def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
view = get_view(brain)
brain.add_label("BA1")
check_view(brain, view)
brain.add_label("BA1", color="blue", scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, subject_id,
"label", "%s.MT.label" % hemi)
brain.add_label(label_file)
brain.add_label("BA44", borders=True)
brain.add_label("BA6", alpha=.7)
brain.show_view("medial")
brain.add_label("V1", color="steelblue", alpha=.6)
brain.add_label("V2", color="#FF6347", alpha=.6)
brain.add_label("entorhinal", color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
brain.show_view(dict(elevation=40, distance=430), distance=430)
with pytest.raises(ValueError, match='!='):
brain.show_view(dict(elevation=40, distance=430), distance=431)
# remove labels
brain.remove_labels('V1')
assert 'V2' in brain.labels_dict
assert 'V1' not in brain.labels_dict
brain.remove_labels()
assert 'V2' not in brain.labels_dict
brain.close()
def __init__(self,
subject_id,
hemi,
surf,
subjects_dir=None,
offset=None,
units='mm'):
from surfer.utils import _check_units, _get_subjects_dir
hemis = ('lh', 'rh')
if hemi not in hemis:
raise ValueError('hemi should be either "lh" or "rh",' +
'given value {0}'.format(hemi))
if offset is not None and ((not isinstance(offset, float)) and
(not isinstance(offset, int))):
raise ValueError('offset should either float or int, given ' +
'type {0}'.format(type(offset).__name__))
self.subject_id = subject_id
self.hemi = hemi
self.surf = surf
self.offset = offset
self.units = _check_units(units)
self.bin_curv = None
self.coords = None
self.curv = None
self.faces = None
self.grey_curv = None
self.nn = None
self.labels = dict()
subjects_dir = _get_subjects_dir(subjects_dir)
self.data_path = path.join(subjects_dir, subject_id)
def test_surface():
"""Test IO for Surface class"""
subj_dir = utils._get_subjects_dir()
for subjects_dir in [None, subj_dir]:
surface = utils.Surface('fsaverage', 'lh', 'inflated',
subjects_dir=subjects_dir)
surface.load_geometry()
surface.load_label('BA1')
surface.load_curvature()
xfm = np.eye(4)
xfm[:3, -1] += 2 # translation
x = surface.x
surface.apply_xfm(xfm)
x_ = surface.x
assert_array_almost_equal(x + 2, x_)
# normals
nn = _slow_compute_normals(surface.coords, surface.faces[:10000])
nn_fast = utils._compute_normals(surface.coords, surface.faces[:10000])
assert_array_almost_equal(nn, nn_fast)
assert 50 < np.linalg.norm(surface.coords, axis=-1).mean() < 100 # mm
surface = utils.Surface('fsaverage', 'lh', 'inflated',
subjects_dir=subj_dir, units='m')
surface.load_geometry()
assert 0.05 < np.linalg.norm(surface.coords, axis=-1).mean() < 0.1 # m
def test_surface():
"""Test IO for Surface class"""
subj_dir = utils._get_subjects_dir()
for subjects_dir in [None, subj_dir]:
surface = utils.Surface('fsaverage',
'lh',
'inflated',
subjects_dir=subjects_dir)
surface.load_geometry()
surface.load_label('BA1')
surface.load_curvature()
xfm = np.eye(4)
xfm[:3, -1] += 2 # translation
x = surface.x
surface.apply_xfm(xfm)
x_ = surface.x
assert_array_almost_equal(x + 2, x_)
# normals
nn = _slow_compute_normals(surface.coords, surface.faces[:10000])
nn_fast = utils._compute_normals(surface.coords, surface.faces[:10000])
assert_array_almost_equal(nn, nn_fast)
assert 50 < np.linalg.norm(surface.coords, axis=-1).mean() < 100 # mm
surface = utils.Surface('fsaverage',
'lh',
'inflated',
subjects_dir=subj_dir,
units='m')
surface.load_geometry()
assert 0.05 < np.linalg.norm(surface.coords, axis=-1).mean() < 0.1 # m
def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
brain.add_label("BA1")
brain.add_label("BA1", color="blue", scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, subject_id, "label", "%s.MT.label" % hemi)
brain.add_label(label_file)
brain.add_label("BA44", borders=True)
brain.add_label("BA6", alpha=.7)
brain.show_view("medial")
brain.add_label("V1", color="steelblue", alpha=.6)
brain.add_label("V2", color="#FF6347", alpha=.6)
brain.add_label("entorhinal", color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
# remove labels
brain.remove_labels('V1')
assert_in('V2', brain.labels_dict)
assert_not_in('V1', brain.labels_dict)
brain.remove_labels()
assert_not_in('V2', brain.labels_dict)
brain.close()
def test_foci():
"""Test plotting of foci."""
_set_backend('test')
brain = Brain(*std_args)
coords = [[-36, 18, -3], [-43, 25, 24], [-48, 26, -2]]
brain.add_foci(coords,
map_surface="white",
color="gold",
name='test1',
resolution=25)
subj_dir = utils._get_subjects_dir()
annot_path = pjoin(subj_dir, subject_id, 'label', 'lh.aparc.a2009s.annot')
ids, ctab, names = nib.freesurfer.read_annot(annot_path)
verts = np.arange(0, len(ids))
coords = np.random.permutation(verts[ids == 74])[:10]
scale_factor = 0.7
brain.add_foci(coords,
coords_as_verts=True,
scale_factor=scale_factor,
color="#A52A2A",
name='test2')
with pytest.raises(ValueError):
brain.remove_foci(['test4'])
brain.remove_foci('test1')
brain.remove_foci()
assert len(brain.foci_dict) == 0
brain.close()
def test_label():
"""Test plotting of label."""
_set_backend()
subject_id = "fsaverage"
hemi = "lh"
surf = "inflated"
brain = Brain(subject_id, hemi, surf)
brain.add_label("BA1")
brain.add_label("BA1", color="blue", scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, subject_id,
"label", "%s.MT.label" % hemi)
brain.add_label(label_file)
brain.add_label("BA44", borders=True)
brain.add_label("BA6", alpha=.7)
brain.show_view("medial")
brain.add_label("V1", color="steelblue", alpha=.6)
brain.add_label("V2", color="#FF6347", alpha=.6)
brain.add_label("entorhinal", color=(.2, 1, .5), alpha=.6)
brain.set_surf('white')
# remove labels
brain.remove_labels('V1')
assert_in('V2', brain.labels_dict)
assert_not_in('V1', brain.labels_dict)
brain.remove_labels()
assert_not_in('V2', brain.labels_dict)
brain.close()
def test_annot():
"""Test plotting of annot."""
_set_backend()
annots = ['aparc', 'aparc.a2005s']
borders = [True, False, 2]
alphas = [1, 0.5]
brain = Brain(*std_args)
view = get_view(brain)
for a, b, p in zip(annots, borders, alphas):
brain.add_annotation(a, b, p, opacity=0.8)
check_view(brain, view)
brain.set_surf('white')
with pytest.raises(ValueError):
brain.add_annotation('aparc', borders=-1)
subj_dir = utils._get_subjects_dir()
annot_path = pjoin(subj_dir, subject_id, 'label', 'lh.aparc.a2009s.annot')
labels, ctab, names = nib.freesurfer.read_annot(annot_path)
brain.add_annotation((labels, ctab))
brain.add_annotation('aparc', color="red", remove_existing=True)
surf = brain.annot["surface"]
ctab = surf.module_manager.scalar_lut_manager.lut.table
for color in ctab:
assert color[:3] == (255, 0, 0)
brain.close()
def test_annot():
"""Test plotting of annot."""
_set_backend()
annots = ['aparc', 'aparc.a2005s']
borders = [True, False, 2]
alphas = [1, 0.5]
brain = Brain(*std_args)
for a, b, p in zip(annots, borders, alphas):
brain.add_annotation(a, b, p)
brain.set_surf('white')
assert_raises(ValueError, brain.add_annotation, 'aparc', borders=-1)
subj_dir = utils._get_subjects_dir()
annot_path = pjoin(subj_dir, subject_id, 'label', 'lh.aparc.a2009s.annot')
labels, ctab, names = nib.freesurfer.read_annot(annot_path)
brain.add_annotation((labels, ctab))
brain.close()
def test_foci():
"""Test plotting of foci."""
_set_backend('test')
brain = Brain(*std_args)
coords = [[-36, 18, -3],
[-43, 25, 24],
[-48, 26, -2]]
brain.add_foci(coords, map_surface="white", color="gold")
subj_dir = utils._get_subjects_dir()
annot_path = pjoin(subj_dir, subject_id, 'label', 'lh.aparc.a2009s.annot')
ids, ctab, names = nib.freesurfer.read_annot(annot_path)
verts = np.arange(0, len(ids))
coords = np.random.permutation(verts[ids == 74])[:10]
scale_factor = 0.7
brain.add_foci(coords, coords_as_verts=True,
scale_factor=scale_factor, color="#A52A2A")
brain.close()
def test_annot():
"""Test plotting of annot."""
