From 009a972652fadbf98dc9fc8ae274d862df276e9d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Boris=20Cl=C3=A9net?=
 <117362283+bclenet@users.noreply.github.com>
Date: Mon, 26 Feb 2024 17:01:38 +0100
Subject: [PATCH 1/3] Pytest fixture to use temporary directories (#182)

* [TEST] Using temp_dir folder [DOC] paths inside container [LINT] pylint config file

* Updating conftest file

* Updating pipeline tests
---
 .gitignore                                    |   2 +-
 .pylintrc                                     | 631 ++++++++++++++++++
 INSTALL.md                                    |  10 +-
 docs/environment.md                           |   4 +-
 .../utils/configuration/default_config.toml   |   6 +-
 .../utils/configuration/testing_config.toml   |  10 +-
 tests/conftest.py                             |  12 +-
 tests/core/test_common.py                     |  65 +-
 tests/pipelines/test_team_J7F9.py             |  21 +-
 tests/pipelines/test_team_T54A.py             |  21 +-
 tests/pipelines/test_team_U26C.py             |  60 +-
 tests/pipelines/test_team_X19V.py             |  40 +-
 tests/test_conftest.py                        |  58 +-
 13 files changed, 746 insertions(+), 194 deletions(-)
 create mode 100755 .pylintrc

diff --git a/.gitignore b/.gitignore
index 5b1b525d..d8afe952 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,6 @@
 
 # to avoid commiting data
-./data/
+data/
 
 # neuro user in docker image
 neuro
diff --git a/.pylintrc b/.pylintrc
new file mode 100755
index 00000000..3bfeb5ee
--- /dev/null
+++ b/.pylintrc
@@ -0,0 +1,631 @@
+[MAIN]
+
+# Analyse import fallback blocks. This can be used to support both Python 2 and
+# 3 compatible code, which means that the block might have code that exists
+# only in one or another interpreter, leading to false positives when analysed.
+analyse-fallback-blocks=no
+
+# Clear in-memory caches upon conclusion of linting. Useful if running pylint
+# in a server-like mode.
+clear-cache-post-run=no
+
+# Load and enable all available extensions. Use --list-extensions to see a list
+# all available extensions.
+#enable-all-extensions=
+
+# In error mode, messages with a category besides ERROR or FATAL are
+# suppressed, and no reports are done by default. Error mode is compatible with
+# disabling specific errors.
+#errors-only=
+
+# Always return a 0 (non-error) status code, even if lint errors are found.
+# This is primarily useful in continuous integration scripts.
+#exit-zero=
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code.
+extension-pkg-allow-list=
+
+# A comma-separated list of package or module names from where C extensions may
+# be loaded. Extensions are loading into the active Python interpreter and may
+# run arbitrary code. (This is an alternative name to extension-pkg-allow-list
+# for backward compatibility.)
+extension-pkg-whitelist=
+
+# Return non-zero exit code if any of these messages/categories are detected,
+# even if score is above --fail-under value. Syntax same as enable. Messages
+# specified are enabled, while categories only check already-enabled messages.
+fail-on=
+
+# Specify a score threshold under which the program will exit with error.
+fail-under=10
+
+# Interpret the stdin as a python script, whose filename needs to be passed as
+# the module_or_package argument.
+#from-stdin=
+
+# Files or directories to be skipped. They should be base names, not paths.
+ignore=CVS
+
+# Add files or directories matching the regular expressions patterns to the
+# ignore-list. The regex matches against paths and can be in Posix or Windows
+# format. Because '\\' represents the directory delimiter on Windows systems,
+# it can't be used as an escape character.
+ignore-paths=
+
+# Files or directories matching the regular expression patterns are skipped.
+# The regex matches against base names, not paths. The default value ignores
+# Emacs file locks
+ignore-patterns=^\.#
+
+# List of module names for which member attributes should not be checked
+# (useful for modules/projects where namespaces are manipulated during runtime
+# and thus existing member attributes cannot be deduced by static analysis). It
+# supports qualified module names, as well as Unix pattern matching.
+ignored-modules=pytest
+
+# Python code to execute, usually for sys.path manipulation such as
+# pygtk.require().
+#init-hook=
+
+# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the
+# number of processors available to use, and will cap the count on Windows to
+# avoid hangs.
+jobs=1
+
+# Control the amount of potential inferred values when inferring a single
+# object. This can help the performance when dealing with large functions or
+# complex, nested conditions.
+limit-inference-results=100
+
+# List of plugins (as comma separated values of python module names) to load,
+# usually to register additional checkers.
+load-plugins=
+
+# Pickle collected data for later comparisons.
+persistent=yes
+
+# Minimum Python version to use for version dependent checks. Will default to
+# the version used to run pylint.
+py-version=3.10
+
+# Discover python modules and packages in the file system subtree.
+recursive=no
+
+# Add paths to the list of the source roots. Supports globbing patterns. The
+# source root is an absolute path or a path relative to the current working
+# directory used to determine a package namespace for modules located under the
+# source root.
+source-roots=
+
+# When enabled, pylint would attempt to guess common misconfiguration and emit
+# user-friendly hints instead of false-positive error messages.
+suggestion-mode=yes
+
+# Allow loading of arbitrary C extensions. Extensions are imported into the
+# active Python interpreter and may run arbitrary code.
+unsafe-load-any-extension=no
+
+# In verbose mode, extra non-checker-related info will be displayed.
+#verbose=
+
+
+[BASIC]
+
+# Naming style matching correct argument names.
+argument-naming-style=snake_case
+
+# Regular expression matching correct argument names. Overrides argument-
+# naming-style. If left empty, argument names will be checked with the set
+# naming style.
+#argument-rgx=
+
+# Naming style matching correct attribute names.
+attr-naming-style=snake_case
+
+# Regular expression matching correct attribute names. Overrides attr-naming-
+# style. If left empty, attribute names will be checked with the set naming
+# style.
+#attr-rgx=
+
+# Bad variable names which should always be refused, separated by a comma.
+bad-names=foo,
+          bar,
+          baz,
+          toto,
+          tutu,
+          tata
+
+# Bad variable names regexes, separated by a comma. If names match any regex,
+# they will always be refused
+bad-names-rgxs=
+
+# Naming style matching correct class attribute names.
+class-attribute-naming-style=any
+
+# Regular expression matching correct class attribute names. Overrides class-
+# attribute-naming-style. If left empty, class attribute names will be checked
+# with the set naming style.
+#class-attribute-rgx=
+
+# Naming style matching correct class constant names.
+class-const-naming-style=UPPER_CASE
+
+# Regular expression matching correct class constant names. Overrides class-
+# const-naming-style. If left empty, class constant names will be checked with
+# the set naming style.
+#class-const-rgx=
+
+# Naming style matching correct class names.
+class-naming-style=PascalCase
+
+# Regular expression matching correct class names. Overrides class-naming-
+# style. If left empty, class names will be checked with the set naming style.
+#class-rgx=
+
+# Naming style matching correct constant names.
+const-naming-style=UPPER_CASE
+
+# Regular expression matching correct constant names. Overrides const-naming-
+# style. If left empty, constant names will be checked with the set naming
+# style.
+#const-rgx=
+
+# Minimum line length for functions/classes that require docstrings, shorter
+# ones are exempt.
+docstring-min-length=-1
+
+# Naming style matching correct function names.
+function-naming-style=snake_case
+
+# Regular expression matching correct function names. Overrides function-
+# naming-style. If left empty, function names will be checked with the set
+# naming style.
+#function-rgx=
+
+# Good variable names which should always be accepted, separated by a comma.
+good-names=i,
+           j,
+           k,
+           ex,
+           Run,
+           _
+
+# Good variable names regexes, separated by a comma. If names match any regex,
+# they will always be accepted
+good-names-rgxs=
+
+# Include a hint for the correct naming format with invalid-name.
+include-naming-hint=no
+
+# Naming style matching correct inline iteration names.
+inlinevar-naming-style=any
+
+# Regular expression matching correct inline iteration names. Overrides
+# inlinevar-naming-style. If left empty, inline iteration names will be checked
+# with the set naming style.
+#inlinevar-rgx=
+
+# Naming style matching correct method names.
+method-naming-style=snake_case
+
+# Regular expression matching correct method names. Overrides method-naming-
+# style. If left empty, method names will be checked with the set naming style.
+#method-rgx=
+
+# Naming style matching correct module names.
+module-naming-style=snake_case
+
+# Regular expression matching correct module names. Overrides module-naming-
+# style. If left empty, module names will be checked with the set naming style.
+#module-rgx=
+
+# Colon-delimited sets of names that determine each other's naming style when
+# the name regexes allow several styles.
+name-group=
+
+# Regular expression which should only match function or class names that do
+# not require a docstring.
+no-docstring-rgx=^_
+
+# List of decorators that produce properties, such as abc.abstractproperty. Add
+# to this list to register other decorators that produce valid properties.
+# These decorators are taken in consideration only for invalid-name.
+property-classes=abc.abstractproperty
+
+# Regular expression matching correct type alias names. If left empty, type
+# alias names will be checked with the set naming style.
+#typealias-rgx=
+
+# Regular expression matching correct type variable names. If left empty, type
+# variable names will be checked with the set naming style.
+#typevar-rgx=
+
+# Naming style matching correct variable names.
+variable-naming-style=snake_case
+
+# Regular expression matching correct variable names. Overrides variable-
+# naming-style. If left empty, variable names will be checked with the set
+# naming style.
+#variable-rgx=
+
+
+[CLASSES]
+
+# Warn about protected attribute access inside special methods
+check-protected-access-in-special-methods=no
+
+# List of method names used to declare (i.e. assign) instance attributes.
+defining-attr-methods=__init__,
+                      __new__,
+                      setUp,
+                      asyncSetUp,
+                      __post_init__
+
+# List of member names, which should be excluded from the protected access
+# warning.
+exclude-protected=_asdict,_fields,_replace,_source,_make,os._exit
+
+# List of valid names for the first argument in a class method.
+valid-classmethod-first-arg=cls
+
+# List of valid names for the first argument in a metaclass class method.
+valid-metaclass-classmethod-first-arg=mcs
+
+
+[DESIGN]
+
+# List of regular expressions of class ancestor names to ignore when counting
+# public methods (see R0903)
+exclude-too-few-public-methods=
+
+# List of qualified class names to ignore when counting class parents (see
+# R0901)
+ignored-parents=
+
+# Maximum number of arguments for function / method.
+max-args=5
+
+# Maximum number of attributes for a class (see R0902).
+max-attributes=7
+
+# Maximum number of boolean expressions in an if statement (see R0916).
+max-bool-expr=5
+
+# Maximum number of branch for function / method body.
+max-branches=12
+
+# Maximum number of locals for function / method body.
+max-locals=15
+
+# Maximum number of parents for a class (see R0901).
+max-parents=7
+
+# Maximum number of public methods for a class (see R0904).
+max-public-methods=20
+
+# Maximum number of return / yield for function / method body.
+max-returns=6
+
+# Maximum number of statements in function / method body.
+max-statements=50
+
+# Minimum number of public methods for a class (see R0903).
+min-public-methods=2
+
+
+[EXCEPTIONS]
+
+# Exceptions that will emit a warning when caught.
+overgeneral-exceptions=builtins.BaseException,builtins.Exception
+
+
+[FORMAT]
+
+# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
+expected-line-ending-format=
+
+# Regexp for a line that is allowed to be longer than the limit.
+ignore-long-lines=^\s*(# )?<?https?://\S+>?$
+
+# Number of spaces of indent required inside a hanging or continued line.
+indent-after-paren=4
+
+# String used as indentation unit. This is usually "    " (4 spaces) or "\t" (1
+# tab).
+indent-string='    '
+
+# Maximum number of characters on a single line.
+max-line-length=100
+
+# Maximum number of lines in a module.
+max-module-lines=1000
+
+# Allow the body of a class to be on the same line as the declaration if body
+# contains single statement.
+single-line-class-stmt=no
+
+# Allow the body of an if to be on the same line as the test if there is no
+# else.
+single-line-if-stmt=no
+
+
+[IMPORTS]
+
+# List of modules that can be imported at any level, not just the top level
+# one.
+allow-any-import-level=
+
+# Allow explicit reexports by alias from a package __init__.
+allow-reexport-from-package=no
+
+# Allow wildcard imports from modules that define __all__.
+allow-wildcard-with-all=no
+
+# Deprecated modules which should not be used, separated by a comma.
+deprecated-modules=
+
+# Output a graph (.gv or any supported image format) of external dependencies
+# to the given file (report RP0402 must not be disabled).
+ext-import-graph=
+
+# Output a graph (.gv or any supported image format) of all (i.e. internal and
+# external) dependencies to the given file (report RP0402 must not be
+# disabled).
+import-graph=
+
+# Output a graph (.gv or any supported image format) of internal dependencies
+# to the given file (report RP0402 must not be disabled).
+int-import-graph=
+
+# Force import order to recognize a module as part of the standard
+# compatibility libraries.
+known-standard-library=
+
+# Force import order to recognize a module as part of a third party library.
+known-third-party=enchant
+
+# Couples of modules and preferred modules, separated by a comma.
+preferred-modules=
+
+
+[LOGGING]
+
+# The type of string formatting that logging methods do. `old` means using %
+# formatting, `new` is for `{}` formatting.
+logging-format-style=old
+
+# Logging modules to check that the string format arguments are in logging
+# function parameter format.
+logging-modules=logging
+
+
+[MESSAGES CONTROL]
+
+# Only show warnings with the listed confidence levels. Leave empty to show
+# all. Valid levels: HIGH, CONTROL_FLOW, INFERENCE, INFERENCE_FAILURE,
+# UNDEFINED.
+confidence=HIGH,
+           CONTROL_FLOW,
+           INFERENCE,
+           INFERENCE_FAILURE,
+           UNDEFINED
+
+# Disable the message, report, category or checker with the given id(s). You
+# can either give multiple identifiers separated by comma (,) or put this
+# option multiple times (only on the command line, not in the configuration
+# file where it should appear only once). You can also use "--disable=all" to
+# disable everything first and then re-enable specific checks. For example, if
+# you want to run only the similarities checker, you can use "--disable=all
+# --enable=similarities". If you want to run only the classes checker, but have
+# no Warning level messages displayed, use "--disable=all --enable=classes
+# --disable=W".
+disable=raw-checker-failed,
+        bad-inline-option,
+        locally-disabled,
+        file-ignored,
+        suppressed-message,
+        useless-suppression,
+        deprecated-pragma,
+        use-symbolic-message-instead
+
+# Enable the message, report, category or checker with the given id(s). You can
+# either give multiple identifier separated by comma (,) or put this option
+# multiple time (only on the command line, not in the configuration file where
+# it should appear only once). See also the "--disable" option for examples.
+enable=c-extension-no-member
+
+
+[METHOD_ARGS]
+
+# List of qualified names (i.e., library.method) which require a timeout
+# parameter e.g. 'requests.api.get,requests.api.post'
+timeout-methods=requests.api.delete,requests.api.get,requests.api.head,requests.api.options,requests.api.patch,requests.api.post,requests.api.put,requests.api.request
+
+
+[MISCELLANEOUS]
+
+# List of note tags to take in consideration, separated by a comma.
+notes=FIXME,
+      XXX,
+      TODO
+
+# Regular expression of note tags to take in consideration.
+notes-rgx=
+
+
+[REFACTORING]
+
+# Maximum number of nested blocks for function / method body
+max-nested-blocks=5
+
+# Complete name of functions that never returns. When checking for
+# inconsistent-return-statements if a never returning function is called then
+# it will be considered as an explicit return statement and no message will be
+# printed.
+never-returning-functions=sys.exit,argparse.parse_error
+
+
+[REPORTS]
+
+# Python expression which should return a score less than or equal to 10. You
+# have access to the variables 'fatal', 'error', 'warning', 'refactor',
+# 'convention', and 'info' which contain the number of messages in each
+# category, as well as 'statement' which is the total number of statements
+# analyzed. This score is used by the global evaluation report (RP0004).
+evaluation=max(0, 0 if fatal else 10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10))
+
+# Template used to display messages. This is a python new-style format string
+# used to format the message information. See doc for all details.
+msg-template=
+
+# Set the output format. Available formats are text, parseable, colorized, json
+# and msvs (visual studio). You can also give a reporter class, e.g.
+# mypackage.mymodule.MyReporterClass.
+#output-format=
+
+# Tells whether to display a full report or only the messages.
+reports=no
+
+# Activate the evaluation score.
+score=yes
+
+
+[SIMILARITIES]
+
+# Comments are removed from the similarity computation
+ignore-comments=yes
+
+# Docstrings are removed from the similarity computation
+ignore-docstrings=yes
+
+# Imports are removed from the similarity computation
+ignore-imports=yes
+
+# Signatures are removed from the similarity computation
+ignore-signatures=yes
+
+# Minimum lines number of a similarity.
+min-similarity-lines=4
+
+
+[SPELLING]
+
+# Limits count of emitted suggestions for spelling mistakes.
+max-spelling-suggestions=4
+
+# Spelling dictionary name. No available dictionaries : You need to install
+# both the python package and the system dependency for enchant to work..
+spelling-dict=
+
+# List of comma separated words that should be considered directives if they
+# appear at the beginning of a comment and should not be checked.
+spelling-ignore-comment-directives=fmt: on,fmt: off,noqa:,noqa,nosec,isort:skip,mypy:
+
+# List of comma separated words that should not be checked.
+spelling-ignore-words=
+
+# A path to a file that contains the private dictionary; one word per line.
+spelling-private-dict-file=
+
+# Tells whether to store unknown words to the private dictionary (see the
+# --spelling-private-dict-file option) instead of raising a message.
+spelling-store-unknown-words=no
+
+
+[STRING]
+
+# This flag controls whether inconsistent-quotes generates a warning when the
+# character used as a quote delimiter is used inconsistently within a module.
+check-quote-consistency=no
+
+# This flag controls whether the implicit-str-concat should generate a warning
+# on implicit string concatenation in sequences defined over several lines.
+check-str-concat-over-line-jumps=no
+
+
+[TYPECHECK]
+
+# List of decorators that produce context managers, such as
+# contextlib.contextmanager. Add to this list to register other decorators that
+# produce valid context managers.
+contextmanager-decorators=contextlib.contextmanager
+
+# List of members which are set dynamically and missed by pylint inference
+# system, and so shouldn't trigger E1101 when accessed. Python regular
+# expressions are accepted.
+generated-members=
+
+# Tells whether to warn about missing members when the owner of the attribute
+# is inferred to be None.
+ignore-none=yes
+
+# This flag controls whether pylint should warn about no-member and similar
+# checks whenever an opaque object is returned when inferring. The inference
+# can return multiple potential results while evaluating a Python object, but
+# some branches might not be evaluated, which results in partial inference. In
+# that case, it might be useful to still emit no-member and other checks for
+# the rest of the inferred objects.
+ignore-on-opaque-inference=yes
+
+# List of symbolic message names to ignore for Mixin members.
+ignored-checks-for-mixins=no-member,
+                          not-async-context-manager,
+                          not-context-manager,
+                          attribute-defined-outside-init
+
+# List of class names for which member attributes should not be checked (useful
+# for classes with dynamically set attributes). This supports the use of
+# qualified names.
