def test_niml_dset_voxsel(self, fn):
if not externals.exists('nibabel'):
return
# This is actually a bit of an integration test.
# It tests storing and retrieving searchlight results.
# Imports are inline here so that it does not mess up the header
# and makes the other unit tests more modular
# XXX put this in a separate file?
from mvpa2.misc.surfing import volgeom, surf_voxel_selection, queryengine
from mvpa2.measures.searchlight import Searchlight
from mvpa2.support.nibabel import surf
from mvpa2.measures.base import Measure
from mvpa2.datasets.mri import fmri_dataset
class _Voxel_Count_Measure(Measure):
# used to check voxel selection results
is_trained = True
def __init__(self, dtype, **kwargs):
Measure.__init__(self, **kwargs)
self.dtype = dtype
def _call(self, dset):
return self.dtype(dset.nfeatures)
sh = (20, 20, 20)
vg = volgeom.VolGeom(sh, np.identity(4))
density = 20
outer = surf.generate_sphere(density) * 10. + 5
inner = surf.generate_sphere(density) * 5. + 5
intermediate = outer * .5 + inner * .5
xyz = intermediate.vertices
radius = 50
sel = surf_voxel_selection.run_voxel_selection(radius, vg, inner, outer)
qe = queryengine.SurfaceVerticesQueryEngine(sel)
for dtype in (int, float):
sl = Searchlight(_Voxel_Count_Measure(dtype), queryengine=qe)
ds = fmri_dataset(vg.get_empty_nifti_image(1))
r = sl(ds)
niml.write(fn, r)
rr = niml.read(fn)
os.remove(fn)
assert_array_equal(r.samples, rr.samples)
def test_niml_dset_voxsel(self, fn):
if not externals.exists('nibabel'):
return
# This is actually a bit of an integration test.
# It tests storing and retrieving searchlight results.
# Imports are inline here so that it does not mess up the header
# and makes the other unit tests more modular
# XXX put this in a separate file?
from mvpa2.misc.surfing import volgeom, surf_voxel_selection, queryengine
from mvpa2.measures.searchlight import Searchlight
from mvpa2.support.nibabel import surf
from mvpa2.measures.base import Measure
from mvpa2.datasets.mri import fmri_dataset
class _Voxel_Count_Measure(Measure):
# used to check voxel selection results
is_trained = True
def __init__(self, dtype, **kwargs):
Measure.__init__(self, **kwargs)
self.dtype = dtype
def _call(self, dset):
return self.dtype(dset.nfeatures)
sh = (20, 20, 20)
vg = volgeom.VolGeom(sh, np.identity(4))
density = 20
outer = surf.generate_sphere(density) * 10. + 5
inner = surf.generate_sphere(density) * 5. + 5
intermediate = outer * .5 + inner * .5
xyz = intermediate.vertices
radius = 50
sel = surf_voxel_selection.run_voxel_selection(radius, vg, inner,
outer)
qe = queryengine.SurfaceVerticesQueryEngine(sel)
for dtype in (int, float):
sl = Searchlight(_Voxel_Count_Measure(dtype), queryengine=qe)
ds = fmri_dataset(vg.get_empty_nifti_image(1))
r = sl(ds)
niml.write(fn, r)
rr = niml.read(fn)
os.remove(fn)
assert_array_equal(r.samples, rr.samples)
def test_afni_niml_dset_with_2d_strings(self, fn):
# test for 2D arrays with strings. These are possibly SUMA-incompatible
# but should still be handled properly for i/o.
# Addresses https://github.com/PyMVPA/PyMVPA/issues/163 (#163)
samples = np.asarray([[1, 2, 3], [4, 5, 6]])
labels = np.asarray(map(list, ['abcd', 'efgh']))
idxs = np.asarray([np.arange(10, 14), np.arange(20, 24)])
ds = Dataset(samples, sa=dict(labels=labels, idxs=idxs))
for fmt in ('binary', 'text', 'base64'):
niml.write(fn, ds, fmt)
ds_ = niml.read(fn)
assert_array_equal(ds.samples, ds_.samples)
for sa_key in ds.sa.keys():
v = ds.sa[sa_key].value
v_ = ds_.sa[sa_key].value
assert_array_equal(v, v_)
def test_afni_niml_dset_with_2d_strings(self, fn):
# test for 2D arrays with strings. These are possibly SUMA-incompatible
# but should still be handled properly for i/o.
# Addresses https://github.com/PyMVPA/PyMVPA/issues/163 (#163)
samples = np.asarray([[1, 2, 3], [4, 5, 6]])
labels = np.asarray(map(list, ['abcd', 'efgh']))
idxs = np.asarray([np.arange(10, 14), np.arange(20, 24)])
ds = Dataset(samples, sa=dict(labels=labels, idxs=idxs))
for fmt in ('binary', 'text', 'base64'):
niml.write(fn, ds, fmt)
ds_ = niml.read(fn)
assert_array_equal(ds.samples, ds_.samples)
for sa_key in ds.sa.keys():
v = ds.sa[sa_key].value
v_ = ds_.sa[sa_key].value
assert_array_equal(v, v_)
