a68785867796cea6990ca7180a2fae269ce6f4ed,dipy/viz/tests/test_apps.py,,test_horizon_events,#,19

Before Change



@npt.dec.skipif(skip_it or not has_fury)
def test_horizon_events():
    affine = np.diag([2., 1, 1, 1]).astype("f8")
    data = 255 * np.random.rand(150, 150, 150)
    images = [(data, affine)]
    // images = None
    from dipy.segment.tests.test_bundles import setup_module

After Change


@npt.dec.skipif(skip_it or not has_fury)
def test_horizon_events():
    // using here MNI template affine
    affine = np.array([[1., 0., 0., -98.],
                       [0., 1., 0., -134.],
                       [0., 0., 1., -72.],
                       [0., 0., 0., 1.]])

    data = 255 * np.random.rand(197, 233, 189)
    vox_size = (1., 1., 1.)

    images = [(data, affine)]
    // images = None
    from dipy.segment.tests.test_bundles import setup_module
    setup_module()
    from dipy.segment.tests.test_bundles import f1
    streamlines = f1.copy()
    streamlines._data += np.array([-98., -134., -72.])

    header = create_nifti_header(affine, data.shape, vox_size)
    sft = StatefulTractogram(streamlines, header, Space.RASMM)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 5

Instances


Project Name: nipy/dipy
Commit Name: a68785867796cea6990ca7180a2fae269ce6f4ed
Time: 2019-11-27
Author: garyfallidis@gmail.com
File Name: dipy/viz/tests/test_apps.py
Class Name:
Method Name: test_horizon_events


Project Name: nipy/dipy
Commit Name: edd701dee2234b6f69d3b994cabf978672e95841
Time: 2019-11-27
Author: garyfallidis@gmail.com
File Name: dipy/viz/tests/test_apps.py
Class Name:
Method Name: test_horizon


Project Name: nipy/dipy
Commit Name: a68785867796cea6990ca7180a2fae269ce6f4ed
Time: 2019-11-27
Author: garyfallidis@gmail.com
File Name: dipy/viz/tests/test_apps.py
Class Name:
Method Name: test_horizon_events


Project Name: rasbt/mlxtend
Commit Name: f4a5be4f4a404c30c9acaac2c2e691021d4715b0
Time: 2015-12-10
Author: mail@sebastianraschka.com
File Name: mlxtend/classifier/perceptron.py
Class Name: Perceptron
Method Name: fit