+ignored-classes=optparse.Values,thread._local,_thread._local,argparse.Namespace,nipype.interfaces.base.support.Bunch
+
+# Show a hint with possible names when a member name was not found. The aspect
+# of finding the hint is based on edit distance.
+missing-member-hint=yes
+
+# The minimum edit distance a name should have in order to be considered a
+# similar match for a missing member name.
+missing-member-hint-distance=1
+
+# The total number of similar names that should be taken in consideration when
+# showing a hint for a missing member.
+missing-member-max-choices=1
+
+# Regex pattern to define which classes are considered mixins.
+mixin-class-rgx=.*[Mm]ixin
+
+# List of decorators that change the signature of a decorated function.
+signature-mutators=
+
+
+[VARIABLES]
+
+# List of additional names supposed to be defined in builtins. Remember that
+# you should avoid defining new builtins when possible.
+additional-builtins=
+
+# Tells whether unused global variables should be treated as a violation.
+allow-global-unused-variables=yes
+
+# List of names allowed to shadow builtins
+allowed-redefined-builtins=
+
+# List of strings which can identify a callback function by name. A callback
+# name must start or end with one of those strings.
+callbacks=cb_,
+          _cb
+
+# A regular expression matching the name of dummy variables (i.e. expected to
+# not be used).
+dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
+
+# Argument names that match this expression will be ignored.
+ignored-argument-names=_.*|^ignored_|^unused_
+
+# Tells whether we should check for unused import in __init__ files.
+init-import=no
+
+# List of qualified module names which can have objects that can redefine
+# builtins.
+redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io
diff --git a/INSTALL.md b/INSTALL.md
index 18de2747..e9f124ba 100644
--- a/INSTALL.md
+++ b/INSTALL.md
@@ -63,7 +63,7 @@ Start a Docker container from the Docker image :
 
 ```bash
 # Replace PATH_TO_THE_REPOSITORY in the following command (e.g.: with /home/user/dev/narps_open_pipelines/)
-docker run -it -v PATH_TO_THE_REPOSITORY:/home/neuro/code/ nipype/nipype:py38
+docker run -it -v PATH_TO_THE_REPOSITORY:/work/ nipype/nipype:py38
 ```
 
 Optionally edit the configuration file `narps_open/utils/configuration/default_config.toml` so that the referred paths match the ones inside the container. E.g.: if using the previous command line, the `directories` part of the configuration file should be :
@@ -73,9 +73,9 @@ Optionally edit the configuration file `narps_open/utils/configuration/default_c
 # ...
 
 [directories]
-dataset = "/home/neuro/code/data/original/ds001734/"
-reproduced_results = "/home/neuro/code/data/reproduced/"
-narps_results = "/home/neuro/code/data/results/"
+dataset = "/work/data/original/ds001734/"
+reproduced_results = "/work/data/reproduced/"
+narps_results = "/work/data/results/"
 
 # ...
 ```
@@ -87,7 +87,7 @@ Install NARPS Open Pipelines inside the container :
 
 ```bash
 source activate neuro
-cd /home/neuro/code/
+cd /work/
 pip install .
 ```
 
diff --git a/docs/environment.md b/docs/environment.md
index a345e94f..31c029b4 100644
--- a/docs/environment.md
+++ b/docs/environment.md
@@ -15,7 +15,7 @@ From this command line, you need to add volumes to be able to link with your loc
 ```bash
 # Replace PATH_TO_THE_REPOSITORY in the following command (e.g.: with /home/user/dev/narps_open_pipelines/)
 docker run -it \
-           -v PATH_TO_THE_REPOSITORY:/home/neuro/code/ \
+           -v PATH_TO_THE_REPOSITORY:/work/ \
            nipype/nipype:py38
 ``` 
 
@@ -25,7 +25,7 @@ If you wish to use [Jupyter](https://jupyter.org/) to run the code, a port forwa
 
 ```bash
 docker run -it \
-           -v PATH_TO_THE_REPOSITORY:/home/neuro/code/ \
+           -v PATH_TO_THE_REPOSITORY:/work/ \
            -p 8888:8888 \
            nipype/nipype:py38
 ``` 
diff --git a/narps_open/utils/configuration/default_config.toml b/narps_open/utils/configuration/default_config.toml
index 81f312a9..119e743f 100644
--- a/narps_open/utils/configuration/default_config.toml
+++ b/narps_open/utils/configuration/default_config.toml
@@ -3,9 +3,9 @@ title = "Default configuration for the NARPS open pipelines project"
 config_type = "default"
 
 [directories]
-dataset = "data/original/ds001734/"
-reproduced_results = "data/reproduced/"
-narps_results = "data/results/"
+dataset = "/work/data/original/ds001734/"
+reproduced_results = "/work/run/reproduced/"
+narps_results = "/work/data/results/"
 
 [runner]
 nb_procs = 8 # Maximum number of threads executed by the runner
diff --git a/narps_open/utils/configuration/testing_config.toml b/narps_open/utils/configuration/testing_config.toml
index 86ba77b8..943ae1aa 100644
--- a/narps_open/utils/configuration/testing_config.toml
+++ b/narps_open/utils/configuration/testing_config.toml
@@ -3,11 +3,11 @@ title = "Testing configuration for the NARPS open pipelines project"
 config_type = "testing"
 
 [directories]
-dataset = "data/original/ds001734/"
-reproduced_results = "run/data/reproduced/"
-narps_results = "data/results/"
-test_data = "tests/test_data/"
-test_runs = "run/"
+dataset = "/work/data/original/ds001734/"
+reproduced_results = "/work/run/reproduced/"
+narps_results = "/work/data/results/"
+test_data = "/work/tests/test_data/"
+test_runs = "/work/run/"
 
 [runner]
 nb_procs = 8 # Maximum number of threads executed by the runner
diff --git a/tests/conftest.py b/tests/conftest.py
index 73dd095e..2223518e 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -6,12 +6,13 @@
 pytest on (a) test file(s) in the same directory.
 """
 
-from os import remove
+from os import remove, mkdir
 from os.path import join, isfile
+from tempfile import mkdtemp
 from shutil import rmtree
 
 from numpy import isclose
-from pytest import helpers
+from pytest import helpers, fixture
 from pathvalidate import is_valid_filepath
 
 from narps_open.pipelines import Pipeline
@@ -24,6 +25,13 @@
 # Init configuration, to ensure it is in testing mode
 Configuration(config_type='testing')
 
+@fixture
+def temporary_data_dir():
+    """ A fixture to create and remove a temporary directory for the tests """
+    data_dir = mkdtemp()
+    yield data_dir
+    rmtree(data_dir, ignore_errors = True)
+
 @helpers.register
 def compare_float_2d_arrays(array_1, array_2):
     """ Assert array_1 and array_2 are close enough """
diff --git a/tests/core/test_common.py b/tests/core/test_common.py
index 1c362023..e430b795 100644
--- a/tests/core/test_common.py
+++ b/tests/core/test_common.py
@@ -10,38 +10,25 @@
     pytest -q test_common.py
     pytest -q test_common.py -k <selected_test>
 """
-from os import mkdir, makedirs
+from os import makedirs
 from os.path import join, exists, abspath
-from shutil import rmtree
 from pathlib import Path
 
-from pytest import mark, fixture
+from pytest import mark
 from nipype import Node, Function, Workflow
 
-from narps_open.utils.configuration import Configuration
 import narps_open.core.common as co
 
-TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_common')
-
-@fixture
-def remove_test_dir():
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-    mkdir(TEMPORARY_DIR)
-    yield # test runs here
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-
 class TestCoreCommon:
     """ A class that contains all the unit tests for the common module."""
 
     @staticmethod
     @mark.unit_test
-    def test_remove_file(remove_test_dir):
+    def test_remove_file(temporary_data_dir):
         """ Test the remove_file function """
 
         # Create a single file
-        test_file_path = abspath(join(TEMPORARY_DIR, 'file1.txt'))
+        test_file_path = abspath(join(temporary_data_dir, 'file1.txt'))
         Path(test_file_path).touch()
 
         # Check file exist
@@ -62,15 +49,15 @@ def test_remove_file(remove_test_dir):
 
     @staticmethod
     @mark.unit_test
-    def test_remove_directory(remove_test_dir):
+    def test_remove_directory(temporary_data_dir):
         """ Test the remove_directory function """
 
         # Create a single inside dir tree
-        dir_path = abspath(join(TEMPORARY_DIR, 'dir_1', 'dir_2'))
+        dir_path = abspath(join(temporary_data_dir, 'dir_1', 'dir_2'))
         makedirs(dir_path)
-        file_path = abspath(join(TEMPORARY_DIR, 'dir_1', 'dir_2', 'file1.txt'))
+        file_path = abspath(join(temporary_data_dir, 'dir_1', 'dir_2', 'file1.txt'))
         Path(file_path).touch()
-        test_dir_path = abspath(join(TEMPORARY_DIR, 'dir_1'))
+        test_dir_path = abspath(join(temporary_data_dir, 'dir_1'))
 
         # Check file exist
         assert exists(file_path)
@@ -90,13 +77,13 @@ def test_remove_directory(remove_test_dir):
 
     @staticmethod
     @mark.unit_test
-    def test_remove_parent_directory(remove_test_dir):
+    def test_remove_parent_directory(temporary_data_dir):
         """ Test the remove_parent_directory function """
 
         # Create a single inside dir tree
-        dir_path = abspath(join(TEMPORARY_DIR, 'dir_1', 'dir_2'))
+        dir_path = abspath(join(temporary_data_dir, 'dir_1', 'dir_2'))
         makedirs(dir_path)
-        file_path = abspath(join(TEMPORARY_DIR, 'dir_1', 'dir_2', 'file1.txt'))
+        file_path = abspath(join(temporary_data_dir, 'dir_1', 'dir_2', 'file1.txt'))
         Path(file_path).touch()
 
         # Check file exist
@@ -151,7 +138,7 @@ def test_node_elements_in_string():
 
     @staticmethod
     @mark.unit_test
-    def test_connect_elements_in_string(remove_test_dir):
+    def test_connect_elements_in_string(temporary_data_dir):
         """ Test the elements_in_string function as evaluated in a connect """
 
         # Inputs
@@ -180,7 +167,7 @@ def test_connect_elements_in_string(remove_test_dir):
 
         # Create Workflow
         test_workflow = Workflow(
-            base_dir = TEMPORARY_DIR,
+            base_dir = temporary_data_dir,
             name = 'test_workflow'
             )
         test_workflow.connect([
@@ -193,11 +180,13 @@ def test_connect_elements_in_string(remove_test_dir):
 
         test_workflow.run()
 
-        test_file_t = join(TEMPORARY_DIR, 'test_workflow', 'node_true', '_report', 'report.rst')
+        test_file_t = join(temporary_data_dir,
+            'test_workflow', 'node_true', '_report', 'report.rst')
         with open(test_file_t, 'r', encoding = 'utf-8') as file:
             assert '* out_value : test_string' in file.read()
 
-        test_file_f = join(TEMPORARY_DIR, 'test_workflow', 'node_false', '_report', 'report.rst')
+        test_file_f = join(temporary_data_dir,
+            'test_workflow', 'node_false', '_report', 'report.rst')
         with open(test_file_f, 'r', encoding = 'utf-8') as file:
             assert '* out_value : None' in file.read()
 
@@ -238,7 +227,7 @@ def test_node_clean_list():
 
     @staticmethod
     @mark.unit_test
-    def test_connect_clean_list(remove_test_dir):
+    def test_connect_clean_list(temporary_data_dir):
         """ Test the clean_list function as evaluated in a connect """
 
         # Inputs
@@ -269,7 +258,7 @@ def test_connect_clean_list(remove_test_dir):
 
         # Create Workflow
         test_workflow = Workflow(
-            base_dir = TEMPORARY_DIR,
+            base_dir = temporary_data_dir,
             name = 'test_workflow'
             )
         test_workflow.connect([
@@ -279,11 +268,13 @@ def test_connect_clean_list(remove_test_dir):
             ])
         test_workflow.run()
 
-        test_file_1 = join(TEMPORARY_DIR, 'test_workflow', 'node_1', '_report', 'report.rst')
+        test_file_1 = join(temporary_data_dir,
+            'test_workflow', 'node_1', '_report', 'report.rst')
         with open(test_file_1, 'r', encoding = 'utf-8') as file:
             assert f'* out_value : {output_list_1}' in file.read()
 
-        test_file_2 = join(TEMPORARY_DIR, 'test_workflow', 'node_2', '_report', 'report.rst')
+        test_file_2 = join(temporary_data_dir,
+            'test_workflow', 'node_2', '_report', 'report.rst')
         with open(test_file_2, 'r', encoding = 'utf-8') as file:
             assert f'* out_value : {output_list_2}' in file.read()
 
@@ -324,7 +315,7 @@ def test_node_list_intersection():
 
     @staticmethod
     @mark.unit_test
-    def test_connect_list_intersection(remove_test_dir):
+    def test_connect_list_intersection(temporary_data_dir):
         """ Test the list_intersection function as evaluated in a connect """
 
         # Inputs / outputs
@@ -355,7 +346,7 @@ def test_connect_list_intersection(remove_test_dir):
 
         # Create Workflow
         test_workflow = Workflow(
-            base_dir = TEMPORARY_DIR,
+            base_dir = temporary_data_dir,
             name = 'test_workflow'
             )
         test_workflow.connect([
@@ -365,11 +356,13 @@ def test_connect_list_intersection(remove_test_dir):
             ])
         test_workflow.run()
 
-        test_file_1 = join(TEMPORARY_DIR, 'test_workflow', 'node_1', '_report', 'report.rst')
+        test_file_1 = join(temporary_data_dir,
+            'test_workflow', 'node_1', '_report', 'report.rst')
         with open(test_file_1, 'r', encoding = 'utf-8') as file:
             assert f'* out_value : {output_list_1}' in file.read()
 
-        test_file_2 = join(TEMPORARY_DIR, 'test_workflow', 'node_2', '_report', 'report.rst')
+        test_file_2 = join(temporary_data_dir,
+            'test_workflow', 'node_2', '_report', 'report.rst')
         with open(test_file_2, 'r', encoding = 'utf-8') as file:
             assert f'* out_value : {output_list_2}' in file.read()
 
diff --git a/tests/pipelines/test_team_J7F9.py b/tests/pipelines/test_team_J7F9.py
index da37e990..bf3aeafc 100644
--- a/tests/pipelines/test_team_J7F9.py
+++ b/tests/pipelines/test_team_J7F9.py
@@ -10,29 +10,16 @@
     pytest -q test_team_J7F9.py
     pytest -q test_team_J7F9.py -k <selected_test>
 """
-from os import mkdir
 from os.path import join, exists
-from shutil import rmtree
 from filecmp import cmp
 
-from pytest import helpers, mark, fixture
+from pytest import helpers, mark
 from nipype import Workflow
 from nipype.interfaces.base import Bunch
 
 from narps_open.utils.configuration import Configuration
 from narps_open.pipelines.team_J7F9 import PipelineTeamJ7F9
 
-TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_J7F9')
-
-@fixture
-def remove_test_dir():
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-    mkdir(TEMPORARY_DIR)
-    yield # test runs here
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-
 class TestPipelinesTeamJ7F9:
     """ A class that contains all the unit tests for the PipelineTeamJ7F9 class."""
 
@@ -188,7 +175,7 @@ def test_subject_information():
 
     @staticmethod
     @mark.unit_test
-    def test_confounds_file(remove_test_dir):
+    def test_confounds_file(temporary_data_dir):
         """ Test the get_confounds_file method """
 
         confounds_file = join(
@@ -197,11 +184,11 @@ def test_confounds_file(remove_test_dir):
             Configuration()['directories']['test_data'], 'pipelines', 'team_J7F9', 'confounds.tsv')
 
         # Get new confounds file
-        PipelineTeamJ7F9.get_confounds_file(confounds_file, 'sid', 'rid', TEMPORARY_DIR)
+        PipelineTeamJ7F9.get_confounds_file(confounds_file, 'sid', 'rid', temporary_data_dir)
 
         # Check confounds file was created
         created_confounds_file = join(
-            TEMPORARY_DIR, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
+            temporary_data_dir, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
         assert exists(created_confounds_file)
 
         # Check contents
diff --git a/tests/pipelines/test_team_T54A.py b/tests/pipelines/test_team_T54A.py
index 2199cf40..954ca1bb 100644
--- a/tests/pipelines/test_team_T54A.py
+++ b/tests/pipelines/test_team_T54A.py
@@ -10,28 +10,15 @@
     pytest -q test_team_T54A.py
     pytest -q test_team_T54A.py -k <selected_test>
 """
-from os import mkdir
 from os.path import exists, join
-from shutil import rmtree
 
-from pytest import helpers, mark, fixture
+from pytest import helpers, mark
 from nipype import Workflow
 from nipype.interfaces.base import Bunch
 
 from narps_open.pipelines.team_T54A import PipelineTeamT54A
 from narps_open.utils.configuration import Configuration
 
-TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_T54A')
-
-@fixture
-def remove_test_dir():
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-    mkdir(TEMPORARY_DIR)
-    yield # test runs here
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-
 class TestPipelinesTeamT54A:
     """ A class that contains all the unit tests for the PipelineTeamT54A class."""
 
@@ -148,7 +135,7 @@ def test_subject_information():
 
     @staticmethod
     @mark.unit_test
-    def test_parameters_file(remove_test_dir):
+    def test_parameters_file(temporary_data_dir):
         """ Test the get_parameters_file method """
 
         confounds_file_path = join(
@@ -158,12 +145,12 @@ def test_parameters_file(remove_test_dir):
             confounds_file_path,
             'fake_subject_id',
             'fake_run_id',
-            TEMPORARY_DIR
+            temporary_data_dir
             )
 
         # Check parameter file was created
         assert exists(join(
-            TEMPORARY_DIR,
+            temporary_data_dir,
             'parameters_file',
             'parameters_file_sub-fake_subject_id_run-fake_run_id.tsv')
         )
diff --git a/tests/pipelines/test_team_U26C.py b/tests/pipelines/test_team_U26C.py
index c670b520..163d005e 100644
--- a/tests/pipelines/test_team_U26C.py
+++ b/tests/pipelines/test_team_U26C.py
@@ -10,38 +10,16 @@
     pytest -q test_team_U26C.py
     pytest -q test_team_U26C.py -k <selected_test>
 """
-from os import mkdir
 from os.path import join, exists
-from shutil import rmtree
 from filecmp import cmp
 
-from pytest import helpers, mark, fixture
-from numpy import isclose
+from pytest import helpers, mark
 from nipype import Workflow
 from nipype.interfaces.base import Bunch
 
 from narps_open.utils.configuration import Configuration
 from narps_open.pipelines.team_U26C import PipelineTeamU26C
 
-TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_U26C')
-
-@fixture
-def remove_test_dir():
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-    mkdir(TEMPORARY_DIR)
-    yield # test runs here
-    #rmtree(TEMPORARY_DIR, ignore_errors = True)
-
-def compare_float_2d_arrays(array_1, array_2):
-    """ Assert array_1 and array_2 are close enough """
-
-    assert len(array_1) == len(array_2)
-    for reference_array, test_array in zip(array_1, array_2):
-        assert len(reference_array) == len(test_array)
-        assert isclose(reference_array, test_array).all()
-
 class TestPipelinesTeamU26C:
     """ A class that contains all the unit tests for the PipelineTeamU26C class."""
