Python testing.example_data函数代码示例

def test_reg_transform_comp_nii():

    # Create a reg_transform object
    nr = RegTransform()

    # Check if the command is properly defined
    assert nr.cmd == get_custom_path('reg_transform')

    # Assign some input data
    ref_file = example_data('im1.nii')
    trans_file = example_data('warpfield.nii')
    trans2_file = example_data('anatomical.nii')
    nr.inputs.ref1_file = ref_file
    nr.inputs.comp_input2 = trans2_file
    nr.inputs.comp_input = trans_file
    nr.inputs.omp_core_val = 4

    cmd_tmp = '{cmd} -ref {ref_file} -omp 4 -comp {trans1} {trans2} {out_file}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('reg_transform'),
        ref_file=ref_file,
        trans1=trans_file,
        trans2=trans2_file,
        out_file=os.path.join(os.getcwd(), 'warpfield_trans.nii.gz'))

    assert nr.cmdline == expected_cmd

def test_overlap():
    from nipype.algorithms.metrics import Overlap

    def check_close(val1, val2):
        import numpy.testing as npt
        return npt.assert_almost_equal(val1, val2, decimal=3)

    tempdir = mkdtemp()
    in1 = example_data('segmentation0.nii.gz')
    in2 = example_data('segmentation1.nii.gz')

    os.chdir(tempdir)
    overlap = Overlap()
    overlap.inputs.volume1 = in1
    overlap.inputs.volume2 = in1
    res = overlap.run()
    yield check_close, res.outputs.jaccard, 1.0
    overlap = Overlap()
    overlap.inputs.volume1 = in1
    overlap.inputs.volume2 = in2
    res = overlap.run()

    yield check_close, res.outputs.jaccard, 0.99705

    overlap = Overlap()
    overlap.inputs.volume1 = in1
    overlap.inputs.volume2 = in2
    overlap.inputs.vol_units = 'mm'
    res = overlap.run()

    yield check_close, res.outputs.jaccard, 0.99705
    yield (check_close, res.outputs.roi_voldiff,
           np.array([0.0063086, -0.0025506, 0.0]))

    rmtree(tempdir)

def test_reg_jacobian_jac_l():

    # Create a reg_jacobian object
    nr = RegJacobian()

    # Check if the command is properly defined
    assert nr.cmd == get_custom_path('reg_jacobian')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        nr.run()

    # Assign some input data
    ref_file = example_data('im1.nii')
    trans_file = example_data('warpfield.nii')
    nr.inputs.ref_file = ref_file
    nr.inputs.trans_file = trans_file
    nr.inputs.type = 'jacL'
    nr.inputs.omp_core_val = 4

    cmd_tmp = '{cmd} -omp 4 -ref {ref} -trans {trans} -jacL {jac}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('reg_jacobian'),
        ref=ref_file,
        trans=trans_file,
        jac=os.path.join(os.getcwd(), 'warpfield_jacL.nii.gz'))

    assert nr.cmdline == expected_cmd

def test_seg_calctopncc():
    """ Test interfaces for seg_CalctoNCC"""
    # Create a node object
    calctopncc = CalcTopNCC()

    # Check if the command is properly defined
    assert calctopncc.cmd == get_custom_path('seg_CalcTopNCC')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        calctopncc.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    file1 = example_data('im2.nii')
    file2 = example_data('im3.nii')
    calctopncc.inputs.in_file = in_file
    calctopncc.inputs.num_templates = 2
    calctopncc.inputs.in_templates = [file1, file2]
    calctopncc.inputs.top_templates = 1

    cmd_tmp = '{cmd} -target {in_file} -templates 2 {file1} {file2} -n 1'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('seg_CalcTopNCC'),
        in_file=in_file,
        file1=file1,
        file2=file2
    )

    assert calctopncc.cmdline == expected_cmd

def test_seg_patchmatch():

