<filename>venv/Lib/site-packages/nipype/algorithms/tests/test_auto_SpecifySparseModel.py
# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
from ..modelgen import SpecifySparseModel


def test_SpecifySparseModel_inputs():
    input_map = dict(
        bids_amplitude_column=dict(),
        bids_condition_column=dict(
            usedefault=True,
        ),
        bids_event_file=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        event_files=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        functional_runs=dict(
            copyfile=False,
            mandatory=True,
        ),
        high_pass_filter_cutoff=dict(
            mandatory=True,
        ),
        input_units=dict(
            mandatory=True,
        ),
        model_hrf=dict(),
        outlier_files=dict(
            copyfile=False,
        ),
        parameter_source=dict(
            usedefault=True,
        ),
        realignment_parameters=dict(
            copyfile=False,
        ),
        save_plot=dict(),
        scale_regressors=dict(
            usedefault=True,
        ),
        scan_onset=dict(
            usedefault=True,
        ),
        stimuli_as_impulses=dict(
            usedefault=True,
        ),
        subject_info=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        time_acquisition=dict(
            mandatory=True,
        ),
        time_repetition=dict(
            mandatory=True,
        ),
        use_temporal_deriv=dict(
            requires=["model_hrf"],
        ),
        volumes_in_cluster=dict(
            usedefault=True,
        ),
    )
    inputs = SpecifySparseModel.input_spec()

    for key, metadata in list(input_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(inputs.traits()[key], metakey) == value


def test_SpecifySparseModel_outputs():
    output_map = dict(
        session_info=dict(),
        sparse_png_file=dict(
            extensions=None,
        ),
        sparse_svg_file=dict(
            extensions=None,
        ),
    )
    outputs = SpecifySparseModel.output_spec()

    for key, metadata in list(output_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(outputs.traits()[key], metakey) == value

<filename>venv/Lib/site-packages/nipype/algorithms/tests/test_auto_SpecifySparseModel.py
# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
from ..modelgen import SpecifySparseModel


def test_SpecifySparseModel_inputs():
    input_map = dict(
        bids_amplitude_column=dict(),
        bids_condition_column=dict(
            usedefault=True,
        ),
        bids_event_file=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        event_files=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        functional_runs=dict(
            copyfile=False,
            mandatory=True,
        ),
        high_pass_filter_cutoff=dict(
            mandatory=True,
        ),
        input_units=dict(
            mandatory=True,
        ),
        model_hrf=dict(),
        outlier_files=dict(
            copyfile=False,
        ),
        parameter_source=dict(
            usedefault=True,
        ),
        realignment_parameters=dict(
            copyfile=False,
        ),
        save_plot=dict(),
        scale_regressors=dict(
            usedefault=True,
        ),
        scan_onset=dict(
            usedefault=True,
        ),
        stimuli_as_impulses=dict(
            usedefault=True,
        ),
        subject_info=dict(
            mandatory=True,
            xor=["subject_info", "event_files", "bids_event_file"],
        ),
        time_acquisition=dict(
            mandatory=True,
        ),
        time_repetition=dict(
            mandatory=True,
        ),
        use_temporal_deriv=dict(
            requires=["model_hrf"],
        ),
        volumes_in_cluster=dict(
            usedefault=True,
        ),
    )
    inputs = SpecifySparseModel.input_spec()

    for key, metadata in list(input_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(inputs.traits()[key], metakey) == value


def test_SpecifySparseModel_outputs():
    output_map = dict(
        session_info=dict(),
        sparse_png_file=dict(
            extensions=None,
        ),
        sparse_svg_file=dict(
            extensions=None,
        ),
    )
    outputs = SpecifySparseModel.output_spec()

    for key, metadata in list(output_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(outputs.traits()[key], metakey) == value

# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT