def test_rsa_temp(self):
"""Test RSA with a temporal searchlight."""
data = np.array([[1, 2, 3, 4], [2, 3, 4, 5], [3, 4, 5, 6]])
model_dsm = np.array([1, 2, 1])
# One model DSM, no parallelization
patches = searchlight(data.shape, temporal_radius=1)
rsa_result = rsa_array(data, model_dsm, patches,
data_dsm_metric='euclidean')
assert rsa_result.shape == (2,)
assert_equal(rsa_result, 1)
# Multiple model DSMs, no parallelization
patches = searchlight(data.shape, temporal_radius=1)
rsa_result = rsa_array(data, [model_dsm, model_dsm], patches,
data_dsm_metric='euclidean')
assert rsa_result.shape == (2, 2)
assert_equal(rsa_result, 1)
# One model DSM, parallelization across 2 CPUs
patches = searchlight(data.shape, temporal_radius=1)
rsa_result = rsa_array(data, model_dsm, patches,
data_dsm_metric='euclidean', n_jobs=2)
assert rsa_result.shape == (2,)
assert_equal(rsa_result, 1)
# Multiple model DSMs, parallelization across 2 CPUs
patches = searchlight(data.shape, temporal_radius=1)
rsa_result = rsa_array(data, [model_dsm, model_dsm], patches,
data_dsm_metric='euclidean', n_jobs=2)
assert rsa_result.shape == (2, 2)
assert_equal(rsa_result, 1)
def test_rsa_spat(self):
"""Test RSA with a spatial searchlight."""
data = np.array([[[1], [2], [3]], [[2], [3], [4]], [[3], [4], [5]]])
model_dsm = np.array([1, 2, 1])
dist = np.array([[0, 1, 2],
[1, 0, 1],
[2, 1, 0]])
# One model DSM, no paralellization
patches = searchlight(data.shape, dist, spatial_radius=1)
rsa_result = rsa_array(data, model_dsm, patches,
data_dsm_metric='euclidean')
assert rsa_result.shape == (3,)
assert_equal(rsa_result, 1)
# Multiple model DSMs, no paralellization
patches = searchlight(data.shape, dist, spatial_radius=1)
rsa_result = rsa_array(data, [model_dsm, model_dsm], patches,
data_dsm_metric='euclidean')
assert rsa_result.shape == (3, 2)
assert_equal(rsa_result, 1)
# One model DSM, paralellization across 2 CPUs
patches = searchlight(data.shape, dist, spatial_radius=1)
rsa_result = rsa_array(data, model_dsm, patches,
data_dsm_metric='euclidean', n_jobs=2)
assert rsa_result.shape == (3,)
assert_equal(rsa_result, 1)
# Multiple model DSMs, paralellization across 2 CPUs
patches = searchlight(data.shape, dist, spatial_radius=1)
rsa_result = rsa_array(data, [model_dsm, model_dsm], patches,
data_dsm_metric='euclidean', n_jobs=2)
assert rsa_result.shape == (3, 2)
assert_equal(rsa_result, 1)
def test_iter_spatial(self):
"""Test generating spatial searchlight patches."""
dist = np.array([[0, 1, 2], [1, 0, 1], [2, 1, 0]])
s = searchlight((5, 10, 3, 4), dist, spatial_radius=2)
assert len(s) == 3
assert s.shape == (3, )
assert_equal(list(s), [
(slice(None), slice(None), np.array([0, 1]), slice(None)),
(slice(None), slice(None), np.array([0, 1, 2]), slice(None)),
(slice(None), slice(None), np.array([1, 2]), slice(None)),
])
s = searchlight((10, 3, 4), dist, spatial_radius=2)
assert len(s) == 3
assert s.shape == (3, )
assert_equal(list(s), [
(slice(None), np.array([0, 1]), slice(None)),
(slice(None), np.array([0, 1, 2]), slice(None)),
(slice(None), np.array([1, 2]), slice(None)),
])
s = searchlight((10, 3), dist, spatial_radius=2)
assert len(s) == 3
assert s.shape == (3, )
assert_equal(list(s), [
(slice(None), np.array([0, 1])),
(slice(None), np.array([0, 1, 2])),
(slice(None), np.array([1, 2])),
])
def test_iter_temporal(self):
"""Test generating temporal searchlight patches."""