    # Create a node object
    seg_patchmatch = PatchMatch()

    # Check if the command is properly defined
    cmd = get_custom_path('seg_PatchMatch', env_dir='NIFTYSEGDIR')
    assert seg_patchmatch.cmd == cmd

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        seg_patchmatch.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    mask_file = example_data('im2.nii')
    db_file = example_data('db.xml')
    seg_patchmatch.inputs.in_file = in_file
    seg_patchmatch.inputs.mask_file = mask_file
    seg_patchmatch.inputs.database_file = db_file

    cmd_tmp = '{cmd} -i {in_file} -m {mask_file} -db {db} -o {out_file}'
    expected_cmd = cmd_tmp.format(
        cmd=cmd,
        in_file=in_file,
        mask_file=mask_file,
        db=db_file,
        out_file='im1_pm.nii.gz',
    )

    assert seg_patchmatch.cmdline == expected_cmd

def test_seg_filllesions():

    # Create a node object
    seg_fill = FillLesions()

    # Check if the command is properly defined
    assert seg_fill.cmd == get_custom_path('seg_FillLesions')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        seg_fill.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    lesion_mask = example_data('im2.nii')
    seg_fill.inputs.in_file = in_file
    seg_fill.inputs.lesion_mask = lesion_mask

    expected_cmd = '{cmd} -i {in_file} -l {lesion_mask} -o {out_file}'.format(
                cmd=get_custom_path('seg_FillLesions'),
                in_file=in_file,
                lesion_mask=lesion_mask,
                out_file=os.path.join(os.getcwd(), 'im1_lesions_filled.nii'))

    assert seg_fill.cmdline == expected_cmd

def test_reg_f3d():
    """ tests for reg_f3d interface"""
    # Create a reg_f3d object
    nr_f3d = RegF3D()

    # Check if the command is properly defined
    assert nr_f3d.cmd == get_custom_path('reg_f3d')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        nr_f3d.run()

    # Assign some input data
    ref_file = example_data('im1.nii')
    flo_file = example_data('im2.nii')
    rmask_file = example_data('mask.nii')
    nr_f3d.inputs.ref_file = ref_file
    nr_f3d.inputs.flo_file = flo_file
    nr_f3d.inputs.rmask_file = rmask_file
    nr_f3d.inputs.omp_core_val = 4
    nr_f3d.inputs.vel_flag = True
    nr_f3d.inputs.be_val = 0.1
    nr_f3d.inputs.le_val = 0.1

    cmd_tmp = '{cmd} -be 0.100000 -cpp {cpp} -flo {flo} -le 0.100000 -omp 4 \
-ref {ref} -res {res} -rmask {rmask} -vel'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('reg_f3d'),
        cpp=os.path.join(os.getcwd(), 'im2_cpp.nii.gz'),
        flo=flo_file,
        ref=ref_file,
        res=os.path.join(os.getcwd(), 'im2_res.nii.gz'),
        rmask=rmask_file)

    assert nr_f3d.cmdline == expected_cmd

def test_staple():

    # Create a node object
    staple = LabelFusion()

    # Check if the command is properly defined
    assert staple.cmd == get_custom_path('seg_LabFusion')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        staple.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    file_to_seg = example_data('im2.nii')
    template_file = example_data('im3.nii')
    staple.inputs.in_file = in_file
    staple.inputs.kernel_size = 2.0
    staple.inputs.file_to_seg = file_to_seg
    staple.inputs.template_file = template_file
    staple.inputs.template_num = 2
    staple.inputs.classifier_type = 'STAPLE'

    cmd_tmp = '{cmd} -in {in_file} -STAPLE -ALL -out {out_file}'
    expected_cmd = cmd_tmp.format(
                        cmd=get_custom_path('seg_LabFusion'),
                        in_file=in_file,
                        file_to_seg=file_to_seg,
                        template_file=template_file,
                        out_file=os.path.join(os.getcwd(), 'im1_staple.nii'))

    assert staple.cmdline == expected_cmd

def test_mv():