 
@@ -91,32 +69,34 @@ def test_subject_information():
         bunch = info[0]
         assert isinstance(bunch, Bunch)
         assert bunch.conditions == ['gamble_run1']
-        compare_float_2d_arrays(bunch.onsets, [[4.071, 11.834, 19.535, 27.535, 36.435]])
-        compare_float_2d_arrays(bunch.durations, [[4.0, 4.0, 4.0, 4.0, 4.0]])
-        assert bunch.amplitudes == None
-        assert bunch.tmod == None
+        helpers.compare_float_2d_arrays(bunch.onsets, [[4.071, 11.834, 19.535, 27.535, 36.435]])
+        helpers.compare_float_2d_arrays(bunch.durations, [[4.0, 4.0, 4.0, 4.0, 4.0]])
+        assert bunch.amplitudes is None
+        assert bunch.tmod is None
         assert bunch.pmod[0].name == ['gain_run1', 'loss_run1']
         assert bunch.pmod[0].poly == [1, 1]
-        compare_float_2d_arrays(bunch.pmod[0].param, [[14.0, 34.0, 38.0, 10.0, 16.0], [6.0, 14.0, 19.0, 15.0, 17.0]])
-        assert bunch.regressor_names == None
-        assert bunch.regressors == None
+        helpers.compare_float_2d_arrays(bunch.pmod[0].param,
+            [[14.0, 34.0, 38.0, 10.0, 16.0], [6.0, 14.0, 19.0, 15.0, 17.0]])
+        assert bunch.regressor_names is None
+        assert bunch.regressors is None
 
         bunch = info[1]
         assert isinstance(bunch, Bunch)
         assert bunch.conditions == ['gamble_run2']
-        compare_float_2d_arrays(bunch.onsets, [[4.071, 11.834, 19.535, 27.535, 36.435]])
-        compare_float_2d_arrays(bunch.durations, [[4.0, 4.0, 4.0, 4.0, 4.0]])
-        assert bunch.amplitudes == None
-        assert bunch.tmod == None
+        helpers.compare_float_2d_arrays(bunch.onsets, [[4.071, 11.834, 19.535, 27.535, 36.435]])
+        helpers.compare_float_2d_arrays(bunch.durations, [[4.0, 4.0, 4.0, 4.0, 4.0]])
+        assert bunch.amplitudes is None
+        assert bunch.tmod is None
         assert bunch.pmod[0].name == ['gain_run2', 'loss_run2']
         assert bunch.pmod[0].poly == [1, 1]
-        compare_float_2d_arrays(bunch.pmod[0].param, [[14.0, 34.0, 38.0, 10.0, 16.0], [6.0, 14.0, 19.0, 15.0, 17.0]])
-        assert bunch.regressor_names == None
-        assert bunch.regressors == None
+        helpers.compare_float_2d_arrays(bunch.pmod[0].param,
+            [[14.0, 34.0, 38.0, 10.0, 16.0], [6.0, 14.0, 19.0, 15.0, 17.0]])
+        assert bunch.regressor_names is None
+        assert bunch.regressors is None
 
     @staticmethod
     @mark.unit_test
-    def test_confounds_file(remove_test_dir):
+    def test_confounds_file(temporary_data_dir):
         """ Test the get_confounds_file method """
 
         confounds_file = join(
@@ -125,11 +105,11 @@ def test_confounds_file(remove_test_dir):
             Configuration()['directories']['test_data'], 'pipelines', 'team_U26C', 'confounds.tsv')
 
         # Get new confounds file
-        PipelineTeamU26C.get_confounds_file(confounds_file, 'sid', 'rid', TEMPORARY_DIR)
+        PipelineTeamU26C.get_confounds_file(confounds_file, 'sid', 'rid', temporary_data_dir)
 
         # Check confounds file was created
         created_confounds_file = join(
-            TEMPORARY_DIR, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
+            temporary_data_dir, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
         assert exists(created_confounds_file)
 
         # Check contents
diff --git a/tests/pipelines/test_team_X19V.py b/tests/pipelines/test_team_X19V.py
index e0a1a7f3..c83595f3 100644
--- a/tests/pipelines/test_team_X19V.py
+++ b/tests/pipelines/test_team_X19V.py
@@ -10,38 +10,16 @@
     pytest -q test_team_X19V.py
     pytest -q test_team_X19V.py -k <selected_test>
 """
-from os import mkdir
 from os.path import join, exists
-from shutil import rmtree
 from filecmp import cmp
 
-from pytest import helpers, mark, fixture
-from numpy import isclose
+from pytest import helpers, mark
 from nipype import Workflow
 from nipype.interfaces.base import Bunch
 
 from narps_open.utils.configuration import Configuration
 from narps_open.pipelines.team_X19V import PipelineTeamX19V
 
-TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_X19V')
-
-@fixture
-def remove_test_dir():
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEMPORARY_DIR, ignore_errors = True)
-    mkdir(TEMPORARY_DIR)
-    yield # test runs here
-    #rmtree(TEMPORARY_DIR, ignore_errors = True)
-
-def compare_float_2d_arrays(array_1, array_2):
-    """ Assert array_1 and array_2 are close enough """
-
-    assert len(array_1) == len(array_2)
-    for reference_array, test_array in zip(array_1, array_2):
-        assert len(reference_array) == len(test_array)
-        assert isclose(reference_array, test_array).all()
-
 class TestPipelinesTeamX19V:
     """ A class that contains all the unit tests for the PipelineTeamX19V class."""
 
@@ -95,24 +73,24 @@ def test_subject_information():
         bunch = info_ok[0]
         assert isinstance(bunch, Bunch)
         assert bunch.conditions == ['trial', 'gain', 'loss']
-        compare_float_2d_arrays(bunch.onsets, [
+        helpers.compare_float_2d_arrays(bunch.onsets, [
             [4.071, 11.834, 19.535, 27.535, 36.435],
             [4.071, 11.834, 19.535, 27.535, 36.435],
             [4.071, 11.834, 19.535, 27.535, 36.435]])
-        compare_float_2d_arrays(bunch.durations, [
+        helpers.compare_float_2d_arrays(bunch.durations, [
             [4.0, 4.0, 4.0, 4.0, 4.0],
             [4.0, 4.0, 4.0, 4.0, 4.0],
             [4.0, 4.0, 4.0, 4.0, 4.0]])
-        compare_float_2d_arrays(bunch.amplitudes, [
+        helpers.compare_float_2d_arrays(bunch.amplitudes, [
             [1.0, 1.0, 1.0, 1.0, 1.0],
             [-8.4, 11.6, 15.6, -12.4, -6.4],
             [-8.2, -0.2, 4.8, 0.8, 2.8]])
-        assert bunch.regressor_names == None
-        assert bunch.regressors == None
+        assert bunch.regressor_names is None
+        assert bunch.regressors is None
 
     @staticmethod
     @mark.unit_test
-    def test_confounds_file(remove_test_dir):
+    def test_confounds_file(temporary_data_dir):
         """ Test the get_confounds_file method """
 
         confounds_file = join(
@@ -121,11 +99,11 @@ def test_confounds_file(remove_test_dir):
             Configuration()['directories']['test_data'], 'pipelines', 'team_X19V', 'confounds.tsv')
 
         # Get new confounds file
-        PipelineTeamX19V.get_confounds_file(confounds_file, 'sid', 'rid', TEMPORARY_DIR)
+        PipelineTeamX19V.get_confounds_file(confounds_file, 'sid', 'rid', temporary_data_dir)
 
         # Check confounds file was created
         created_confounds_file = join(
-            TEMPORARY_DIR, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
+            temporary_data_dir, 'confounds_files', 'confounds_file_sub-sid_run-rid.tsv')
         assert exists(created_confounds_file)
 
         # Check contents
diff --git a/tests/test_conftest.py b/tests/test_conftest.py
index 4ea92fb5..398a9a70 100644
--- a/tests/test_conftest.py
+++ b/tests/test_conftest.py
@@ -11,13 +11,12 @@
     pytest -q test_conftest.py -k <selected_test>
 """
 
-from os import makedirs, remove
-from os.path import join, abspath, isdir, isfile
-from shutil import rmtree
+from os import remove
+from os.path import join, isdir, isfile
 
 from datetime import datetime
 
-from pytest import mark, helpers, fixture, raises
+from pytest import mark, helpers, raises
 
 from nipype import Node, Workflow
 from nipype.interfaces.utility import Function
@@ -26,24 +25,13 @@
 from narps_open.runner import PipelineRunner
 from narps_open.pipelines import Pipeline
 
-TEST_DIR = abspath(join(Configuration()['directories']['test_runs'], 'test_conftest'))
-
-@fixture
-def set_test_directory(scope = 'function'):
-    """ A fixture to remove temporary directory created by tests """
-
-    rmtree(TEST_DIR, ignore_errors = True)
-    makedirs(TEST_DIR, exist_ok = True)
-    yield
-    # Comment this line for debugging
-    rmtree(TEST_DIR, ignore_errors = True)
-
 class MockupPipeline(Pipeline):
     """ A simple Pipeline class for test purposes """
 
-    def __init__(self):
+    def __init__(self, base_dir: str):
         super().__init__()
-        self.test_file = join(TEST_DIR, 'test_conftest.txt')
+        self.base_dir = base_dir
+        self.test_file = join(base_dir, 'test_conftest.txt')
 
         # Init the test_file : write a number of execution set to zero
         with open(self.test_file, 'w', encoding = 'utf-8') as file:
@@ -126,7 +114,7 @@ def create_workflow(self, workflow_name: str, file_list: list):
         node_files.inputs.file_list = file_list
 
         workflow = Workflow(
-            base_dir = TEST_DIR,
+            base_dir = self.base_dir,
             name = workflow_name
             )
         workflow.add_nodes([node_count, node_decide, node_files])
@@ -166,21 +154,21 @@ def get_group_level_analysis(self):
 
     def get_preprocessing_outputs(self):
         """ Return a list of templates of the output files generated by the preprocessing """
-        template = join(TEST_DIR, 'subject_id_{subject_id}_output_preprocessing_1.md')
+        template = join(self.base_dir, 'subject_id_{subject_id}_output_preprocessing_1.md')
         return [template.format(subject_id = s) for s in self.subject_list]
 
     def get_run_level_outputs(self):
         """ Return a list of templates of the output files generated by the run level analysis.
             Templates are expressed relatively to the self.directories.output_dir.
         """
-        template = join(TEST_DIR, 'subject_id_{subject_id}_output_run_1.md')
+        template = join(self.base_dir, 'subject_id_{subject_id}_output_run_1.md')
         return [template.format(subject_id = s) for s in self.subject_list]
 
     def get_subject_level_outputs(self):
         """ Return a list of templates of the output files generated by the subject level analysis.
             Templates are expressed relatively to the self.directories.output_dir.
         """
-        template = join(TEST_DIR, 'subject_id_{subject_id}_output_analysis_1.md')
+        template = join(self.base_dir, 'subject_id_{subject_id}_output_analysis_1.md')
         return [template.format(subject_id = s) for s in self.subject_list]
 
     def get_group_level_outputs(self):
@@ -188,19 +176,19 @@ def get_group_level_outputs(self):
             Templates are expressed relatively to the self.directories.output_dir.
         """
         templates = [
-            join(TEST_DIR, 'group_{nb_subjects}_output_a.md'),
-            join(TEST_DIR, 'group_{nb_subjects}_output_b.md')
+            join(self.base_dir, 'group_{nb_subjects}_output_a.md'),
+            join(self.base_dir, 'group_{nb_subjects}_output_b.md')
             ]
         return_list = [t.format(nb_subjects = len(self.subject_list)) for t in  templates]
 
-        template = join(TEST_DIR, 'hypothesis_{id}.md')
+        template = join(self.base_dir, 'hypothesis_{id}.md')
         return_list += [template.format(id = i) for i in range(1,19)]
 
         return return_list
 
     def get_hypotheses_outputs(self):
         """ Return the names of the files used by the team to answer the hypotheses of NARPS. """
-        template = join(TEST_DIR, 'hypothesis_{id}.md')
+        template = join(self.base_dir, 'hypothesis_{id}.md')
         return [template.format(id = i) for i in range(1,19)]
 
 class MockupResultsCollection():
@@ -263,11 +251,11 @@ def test_compare_float_2d_arrays():
 
     @staticmethod
     @mark.unit_test
-    def test_test_outputs(set_test_directory):
+    def test_test_outputs(temporary_data_dir):
         """ Test the test_pipeline_outputs helper """
 
         # Test pipeline
-        pipeline = MockupPipeline()
+        pipeline = MockupPipeline(temporary_data_dir)
         pipeline.subject_list = ['001', '002']
 
         # Wrong length for nb_of_outputs
@@ -343,7 +331,7 @@ def test_test_correlation_results(mocker):
 
     @staticmethod
     @mark.unit_test
-    def test_test_pipeline_execution(mocker, set_test_directory):
+    def test_test_pipeline_execution(mocker, temporary_data_dir):
         """ Test the test_pipeline_execution helper """
 
         # Set subgroups of subjects
@@ -352,7 +340,7 @@ def test_test_pipeline_execution(mocker, set_test_directory):
         # Create mocks
         mocker.patch('conftest.get_correlation_coefficient', return_value = 1.0)
         fake_runner = PipelineRunner('2T6S')
-        fake_runner._pipeline = MockupPipeline()
+        fake_runner._pipeline = MockupPipeline(temporary_data_dir)
         mocker.patch('conftest.PipelineRunner', return_value = fake_runner)
         mocker.patch('conftest.ResultsCollection', return_value = MockupResultsCollection('2T6S'))
 
@@ -360,13 +348,13 @@ def test_test_pipeline_execution(mocker, set_test_directory):
         helpers.test_pipeline_execution('test_conftest', 7)
 
         # Check outputs
-        assert isdir(join(TEST_DIR, 'TestConftest_preprocessing_workflow'))
-        assert isdir(join(TEST_DIR, 'TestConftest_run_level_workflow'))
-        assert isdir(join(TEST_DIR, 'TestConftest_subject_level_workflow'))
-        assert isdir(join(TEST_DIR, 'TestConftest_group_level_workflow'))
+        assert isdir(join(temporary_data_dir, 'TestConftest_preprocessing_workflow'))
+        assert isdir(join(temporary_data_dir, 'TestConftest_run_level_workflow'))
+        assert isdir(join(temporary_data_dir, 'TestConftest_subject_level_workflow'))
+        assert isdir(join(temporary_data_dir, 'TestConftest_group_level_workflow'))
 
         # Check executions
-        with open(join(TEST_DIR, 'test_conftest.txt'), 'r', encoding = 'utf-8') as file:
+        with open(join(temporary_data_dir, 'test_conftest.txt'), 'r', encoding = 'utf-8') as file:
             assert file.readline() == '0\n'
             # First exec of preprocessing creates an exception (execution counter == 1)
             assert file.readline() == 'TestConftest_preprocessing_workflow 4 1\n'

From 931f76cba6eb7eede837352b188151a5cfdfe773 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Boris=20Cl=C3=A9net?=
 <117362283+bclenet@users.noreply.github.com>
Date: Wed, 6 Mar 2024 10:19:23 +0100
Subject: [PATCH 2/3] 98BT refactoring (#119)

* [BUG] inside unit_tests workflow

* Refactoring pipeline 98BT

* [TEST] update tests [REFAC] pep8 and bug correction

* Using narps_open.data.task module inside 98BT

* [TEST] update + dependancy to niflow

* [REFAC][skip ci]

* [BUG] input of get_contrats [skip ci]

* Light bugs + remove large files [skip ci]

* [TEST] adding tests for 98BT

* [TEST] adding tests for 98BT

* [TEST] adding tests for 98BT

* Output names for 98BT

* Preprocessing output names

* Subject info issue + output names

* 98BT - Refac get_parameters_files

* [TEST] 98BT get_parameters_file

* Using fixture for temporary test dir creation / removal

* Linting pipelines test files

* Bug with regressors naming

* pylintrc for pylint config
---
 narps_open/pipelines/__init__.py              |    2 +-
 narps_open/pipelines/team_98BT.py             | 1702 +++++++++--------
 setup.py                                      |    3 +-
 tests/conftest.py                             |    1 +
 tests/pipelines/templates/template_test.py    |   46 +-
 tests/pipelines/test_team_98BT.py             |  153 ++
 tests/test_data/pipelines/phasediff_1.json    |    1 +
 tests/test_data/pipelines/phasediff_2.json    |    1 +
 .../pipelines/team_98BT/parameters_file.tsv   |    4 +
 ...-001_task-MGT_run-01_bold_resampled-32.nii |  Bin 0 -> 2752 bytes
 .../pipelines/team_98BT/wc2sub-001_T1w-32.nii |  Bin 0 -> 1552 bytes
 11 files changed, 1102 insertions(+), 811 deletions(-)
 create mode 100644 tests/pipelines/test_team_98BT.py
 create mode 100644 tests/test_data/pipelines/phasediff_1.json
 create mode 100644 tests/test_data/pipelines/phasediff_2.json
 create mode 100644 tests/test_data/pipelines/team_98BT/parameters_file.tsv
 create mode 100644 tests/test_data/pipelines/team_98BT/uasub-001_task-MGT_run-01_bold_resampled-32.nii
 create mode 100644 tests/test_data/pipelines/team_98BT/wc2sub-001_T1w-32.nii

diff --git a/narps_open/pipelines/__init__.py b/narps_open/pipelines/__init__.py
index e9bf1f0b..2d67eeee 100644
--- a/narps_open/pipelines/__init__.py
+++ b/narps_open/pipelines/__init__.py
@@ -35,7 +35,7 @@
     '6VV2': None,
     '80GC': None,
     '94GU': None,
-    '98BT': None,
+    '98BT': 'PipelineTeam98BT',
     '9Q6R': None,
     '9T8E': None,
     '9U7M': None,
diff --git a/narps_open/pipelines/team_98BT.py b/narps_open/pipelines/team_98BT.py
index 653593fc..3cc0675f 100755
--- a/narps_open/pipelines/team_98BT.py
+++ b/narps_open/pipelines/team_98BT.py
@@ -1,788 +1,926 @@
-# pylint: skip-file
-from nipype.interfaces.spm import (Coregister, Smooth, OneSampleTTestDesign, EstimateModel, EstimateContrast, 
-                                   Level1Design, TwoSampleTTestDesign, RealignUnwarp, NewSegment, SliceTiming,
-                                  DARTEL, DARTELNorm2MNI, FieldMap)
-from nipype.interfaces.spm import Threshold
-from nipype.interfaces.fsl import ApplyMask, ExtractROI
-
-import niflow.nipype1.workflows.fmri.spm as spm_wf  # spm
-from nipype.algorithms.modelgen import SpecifySPMModel
-from nipype.interfaces.utility import IdentityInterface, Function, Rename
+#!/usr/bin/python
+# coding: utf-8
+
+""" Write the work of NARPS team 98BT using Nipype """
+from os.path import join
+from itertools import product
+
+from nipype import Workflow, Node, MapNode, JoinNode
+from nipype.interfaces.utility import IdentityInterface, Function, Rename, Merge
 from nipype.interfaces.io import SelectFiles, DataSink
 from nipype.algorithms.misc import Gunzip
-from nipype import Workflow, Node, MapNode, JoinNode
-from nipype.interfaces.base import Bunch
-
-from os.path import join as opj
-import os
-import json
-
-def get_dartel_template_wf(exp_dir, result_dir, working_dir, output_dir, subject_list):
-    
-
-    infosource_dartel = Node(IdentityInterface(fields=['subject_id']), name="infosource_dartel")
-    infosource_dartel.iterables = ('subject_id', subject_list)
-    
-    # Templates to select files node
-    anat_file = opj('sub-{subject_id}', 'anat', 
-                    'sub-{subject_id}_T1w.nii.gz')
-
-    template = {'anat' : anat_file}
-
-    # SelectFiles node - to select necessary files
-    selectfiles_dartel = Node(SelectFiles(template, base_directory=exp_dir), name = 'selectfiles_dartel')
-    
-    # GUNZIP NODE : SPM do not use .nii.gz files
-    gunzip_anat = Node(Gunzip(), name = 'gunzip_anat')
-    
-    def get_dartel_input(structural_files):
-        print(structural_files)
-        return structural_files
-
-    dartel_input = JoinNode(Function(input_names = ['structural_files'],
-                                output_names = ['structural_files'],
-                                function = get_dartel_input), name = 'dartel_input', 
-                            joinsource="infosource_dartel", joinfield="structural_files")
-    
-    rename_dartel = MapNode(Rename(format_string="subject_id_%(subject_id)s_struct"),
-                            iterfield=['in_file', 'subject_id'],
-                            name='rename_dartel')
-    
-    rename_dartel.inputs.subject_id = subject_list
-    rename_dartel.inputs.keep_ext = True
-
-    dartel_workflow = spm_wf.create_DARTEL_template(name='dartel_workflow')
-    dartel_workflow.inputs.inputspec.template_prefix = "template"
-    
-    # DataSink Node - store the wanted results in the wanted repository
-    datasink_dartel = Node(DataSink(base_directory=result_dir, container=output_dir), 
-                            name='datasink_dartel')
-    
-    dartel =  Workflow(base_dir = opj(result_dir, working_dir), name = "dartel")
-
-    dartel.connect([(infosource_dartel, selectfiles_dartel, [('subject_id', 'subject_id')]),
-                    (selectfiles_dartel, gunzip_anat, [('anat', 'in_file')]),
-                    (gunzip_anat, dartel_input, [('out_file', 'structural_files')]),
-                    (dartel_input, rename_dartel, [('structural_files', 'in_file')]),
-                    (rename_dartel, dartel_workflow, [('out_file', 'inputspec.structural_files')]),
-                    (dartel_workflow, datasink_dartel, 
-                     [('outputspec.template_file', 'dartel_template.@template_file'),
-                     ('outputspec.flow_fields', 'dartel_template.@flow_fields')])])
-    
-    return dartel
-
-
-def get_fieldmap_infos(info_fmap, magnitude):
-    """
-    Function to get information necessary to compute the fieldmap. 
