4. reports: Data acquisition report generation

4.1. Initializing reports

The bids.reports.BIDSReport class requires a bids.BIDSLayout object as an argument:

>>> from os.path import join
>>> from bids import BIDSLayout
>>> from bids.reports import BIDSReport
>>> from bids.tests import get_test_data_path
>>> layout = BIDSLayout(join(get_test_data_path(), 'synthetic'))
>>> report = BIDSReport(layout)

4.2. Generating reports

Pybids reports are then generated with the generate method, which returns a collections.Counter of reports:

>>> counter = report.generate()
>>> main_report = counter.most_common()[0][0]
>>> print(main_report)
r"""
For session 01:
    MR data were acquired using a UNKNOWN-Tesla MANUFACTURER MODEL MRI scanner.
    Ten runs of N-Back UNKNOWN-echo fMRI data were collected (64 slices; repetition time, TR=2500ms;
echo time, TE=UNKNOWNms; flip angle, FA=UNKNOWN<deg>; field of view, FOV=128x128mm;
matrix size=64x64; voxel size=2x2x2mm). Each run was 2:40 minutes in length, during
which 64 functional volumes were acquired.
    Five runs of Rest UNKNOWN-echo fMRI data were collected (64 slices; repetition time, TR=2500ms;
echo time, TE=UNKNOWNms; flip angle, FA=UNKNOWN<deg>; field of view, FOV=128x128mm;
matrix size=64x64; voxel size=2x2x2mm). Each run was 2:40 minutes in length, during
which 64 functional volumes were acquired.

For session 02:
    MR data were acquired using a UNKNOWN-Tesla MANUFACTURER MODEL MRI scanner.
    Ten runs of N-Back UNKNOWN-echo fMRI data were collected (64 slices; repetition time, TR=2500ms;
echo time, TE=UNKNOWNms; flip angle, FA=UNKNOWN<deg>; field of view, FOV=128x128mm;
matrix size=64x64; voxel size=2x2x2mm). Each run was 2:40 minutes in length, during
which 64 functional volumes were acquired.
    Five runs of Rest UNKNOWN-echo fMRI data were collected (64 slices; repetition time, TR=2500ms;
echo time, TE=UNKNOWNms; flip angle, FA=UNKNOWN<deg>; field of view, FOV=128x128mm;
matrix size=64x64; voxel size=2x2x2mm). Each run was 2:40 minutes in length, during
which 64 functional volumes were acquired.

Dicoms were converted to NIfTI-1 format. This section was (in part) generated
automatically using pybids (0.5)."""

4.2.1. Generating reports on subsets of the data

The generate method allows for keyword restrictions, just like bids.BIDSLayout’s get method. For example, to generate a report only for nback task data in session 01:

>>> counter = report.generate(session='01', task='nback')
>>> main_report = counter.most_common()[0][0]
>>> print(main_report)
r"""
For session 01:
  MR data were acquired using a UNKNOWN-Tesla MANUFACTURER MODEL MRI scanner.
  Ten runs of N-Back fMRI data were collected (64 slices; repetition time,
TR=2500ms; echo time, TE=UNKNOWNms; flip angle, FA=UNKNOWN<deg>; field of
view, FOV=128x128mm; matrix size=64x64; voxel size=2x2x2mm). Each run was
2:40 minutes in length, during which 64 functional volumes were acquired.

Dicoms were converted to NIfTI-1 format. This section was (in part)
generated automatically using pybids (0.5)."""

Note

For a more detailed set of examples, please refer to the Tutorial: Writing methods reports with pybids.reports.