    # Create a node object
    mv = LabelFusion()

    # Check if the command is properly defined
    assert mv.cmd == get_custom_path('seg_LabFusion')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        mv.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    file_to_seg = example_data('im2.nii')
    template_file = example_data('im3.nii')
    mv.inputs.in_file = in_file
    mv.inputs.file_to_seg = file_to_seg
    mv.inputs.template_file = template_file
    mv.inputs.template_num = 2
    mv.inputs.classifier_type = 'MV'
    mv.inputs.sm_ranking = 'ROINCC'
    mv.inputs.dilation_roi = 2

    cmd_tmp = '{cmd} -in {in_file} -MV -ROINCC 2 2 {file_to_seg} \
{template_file} -out {out_file}'
    expected_cmd = cmd_tmp.format(
                        cmd=get_custom_path('seg_LabFusion'),
                        in_file=in_file,
                        file_to_seg=file_to_seg,
                        template_file=template_file,
                        out_file=os.path.join(os.getcwd(), 'im1_mv.nii'))

    assert mv.cmdline == expected_cmd

def test_reg_measure():
    """ tests for reg_measure interface """
    # Create a reg_measure object
    nr_measure = RegMeasure()

    # Check if the command is properly defined
    assert nr_measure.cmd == get_custom_path('reg_measure')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        nr_measure.run()

    # Assign some input data
    ref_file = example_data('im1.nii')
    flo_file = example_data('im2.nii')
    nr_measure.inputs.ref_file = ref_file
    nr_measure.inputs.flo_file = flo_file
    nr_measure.inputs.measure_type = 'lncc'
    nr_measure.inputs.omp_core_val = 4

    cmd_tmp = '{cmd} -flo {flo} -lncc -omp 4 -out {out} -ref {ref}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('reg_measure'),
        flo=flo_file,
        out='im2_lncc.txt',
        ref=ref_file)

    assert nr_measure.cmdline == expected_cmd

def test_dvars(tmpdir):
    ground_truth = np.loadtxt(example_data('ds003_sub-01_mc.DVARS'))
    dvars = ComputeDVARS(in_file=example_data('ds003_sub-01_mc.nii.gz'),
                         in_mask=example_data('ds003_sub-01_mc_brainmask.nii.gz'),
                         save_all=True,
                         intensity_normalization=0)
    os.chdir(str(tmpdir))
    res = dvars.run()

    dv1 = np.loadtxt(res.outputs.out_all, skiprows=1)
    assert (np.abs(dv1[:, 0] - ground_truth[:, 0]).sum()/ len(dv1)) < 0.05

    assert (np.abs(dv1[:, 1] - ground_truth[:, 1]).sum() / len(dv1)) < 0.05

    assert (np.abs(dv1[:, 2] - ground_truth[:, 2]).sum() / len(dv1)) < 0.05

    dvars = ComputeDVARS(in_file=example_data('ds003_sub-01_mc.nii.gz'),
                         in_mask=example_data(
                             'ds003_sub-01_mc_brainmask.nii.gz'),
                         save_all=True)
    res = dvars.run()

    dv1 = np.loadtxt(res.outputs.out_all, skiprows=1)
    assert (np.abs(dv1[:, 0] - ground_truth[:, 0]).sum() / len(dv1)) < 0.05

    assert (np.abs(dv1[:, 1] - ground_truth[:, 1]).sum() / len(dv1)) > 0.05

    assert (np.abs(dv1[:, 2] - ground_truth[:, 2]).sum() / len(dv1)) < 0.05

def test_merge():