-
-    Parameters: 
-        - info_fmap: str, file with fieldmap information
-        - magnitude: list of str, list of magnitude files
-
-    Returns: 
-        - TE: float, echo time obtained from fieldmap information file
-        - magnitude_file: str, necessary file to compute fieldmap
-    """
-    import json 
-    
-    with open(info_fmap, 'rt') as fp:
-        fmap_info = json.load(fp)
-        
-    short_TE = min(float(fmap_info['EchoTime1']), float(fmap_info['EchoTime2']))
-    long_TE = max(float(fmap_info['EchoTime1']), float(fmap_info['EchoTime2']))
-    if short_TE == float(fmap_info['EchoTime1']):
-        magnitude_file = magnitude[0]
-    elif short_TE == float(fmap_info['EchoTime2']):
-        magnitude_file = magnitude[1]
-        
-    TE = (short_TE, long_TE)
-        
-    return TE, magnitude_file
-
-def rm_field_files(files, subject_id, run_id, result_dir, working_dir):
-    import shutil
-    from os.path import join as opj
-
-    preproc_dir = opj(result_dir, working_dir, 'preprocessing', f"run_id_{run_id}_subject_id_{subject_id}")
-    
-    dir_to_rm = ['gunzip_func', 'gunzip_phasediff', 'fieldmap_infos', 'gunzip_magnitude', 'fieldmap', 
-                'slice_timing']
-    for dirs in dir_to_rm:
-        try:
-            shutil.rmtree(opj(preproc_dir, dirs))
-        except OSError as e:
-            print(e)
-        else:
-            print(f"The directory {dirs} is deleted successfully")
-    
-    return files
-
-def get_preprocessing(exp_dir, result_dir, working_dir, output_dir, subject_list, run_list, fwhm, N, ST, TA, TR, total_readout_time): 
-    
-    infosource = Node(IdentityInterface(fields=['subject_id', 'run_id']), name="infosource")
-
-    infosource.iterables = [('subject_id', subject_list), ('run_id', run_list)]
-
-    # Templates to select files node
-    anat_file = opj('sub-{subject_id}', 'anat', 
-                    'sub-{subject_id}_T1w.nii.gz')
-
-    func_file = opj('sub-{subject_id}', 'func', 
-                    'sub-{subject_id}_task-MGT_run-{run_id}_bold.nii.gz')
-
-    magnitude_file = opj('sub-{subject_id}', 'fmap', 'sub-{subject_id}_magnitude*.nii.gz')
-
-    phasediff_file = opj('sub-{subject_id}', 'fmap', 'sub-{subject_id}_phasediff.nii.gz')
-
-    info_fieldmap_file = opj('sub-{subject_id}', 'fmap', 'sub-{subject_id}_phasediff.json')
-    
-    dartel_flowfields_file = opj(result_dir, output_dir, 'dartel_template', 
-                                 'u_rc1subject_id_{subject_id}_struct_template.nii')
-    
-    dartel_template_file = opj(result_dir, output_dir, 'dartel_template', 'template_6.nii')
-
-    template = {'anat' : anat_file, 'func' : func_file, 'magnitude' : magnitude_file, 'phasediff' : phasediff_file,
-                'info_fmap' : info_fieldmap_file, 'dartel_template' : dartel_template_file, 
-                'dartel_flow_field' : dartel_flowfields_file}
-
-    # SelectFiles node - to select necessary files
-    selectfiles_preproc = Node(SelectFiles(template, base_directory=exp_dir), name = 'selectfiles_preproc')
-
-    # GUNZIP NODE : SPM do not use .nii.gz files
-    gunzip_anat = Node(Gunzip(), name = 'gunzip_anat')
-
-    gunzip_func = Node(Gunzip(), name = 'gunzip_func')
-
-    gunzip_magnitude = Node(Gunzip(), name = 'gunzip_magnitude')
-
-    gunzip_phasediff = Node(Gunzip(), name = 'gunzip_phasediff')
-
-
-    fieldmap_infos = Node(Function(input_names = ['info_fmap', 'magnitude'],
-                                      output_names = ['TE', 'magnitude_file'],
-                                      function = get_fieldmap_infos), name = 'fieldmap_infos')
-
-    fieldmap = Node(FieldMap(blip_direction = -1), name = 'fieldmap')
-
-    fieldmap.inputs.total_readout_time = total_readout_time
-
-    """
-    - **Segmentation** : SPM Segment function via custom scripts (defaults left in place)
-    """
-    
-    tissue1 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 1), 1, (True,False), (True, False)]
-    tissue2 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 2), 1, (True,False), (True, False)]
-    tissue3 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 3), 2, (True,False), (False, False)]
-    tissue4 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 4), 3, (True,False), (False, False)]
-    tissue5 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 5), 4, (True,False), (False, False)]
-    tissue6 = [('/opt/spm12-r7771/spm12_mcr/spm12/tpm/TPM.nii', 6), 2, (False,False), (False, False)]
-    
-    tissue_list = [tissue1, tissue2, tissue3, tissue4, tissue5, tissue6]
-    
-    segmentation = Node(NewSegment(write_deformation_fields = [True, True], tissues = tissue_list, 
-                                  channel_info = (0.0001, 60, (True, True))), name = "segmentation")
-
-    """
-    - **Slice timing** : SPM slice time correction with default parameters 
-    (shift via sinc interpolation and Fourier transform), with ref =2. Slice time correction performed 
-    as first step of preprocessing, prior to motion correction.
-    """
-
-    slice_timing = Node(SliceTiming(num_slices = N, ref_slice = 2, slice_order = ST, 
-                                   time_acquisition = TA, time_repetition = TR), name = "slice_timing")
-
-    #in_files = func
-    """
-    - **Motion correction** : SPM realign and unwarp, incorporating field maps into motion correction for unwarping.
-    Most parameters as SPM default, but 4th degree bslines interpolation was used for estimation. 
-    Images were rereferenced to the first scan in each run. 
-    """
-
-    motion_correction = Node(RealignUnwarp(interp = 4), name = "motion_correction")
-
-    #in_files = timecorrected_files
-
-    """
-    - **Intrasubject coregistration** : Each EPI scan was coregistered to the structural scan via SPM's coreg 
-    function, using normalized mutual information. 
-    """
-    extract_first = Node(ExtractROI(t_min = 1, t_size=1, output_type = 'NIFTI'), name = 'extract_first')
-    
-    coregistration = Node(Coregister(cost_function = 'nmi', jobtype = 'estimate'), name = "coregistration")
-
-    #target = anat
-    #source = realigned_unwarped_files
-
-    dartel_norm_func = Node(DARTELNorm2MNI(fwhm = fwhm, modulate = False, voxel_size = (2.3, 2.3, 2.15)), name = "dartel_norm_func")
-    #apply_to_files = coregistered_source
-    
-    dartel_norm_anat = Node(DARTELNorm2MNI(fwhm = fwhm, voxel_size = (1, 1, 1)), name = "dartel_norm_anat")
-
-    remove_field_files = Node(Function(input_names = ['files', 'subject_id', 'run_id', 'result_dir', 'working_dir'],
-                                    output_names = ['files'],
-                                    function = rm_field_files), name = 'remove_field_files')
-
-    remove_field_files.inputs.result_dir = result_dir
-    remove_field_files.inputs.working_dir = working_dir
-
-    # DataSink Node - store the wanted results in the wanted repository
-    datasink_preproc = Node(DataSink(base_directory=result_dir, container=output_dir), name='datasink_preproc')
-    
-    #dartel = get_dartel_template_wf(exp_dir, result_dir, working_dir, output_dir, subject_list)
-
-    preprocessing =  Workflow(base_dir = opj(result_dir, working_dir), name = "preprocessing")
-
-    preprocessing.connect([(infosource, selectfiles_preproc, [('subject_id', 'subject_id'), 
-                                                             ('run_id', 'run_id')]),
-                           (infosource, remove_field_files, [('subject_id', 'subject_id'), 
-                                                            ('run_id', 'run_id')]),
-                           (selectfiles_preproc, gunzip_anat, [('anat', 'in_file')]),
-                           (selectfiles_preproc, gunzip_func, [('func', 'in_file')]),
-                           (selectfiles_preproc, gunzip_phasediff, [('phasediff', 'in_file')]),
-                           (selectfiles_preproc, fieldmap_infos, [('info_fmap', 'info_fmap'), 
-                                                                  ('magnitude', 'magnitude')]),
-                           (fieldmap_infos, gunzip_magnitude, [('magnitude_file', 'in_file')]),
-                           (fieldmap_infos, fieldmap, [('TE', 'echo_times')]),
-                           (gunzip_magnitude, fieldmap, [('out_file', 'magnitude_file')]),
-                           (gunzip_phasediff, fieldmap, [('out_file', 'phase_file')]),
-                           (gunzip_func, fieldmap, [('out_file', 'epi_file')]),
-                           (fieldmap, motion_correction, [('vdm', 'phase_map')]),
-                           (gunzip_anat, segmentation, [('out_file', 'channel_files')]),
-                           (gunzip_func, slice_timing, [('out_file', 'in_files')]),
-                           (slice_timing, motion_correction, [('timecorrected_files', 'in_files')]),
-                           (motion_correction, remove_field_files, [('realigned_unwarped_files', 'files')]), 
-                           (remove_field_files, coregistration, [('files', 'apply_to_files')]),
-                           (gunzip_anat, coregistration, [('out_file', 'target')]),
-                           (remove_field_files, extract_first, [('files', 'in_file')]),
-                           (extract_first, coregistration, [('roi_file', 'source')]),
-                           (selectfiles_preproc, dartel_norm_func, [('dartel_flow_field', 'flowfield_files'), 
-                                                                   ('dartel_template', 'template_file')]),
-                           (selectfiles_preproc, dartel_norm_anat, [('dartel_flow_field', 'flowfield_files'), 
-                                                                  ('dartel_template', 'template_file')]),
-                           (gunzip_anat, dartel_norm_anat, [('out_file', 'apply_to_files')]),
-                           (coregistration, dartel_norm_func, [('coregistered_files', 'apply_to_files')]),
-                           (dartel_norm_func, datasink_preproc, 
-                            [('normalized_files', 'preprocessing.@normalized_files')]),
-                           #(dartel_norm_anat, datasink_preproc, 
-                           # [('normalized_files', 'preprocessing.@normalized_anat')]),
-                           (motion_correction, datasink_preproc, 
-                            [('realigned_unwarped_files', 'preprocessing.@motion_corrected'), 
-                             ('realignment_parameters', 'preprocessing.@param')]), 
-                           (segmentation, datasink_preproc, [('normalized_class_images', 'preprocessing.@seg')])
-                          ])
-    
-    return preprocessing
-
-def compute_parameters(parameters_files, wc2_file, motion_corrected_files, subject_id, result_dir, working_dir):
-    import pandas as pd
-    from os.path import join as opj 
-    import os
-    import nibabel as nib
-    import numpy as np
-    from nilearn import image
-    from nilearn.image import resample_to_img, resample_img
-    # import warnings filter
-    from warnings import simplefilter
-    # ignore all future warnings
-    simplefilter(action='ignore', category=FutureWarning)
-    simplefilter(action='ignore', category=UserWarning)
-    simplefilter(action='ignore', category=RuntimeWarning)
-    
-    mean_wm = [[] for i in range(len(motion_corrected_files))]
-    
-    wc2 = nib.load(wc2_file)
-    wc2_mask = wc2.get_fdata() > 0.6
-    wc2_mask = wc2_mask.astype(int)
-    
-
-    for i, functional_file in enumerate(sorted(motion_corrected_files)):
-        functional = nib.load(functional_file)
-        
-        
-        for slices in image.iter_img(functional):
-            slice_img = resample_to_img(slices, wc2, interpolation='nearest', clip = True)
-
-            slice_data = slice_img.get_fdata()
-            masked_slice = slice_data * wc2_mask
-            mean_wm[i].append(np.mean(masked_slice))
-    
-    new_parameters_files = []
-    for i, file in enumerate(sorted(parameters_files)):
-        df = pd.read_table(file, sep = '  ', header = None)
-        
-        df['Mean_WM'] = mean_wm[i]
-        
-        new_path =opj(result_dir, working_dir, 'parameters_file', 
-                      f"parameters_file_sub-{subject_id}_run{'0' + str(i+1)}.tsv")
-        if not os.path.isdir(opj(result_dir, working_dir)):
-            os.mkdir(opj(result_dir, working_dir))
-        if not os.path.isdir(opj(result_dir, working_dir, 'parameters_file')):
-            os.mkdir(opj(result_dir, working_dir, 'parameters_file'))
-        writer = open(new_path, "w")
-        writer.write(df.to_csv(sep = '\t', index = False, header = False, na_rep = '0.0'))
-        writer.close()
-
-        new_parameters_files.append(new_path)
-
-    return new_parameters_files
-
-"""
-An event related design was used. Events were entered as a single events with a 4 second duration. 
-Paramteric modualtors were added for each condition for gain, loss, and for accept or reject 
-(in that order; note that SPM performs serial orthogonalization of modulators).
-
-Canonical HRFs were used along with the derivative and dispersion functions.
-SPM defaults were used for other analysis parameters (Volterra=1, 1st order autocorrelation, high pass filter=128).
-The six motion parameters, the absolute value of the 1st derivative of the six parameters, 
-and the mean WM signal were entered as covariates into the model.
-Mean WM signal was calculated for each individual by taking their SPM segmentation WM mask, 
-thresholded at 0.6, as a mask to the motion corrected BOLD data, taking the mean timeseries of 
-all voxels determined to be within the white matter.
-
-All four scans were entered into a single fixed effects model for each individual, as separate sessions. 
-For each individual, a contrast map was calculated for the parametric effects of gains and the parametric
-effects of losses, with both positive and negative contrasts run, collapsing across runs.
-Contrast beta maps for the parametric effects of losses or gains were entered into the second level analysis. 
-Mass univariate modelling was used. A group analysis (radom effects) model was run for the equaldifference group, 
-equalrange group, and the difference between groups (as separate GLMs)
-The main effects of the parametric modulators for gains and losses were tested. The whole brain was used for 
-calculating cluster statistics.
-The data was thresholded such that only clusters above p<0.05 FDR corrected were kept, and data was then masked 
-to answer the specific hypotheses. Cluster extent, using SPM's FDR corrected cluster extent statistic, 
-and a threshold of p<0.001 uncorrected.
-"""
-
-def get_subject_infos(event_files, runs):
-    '''
-    Create Bunchs for specifySPMModel.
-
-    Parameters :
-    - event_files: list of str, list of events files (one per run) for the subject
-    - runs: list of str, list of runs to use
-    
-    Returns :
-    - subject_info : list of Bunch for 1st level analysis.
-    '''
-
-    from nipype.interfaces.base import Bunch
-    
-    cond_names = ['gamble']
-    onset = {}
-    duration = {}
-    weights_gain = {}
-    weights_loss = {}
-    answers = {}
-    
-    for r in range(len(runs)):  # Loop over number of runs.
-        onset.update({s + '_run' + str(r+1) : [] for s in cond_names}) # creates dictionary items with empty lists
-        duration.update({s + '_run' + str(r+1) : [] for s in cond_names}) 
-        weights_gain.update({'gain_run' + str(r+1) : []})
-        weights_loss.update({'loss_run' + str(r+1) : []})
-        answers.update({'answers_run' + str(r+1) : []})
-    
-    for r, run in enumerate(runs):
-        
-        f_events = event_files[r]
-        
-        with open(f_events, 'rt') as f:
-            next(f)  # skip the header
-            
-            for line in f:
-                info = line.strip().split()
-                
-                for cond in cond_names:
-                    val = cond + '_run' + str(r+1) # trial_run1
-                    val_gain = 'gain_run' + str(r+1) # gain_run1
-                    val_loss = 'loss_run' + str(r+1) # loss_run1
-                    val_answer = 'answers_run' + str(r+1)
-                    onset[val].append(float(info[0])) # onsets for trial_run1 
-                    duration[val].append(float(4))
-                    weights_gain[val_gain].append(float(info[2])) # weights gain for trial_run1
-                    weights_loss[val_loss].append(float(info[3])) # weights loss for trial_run1
-                    if "accept" in str(info[5]):
-                        answers[val_answer].append(1)
-                    else: 
-                        answers[val_answer].append(0)
-
-    # Bunching is done per run, i.e. trial_run1, trial_run2, etc.