_set_backend()
annots = ['aparc', 'aparc.a2005s']
borders = [True, False, 2]
alphas = [1, 0.5]
brain = Brain(*std_args)
for a, b, p in zip(annots, borders, alphas):
brain.add_annotation(a, b, p)
brain.set_surf('white')
assert_raises(ValueError, brain.add_annotation, 'aparc', borders=-1)
subj_dir = utils._get_subjects_dir()
annot_path = pjoin(subj_dir, subject_id, 'label', 'lh.aparc.a2009s.annot')
labels, ctab, names = nib.freesurfer.read_annot(annot_path)
brain.add_annotation((labels, ctab))
brain.close()
def test_brains():
"""Test plotting of Brain with different arguments."""
# testing backend breaks when passing in a figure, so we use 'auto' here
# (shouldn't affect usability, but it makes testing more annoying)
_set_backend('auto')
with warnings.catch_warnings(record=True): # traits for mlab.figure()
mlab.figure(101)
surfs = ['inflated', 'white', 'white', 'white', 'white', 'white', 'white']
hemis = ['lh', 'rh', 'both', 'both', 'rh', 'both', 'both']
titles = [None, 'Hello', 'Good bye!', 'lut test',
'dict test', 'None test', 'RGB test']
cortices = ["low_contrast", ("Reds", 0, 1, False), 'hotpink',
['yellow', 'blue'], dict(colormap='Greys'),
None, (0.5, 0.5, 0.5)]
sizes = [500, (400, 300), (300, 300), (300, 400), 500, 400, 300]
backgrounds = ["white", "blue", "black", "0.75",
(0.2, 0.2, 0.2), "black", "0.75"]
foregrounds = ["black", "white", "0.75", "red",
(0.2, 0.2, 0.2), "blue", "black"]
with warnings.catch_warnings(record=True): # traits for mlab.figure()
figs = [101, mlab.figure(), None, None, mlab.figure(), None, None]
subj_dir = utils._get_subjects_dir()
subj_dirs = [None, subj_dir, subj_dir, subj_dir,
subj_dir, subj_dir, subj_dir]
alphas = [1.0, 0.5, 0.25, 0.7, 0.5, 0.25, 0.7]
for surf, hemi, title, cort, s, bg, fg, fig, sd, alpha \
in zip(surfs, hemis, titles, cortices, sizes,
backgrounds, foregrounds, figs, subj_dirs, alphas):
brain = Brain(subject_id, hemi, surf, title=title, cortex=cort,
alpha=alpha, size=s, background=bg, foreground=fg,
figure=fig, subjects_dir=sd)
with np.errstate(invalid='ignore'): # encountered in double_scalars
brain.set_distance()
brain.close()
brain = Brain(subject_id, hemi, surf, subjects_dir=sd,
interaction='terrain')
brain.close()
pytest.raises(ValueError, Brain, subject_id, 'lh', 'inflated',
subjects_dir='')
pytest.raises(ValueError, Brain, subject_id, 'lh', 'inflated',
interaction='foo', subjects_dir=sd)
def test_brains():
"""Test plotting of Brain with different arguments."""
# testing backend breaks when passing in a figure, so we use 'auto' here
# (shouldn't affect usability, but it makes testing more annoying)
_set_backend('auto')
with warnings.catch_warnings(record=True): # traits for mlab.figure()
mlab.figure(101)
surfs = ['inflated', 'white', 'white', 'white', 'white', 'white', 'white']
hemis = ['lh', 'rh', 'both', 'both', 'rh', 'both', 'both']
titles = [None, 'Hello', 'Good bye!', 'lut test',
'dict test', 'None test', 'RGB test']
cortices = ["low_contrast", ("Reds", 0, 1, False), 'hotpink',
['yellow', 'blue'], dict(colormap='Greys'),
None, (0.5, 0.5, 0.5)]
sizes = [500, (400, 300), (300, 300), (300, 400), 500, 400, 300]
backgrounds = ["white", "blue", "black", "0.75",
(0.2, 0.2, 0.2), "black", "0.75"]
foregrounds = ["black", "white", "0.75", "red",
(0.2, 0.2, 0.2), "blue", "black"]
with warnings.catch_warnings(record=True): # traits for mlab.figure()
figs = [101, mlab.figure(), None, None, mlab.figure(), None, None]
subj_dir = utils._get_subjects_dir()
subj_dirs = [None, subj_dir, subj_dir, subj_dir,
subj_dir, subj_dir, subj_dir]
alphas = [1.0, 0.5, 0.25, 0.7, 0.5, 0.25, 0.7]
for surf, hemi, title, cort, s, bg, fg, fig, sd, alpha \
in zip(surfs, hemis, titles, cortices, sizes,
backgrounds, foregrounds, figs, subj_dirs, alphas):
brain = Brain(subject_id, hemi, surf, title=title, cortex=cort,
alpha=alpha, size=s, background=bg, foreground=fg,
figure=fig, subjects_dir=sd)
with np.errstate(invalid='ignore'): # encountered in double_scalars
brain.set_distance()
brain.close()
brain = Brain(subject_id, hemi, surf, subjects_dir=sd,
interaction='terrain')
brain.close()
pytest.raises(ValueError, Brain, subject_id, 'lh', 'inflated',
subjects_dir='')
pytest.raises(ValueError, Brain, subject_id, 'lh', 'inflated',
interaction='foo', subjects_dir=sd)
def test_probabilistic_labels():
"""Test plotting of probabilistic labels."""
