Ejemplos de define_analysis en Python

Ejemplo n.º 1

Archivo: test_flywheel_analyzer.py Proyecto: scitran/python-client

def test_label_matcher_find_op():
    with pytest.raises(AssertionError) as e:
        fa.define_analysis('afq',
                           lambda **kwargs: {},
                           label_matcher=lambda val: val.startswith('afq '))
    assert 'does not detect this operation' in str(e)

    fa.define_analysis('afq',
                       lambda **kwargs: {},
                       label_matcher=lambda val: val.startswith('afq'))

Ejemplo n.º 2

Archivo: flywheel_analyzer_engage.py Proyecto: scitran/python-client

def define_analysis(gear_name, acquisition_label, create_inputs):
    '''Light wrapper around define_analysis that lets us pass in an acquisition_label
    in to create_inputs.
    '''
    return fa.define_analysis(
        gear_name,
        lambda **kwargs: create_inputs(acquisition_label, **kwargs),
        label=analysis_label(gear_name, acquisition_label))

Ejemplo n.º 3

Archivo: flywheel_analyzer_dti_meta.py Proyecto: scitran/python-client

def dtiinit_inputs(acquisitions, **kwargs):
    diffusion = fa.find(acquisitions, label='Diffusion')

    return dict(
        bvec=diffusion.find_file('*1000.bvec'),
        bval=diffusion.find_file('*1000.bval'),
        dwi=diffusion.find_file('*1000.nii.gz'),
    ), dict(
        # Here you can add any configuration. So for instance to add robust tensor, do:
        # fitMethod='rt'
    )


def afq_inputs(analyses, **kwargs):
    dtiinit = fa.find(analyses, label=dtiinit_label)

    return dict(dtiInit_Archive=dtiinit.find_file('dtiInit_*.zip'), )


if __name__ == '__main__':
    with fa.installed_client(client):
        ops = [
            fa.define_analysis('dtiinit', dtiinit_inputs, label=dtiinit_label),
            fa.define_analysis('afq', afq_inputs, label=afq_label),
        ]
        fa.run(ops,
               project=fa.find_project(label='HCP_preproc'),
               session_limit=1)

Ejemplo n.º 4

from scitran_client import ScitranClient
import scitran_client.flywheel_analyzer as fa

client = ScitranClient('https://flywheel.scitran.stanford.edu')

with fa.installed_client(client):
    D99 = fa.find(client.request(
        'sessions/588bd1ac449f9800159305c2/acquisitions').json(),
                  label='atlas')


def anatomical_warp_inputs(acquisitions, **kwargs):
    anatomical = fa.find(acquisitions, label='anatomical_mdeft')
    return dict(
        native=anatomical.find_file('*.nii.gz'),
        standard=D99.find_file('D99_template.nii.gz'),
        warp_target=D99.find_file('D99_atlas_1.2a.nii.gz'),
    )


if __name__ == '__main__':
    with fa.installed_client(client):
        fa.run([
            fa.define_analysis('afni-brain-warp',
                               anatomical_warp_inputs,
                               label='anatomical warp'),
        ],
               project=fa.find_project(label='showdes'),
               max_workers=2)

Ejemplo n.º 5

Archivo: flywheel_analyzer_afq.py Proyecto: scitran/python-client

dtiinit_matcher = prefix_matcher('dtiinit')
afq_matcher = prefix_matcher('afq')


def dtiinit_inputs(acquisitions, **kwargs):
    diffusion = fa.find(acquisitions, label='DTI 2mm b1250 84dir(axial)')

    return dict(
        bvec=diffusion.find_file('*.bvec'),
        bval=diffusion.find_file('*.bval'),
        nifti=diffusion.find_file('*.nii.gz'),
    )


def afq_inputs(analyses, **kwargs):
    dtiinit = fa.find(analyses, label=dtiinit_matcher)

    return dict(dtiInit_Archive=dtiinit.find_file('dtiInit_*.zip'), )


if __name__ == '__main__':
    with fa.installed_client(client):
        fa.run([
            fa.define_analysis(
                'dtiinit', dtiinit_inputs, label_matcher=dtiinit_matcher),
            fa.define_analysis('afq', afq_inputs, label_matcher=afq_matcher),
        ],
               project=fa.find_project(label='ENGAGE'))