-    # But names must not have '_run1' etc because we concatenate runs 
-    subject_info = []
-    for r in range(len(runs)):
-
-        cond = [c + '_run' + str(r+1) for c in cond_names]
-        gain = 'gain_run' + str(r+1)
-        loss = 'loss_run' + str(r+1)
-        answer = 'answers_run' + str(r+1)
-
-        subject_info.insert(r,
-                           Bunch(conditions=cond,
-                                 onsets=[onset[k] for k in cond],
-                                 durations=[duration[k] for k in cond],
-                                 amplitudes=None,
-                                 tmod=None,
-                                 pmod=[Bunch(name=[gain, loss, answer],
-                                             poly=[1, 1, 1],
-                                             param=[weights_gain[gain],
-                                                    weights_loss[loss], 
-                                                   answers[answer]])],
-                                 regressor_names=None,
-                                 regressors=None))
-
-    return subject_info
-
-def get_contrasts(subject_id):
-    '''
-    Create the list of tuples that represents contrasts. 
-    Each contrast is in the form : 
-    (Name,Stat,[list of condition names],[weights on those conditions])
-
-    Parameters:
-        - subject_id: str, ID of the subject 
-
-    Returns:
-        - contrasts: list of tuples, list of contrasts to analyze
-    '''
-    runs = 4
-
-    gamble = []
-    gain = []
-    loss = []
-    for ir in range(runs):
-        ir += 1
-        gamble.append('gamble_run%i' % ir)
-        gain.append('gamble_run%ixgain_run%i^1' % (ir, ir))
-        loss.append('gamble_run%ixloss_run%i^1' % (ir, ir))
-
-    pos_1 = [1] * runs
-    neg_1 = [-1] * runs
-
-
-    pos_gain = (
-        'pos_gain', 'T',
-        gain, pos_1)
-
-    pos_loss = (
-        'pos_loss', 'T',
-        loss, pos_1)
-    
-    neg_gain = (
-        'neg_gain', 'T',
-        gain, neg_1)
-
-    neg_loss = (
-        'neg_loss', 'T',
-        loss, neg_1)
-
-    contrasts = [pos_gain, pos_loss, neg_gain, neg_loss]
-
-    return contrasts
-
-def get_l1_analysis(subject_list, TR, run_list, exp_dir, result_dir, working_dir, output_dir):
-    """
-    Returns the first level analysis workflow.
-
-    Parameters: 
-        - exp_dir: str, directory where raw data are stored
-        - result_dir: str, directory where results will be stored
-        - working_dir: str, name of the sub-directory for intermediate results
-        - output_dir: str, name of the sub-directory for final results
-        - subject_list: list of str, list of subject for which you want to do the analysis
-        - run_list: list of str, list of runs for which you want to do the analysis 
-        - TR: float, time repetition used during acquisition
-
-    Returns: 
-        - l1_analysis : Nipype WorkFlow 
-    """
-    # Infosource Node - To iterate on subjects
-    infosource = Node(IdentityInterface(fields = ['subject_id', 'run_list'], 
-                                        run_list = run_list),
-                      name = 'infosource')
-
-    infosource.iterables = [('subject_id', subject_list)]
-
-    
-    func_file = opj(result_dir, output_dir, 'preprocessing', '_run_id_*_subject_id_{subject_id}', 
-                    'swuasub-{subject_id}_task-MGT_run-*_bold.nii')
-    
-    motion_corrected_file = opj(result_dir, output_dir, 'preprocessing', '_run_id_*_subject_id_{subject_id}', 
-                    'uasub-{subject_id}_task-MGT_run-*_bold.nii')
-    
-    parameter_file = opj(result_dir, output_dir, 'preprocessing', '_run_id_*_subject_id_{subject_id}', 
-                         'rp_asub-{subject_id}_task-MGT_run-*_bold.txt')
-    
-    wc2_file = opj(result_dir, output_dir, 'preprocessing', '_run_id_01_subject_id_{subject_id}', 
-                         'wc2sub-{subject_id}_T1w.nii')
-    
-    event_file = opj('sub-{subject_id}', 'func', 
-                     'sub-{subject_id}_task-MGT_run-*_events.tsv')
-
-    template = {'func' : func_file, 'param' : parameter_file, 'event' : event_file, 'wc2' : wc2_file, 
-               'motion_correction': motion_corrected_file}
-
-    # SelectFiles node - to select necessary files
-    selectfiles = Node(SelectFiles(template, base_directory=exp_dir), name = 'selectfiles')
-    
-    # DataSink Node - store the wanted results in the wanted repository
-    datasink = Node(DataSink(base_directory=result_dir, container=output_dir), name='datasink')
-    
-
-    # Get Subject Info - get subject specific condition information
-    subject_infos = Node(Function(input_names=['event_files', 'runs'],
-                                   output_names=['subject_info'],
-                                   function=get_subject_infos),
-                          name='subject_infos')
-    
-    # Get parameters 
-    # compute_parameters(parameters_files, wc2_file, functional_files, subject_id, result_dir, working_dir)
-    
-    parameters = Node(Function(input_names = ['parameters_files', 'wc2_file', 'motion_corrected_files', 'subject_id', 
-                                              'result_dir', 'working_dir'], 
-                              output_names = ['new_parameters_files'],
-                              function = compute_parameters), name = 'parameters')
-    
-    parameters.inputs.working_dir = working_dir
-    parameters.inputs.result_dir = result_dir
-    
-
-    # SpecifyModel - Generates SPM-specific Model
-    specify_model = Node(SpecifySPMModel(concatenate_runs = False, input_units = 'secs', output_units = 'secs',
-                                        time_repetition = TR, high_pass_filter_cutoff = 128), name='specify_model')
-
-    # Level1Design - Generates an SPM design matrix
-    l1_design = Node(Level1Design(bases = {'hrf': {'derivs': [1, 1]}}, timing_units = 'secs', 
-                                    interscan_interval = TR), name='l1_design')
-
-    # EstimateModel - estimate the parameters of the model
-    l1_estimate = Node(EstimateModel(estimation_method={'Classical': 1}),
-                          name="l1_estimate")
-
-    # Node contrasts to get contrasts 
-    contrasts = Node(Function(function=get_contrasts,
-                              input_names=['subject_id'],
-                              output_names=['contrasts']),
-                     name='contrasts')
-
-
-    # EstimateContrast - estimates contrasts
-    contrast_estimate = Node(EstimateContrast(), name="contrast_estimate")
-
-    
-    # Create l1 analysis workflow and connect its nodes
-    l1_analysis = Workflow(base_dir = opj(result_dir, working_dir), name = "l1_analysis")
-
-    l1_analysis.connect([(infosource, selectfiles, [('subject_id', 'subject_id')]),
-                        (infosource, subject_infos, [('run_list', 'runs')]),
-                        (infosource, contrasts, [('subject_id', 'subject_id')]),
-                        (infosource, parameters, [('subject_id', 'subject_id')]),
-                        (subject_infos, specify_model, [('subject_info', 'subject_info')]),
-                        (contrasts, contrast_estimate, [('contrasts', 'contrasts')]),
-                        (selectfiles, subject_infos, [('event', 'event_files')]),
-                        (selectfiles, parameters, [('motion_correction', 'motion_corrected_files'),
-                                                  ('param', 'parameters_files'),
-                                                  ('wc2', 'wc2_file')]),
-                        (selectfiles, specify_model, [('func', 'functional_runs')]),
-                        (parameters, specify_model, [('new_parameters_files', 
-                                                      'realignment_parameters')]),
-                        (specify_model, l1_design, [('session_info', 'session_info')]),
-                        (l1_design, l1_estimate, [('spm_mat_file', 'spm_mat_file')]),
-                        (l1_estimate, contrast_estimate, [('spm_mat_file', 'spm_mat_file'),
-                                                          ('beta_images', 'beta_images'),
-                                                          ('residual_image', 'residual_image')]),
-                        (contrast_estimate, datasink, [('con_images', 'l1_analysis.@con_images'),
-                                                                ('spmT_images', 'l1_analysis.@spmT_images'),
-                                                                ('spm_mat_file', 'l1_analysis.@spm_mat_file')])
-                        ])
-    
-    return l1_analysis
-
-
-def get_subset_contrasts(file_list, method, subject_list, participants_file):
-    ''' 
-    Parameters :
-    - file_list : original file list selected by selectfiles node 
-    - subject_list : list of subject IDs that are in the wanted group for the analysis
-    - participants_file: str, file containing participants characteristics
-    - method: str, one of "equalRange", "equalIndifference" or "groupComp"
-    
-    This function return the file list containing only the files belonging to subject in the wanted group.
-    '''
-    equalIndifference_id = []
-    equalRange_id = []
-    equalIndifference_files = []
-    equalRange_files = []
-
-    with open(participants_file, 'rt') as f:
-            next(f)  # skip the header
-            
-            for line in f:
+from nipype.interfaces.spm import (
+    Coregister, OneSampleTTestDesign,
+    EstimateModel, EstimateContrast, Level1Design,
+    TwoSampleTTestDesign, RealignUnwarp, NewSegment, SliceTiming,
+    DARTELNorm2MNI, FieldMap, Threshold
+    )
+from nipype.interfaces.spm.base import Info as SPMInfo
+from nipype.interfaces.fsl import ExtractROI
+from nipype.algorithms.modelgen import SpecifySPMModel
+from niflow.nipype1.workflows.fmri.spm import create_DARTEL_template
+
+from narps_open.pipelines import Pipeline
+from narps_open.data.task import TaskInformation
+from narps_open.data.participants import get_group
+from narps_open.core.common import (
+    remove_parent_directory, list_intersection, elements_in_string, clean_list
+    )
+from narps_open.utils.configuration import Configuration
+
+class PipelineTeam98BT(Pipeline):
+    """ A class that defines the pipeline of team 98BT. """
+
+    def __init__(self):
+        super().__init__()
+        self.fwhm = 8.0
+        self.team_id = '98BT'
+        self.contrast_list = ['0001', '0002', '0003', '0004']
+
+        # Define contrasts
+        gain_conditions = [f'gamble_run{r}xgain_run{r}^1' for r in range(1,len(self.run_list) + 1)]
+        loss_conditions = [f'gamble_run{r}xloss_run{r}^1' for r in range(1,len(self.run_list) + 1)]
+        self.subject_level_contrasts = [
+            ('pos_gain', 'T', gain_conditions, [1, 1, 1, 1]),
+            ('pos_loss', 'T', loss_conditions, [1, 1, 1, 1]),
+            ('neg_gain', 'T', gain_conditions, [-1, -1, -1, -1]),
+            ('neg_loss', 'T', loss_conditions, [-1, -1, -1, -1])
+            ]
+
+    def get_dartel_template_sub_workflow(self):
+        """
+        Create a dartel workflow, as first part of the preprocessing.
+
+        DARTEL allows to create a study-specific template in 3D volume space.
+        This study template can then be used for normalizating each subject’s
+        scans to the MNI space.
+
+        Returns:
+            - dartel : nipype.WorkFlow
+        """
+        # Infosource Node - To iterate on subjects
+        information_source = Node(IdentityInterface(
+            fields = ['subject_id']),
+            name = 'information_source')
+        information_source.iterables = ('subject_id', self.subject_list)
+
+        # SelectFiles Node - to select necessary files
+        template = {
+            'anat' : join('sub-{subject_id}', 'anat', 'sub-{subject_id}_T1w.nii.gz')
+        }
+        select_files = Node(SelectFiles(template), name = 'select_files')
+        select_files.inputs.base_directory = self.directories.dataset_dir
+
+        # Gunzip node - SPM do not use .nii.gz files
+        gunzip_anat = Node(Gunzip(), name = 'gunzip_anat')
+
+        def get_dartel_input(structural_files):
+            print(structural_files)
+            return structural_files
+
+        dartel_input = JoinNode(Function(
+            function = get_dartel_input,
+            input_names = ['structural_files'],
+            output_names = ['structural_files']),
+            name = 'dartel_input',
+            joinsource = 'information_source',
+            joinfield = 'structural_files')
+
+        rename_dartel = MapNode(Rename(format_string = 'subject_id_%(subject_id)s_struct'),
+            iterfield = ['in_file', 'subject_id'],
+            name = 'rename_dartel')
+        rename_dartel.inputs.subject_id = self.subject_list
+        rename_dartel.inputs.keep_ext = True
+
+        dartel_sub_workflow = create_DARTEL_template(name = 'dartel_sub_workflow')
+        dartel_sub_workflow.inputs.inputspec.template_prefix = 'template'
+
+        # DataSink Node - store the wanted results in the wanted repository
+        data_sink = Node(DataSink(), name = 'data_sink')
+        data_sink.inputs.base_directory = self.directories.output_dir
+
+        # Create dartel workflow and connect its nodes
+        dartel_workflow = Workflow(
+            base_dir = self.directories.working_dir, name = 'dartel_workflow')
+        dartel_workflow.connect([
+            (information_source, select_files, [('subject_id', 'subject_id')]),
+            (select_files, gunzip_anat, [('anat', 'in_file')]),
+            (gunzip_anat, dartel_input, [('out_file', 'structural_files')]),
+            (dartel_input, rename_dartel, [('structural_files', 'in_file')]),
+            (rename_dartel, dartel_sub_workflow, [('out_file', 'inputspec.structural_files')]),
+            (dartel_sub_workflow, data_sink, [
+                ('outputspec.template_file', 'dartel_template.@template_file'),
+                ('outputspec.flow_fields', 'dartel_template.@flow_fields')])
+            ])
+
+        # Remove large files, if requested
+        if Configuration()['pipelines']['remove_unused_data']:
+
+            # Function Nodes remove_parent_directory - Remove gunziped files
+            remove_gunzip = Node(Function(
+                function = remove_parent_directory,
+                input_names = ['_', 'file_name'],
+                output_names = []
+                ), name = 'remove_gunzip')
+
+            # Add connections
+            dartel_workflow.connect([
+                (gunzip_anat, remove_gunzip, [('out_file', 'file_name')]),
+                (data_sink, remove_gunzip, [('out_file', '_')])
+            ])
+
+        return dartel_workflow
+
+    def get_fieldmap_info(fieldmap_info_file, magnitude_files):
+        """
+        Function to get information necessary to compute the fieldmap.
+
+        Parameters:
+            - fieldmap_info_file: str, file with fieldmap information
+            - magnitude_files: list of str, list of magnitude files
+
+        Returns:
+            - echo_times: tuple of floats, echo time obtained from fieldmap information file
+            - magnitude_file: str, necessary file to compute fieldmap
+        """
+        from json import load
+
+        with open(fieldmap_info_file, 'rt') as file:
+            fieldmap_info = load(file)
+
+        short_echo_time = min(float(fieldmap_info['EchoTime1']), float(fieldmap_info['EchoTime2']))
+        long_echo_time = max(float(fieldmap_info['EchoTime1']), float(fieldmap_info['EchoTime2']))
+
+        if short_echo_time == float(fieldmap_info['EchoTime1']):
+            magnitude_file = magnitude_files[0]
+        elif short_echo_time == float(fieldmap_info['EchoTime2']):
+            magnitude_file = magnitude_files[1]
+
+        return (short_echo_time, long_echo_time), magnitude_file
+
+    def get_preprocessing_sub_workflow(self):
+        """
+        Create the second part of the preprocessing workflow.
