5.1. Code-less Configuration#
One of the most important features of junifer is its capacity to run without
writing a single line of code. This is achieved by using a configuration file
that is written in YAML. In this file, we configure the different steps of
The junifer Pipeline.
As a reminder, this is how the pipeline looks like:
Thus, the configuration file must configure each of the sections of the pipeline, as well as some general parameters.
As an example, we will generate the configuration file for a pipeline that will
extract the mean VBM_GM values using two different parcellations and one set
of coordinates, from the Oasis VBM Testing dataset included in junifer.
5.1.1. General Parameters#
The general parameters are the ones that are not specific to any of the sections
of the pipeline, but configure junifer as a whole. These parameters are:
with: A section used to specify modules andjuniferextensions to use.workdir: The working directory wherejuniferwill store temporary files.
Since the example uses a specific DataGrabber for testing, we need to add
junifer.testing.registry to the with section. This will allow junifer
to find the DataGrabber. We will set the workdir to /tmp.
with: junifer.testing.registry
workdir: /tmp
5.1.2. Step-by-step Configuration#
In order to configure the pipeline, we need to configure each step:
datagrabberdatareaderpreprocessmarkersstorage
Important
The datareader step configuration is optional, as junifer only
provides one DataReader. Nevertheless, it is possible to extend junifer
with custom DataReaders, and thus, it is also possible to configure this step.
Data Grabber#
The datagrabber section must be configured using the kind key to specify
the DataGrabber to use. Additional keys correspond to the parameters of the
DataGrabber constructor.
For example, to use the DataladAOMICPIOP1 DataGrabber, we just need to
specify its name as the kind key.
datagrabber:
kind: DataladAOMICPIOP1
However, it is also possible to pass parameters to the DataGrabber constructor.
In this case, we can restrict the DataGrabber to fetch only the restingstate
task.
datagrabber:
kind: DataladAOMICPIOP1
tasks: restingstate
In the Oasis VBM Testing dataset example, the section will look like this:
datagrabber:
kind: OasisVBMTestingDataGrabber
Data Reader#
As mentioned before, this section is entirely optional, as junifer only
provides one DataReader (DefaultDataReader), which is the default in
case the section is not specified.
In any case, the syntax of the section is the same as for the datagrabber
section, using the kind key to specify the DataReader to use, and additional
keys to pass parameters to the DataReader constructor:
datareader:
kind: DefaultDataReader
For the Oasis VBM Testing dataset example, we will not specify a
datareader step.
Preprocess#
preprocess is also an optional step, as it might be the case that no
pre-processing is needed. As we can perform multiple preprocessing steps, it’s
passed as a list of Preprocessors. In the case that pre-processing is needed,
each Preprocessord must be configured using the kind key to specify the
Preprocessor to use, and additional keys to pass parameters to the Preprocessor.
For example, to use the fMRIPrepConfoundRemover Preprocessor, we just
need to specify its name as the kind key, as well as its parameters.
preprocess:
- kind: fMRIPrepConfoundRemover
strategy:
motion: full
wm_csf: full
global_signal: basic
spike: 0.2
detrend: false
standardize: true
For the Oasis VBM Testing dataset example, we will not specify a
preprocessing step.
Marker#
The markers section like the preprocess section expects a list of
markers. Each Marker has a name that we can use to refer to it later,
and a set of parameters that will be passed to the Marker.
For the Oasis VBM Testing dataset example, we want to compute the mean
VBM_GM value for each parcel using the Schaefer parcellation (100 parcels,
7 networks), Schaefer parcellation (200 parcels, 7 networks), and the
DMNBuckner network, using 5mm spheres. Thus, we will configure the
markers section as follows:
markers:
- name: Schaefer100x7_mean
kind: ParcelAggregation
parcellation: Schaefer100x7
method: mean
- name: Schaefer200x7_mean
kind: ParcelAggregation
parcellation: Schaefer200x7
method: mean
- name: DMNBuckner_5mm_mean
kind: SphereAggregation
coords: DMNBuckner
radius: 5
method: mean
Storage#
Finally, we need to define how and where the results will be stored. This is
done using the storage section, which must be configured using the kind
key to specify the storage to use, and additional keys to pass parameters.
For example, to use the HDF5FeatureStorage storage, we just need to
specify where we want to store the results:
storage:
kind: HDF5FeatureStorage
uri: /data/junifer/example/oasis_vbm_testing.hdf5
5.1.3. Complete Example#
This is how the full Oasis VBM Testing dataset example configuration file
looks like:
with: junifer.testing.registry
workdir: /tmp
datagrabber:
kind: OasisVBMTestingDataGrabber
markers:
- name: Schaefer100x7_mean
kind: ParcelAggregation
parcellation: Schaefer100x7
method: mean
- name: Schaefer200x7_mean
kind: ParcelAggregation
parcellation: Schaefer200x7
method: mean
- name: DMNBuckner_5mm_mean
kind: SphereAggregation
coords: DMNBuckner
radius: 5
method: mean
storage:
kind: HDF5FeatureStorage
uri: /data/junifer/example/oasis_vbm_testing.hdf5