    # Create a node object
    merge = Merge()

    # Check if the command is properly defined
    assert merge.cmd == get_custom_path('seg_maths')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        merge.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    file1 = example_data('im2.nii')
    file2 = example_data('im3.nii')
    merge.inputs.in_file = in_file
    merge.inputs.merge_files = [file1, file2]
    merge.inputs.dimension = 2
    merge.inputs.output_datatype = 'float'

    cmd_tmp = '{cmd} {in_file} -merge 2 2 {f1} {f2} -odt float {out_file}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('seg_maths'),
        in_file=in_file,
        f1=file1,
        f2=file2,
        out_file=os.path.join(os.getcwd(), 'im1_merged.nii'))

    assert merge.cmdline == expected_cmd

def test_tuple_maths():

    # Create a node object
    tuplem = TupleMaths()

    # Check if the command is properly defined
    assert tuplem.cmd == get_custom_path('seg_maths')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        tuplem.run()

    # Assign some input data
    in_file = example_data('im1.nii')
    op_file = example_data('im2.nii')
    tuplem.inputs.in_file = in_file
    tuplem.inputs.operation = 'lncc'
    tuplem.inputs.operand_file1 = op_file
    tuplem.inputs.operand_value2 = 2.0
    tuplem.inputs.output_datatype = 'float'

    cmd_tmp = '{cmd} {in_file} -lncc {op} 2.00000000 -odt float {out_file}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('seg_maths'),
        in_file=in_file,
        op=op_file,
        out_file=os.path.join(os.getcwd(), 'im1_lncc.nii'))

    assert tuplem.cmdline == expected_cmd

def test_reg_aladin():

    # Create a reg_aladin object
    nr = RegAladin()

    # Check if the command is properly defined
    assert nr.cmd == get_custom_path('reg_aladin')

    # test raising error with mandatory args absent
    with pytest.raises(ValueError):
        nr.run()

    # Assign some input data
    ref_file = example_data('im1.nii')
    flo_file = example_data('im2.nii')
    rmask_file = example_data('mask.nii')
    nr.inputs.ref_file = ref_file
    nr.inputs.flo_file = flo_file
    nr.inputs.rmask_file = rmask_file
    nr.inputs.omp_core_val = 4

    cmd_tmp = '{cmd} -aff {aff} -flo {flo} -omp 4 -ref {ref} -res {res} \
-rmask {rmask}'
    expected_cmd = cmd_tmp.format(
        cmd=get_custom_path('reg_aladin'),
        aff=os.path.join(os.getcwd(), 'im2_aff.txt'),
        flo=flo_file,
        ref=ref_file,
        res=os.path.join(os.getcwd(), 'im2_res.nii.gz'),
        rmask=rmask_file)

    assert nr.cmdline == expected_cmd

def test_normalize_tpms(tmpdir):
    tempdir = str(tmpdir)

    in_mask = example_data('tpms_msk.nii.gz')
    mskdata = nb.load(in_mask, mmap=NUMPY_MMAP).get_data()
    mskdata[mskdata > 0.0] = 1.0

    mapdata = []
    in_files = []
    out_files = []

    for i in range(3):
        mapname = example_data('tpm_%02d.nii.gz' % i)
        filename = os.path.join(tempdir, 'modtpm_%02d.nii.gz' % i)
        out_files.append(os.path.join(tempdir, 'normtpm_%02d.nii.gz' % i))

        im = nb.load(mapname, mmap=NUMPY_MMAP)
        data = im.get_data()
        mapdata.append(data.copy())

        nb.Nifti1Image(2.0 * (data * mskdata), im.affine,
                       im.header).to_filename(filename)
        in_files.append(filename)

    normalize_tpms(in_files, in_mask, out_files=out_files)

    sumdata = np.zeros_like(mskdata)

    for i, tstfname in enumerate(out_files):
        normdata = nb.load(tstfname, mmap=NUMPY_MMAP).get_data()
        sumdata += normdata
        assert np.all(normdata[mskdata == 0] == 0)
        assert np.allclose(normdata, mapdata[i])

    assert np.allclose(sumdata[sumdata > 0.0], 1.0)