+
+        Returns:
+            - preprocessing : nipype.WorkFlow
+        """
+        # Infosource Node - To iterate on subjects
+        information_source = Node(IdentityInterface(
+            fields = ['subject_id', 'run_id']),
+            name = 'information_source')
+        information_source.iterables = [
+            ('subject_id', self.subject_list), ('run_id', self.run_list)
+            ]
+
+        # SelectFiles Node - Select necessary files
+        templates = {
+            'anat' : join('sub-{subject_id}', 'anat', 'sub-{subject_id}_T1w.nii.gz'),
+            'func' : join('sub-{subject_id}', 'func',
+                'sub-{subject_id}_task-MGT_run-{run_id}_bold.nii.gz'),
+            'magnitude' : join('sub-{subject_id}', 'fmap', 'sub-{subject_id}_magnitude*.nii.gz'),
+            'phasediff' : join('sub-{subject_id}', 'fmap', 'sub-{subject_id}_phasediff.nii.gz'),
+            'info_fmap' : join('sub-{subject_id}', 'fmap', 'sub-{subject_id}_phasediff.json'),
+            'dartel_flow_field' : join(self.directories.output_dir, 'dartel_template',
+                'u_rc1subject_id_{subject_id}_struct_template.nii'),
+            'dartel_template' :join(
+                self.directories.output_dir, 'dartel_template', 'template_6.nii')
+        }
+        select_files = Node(SelectFiles(templates), name = 'select_files')
+        select_files.inputs.base_directory = self.directories.dataset_dir
+
+        # Gunzip nodes - gunzip files because SPM do not use .nii.gz files
+        gunzip_anat = Node(Gunzip(), name = 'gunzip_anat')
+        gunzip_func = Node(Gunzip(), name = 'gunzip_func')
+        gunzip_magnitude = Node(Gunzip(), name = 'gunzip_magnitude')
+        gunzip_phasediff = Node(Gunzip(), name = 'gunzip_phasediff')
+
+        # Function Node get_fieldmap_info -
+        fieldmap_info = Node(Function(
+            function = self.get_fieldmap_info,
+            input_names = ['fieldmap_info_file', 'magnitude_files'],
+            output_names = ['echo_times', 'magnitude_file']),
+            name = 'fieldmap_info')
+
+        # FieldMap Node -
+        fieldmap = Node(FieldMap(), name = 'fieldmap')
+        fieldmap.inputs.blip_direction = -1
+        fieldmap.inputs.total_readout_time = TaskInformation()['TotalReadoutTime']
+
+        # Get SPM Tissue Probability Maps file
+        spm_tissues_file = join(SPMInfo.getinfo()['path'], 'tpm', 'TPM.nii')
+
+        # Segmentation Node - SPM Segment function via custom scripts (defaults left in place)
+        segmentation = Node(NewSegment(), name = 'segmentation')
+        segmentation.inputs.write_deformation_fields = [True, True]
+        segmentation.inputs.channel_info = (0.0001, 60, (True, True))
+        segmentation.inputs.tissues = [
+            [(spm_tissues_file, 1), 1, (True,False), (True, False)],
+            [(spm_tissues_file, 2), 1, (True,False), (True, False)],
+            [(spm_tissues_file, 3), 2, (True,False), (False, False)],
+            [(spm_tissues_file, 4), 3, (True,False), (False, False)],
+            [(spm_tissues_file, 5), 4, (True,False), (False, False)],
+            [(spm_tissues_file, 6), 2, (False,False), (False, False)]
+        ]
+
+        # Slice timing - SPM slice time correction with default parameters
+        slice_timing = Node(SliceTiming(), name = 'slice_timing')
+        slice_timing.inputs.num_slices = TaskInformation()['NumberOfSlices']
+        slice_timing.inputs.ref_slice = 2
+        slice_timing.inputs.slice_order = TaskInformation()['SliceTiming']
+        slice_timing.inputs.time_acquisition = TaskInformation()['AcquisitionTime']
+        slice_timing.inputs.time_repetition = TaskInformation()['RepetitionTime']
+
+        # Motion correction - SPM realign and unwarp
+        motion_correction = Node(RealignUnwarp(), name = 'motion_correction')
+        motion_correction.inputs.interp = 4
+
+        # Intrasubject coregistration
+        extract_first = Node(ExtractROI(), name = 'extract_first')
+        extract_first.inputs.t_min = 1
+        extract_first.inputs.t_size = 1
+        extract_first.inputs.output_type = 'NIFTI'
+
+        coregistration = Node(Coregister(), name = 'coregistration')
+        coregistration.inputs.cost_function = 'nmi'
+        coregistration.inputs.jobtype = 'estimate'
+
+        dartel_norm_func = Node(DARTELNorm2MNI(), name = 'dartel_norm_func')
+        dartel_norm_func.inputs.fwhm = self.fwhm
+        dartel_norm_func.inputs.modulate = False
+        dartel_norm_func.inputs.voxel_size = (2.3, 2.3, 2.15)
+
+        dartel_norm_anat = Node(DARTELNorm2MNI(), name = 'dartel_norm_anat')
+        dartel_norm_anat.inputs.fwhm = self.fwhm
+        dartel_norm_anat.inputs.voxel_size = (1, 1, 1)
+
+        # DataSink Node - store the wanted results in the wanted repository
+        data_sink = Node(DataSink(), name = 'data_sink')
+        data_sink.inputs.base_directory = self.directories.output_dir
+
+        # Create preprocessing workflow and connect its nodes
+        preprocessing =  Workflow(base_dir = self.directories.working_dir, name = 'preprocessing')
+        preprocessing.connect([
+            (information_source, select_files, [
+                ('subject_id', 'subject_id'),
+                ('run_id', 'run_id')]),
+            (select_files, gunzip_anat, [('anat', 'in_file')]),
+            (select_files, gunzip_func, [('func', 'in_file')]),
+            (select_files, gunzip_phasediff, [('phasediff', 'in_file')]),
+            (select_files, fieldmap_info, [
+                ('info_fmap', 'fieldmap_info_file'),
+                ('magnitude', 'magnitude_files')]),
+            (fieldmap_info, gunzip_magnitude, [('magnitude_file', 'in_file')]),
+            (fieldmap_info, fieldmap, [('echo_times', 'echo_times')]),
+            (gunzip_magnitude, fieldmap, [('out_file', 'magnitude_file')]),
+            (gunzip_phasediff, fieldmap, [('out_file', 'phase_file')]),
+            (gunzip_func, fieldmap, [('out_file', 'epi_file')]),
+            (fieldmap, motion_correction, [('vdm', 'phase_map')]),
+            (gunzip_anat, segmentation, [('out_file', 'channel_files')]),
+            (gunzip_func, slice_timing, [('out_file', 'in_files')]),
+            (slice_timing, motion_correction, [('timecorrected_files', 'in_files')]),
+            (motion_correction, coregistration, [('realigned_unwarped_files', 'apply_to_files')]),
+            (gunzip_anat, coregistration, [('out_file', 'target')]),
+            (motion_correction, extract_first, [('realigned_unwarped_files', 'in_file')]),
+            (extract_first, coregistration, [('roi_file', 'source')]),
+            (select_files, dartel_norm_func, [
+                ('dartel_flow_field', 'flowfield_files'),
+                ('dartel_template', 'template_file')]),
+            (select_files, dartel_norm_anat, [
+                ('dartel_flow_field', 'flowfield_files'),
+                ('dartel_template', 'template_file')]),
+            (gunzip_anat, dartel_norm_anat, [('out_file', 'apply_to_files')]),
+            (coregistration, dartel_norm_func, [('coregistered_files', 'apply_to_files')]),
+            (dartel_norm_func, data_sink, [
+                ('normalized_files', 'preprocessing.@normalized_files')]),
+            (motion_correction, data_sink, [
+                ('realigned_unwarped_files', 'preprocessing.@motion_corrected'),
+                ('realignment_parameters', 'preprocessing.@param')]),
+            (segmentation, data_sink, [('normalized_class_images', 'preprocessing.@seg')]),
+        ])
+
+        # Remove large files, if requested
+        if Configuration()['pipelines']['remove_unused_data']:
+
+            # Merge Node - Merge file names to be removed after datasink node is performed
+            merge_removable_files = Node(Merge(5), name = 'merge_removable_files')
+            merge_removable_files.inputs.ravel_inputs = True
+
+            # Function Nodes remove_files - Remove sizeable files once they aren't needed
+            remove_after_datasink = MapNode(Function(
+                function = remove_parent_directory,
+                input_names = ['_', 'file_name'],
+                output_names = []
+                ), name = 'remove_after_datasink', iterfield = 'file_name')
+
+            # Add connections
+            preprocessing.connect([
+                (gunzip_func, merge_removable_files, [('out_file', 'in1')]),
+                (gunzip_phasediff, merge_removable_files, [('out_file', 'in2')]),
+                (gunzip_magnitude, merge_removable_files, [('out_file', 'in3')]),
+                (fieldmap, merge_removable_files, [('vdm', 'in4')]),
+                (slice_timing, merge_removable_files, [('timecorrected_files', 'in5')]),
+                (merge_removable_files, remove_after_datasink, [('out', 'file_name')]),
+                (data_sink, remove_after_datasink, [('out_file', '_')])
+            ])
+
+        return preprocessing
+
+    def get_preprocessing(self):
+        """
+        Create the full preprocessing workflow.
+
+        Returns: a list of nipype.WorkFlow
+        """
+        return [
+            self.get_dartel_template_sub_workflow(),
+            self.get_preprocessing_sub_workflow()
+        ]
+
+    def get_preprocessing_outputs(self):
+        """ Return the names of the files the preprocessing is supposed to generate. """
+
+        # Outputs from dartel workflow
+        return_list = [join(self.directories.output_dir, 'dartel_template', 'template_6.nii')]
+        return_list += [join(self.directories.output_dir, 'dartel_template',
+            f'u_rc1subject_id_{subject_id}_struct_template.nii')\
+            for subject_id in self.subject_list]
+
+        # Outputs from preprocessing
+        parameters = {
+            'subject_id': self.subject_list,
+            'run_id': self.run_list,
+        }
+        parameter_sets = product(*parameters.values())
+        output_dir = join(
+            self.directories.output_dir,
+            'preprocessing',
+            '_run_id_{run_id}_subject_id_{subject_id}'
+        )
+        templates = [
+            # Realignment parameters
+            join(output_dir, 'rp_asub-{subject_id}_task-MGT_run-{run_id}_bold.txt'),
+            # Realigned unwarped files
+            join(output_dir, 'uasub-{subject_id}_task-MGT_run-{run_id}_bold.nii'),
+            # Normalized_files
+            join(output_dir, 'swuasub-{subject_id}_task-MGT_run-{run_id}_bold.nii'),
+            # Normalized class images
+            join(output_dir, 'wc2sub-{subject_id}_T1w.nii'),
+            join(output_dir, 'wc1sub-{subject_id}_T1w.nii')
+        ]
+        return_list += [template.format(**dict(zip(parameters.keys(), parameter_values)))\
+            for parameter_values in parameter_sets for template in templates]
+
+        return return_list
+
+    def get_run_level_analysis(self):
+        """ No run level analysis has been done by team 98BT """
+        return None
+
+    def get_parameters_file(
+        parameters_file: str,
+        wc2_file: str,
+        func_file: str, subject_id: str, run_id: str, working_dir: str):
+        """
+        Create a new tsv file, by adding the mean signal in white matter to other parameters
+            in parameters_file.
+
+        Parameters :
+        - parameters_file : path to subject parameters file (i.e. one per run)
+        - wc2_file : path to the segmented white matter file
+        - func_file : path to the functional data
+        - run_id : run for which the analysis is made
+        - subject_id : subject for whom the analysis is made
+        - working_dir : directory where to store the output files
+
+        Return :
+        - path to new file containing only desired parameters.
+        """
+        from os import makedirs
+        from os.path import join
+        from nibabel import load
+        from numpy import mean
+        from pandas import read_table
+        from nilearn.image import iter_img, resample_to_img
+
+        # Ignore all future warnings
+        from warnings import simplefilter
+        simplefilter(action = 'ignore', category = FutureWarning)
+        simplefilter(action = 'ignore', category = UserWarning)
+        simplefilter(action = 'ignore', category = RuntimeWarning)
+
+        # Load wc2 file and create a mask out of it
+        wc2 = load(wc2_file)
+        wc2_mask = wc2.get_fdata() > 0.6
+        wc2_mask = wc2_mask.astype(int)
+
+        # Compute the mean signal in white matter, for each slice of the functional data
+        mean_wm = []
+        for current_slice in iter_img(load(func_file)):
+            slice_data = resample_to_img(
+                current_slice, wc2, interpolation = 'nearest', clip = True).get_fdata()
+            # Append mean value of masked data
+            mean_wm.append(mean(slice_data * wc2_mask))
+
+        # Create new parameters file
+        data_frame = read_table(parameters_file, sep = '  ', header = None)
+        data_frame['Mean_WM'] = mean_wm
+
+        new_parameters_file = join(working_dir, 'parameters_files',
+            f'parameters_file_sub-{subject_id}_run-{run_id}.tsv')
+
+        makedirs(join(working_dir, 'parameters_files'), exist_ok = True)
+
+        with open(new_parameters_file, 'w') as writer:
+            writer.write(data_frame.to_csv(
+                sep = '\t', index = False, header = False, na_rep = '0.0'))
+
+        return new_parameters_file
+
+    def get_subject_information(event_file: str, short_run_id: int):
+        """
+        Create Bunch for specifySPMModel.
+
+        Parameters :
+        - event_file: str, events file for a run of a subject
+        - short_run_id: str, an identifier for the run corresponding to the event_file
+            must be '1' for the first run, '2' for the second run, etc.
+
+        Returns :
+        - subject_info : Bunch corresponding to the event file
+        """
+        from nipype.interfaces.base import Bunch
+
+        # Create empty lists
+        onsets = []
+        durations = []
+        weights_gain = []
+        weights_loss = []
+        answers = []
+
+        # Parse event file
+        with open(event_file, 'rt') as file:
+            next(file)  # skip the header
+
+            for line in file:
                 info = line.strip().split()
-                
-                if info[0][-3:] in subject_list and info[1] == "equalIndifference":
-                    equalIndifference_id.append(info[0][-3:])
-                elif info[0][-3:] in subject_list and info[1] == "equalRange":
-                    equalRange_id.append(info[0][-3:])
-    
-    for file in file_list:
-        sub_id = file.split('/')
-        if sub_id[-2][-3:] in equalIndifference_id:
-            equalIndifference_files.append(file)
-        elif sub_id[-2][-3:] in equalRange_id:
-            equalRange_files.append(file)
-            
-    return equalIndifference_id, equalRange_id, equalIndifference_files, equalRange_files 
-
-
-def get_l2_analysis(subject_list, n_sub, contrast_list, method, exp_dir, result_dir, working_dir, output_dir):
-    """
-    Returns the 2nd level of analysis workflow.
-
-    Parameters: 
-        - exp_dir: str, directory where raw data are stored
-        - result_dir: str, directory where results will be stored
-        - working_dir: str, name of the sub-directory for intermediate results
-        - output_dir: str, name of the sub-directory for final results
-        - subject_list: list of str, list of subject for which you want to do the preprocessing
-        - contrast_list: list of str, list of contrasts to analyze
-        - method: one of "equalRange", "equalIndifference" or "groupComp"
-        - n_sub: int, number of subject
-
-    Returns: 
-        - l2_analysis: Nipype WorkFlow 
-    """
-    # Infosource - a function free node to iterate over the list of subject names
-    infosource_groupanalysis = Node(IdentityInterface(fields=['contrast_id', 'subjects'],
-                                                      subjects = subject_list),
-                      name="infosource_groupanalysis")
-
-    infosource_groupanalysis.iterables = [('contrast_id', contrast_list)]
-
-    # SelectFiles
-    contrast_file = opj(result_dir, output_dir, 'l1_analysis', '_subject_id_*', "con_00{contrast_id}.nii")
-
-    participants_file = opj(exp_dir, 'participants.tsv')
-
-    templates = {'contrast' : contrast_file, 'participants' : participants_file}
-    
-    selectfiles_groupanalysis = Node(SelectFiles(templates, base_directory=result_dir, force_list= True),
-                       name="selectfiles_groupanalysis")
-    
-    # Datasink node : to save important files 
-    datasink_groupanalysis = Node(DataSink(base_directory = result_dir, container = output_dir), 
-                                  name = 'datasink_groupanalysis')
-    
-    # Node to select subset of contrasts
-    sub_contrasts = Node(Function(input_names = ['file_list', 'method', 'subject_list', 'participants_file'],
-                                 output_names = ['equalIndifference_id', 'equalRange_id', 
-                                                 'equalIndifference_files', 'equalRange_files'],
-                                 function = get_subset_contrasts),
-                        name = 'sub_contrasts')
-    
-    sub_contrasts.inputs.method = method
-
-    ## Estimate model 
-    estimate_model = Node(EstimateModel(estimation_method={'Classical':1}), name = "estimate_model")
-
-    ## Estimate contrasts
-    estimate_contrast = Node(EstimateContrast(group_contrast=True),
-                             name = "estimate_contrast")
-
-    ## Create thresholded maps 
-    threshold = MapNode(Threshold(use_fwe_correction=False, height_threshold = 0.01,
-                                 extent_fdr_p_threshold = 0.05, use_topo_fdr = False, force_activation = True), name = "threshold", 
-                        iterfield = ["stat_image", "contrast_index"])
-    
-
-    l2_analysis = Workflow(base_dir = opj(result_dir, working_dir), name = f"l2_analysis_{method}_nsub_{n_sub}")
-
-    l2_analysis.connect([(infosource_groupanalysis, selectfiles_groupanalysis, [('contrast_id', 'contrast_id')]),
-        (infosource_groupanalysis, sub_contrasts, [('subjects', 'subject_list')]),
-        (selectfiles_groupanalysis, sub_contrasts, [('contrast', 'file_list'),
-                                                    ('participants', 'participants_file')]),
-        (estimate_model, estimate_contrast, [('spm_mat_file', 'spm_mat_file'),
-            ('residual_image', 'residual_image'),
-            ('beta_images', 'beta_images')]),
-        (estimate_contrast, threshold, [('spm_mat_file', 'spm_mat_file'),('spmT_images', 'stat_image')]),
-        (threshold, datasink_groupanalysis, [('thresholded_map', f"l2_analysis_{method}_nsub_{n_sub}.@thresh")]),
-        (estimate_model, datasink_groupanalysis, [('mask_image', f"l2_analysis_{method}_nsub_{n_sub}.@mask")]),
-        (estimate_contrast, datasink_groupanalysis, [('spm_mat_file', f"l2_analysis_{method}_nsub_{n_sub}.@spm_mat"),
-            ('spmT_images', f"l2_analysis_{method}_nsub_{n_sub}.@T"),
-            ('con_images', f"l2_analysis_{method}_nsub_{n_sub}.@con")])])
-    
-    
-    if method=='equalRange' or method=='equalIndifference':
-        contrasts = [('Group', 'T', ['mean'], [1]), ('Group', 'T', ['mean'], [-1])] 
-        ## Specify design matrix 
-        one_sample_t_test_design = Node(OneSampleTTestDesign(), name = "one_sample_t_test_design")
-
-        l2_analysis.connect([(sub_contrasts, one_sample_t_test_design, [(f"{method}_files", 'in_files')]),
-            (one_sample_t_test_design, estimate_model, [('spm_mat_file', 'spm_mat_file')])])
-        
-        threshold.inputs.contrast_index = [1, 2]
-        threshold.synchronize = True
 
-    elif method == 'groupComp':
-        contrasts = [('Eq range vs Eq indiff in loss', 'T', ['Group_{1}', 'Group_{2}'], [1, -1])]
-        # Node for the design matrix
-        two_sample_t_test_design = Node(TwoSampleTTestDesign(), 
-                                        name = 'two_sample_t_test_design')
-
-        l2_analysis.connect([(sub_contrasts, two_sample_t_test_design, [('equalRange_files', "group1_files"), 
-            ('equalIndifference_files', 'group2_files')]),
-            (two_sample_t_test_design, estimate_model, [("spm_mat_file", "spm_mat_file")])])
-        
-        threshold.inputs.contrast_index = [1]
+                onsets.append(float(info[0]))
+                durations.append(4.0)
+                weights_gain.append(float(info[2]))
+                weights_loss.append(float(info[3]))
+                if 'accept' in str(info[5]):
+                    answers.append(1)
+                else:
+                    answers.append(0)
+
+        # Create Bunch
+        return Bunch(
+            conditions = [f'gamble_run{short_run_id}'],
+            onsets = [onsets],
+            durations = [durations],
+            amplitudes = None,
+            tmod = None,
+            pmod = [
+                Bunch(
+                    name = [
+                        f'gain_run{short_run_id}',
+                        f'loss_run{short_run_id}',
+                        f'answers_run{short_run_id}'],
+                    poly = [1, 1, 1],
+                    param = [weights_gain, weights_loss, answers]
+                )
+            ],
+            regressor_names = None,
+            regressors = None
+        )
+
+    def get_subject_level_analysis(self):
+        """
+        Create the subject level analysis workflow.
