'Q6O0': 'PipelineTeamQ6O0',
     'R42Q': None,
     'R5K7': None,
     'R7D1': None,