s = searchlight((10, 3, 4), temporal_radius=1)
assert len(s) == 2
assert s.shape == (2, )
assert_equal(list(s), [
(slice(None), slice(None), slice(0, 3)),
(slice(None), slice(None), slice(1, 4)),
])
s = searchlight((10, 4), temporal_radius=1)
assert len(s) == 2
assert s.shape == (2, )
assert_equal(list(s), [
(slice(None), slice(0, 3)),
(slice(None), slice(1, 4)),
])
def test_temporal(self):
"""Test computing DSMs using a temporal searchlight."""
data = np.array([[1, 2, 3, 4], [1, 2, 3, 4]])
patches = searchlight(data.shape, temporal_radius=1)
dsms = dsm_array(data, patches, dist_metric='euclidean')
assert len(dsms) == len(patches)
assert dsms.shape == (2, 1)
assert_equal(list(dsms), [0, 0])
def test_spatial(self):
"""Test computing DSMs using a spatial searchlight."""
dist = np.array([[0, 1, 2, 3], [1, 0, 1, 2], [2, 1, 0, 1],
[3, 2, 1, 0]])
data = np.array([[1, 2, 3, 4], [1, 2, 3, 4]])
patches = searchlight(data.shape, dist, spatial_radius=1)
dsms = dsm_array(data, patches, dist_metric='euclidean')
assert len(dsms) == len(patches)
assert dsms.shape == (4, 1)
assert_equal(list(dsms), [0, 0, 0, 0])
def test_iter_single(self):
"""Test generating a single searchlight patch."""
s = searchlight((5, 10, 3, 4))
assert len(s) == 1
assert s.shape == tuple()
assert_equal(next(s), tuple([slice(None)] * 4))
s = searchlight((10, 3, 4))
assert len(s) == 1
assert s.shape == tuple()
assert_equal(next(s), tuple([slice(None)] * 3))
s = searchlight((10, 3))
assert len(s) == 1
assert s.shape == tuple()
assert_equal(next(s), tuple([slice(None)] * 2))
s = searchlight((10, ))
assert len(s) == 1
assert s.shape == tuple()
assert_equal(next(s), (slice(None), ))
def test_spatio_temporal(self):
"""Test computing DSMs using a spatio-temporal searchlight."""
data = np.array([[[1, 2, 3], [2, 3, 4]], [[2, 3, 4], [3, 4, 5]],
[[3, 4, 5], [4, 5, 6]]])
dist = np.array([[0, 1, 2], [1, 0, 1], [2, 1, 0]])
patches = searchlight(data.shape,
dist,
spatial_radius=1,
temporal_radius=1)
dsms = dsm_array(data, patches, dist_metric='correlation')
assert len(dsms) == len(patches)
assert dsms.shape == (2, 1, 3)
assert_allclose(list(dsms), [[0, 0, 0], [0, 0, 0]], atol=1E-15)
def test_crossvalidation(self):
"""Test computing DSMs using a searchlight and cross-validation."""
data = np.array([[[1, 2, 3], [2, 3, 4]], [[2, 3, 4], [3, 4, 5]],
[[3, 4, 5], [4, 5, 6]], [[1, 2, 3], [2, 3, 4]],
[[2, 3, 4], [3, 4, 5]], [[3, 4, 5], [4, 5, 6]]])
dist = np.array([[0, 1, 2], [1, 0, 1], [2, 1, 0]])
patches = searchlight(data.shape,
dist,
spatial_radius=1,
temporal_radius=1)
dsms = dsm_array(data, patches, y=[1, 2, 3, 1, 2, 3], n_folds=2)
assert len(dsms) == len(patches)
assert dsms.shape == (2, 1, 3)
assert_allclose(list(dsms), [[0, 0, 0], [0, 0, 0]], atol=1E-15)
def test_invalid_input(self):
"""Test giving invalid input to searchlight generator."""
dist = np.array([[0, 1, 2], [1, 0, 1], [2, 1, 0]])
# Spatio-temporal case
with pytest.raises(ValueError, match='no spatial dimension'):
searchlight((10, ), dist=dist, spatial_radius=1, temporal_radius=1)
with pytest.raises(ValueError, match='no temporal dimension'):
searchlight((10, 3),
dist=dist,
spatial_radius=1,
temporal_radius=1)
with pytest.raises(ValueError, match='no distance information'):
searchlight((10, 3, 4), spatial_radius=1, temporal_radius=1)
# Spatial case
with pytest.raises(ValueError, match='no spatial dimension'):
searchlight((10, ), dist=dist, spatial_radius=1)
with pytest.raises(ValueError, match='no distance information'):
searchlight((10, 5), spatial_radius=1)
# Temporal case
with pytest.raises(ValueError, match='no temporal dimension'):
searchlight((10, ), dist=dist, temporal_radius=1)