+
+        Returns:
+            - subject_level_analysis : nipype.WorkFlow
+        """
+        # Infosource Node - To iterate on subjects
+        information_source = Node(IdentityInterface(
+            fields = ['subject_id']),
+            name = 'information_source')
+        information_source.iterables = [('subject_id', self.subject_list)]
+
+        # SelectFiles Node - to select necessary files
+        templates = {
+            'func' : join(self.directories.output_dir,
+                'preprocessing', '_run_id_*_subject_id_{subject_id}',
+                'swuasub-{subject_id}_task-MGT_run-*_bold.nii'),
+            'motion_correction': join(self.directories.output_dir,
+                'preprocessing', '_run_id_*_subject_id_{subject_id}',
+                'uasub-{subject_id}_task-MGT_run-*_bold.nii'),
+            'param' : join(self.directories.output_dir,
+                'preprocessing', '_run_id_*_subject_id_{subject_id}',
+                'rp_asub-{subject_id}_task-MGT_run-*_bold.txt'),
+            'wc2' : join(self.directories.output_dir,
+                'preprocessing', '_run_id_01_subject_id_{subject_id}',
+                'wc2sub-{subject_id}_T1w.nii'),
+            'events' : join(self.directories.dataset_dir,
+                'sub-{subject_id}', 'func', 'sub-{subject_id}_task-MGT_run-*_events.tsv')
+        }
+        select_files = Node(SelectFiles(templates),name = 'select_files')
+        select_files.inputs.base_directory = self.directories.results_dir
+
+        # DataSink Node - store the wanted results in the wanted repository
+        data_sink = Node(DataSink(), name = 'data_sink')
+        data_sink.inputs.base_directory = self.directories.output_dir
+
+        # Get Subject Info - get subject specific condition information
+        subject_information = MapNode(Function(
+            function = self.get_subject_information,
+            input_names = ['event_file', 'short_run_id'],
+            output_names = ['subject_info']),
+            name = 'subject_information', iterfield = ['event_file', 'short_run_id'])
+        subject_information.inputs.short_run_id = list(range(1, len(self.run_list) + 1))
+
+        # Get parameters
+        parameters = MapNode(Function(
+            function = self.get_parameters_file,
+            input_names = [
+                'parameters_file',
+                'wc2_file',
+                'func_file',
+                'subject_id',
+                'run_id',
+                'working_dir'
+                ],
+            output_names = ['new_parameters_file']),
+            iterfield = ['parameters_file', 'func_file'],
+            name = 'parameters')
+        parameters.inputs.run_id = self.run_list
+        parameters.inputs.working_dir = self.directories.working_dir
+
+        # SpecifyModel - Generates SPM-specific Model
+        specify_model = Node(SpecifySPMModel(), name = 'specify_model')
+        specify_model.inputs.concatenate_runs = False
+        specify_model.inputs.input_units = 'secs'
+        specify_model.inputs.output_units = 'secs'
+        specify_model.inputs.time_repetition = TaskInformation()['RepetitionTime']
+        specify_model.inputs.high_pass_filter_cutoff = 128
+
+        # Level1Design - Generates an SPM design matrix
+        model_design = Node(Level1Design(), name = 'model_design')
+        model_design.inputs.bases = {'hrf': {'derivs': [1, 1]}}
+        model_design.inputs.timing_units = 'secs'
+        model_design.inputs.interscan_interval = TaskInformation()['RepetitionTime']
+
+        # EstimateModel - estimate the parameters of the model
+        model_estimate = Node(EstimateModel(), name = 'model_estimate')
+        model_estimate.inputs.estimation_method = {'Classical': 1}
+
+        # EstimateContrast - estimates contrasts
+        contrast_estimate = Node(EstimateContrast(), name = 'contrast_estimate')
+        contrast_estimate.inputs.contrasts = self.subject_level_contrasts
+
+        # Create l1 analysis workflow and connect its nodes
+        subject_level_analysis = Workflow(
+            base_dir = self.directories.working_dir,
+            name = 'subject_level_analysis'
+            )
+        subject_level_analysis.connect([
+            (information_source, select_files, [('subject_id', 'subject_id')]),
+            (information_source, parameters, [('subject_id', 'subject_id')]),
+            (select_files, subject_information, [('events', 'event_file')]),
+            (select_files, parameters, [
+                ('motion_correction', 'func_file'),
+                ('param', 'parameters_file'),
+                ('wc2', 'wc2_file')]),
+            (select_files, specify_model, [('func', 'functional_runs')]),
+            (subject_information, specify_model, [('subject_info', 'subject_info')]),
+            (parameters, specify_model, [
+                ('new_parameters_file', 'realignment_parameters')]),
+            (specify_model, model_design, [('session_info', 'session_info')]),
+            (model_design, model_estimate, [('spm_mat_file', 'spm_mat_file')]),
+            (model_estimate, contrast_estimate, [
+                ('spm_mat_file', 'spm_mat_file'),
+                ('beta_images', 'beta_images'),
+                ('residual_image', 'residual_image')]),
+            (contrast_estimate, data_sink, [
+                ('con_images', 'subject_level_analysis.@con_images'),
+                ('spmT_images', 'subject_level_analysis.@spmT_images'),
+                ('spm_mat_file', 'subject_level_analysis.@spm_mat_file')])
+        ])
+
+        return subject_level_analysis
+
+    def get_subject_level_outputs(self):
+        """ Return the names of the files the subject level analysis is supposed to generate. """
+
+        # Contrat maps
+        templates = [join(
+            self.directories.output_dir,
+            'subject_level_analysis', '_subject_id_{subject_id}', f'con_{contrast_id}.nii')\
+            for contrast_id in self.contrast_list]
+
+        # SPM.mat file
+        templates += [join(
+            self.directories.output_dir,
+            'subject_level_analysis', '_subject_id_{subject_id}', 'SPM.mat')]
+
+        # spmT maps
+        templates += [join(
+            self.directories.output_dir,
+            'subject_level_analysis', '_subject_id_{subject_id}', f'spmT_{contrast_id}.nii')\
+            for contrast_id in self.contrast_list]
+
+        # Format with subject_ids
+        return_list = []
+        for template in templates:
+            return_list += [template.format(subject_id = s) for s in self.subject_list]
+
+        return return_list
+
+    def get_group_level_analysis(self):
+        """
+        Return all workflows for the group level analysis.
+
+        Returns;
+            - a list of nipype.WorkFlow
+        """
+
+        methods = ['equalRange', 'equalIndifference', 'groupComp']
+        return [self.get_group_level_analysis_sub_workflow(method) for method in methods]
+
+    def get_group_level_analysis_sub_workflow(self, method):
+        """
+        Returns the 2nd level of analysis workflow.
+
+        Parameters:
+            - method: one of "equalRange", "equalIndifference" or "groupComp"
+
+        Returns:
+            - group_level_analysis: Nipype WorkFlow
+        """
+        # Compute the number of participants used to do the analysis
+        nb_subjects = len(self.subject_list)
+
+        # Infosource - a function free node to iterate over the list of subject names
+        information_source = Node(
+            IdentityInterface(
+                fields = ['contrast_id', 'subjects']),
+                name = 'information_source')
+        information_source.iterables = [('contrast_id', self.contrast_list)]
+
+        # SelectFiles
+        templates = {
+            'contrasts' : join(self.directories.output_dir,
+                'subject_level_analysis', '_subject_id_*', 'con_{contrast_id}.nii')
+        }
+
+        select_files = Node(SelectFiles(templates), name = 'select_files')
+        select_files.inputs.base_directory = self.directories.results_dir
+        select_files.inputs.force_list = True
+
+        # Datasink - save important files
+        data_sink = Node(DataSink(), name = 'data_sink')
+        data_sink.inputs.base_directory = self.directories.output_dir
+
+        # Function Node get_equal_range_subjects
+        #   Get subjects in the equalRange group and in the subject_list
+        get_equal_range_subjects = Node(Function(
+            function = list_intersection,
+            input_names = ['list_1', 'list_2'],
+            output_names = ['out_list']
+            ),
+            name = 'get_equal_range_subjects'
+        )
+        get_equal_range_subjects.inputs.list_1 = get_group('equalRange')
+        get_equal_range_subjects.inputs.list_2 = self.subject_list
+
+        # Function Node get_equal_indifference_subjects
+        #   Get subjects in the equalIndifference group and in the subject_list
+        get_equal_indifference_subjects = Node(Function(
+            function = list_intersection,
+            input_names = ['list_1', 'list_2'],
+            output_names = ['out_list']
+            ),
+            name = 'get_equal_indifference_subjects'
+        )
+        get_equal_indifference_subjects.inputs.list_1 = get_group('equalIndifference')
+        get_equal_indifference_subjects.inputs.list_2 = self.subject_list
+
+        # Function Node elements_in_string
+        #   Get contrast files for required subjects
+        # Note : using a MapNode with elements_in_string requires using clean_list to remove
+        #   None values from the out_list
+        get_contrasts = MapNode(Function(
+            function = elements_in_string,
+            input_names = ['input_str', 'elements'],
+            output_names = ['out_list']
+            ),
+            name = 'get_contrasts', iterfield = 'input_str'
+        )
+
+        # Estimate model
+        estimate_model = Node(EstimateModel(), name = 'estimate_model')
+        estimate_model.inputs.estimation_method = {'Classical':1}
+
+        # Estimate contrasts
+        estimate_contrast = Node(EstimateContrast(), name = 'estimate_contrast')
+        estimate_contrast.inputs.group_contrast = True
+
+        # Create thresholded maps
+        threshold = MapNode(Threshold(),
+            name = 'threshold', iterfield = ['stat_image', 'contrast_index'])
+        threshold.inputs.use_fwe_correction = False
+        threshold.inputs.height_threshold = 0.01
+        threshold.inputs.extent_fdr_p_threshold = 0.05
+        threshold.inputs.use_topo_fdr = False
+        threshold.inputs.force_activation = True
         threshold.synchronize = True
 
-    estimate_contrast.inputs.contrasts = contrasts
-
-    return l2_analysis
-
-def reorganize_results(result_dir, output_dir, n_sub, team_ID):
-    """
-    Reorganize the results to analyze them. 
-
-    Parameters: 
-        - result_dir: str, directory where results will be stored
-        - output_dir: str, name of the sub-directory for final results
-        - n_sub: int, number of subject used for analysis
-        - team_ID: str, name of the team ID for which we reorganize files
-    """
-    from os.path import join as opj
-    import os
-    import shutil
-    import gzip
-
-    h1 = opj(result_dir, output_dir, f"l2_analysis_equalIndifference_nsub_{n_sub}", '_contrast_id_01')
-    h2 = opj(result_dir, output_dir, f"l2_analysis_equalRange_nsub_{n_sub}", '_contrast_id_01')
-    h3 = opj(result_dir, output_dir, f"l2_analysis_equalIndifference_nsub_{n_sub}", '_contrast_id_01')
-    h4 = opj(result_dir, output_dir, f"l2_analysis_equalRange_nsub_{n_sub}", '_contrast_id_01')
-    h5 = opj(result_dir, output_dir, f"l2_analysis_equalIndifference_nsub_{n_sub}", '_contrast_id_02')
-    h6 = opj(result_dir, output_dir, f"l2_analysis_equalRange_nsub_{n_sub}", '_contrast_id_02')
-    h7 = opj(result_dir, output_dir, f"l2_analysis_equalIndifference_nsub_{n_sub}", '_contrast_id_02')
-    h8 = opj(result_dir, output_dir, f"l2_analysis_equalRange_nsub_{n_sub}", '_contrast_id_02')
-    h9 = opj(result_dir, output_dir, f"l2_analysis_groupComp_nsub_{n_sub}", '_contrast_id_02')
-
-    h = [h1, h2, h3, h4, h5, h6, h7, h8, h9]
-
-    repro_unthresh = [opj(filename, "spmT_0002.nii") if i in [4, 5] else opj(filename, 
-                     "spmT_0001.nii") for i, filename in enumerate(h)]
-
-    repro_thresh = [opj(filename, "_threshold1", 
-         "spmT_0002_thr.nii") if i in [4, 5] else opj(filename, 
-          "_threshold0", "spmT_0001_thr.nii")  for i, filename in enumerate(h)]
-    
-    if not os.path.isdir(opj(result_dir, "NARPS-reproduction")):
-        os.mkdir(opj(result_dir, "NARPS-reproduction"))
-    
-    for i, filename in enumerate(repro_unthresh):
-        f_in = filename
-        f_out = opj(result_dir, "NARPS-reproduction", f"team_{team_ID}_nsub_{n_sub}_hypo{i+1}_unthresholded.nii")
-        shutil.copyfile(f_in, f_out)
-
-    for i, filename in enumerate(repro_thresh):
-        f_in = filename
-        f_out = opj(result_dir, "NARPS-reproduction", f"team_{team_ID}_nsub_{n_sub}_hypo{i+1}_thresholded.nii")
-        shutil.copyfile(f_in, f_out)
-    
-    print(f"Results files of team {team_ID} reorganized.")
\ No newline at end of file
+        group_level_analysis = Workflow(
+            base_dir = self.directories.working_dir,
+            name = f'group_level_analysis_{method}_nsub_{nb_subjects}')
+        group_level_analysis.connect([
+            (information_source, select_files, [('contrast_id', 'contrast_id')]),
+            (select_files, get_contrasts, [('contrasts', 'input_str')]),
+            (estimate_model, estimate_contrast, [
+                ('spm_mat_file', 'spm_mat_file'),
+                ('residual_image', 'residual_image'),
+                ('beta_images', 'beta_images')]),
+            (estimate_contrast, threshold, [
+                ('spm_mat_file', 'spm_mat_file'),
+                ('spmT_images', 'stat_image')]),
+            (threshold, data_sink, [
+                ('thresholded_map', f'group_level_analysis_{method}_nsub_{nb_subjects}.@thresh')]),
+            (estimate_model, data_sink, [
+                ('mask_image', f'group_level_analysis_{method}_nsub_{nb_subjects}.@mask')]),
+            (estimate_contrast, data_sink, [
+                ('spm_mat_file', f'group_level_analysis_{method}_nsub_{nb_subjects}.@spm_mat'),
+                ('spmT_images', f'group_level_analysis_{method}_nsub_{nb_subjects}.@T'),
+                ('con_images', f'group_level_analysis_{method}_nsub_{nb_subjects}.@con')])])
+
+        if method in ('equalRange', 'equalIndifference'):
+            estimate_contrast.inputs.contrasts = [
+                ('Group', 'T', ['mean'], [1]),
+                ('Group', 'T', ['mean'], [-1])
+                ]
+
+            threshold.inputs.contrast_index = [1, 2]
+
+            # Specify design matrix
+            one_sample_t_test_design = Node(OneSampleTTestDesign(),
+                name = 'one_sample_t_test_design')
+
+            group_level_analysis.connect([
+                (get_contrasts, one_sample_t_test_design, [
+                    (('out_list', clean_list), 'in_files')
+                    ]),
+                (one_sample_t_test_design, estimate_model, [('spm_mat_file', 'spm_mat_file')])
+                ])
+
+        if method == 'equalRange':
+            group_level_analysis.connect([
+                (get_equal_range_subjects, get_contrasts, [('out_list', 'elements')])
+                ])
+
+        elif method == 'equalIndifference':
+            group_level_analysis.connect([
+                (get_equal_indifference_subjects, get_contrasts, [('out_list', 'elements')])
+                ])
+
+        elif method == 'groupComp':
+            estimate_contrast.inputs.contrasts = [
+                ('Eq range vs Eq indiff in loss', 'T', ['Group_{1}', 'Group_{2}'], [1, -1])
+                ]
+
+            threshold.inputs.contrast_index = [1]
+
+            # Function Node elements_in_string
+            #   Get contrast files for required subjects
+            # Note : using a MapNode with elements_in_string requires using clean_list to remove
+            #   None values from the out_list
+            get_contrasts_2 = MapNode(Function(
+                function = elements_in_string,
+                input_names = ['input_str', 'elements'],
+                output_names = ['out_list']
+                ),
+                name = 'get_contrasts_2', iterfield = 'input_str'
+            )
+
+            # Node for the design matrix
+            two_sample_t_test_design = Node(TwoSampleTTestDesign(),
+                name = 'two_sample_t_test_design')
+
+            group_level_analysis.connect([
+                (select_files, get_contrasts_2, [('contrasts', 'input_str')]),
+                (get_equal_range_subjects, get_contrasts, [('out_list', 'elements')]),
+                (get_equal_indifference_subjects, get_contrasts_2, [('out_list', 'elements')]),
+                (get_contrasts, two_sample_t_test_design, [
+                    (('out_list', clean_list), 'group1_files')
+                    ]),
+                (get_contrasts_2, two_sample_t_test_design, [
+                    (('out_list', clean_list), 'group2_files')
+                    ]),
+                (two_sample_t_test_design, estimate_model, [('spm_mat_file', 'spm_mat_file')])
+                ])
+
+        return group_level_analysis
+
+    def get_group_level_outputs(self):
+        """ Return all names for the files the group level analysis is supposed to generate. """
+
+        # Handle equalRange and equalIndifference
+        parameters = {
+            'contrast_id': self.contrast_list,
+            'method': ['equalRange', 'equalIndifference'],
+            'file': [
+                'con_0001.nii', 'con_0002.nii', 'mask.nii', 'SPM.mat',
+                'spmT_0001.nii', 'spmT_0002.nii',
+                join('_threshold0', 'spmT_0001_thr.nii'), join('_threshold1', 'spmT_0002_thr.nii')
+                ],
+            'nb_subjects' : [str(len(self.subject_list))]
+        }
+        parameter_sets = product(*parameters.values())
+        template = join(
+            self.directories.output_dir,
+            'group_level_analysis_{method}_nsub_{nb_subjects}',
+            '_contrast_id_{contrast_id}',
+            '{file}'
+            )
+
+        return_list = [template.format(**dict(zip(parameters.keys(), parameter_values)))\
+            for parameter_values in parameter_sets]
+
+        # Handle groupComp
+        parameters = {
+            'contrast_id': self.contrast_list,
+            'method': ['groupComp'],
+            'file': [
+                'con_0001.nii', 'mask.nii', 'SPM.mat', 'spmT_0001.nii',
+                join('_threshold0', 'spmT_0001_thr.nii')
+                ],
+            'nb_subjects' : [str(len(self.subject_list))]
+        }
+        parameter_sets = product(*parameters.values())
+        template = join(
+            self.directories.output_dir,
+            'group_level_analysis_{method}_nsub_{nb_subjects}',
+            '_contrast_id_{contrast_id}',
+            '{file}'
+            )
+
+        return_list += [template.format(**dict(zip(parameters.keys(), parameter_values)))\
+            for parameter_values in parameter_sets]
+
+        return return_list
+
+    def get_hypotheses_outputs(self):
+        """ Return all hypotheses output file names. """
+        nb_sub = len(self.subject_list)
+        files = [
+            # Hypothesis 1
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0001', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0001', 'spmT_0001.nii'),
+            # Hypothesis 2
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0001', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0001', 'spmT_0001.nii'),
+            # Hypothesis 3
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0001', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0001', 'spmT_0001.nii'),
+            # Hypothesis 4
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0001', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0001', 'spmT_0001.nii'),
+            # Hypothesis 5
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0002', '_threshold0', 'spmT_0002_thr.nii'),
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0002', 'spmT_0002.nii'),
+            # Hypothesis 6
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0002', '_threshold1', 'spmT_0002_thr.nii'),
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0002', 'spmT_0002.nii'),
+            # Hypothesis 7
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0002', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
+                '_contrast_id_0002', 'spmT_0001.nii'),
+            # Hypothesis 8
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0002', '_threshold1', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
+                '_contrast_id_0002', 'spmT_0001.nii'),
+            # Hypothesis 9
+            join(f'group_level_analysis_groupComp_nsub_{nb_sub}',
+                '_contrast_id_0002', '_threshold0', 'spmT_0001_thr.nii'),
+            join(f'group_level_analysis_groupComp_nsub_{nb_sub}',
+                '_contrast_id_0002', 'spmT_0001.nii')
+        ]
+        return [join(self.directories.output_dir, f) for f in files]
diff --git a/setup.py b/setup.py
index ec22904f..b17409b6 100644
--- a/setup.py
+++ b/setup.py
@@ -19,7 +19,8 @@
     'networkx>=2.0,<3.0', # a workaround to nipype's bug (issue 3530)
     'nilearn>=0.10.0,<0.11',
     'nipype>=1.8.6,<1.9',
-    'pandas>=1.5.2,<1.6'
+    'pandas>=1.5.2,<1.6',
+    'niflow-nipype1-workflows>=0.0.5,<0.1.0'
 ]
 extras_require = {
     'tests': [
diff --git a/tests/conftest.py b/tests/conftest.py
index 2223518e..f12f77a0 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -14,6 +14,7 @@
 from numpy import isclose
 from pytest import helpers, fixture
 from pathvalidate import is_valid_filepath
+from numpy import isclose
 
 from narps_open.pipelines import Pipeline
 from narps_open.runner import PipelineRunner
diff --git a/tests/pipelines/templates/template_test.py b/tests/pipelines/templates/template_test.py
index 0c3683fd..f0c459c5 100644
--- a/tests/pipelines/templates/template_test.py
+++ b/tests/pipelines/templates/template_test.py
@@ -3,21 +3,21 @@
 
 """ This template can be use to test a pipeline.
 
-    - Replace all occurrences of XXXX by the actual id of the team.
+    - Replace all occurrences of 2T6S by the actual id of the team.
