本文整理汇总了Python中mvpa.datasets.base.Dataset.fa['lit']方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.fa['lit']方法的具体用法？Python Dataset.fa['lit']怎么用？Python Dataset.fa['lit']使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mvpa.datasets.base.Dataset的用法示例。
在下文中一共展示了Dataset.fa['lit']方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_query_engine
# 需要导入模块: from mvpa.datasets.base import Dataset [as 别名]
# 或者: from mvpa.datasets.base.Dataset import fa['lit'] [as 别名]
def test_query_engine():
data = np.arange(54)
# indices in 3D
ind = np.transpose((np.ones((3, 3, 3)).nonzero()))
# sphere generator for 3 elements diameter
sphere = ne.Sphere(1)
# dataset with just one "space"
ds = Dataset([data, data], fa={'s_ind': np.concatenate((ind, ind))})
# and the query engine attaching the generator to the "index-space"
qe = ne.IndexQueryEngine(s_ind=sphere)
# cannot train since the engine does not know about the second space
assert_raises(ValueError, qe.train, ds)
# now do it again with a full spec
ds = Dataset([data, data], fa={'s_ind': np.concatenate((ind, ind)),
't_ind': np.repeat([0,1], 27)})
qe = ne.IndexQueryEngine(s_ind=sphere, t_ind=None)
qe.train(ds)
# internal representation check
# YOH: invalid for new implementation with lookup tables (dictionaries)
#assert_array_equal(qe._searcharray,
# np.arange(54).reshape(qe._searcharray.shape) + 1)
# should give us one corner, collapsing the 't_ind'
assert_array_equal(qe(s_ind=(0, 0, 0)),
[0, 1, 3, 9, 27, 28, 30, 36])
# directly specifying an index for 't_ind' without having an ROI
# generator, should give the same corner, but just once
assert_array_equal(qe(s_ind=(0, 0, 0), t_ind=0), [0, 1, 3, 9])
# just out of the mask -- no match
assert_array_equal(qe(s_ind=(3, 3, 3)), [])
# also out of the mask -- but single match
assert_array_equal(qe(s_ind=(2, 2, 3), t_ind=1), [53])
# query by id
assert_array_equal(qe(s_ind=(0, 0, 0), t_ind=0), qe[0])
assert_array_equal(qe(s_ind=(0, 0, 0), t_ind=[0, 1]),
qe(s_ind=(0, 0, 0)))
# should not fail if t_ind is outside
assert_array_equal(qe(s_ind=(0, 0, 0), t_ind=[0, 1, 10]),
qe(s_ind=(0, 0, 0)))
# should fail if asked about some unknown thing
assert_raises(ValueError, qe.__call__, s_ind=(0, 0, 0), buga=0)
# Test by using some literal feature atttribute
ds.fa['lit'] = ['roi1', 'ro2', 'r3']*18
# should work as well as before
assert_array_equal(qe(s_ind=(0, 0, 0)), [0, 1, 3, 9, 27, 28, 30, 36])
# should fail if asked about some unknown (yet) thing
assert_raises(ValueError, qe.__call__, s_ind=(0,0,0), lit='roi1')
# Create qe which can query literals as well
qe_lit = ne.IndexQueryEngine(s_ind=sphere, t_ind=None, lit=None)
qe_lit.train(ds)
# should work as well as before
assert_array_equal(qe_lit(s_ind=(0, 0, 0)), [0, 1, 3, 9, 27, 28, 30, 36])
# and subselect nicely -- only /3 ones
assert_array_equal(qe_lit(s_ind=(0, 0, 0), lit='roi1'),
[0, 3, 9, 27, 30, 36])
assert_array_equal(qe_lit(s_ind=(0, 0, 0), lit=['roi1', 'ro2']),
[0, 1, 3, 9, 27, 28, 30, 36])