_set_backend()
brain = Brain("fsaverage", "lh", "inflated", cortex="low_contrast")
brain.add_label("BA1", color="darkblue")
brain.add_label("BA1", color="dodgerblue", scalar_thresh=.5)
brain.add_label("BA45", color="firebrick", borders=True)
brain.add_label("BA45", color="salmon", borders=True, scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, "fsaverage", "label", "lh.BA6.label")
prob_field = np.zeros_like(brain.geo['lh'].x)
ids, probs = nib.freesurfer.read_label(label_file, read_scalars=True)
prob_field[ids] = probs
brain.add_data(prob_field, thresh=1e-5)
with warnings.catch_warnings(record=True):
brain.data["colorbar"].number_of_colors = 10
brain.data["colorbar"].number_of_labels = 11
brain.close()
def test_probabilistic_labels():
"""Test plotting of probabilistic labels."""
_set_backend()
brain = Brain("fsaverage", "lh", "inflated",
cortex="low_contrast")
brain.add_label("BA1", color="darkblue")
brain.add_label("BA1", color="dodgerblue", scalar_thresh=.5)
brain.add_label("BA45", color="firebrick", borders=True)
brain.add_label("BA45", color="salmon", borders=True, scalar_thresh=.5)
subj_dir = utils._get_subjects_dir()
label_file = pjoin(subj_dir, "fsaverage", "label", "lh.BA6.label")
prob_field = np.zeros_like(brain.geo['lh'].x)
ids, probs = nib.freesurfer.read_label(label_file, read_scalars=True)
prob_field[ids] = probs
brain.add_data(prob_field, thresh=1e-5)
with warnings.catch_warnings(record=True):
brain.data["colorbar"].number_of_colors = 10
brain.data["colorbar"].number_of_labels = 11
brain.close()
import numpy as np
import os
import os.path as op
from os.path import join as pjoin
from numpy.testing import assert_raises, assert_array_equal
from tempfile import mktemp
import nibabel as nib
from surfer import Brain, io, utils
from surfer.utils import requires_fsaverage
from mayavi import mlab
subj_dir = utils._get_subjects_dir()
subject_id = 'fsaverage'
std_args = [subject_id, 'lh', 'inflated']
data_dir = pjoin(op.dirname(__file__), '..', '..', 'examples', 'example_data')
small_brain = dict(size=100)
overlay_fname = pjoin(data_dir, 'lh.sig.nii.gz')
def has_freesurfer():
if 'FREESURFER_HOME' not in os.environ:
return False
else:
return True
requires_fs = np.testing.dec.skipif(not has_freesurfer(),
'Requires FreeSurfer command line tools')
from os.path import join as pjoin
import numpy as np
import nose.tools as nt
from numpy.testing import assert_array_almost_equal, assert_array_equal
from surfer import utils
subj_dir = utils._get_subjects_dir()
subject_id = 'fsaverage'
data_path = pjoin(subj_dir, subject_id)
def _slow_compute_normals(rr, tris):
"""Efficiently compute vertex normals for triangulated surface"""
# first, compute triangle normals
r1 = rr[tris[:, 0], :]
r2 = rr[tris[:, 1], :]
r3 = rr[tris[:, 2], :]
tri_nn = np.cross((r2 - r1), (r3 - r1))
# Triangle normals and areas
size = np.sqrt(np.sum(tri_nn * tri_nn, axis=1))
zidx = np.where(size == 0)[0]
size[zidx] = 1.0 # prevent ugly divide-by-zero
tri_nn /= size[:, np.newaxis]
# accumulate the normals
nn = np.zeros((len(rr), 3))
for p, verts in enumerate(tris):
nn[verts] += tri_nn[p, :]