     - All lines starting with [INFO], are meant to help you during the reproduction,
     these can be removed eventually.
     - Also remove lines starting with [TODO], once you did what they suggested.
     - Remove this docstring once you are done with coding the tests.
 """
 
-""" Tests of the 'narps_open.pipelines.team_XXXX' module.
+""" Tests of the 'narps_open.pipelines.team_2T6S' module.
 
 Launch this test with PyTest
 
 Usage:
 ======
-    pytest -q test_team_XXXX.py
-    pytest -q test_team_XXXX.py -k <selected_test>
+    pytest -q test_team_2T6S.py
+    pytest -q test_team_2T6S.py -k <selected_test>
 """
 
 # [INFO] About these imports :
@@ -28,12 +28,12 @@
 # [INFO] Only for type testing
 from nipype import Workflow
 
-# [INFO] Of course, import the class you want to test, here the Pipeline class for the team XXXX
-from narps_open.pipelines.team_XXXX import PipelineTeamXXXX
+# [INFO] Of course, import the class you want to test, here the Pipeline class for the team 2T6S
+from narps_open.pipelines.team_2T6S import PipelineTeam2T6S
 
 # [INFO] All tests should be contained in the following class, in order to sort them.
-class TestPipelinesTeamXXXX:
-    """ A class that contains all the unit tests for the PipelineTeamXXXX class."""
+class TestPipelinesTeam2T6S:
+    """ A class that contains all the unit tests for the PipelineTeam2T6S class."""
 
     # [TODO] Write one or several unit_test (and mark them as such)
     # [TODO]    ideally for each method of the class you test.
@@ -42,19 +42,19 @@ class TestPipelinesTeamXXXX:
     @staticmethod
     @mark.unit_test
     def test_create():
-        """ Test the creation of a PipelineTeamXXXX object """
+        """ Test the creation of a PipelineTeam2T6S object """
 
-        pipeline = PipelineTeamXXXX()
+        pipeline = PipelineTeam2T6S()
         assert pipeline.fwhm == 8.0
-        assert pipeline.team_id == 'XXXX'
+        assert pipeline.team_id == '2T6S'
 
     # [INFO] Here is one example for the methods returning workflows
     @staticmethod
     @mark.unit_test
     def test_workflows():
-        """ Test the workflows of a PipelineTeamXXXX object """
+        """ Test the workflows of a PipelineTeam2T6S object """
 
-        pipeline = PipelineTeamXXXX()
+        pipeline = PipelineTeam2T6S()
         assert pipeline.get_preprocessing() is None
         assert pipeline.get_run_level_analysis() is None
         assert isinstance(pipeline.get_subject_level_analysis(), Workflow)
@@ -68,24 +68,16 @@ def test_workflows():
     @staticmethod
     @mark.unit_test
     def test_outputs():
-        """ Test the expected outputs of a PipelineTeamXXXX object """
-        pipeline = PipelineTeamXXXX()
+        """ Test the expected outputs of a PipelineTeam2T6S object """
+        pipeline = PipelineTeam2T6S()
 
         # 1 - 1 subject outputs
         pipeline.subject_list = ['001']
-        assert len(pipeline.get_preprocessing_outputs()) == 0
-        assert len(pipeline.get_run_level_outputs()) == 0
-        assert len(pipeline.get_subject_level_outputs()) == 7
-        assert len(pipeline.get_group_level_outputs()) == 63
-        assert len(pipeline.get_hypotheses_outputs()) == 18
+        helpers.test_pipeline_outputs(pipeline, [0, 0, 7, 63, 18])
 
         # 2 - 4 subjects outputs
         pipeline.subject_list = ['001', '002', '003', '004']
-        assert len(pipeline.get_preprocessing_outputs()) == 0
-        assert len(pipeline.get_run_level_outputs()) == 0
-        assert len(pipeline.get_subject_level_outputs()) == 28
-        assert len(pipeline.get_group_level_outputs()) == 63
-        assert len(pipeline.get_hypotheses_outputs()) == 18
+        helpers.test_pipeline_outputs(pipeline, [0, 0, 28, 63, 18])
 
     # [TODO] Feel free to add other methods, e.g. to test the custom node functions of the pipeline
 
@@ -95,8 +87,8 @@ def test_outputs():
     @staticmethod
     @mark.pipeline_test
     def test_execution():
-        """ Test the execution of a PipelineTeamXXXX and compare results """
+        """ Test the execution of a PipelineTeam2T6S and compare results """
 
         # [INFO] We use the `test_pipeline_evaluation` helper which is responsible for running the
         # [INFO]    pipeline, iterating over subjects and comparing output with expected results.
-        helpers.test_pipeline_evaluation('XXXX')
+        helpers.test_pipeline_evaluation('2T6S')
diff --git a/tests/pipelines/test_team_98BT.py b/tests/pipelines/test_team_98BT.py
new file mode 100644
index 00000000..6e2a0afb
--- /dev/null
+++ b/tests/pipelines/test_team_98BT.py
@@ -0,0 +1,153 @@
+#!/usr/bin/python
+# coding: utf-8
+
+""" Tests of the 'narps_open.pipelines.team_98BT' module.
+
+Launch this test with PyTest
+
+Usage:
+======
+    pytest -q test_team_98BT.py
+    pytest -q test_team_98BT.py -k <selected_test>
+"""
+from os.path import join, exists
+from filecmp import cmp
+
+from pytest import helpers, mark
+from nipype import Workflow
+from nipype.interfaces.base import Bunch
+
+from narps_open.utils.configuration import Configuration
+from narps_open.pipelines.team_98BT import PipelineTeam98BT
+
+TEMPORARY_DIR = join(Configuration()['directories']['test_runs'], 'test_98BT')
+
+class TestPipelinesTeam98BT:
+    """ A class that contains all the unit tests for the PipelineTeam98BT class."""
+
+    @staticmethod
+    @mark.unit_test
+    def test_create():
+        """ Test the creation of a PipelineTeam98BT object """
+
+        pipeline = PipelineTeam98BT()
+
+        # 1 - check the parameters
+        assert pipeline.fwhm == 8.0
+        assert pipeline.team_id == '98BT'
+
+        # 2 - check workflows
+        processing = pipeline.get_preprocessing()
+        assert len(processing) == 2
+        for sub_workflow in processing:
+            assert isinstance(sub_workflow, Workflow)
+
+        assert pipeline.get_run_level_analysis() is None
+        assert isinstance(pipeline.get_subject_level_analysis(), Workflow)
+
+        group_level = pipeline.get_group_level_analysis()
+        assert len(group_level) == 3
+        for sub_workflow in group_level:
+            assert isinstance(sub_workflow, Workflow)
+
+    @staticmethod
+    @mark.unit_test
+    def test_outputs():
+        """ Test the expected outputs of a PipelineTeam98BT object """
+        pipeline = PipelineTeam98BT()
+        # 1 - 1 subject outputs
+        pipeline.subject_list = ['001']
+        helpers.test_pipeline_outputs(pipeline, [1 + 1*1 + 4*1*5,0,9,84,18])
+
+        # 2 - 4 subjects outputs
+        pipeline.subject_list = ['001', '002', '003', '004']
+        helpers.test_pipeline_outputs(pipeline, [1 + 4*1 + 4*4*5,0,36,84,18])
+
+    @staticmethod
+    @mark.unit_test
+    def test_fieldmap_info():
+        """ Test the get_fieldmap_info method """
+
+        filedmap_file_1 = join(
+            Configuration()['directories']['test_data'], 'pipelines', 'phasediff_1.json')
+        filedmap_file_2 = join(
+            Configuration()['directories']['test_data'], 'pipelines', 'phasediff_2.json')
+
+        test_result = PipelineTeam98BT.get_fieldmap_info(
+            filedmap_file_1, ['magnitude_1', 'magnitude_2'])
+        assert test_result[0] == (0.00492, 0.00738)
+        assert test_result[1] == 'magnitude_1'
+        test_result = PipelineTeam98BT.get_fieldmap_info(
+            filedmap_file_2, ['magnitude_1', 'magnitude_2'])
+        assert test_result[0] == (0.00492, 0.00738)
+        assert test_result[1] == 'magnitude_2'
+
+    @staticmethod
+    @mark.unit_test
+    @mark.parametrize('remove_test_dir', TEMPORARY_DIR)
+    def test_parameters_files(remove_test_dir):
+        """ Test the get_parameters_files method
+            For this test, we created the two following files by downsampling output files
+                from the preprocessing pipeline :
+                - wc2sub-001_T1w-32.nii (white matter file)
+                - uasub-001_task-MGT_run-01_bold_resampled-32.nii (motion corrected file)
+            Voxel dimension was multiplied by 32, number of slices was reduced to 4.
+        """
+        parameters_file = join(
+            Configuration()['directories']['test_data'], 'pipelines', 'confounds.tsv')
+        func_file = join(Configuration()['directories']['test_data'], 'pipelines',
+            'team_98BT', 'uasub-001_task-MGT_run-01_bold_resampled-32.nii')
+        wc2_file = join(Configuration()['directories']['test_data'], 'pipelines',
+            'team_98BT', 'wc2sub-001_T1w-32.nii')
+        reference_file = join(
+            Configuration()['directories']['test_data'], 'pipelines',
+            'team_98BT', 'parameters_file.tsv')
+
+        # Get new parameters file
+        PipelineTeam98BT.get_parameters_file(
+            parameters_file, wc2_file, func_file, 'sid', 'rid', TEMPORARY_DIR)
+
+        # Check parameters file was created
+        created_parameters_file = join(
+            TEMPORARY_DIR, 'parameters_files', 'parameters_file_sub-sid_run-rid.tsv')
+        assert exists(created_parameters_file)
+
+        # Check contents
+        assert cmp(reference_file, created_parameters_file)
+
+    @staticmethod
+    @mark.unit_test
+    def test_subject_information():
+        """ Test the get_subject_information method """
+
+        # Get test files
+        test_file = join(Configuration()['directories']['test_data'], 'pipelines', 'events.tsv')
+
+        bunch = PipelineTeam98BT.get_subject_information(test_file, 1)
+
+        # Compare bunches to expected
+        assert isinstance(bunch, Bunch)
+        assert bunch.conditions == ['gamble_run1']
+        helpers.compare_float_2d_arrays(bunch.onsets, [
+            [4.071, 11.834, 19.535, 27.535, 36.435]])
+        helpers.compare_float_2d_arrays(bunch.durations, [
+            [4.0, 4.0, 4.0, 4.0, 4.0]])
+        assert bunch.amplitudes is None
+        assert bunch.tmod is None
+        assert bunch.regressor_names is None
+        assert bunch.regressors is None
+        pmod = bunch.pmod[0]
+        assert isinstance(pmod, Bunch)
+        assert pmod.name == ['gain_run1', 'loss_run1', 'answers_run1']
+        assert pmod.poly == [1, 1, 1]
+        helpers.compare_float_2d_arrays(pmod.param, [
+            [14.0, 34.0, 38.0, 10.0, 16.0],
+            [6.0, 14.0, 19.0, 15.0, 17.0],
+            [1, 1, 0, 0, 0]
+            ])
+
+    @staticmethod
+    @mark.pipeline_test
+    def test_execution():
+        """ Test the execution of a PipelineTeam98BT and compare results """
+        helpers.test_pipeline_evaluation('98BT')
diff --git a/tests/test_data/pipelines/phasediff_1.json b/tests/test_data/pipelines/phasediff_1.json
new file mode 100644
index 00000000..625980c6
--- /dev/null
+++ b/tests/test_data/pipelines/phasediff_1.json
@@ -0,0 +1 @@
+{"EchoTime1": 0.00492, "EchoTime2": 0.00738, "IntendedFor": ["func/sub-001_task-MGT_run-01_bold.nii.gz", "func/sub-001_task-MGT_run-02_bold.nii.gz", "func/sub-001_task-MGT_run-03_bold.nii.gz", "func/sub-001_task-MGT_run-04_bold.nii.gz"]}
\ No newline at end of file
diff --git a/tests/test_data/pipelines/phasediff_2.json b/tests/test_data/pipelines/phasediff_2.json
new file mode 100644
index 00000000..d7f3c9d0
--- /dev/null
+++ b/tests/test_data/pipelines/phasediff_2.json
@@ -0,0 +1 @@
+{"EchoTime1": 0.00738, "EchoTime2": 0.00492, "IntendedFor": ["func/sub-001_task-MGT_run-01_bold.nii.gz", "func/sub-001_task-MGT_run-02_bold.nii.gz", "func/sub-001_task-MGT_run-03_bold.nii.gz", "func/sub-001_task-MGT_run-04_bold.nii.gz"]}
\ No newline at end of file
diff --git a/tests/test_data/pipelines/team_98BT/parameters_file.tsv b/tests/test_data/pipelines/team_98BT/parameters_file.tsv
new file mode 100644
index 00000000..515041a1
--- /dev/null
+++ b/tests/test_data/pipelines/team_98BT/parameters_file.tsv
@@ -0,0 +1,4 @@
+"CSF	WhiteMatter	GlobalSignal	stdDVARS	non-stdDVARS	vx-wisestdDVARS	FramewiseDisplacement	tCompCor00	tCompCor01	tCompCor02	tCompCor03	tCompCor04	tCompCor05	aCompCor00	aCompCor01	aCompCor02	aCompCor03	aCompCor04	aCompCor05	Cosine00	Cosine01	Cosine02	Cosine03	Cosine04	Cosine05	NonSteadyStateOutlier00	X	Y	Z	RotX	RotY	RotZ"	261.948061726888
+"6551.281999999999	6476.4653	9874.576	n/a	n/a	n/a	n/a	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	1.0	0.0	0.0	0.0	0.0	-0.0	0.0"	241.43458658854166
+"6484.7285	6473.4890000000005	9830.212	1.09046686	52.78273392	1.05943739	0.13527900930999998	0.0263099209	-0.0673065879	0.0934882554	-0.0079328884	0.0338007737	-0.011491083999999999	-0.042411347099999996	0.027736422900000002	0.0453303087	-0.07022609490000001	0.0963618709	-0.0200867957	0.0665186088	0.0665174038	0.0665153954	0.0665125838	0.0665089688	0.06650455059999999	0.0	-0.00996895	-0.0313444	-3.00931e-06	0.00132687	-0.000384193	-0.00016819"	246.2539803059896
+"6441.5337	6485.7256	9821.212	1.07520139	52.04382706	1.03821933	0.12437666391	-0.0404820317	0.034150583	0.13661184210000002	0.0745358691	-0.0054829985999999995	-0.0217322686	0.046214115199999996	0.005774624	-0.043909359800000006	-0.075619539	0.17546891539999998	-0.0345256763	0.0665153954	0.06650455059999999	0.06648647719999999	0.0664611772	0.0664286533	0.0663889091	0.0	-2.56954e-05	-0.00923735	0.0549667	0.000997278	-0.00019745	-0.000398988"	246.21754170735676
diff --git a/tests/test_data/pipelines/team_98BT/uasub-001_task-MGT_run-01_bold_resampled-32.nii b/tests/test_data/pipelines/team_98BT/uasub-001_task-MGT_run-01_bold_resampled-32.nii
new file mode 100644
index 0000000000000000000000000000000000000000..2f1f3722f60928793bc332fe5e18983b8ff0701e
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diff --git a/tests/test_data/pipelines/team_98BT/wc2sub-001_T1w-32.nii b/tests/test_data/pipelines/team_98BT/wc2sub-001_T1w-32.nii
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From 72097399f439f455cac8d10c5c3e701e91921f7c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Boris=20Cl=C3=A9net?=
 <117362283+bclenet@users.noreply.github.com>
Date: Wed, 6 Mar 2024 13:47:44 +0100
Subject: [PATCH 3/3] 98BT bug with subject IDs (#183)

* [BUG] inside unit_tests workflow

* Refactoring pipeline 98BT

* [TEST] update tests [REFAC] pep8 and bug correction

* Using narps_open.data.task module inside 98BT

* [TEST] update + dependancy to niflow

* [REFAC][skip ci]

* [BUG] input of get_contrats [skip ci]

* Light bugs + remove large files [skip ci]

* [TEST] adding tests for 98BT

* [TEST] adding tests for 98BT

* [TEST] adding tests for 98BT

* Output names for 98BT

* Preprocessing output names

* Subject info issue + output names

* 98BT - Refac get_parameters_files

* [TEST] 98BT get_parameters_file

* Using fixture for temporary test dir creation / removal

* Linting pipelines test files

* Bug with regressors naming

* pylintrc for pylint config

* Subject ID completion in get_contrast
---
 narps_open/pipelines/team_98BT.py | 27 +++++++++++++++++++--------
 1 file changed, 19 insertions(+), 8 deletions(-)

diff --git a/narps_open/pipelines/team_98BT.py b/narps_open/pipelines/team_98BT.py
index 3cc0675f..2c1a1911 100755
--- a/narps_open/pipelines/team_98BT.py
+++ b/narps_open/pipelines/team_98BT.py
@@ -706,6 +706,11 @@ def get_group_level_analysis_sub_workflow(self, method):
         get_equal_indifference_subjects.inputs.list_1 = get_group('equalIndifference')
         get_equal_indifference_subjects.inputs.list_2 = self.subject_list
 
+        # Create a function to complete the subject ids out from the get_equal_*_subjects nodes
+        #   If not complete, subject id '001' in search patterns
+        #   would match all contrast files with 'con_0001.nii'.
+        complete_subject_ids = lambda l : [f'_subject_id_{a}' for a in l]
+
         # Function Node elements_in_string
         #   Get contrast files for required subjects
         # Note : using a MapNode with elements_in_string requires using clean_list to remove
@@ -778,14 +783,16 @@ def get_group_level_analysis_sub_workflow(self, method):
                 ])
 
         if method == 'equalRange':
-            group_level_analysis.connect([
-                (get_equal_range_subjects, get_contrasts, [('out_list', 'elements')])
-                ])
+            group_level_analysis.connect(
+                get_equal_range_subjects, ('out_list', complete_subject_ids),
+                get_contrasts, 'elements'
+                )
 
         elif method == 'equalIndifference':
-            group_level_analysis.connect([
-                (get_equal_indifference_subjects, get_contrasts, [('out_list', 'elements')])
-                ])
+            group_level_analysis.connect(
+                get_equal_indifference_subjects, ('out_list', complete_subject_ids),
+                get_contrasts, 'elements'
+                )
 
         elif method == 'groupComp':
             estimate_contrast.inputs.contrasts = [
@@ -812,8 +819,12 @@ def get_group_level_analysis_sub_workflow(self, method):
 
             group_level_analysis.connect([
                 (select_files, get_contrasts_2, [('contrasts', 'input_str')]),
-                (get_equal_range_subjects, get_contrasts, [('out_list', 'elements')]),
-                (get_equal_indifference_subjects, get_contrasts_2, [('out_list', 'elements')]),
+                (get_equal_range_subjects, get_contrasts, [
+                    (('out_list', complete_subject_ids), 'elements')
+                    ]),
+                (get_equal_indifference_subjects, get_contrasts_2, [
+                    (('out_list', complete_subject_ids), 'elements')
+                    ]),
                 (get_contrasts, two_sample_t_test_design, [
                     (('out_list', clean_list), 'group1_files')
                     ]),