def test_factor_too_big():
"Factor is between 0 and 1."
Blend([t1, t2], factor=1.5)
def test_bare_blend():
'''
A matrix blended with nothing else changes nothing.
'''
b = Blend([t1], weights=[1])
assertSetEquals(set(t1.label_list(0)), set(b.label_list(0)))
def test_specifying_factor():
'''
When a factor is supplied, use it as the weight of the second matrix.
'''
eq_(Blend([t1, t2], factor=.25).weights, (0.75, 0.25))
def predicted_by_overlap(factors, mat1, mat2, row_overlap, col_overlap):
blend = Blend(overlap_matrices(mat1, mat2, row_overlap, col_overlap),
factor=0)
return [
blend.predicted_svals_at_factor(factor, num=15) for factor in factors
]
def veering_by_overlap(mat1, mat2, row_overlap, col_overlap):
t1, t2 = overlap_matrices(mat1, mat2, row_overlap, col_overlap)
blend = Blend([t1, t2], factor=0)
return [
blend.total_veering_at_factor(factor, num=15) for factor in factors
]
def svals_by_overlap(factors, mat1, mat2, row_overlap, col_overlap):
blend = Blend(overlap_matrices(mat1, mat2, row_overlap, col_overlap),
factor=0)
return [blend.svals_at_factor(factor, k=15) for factor in factors]
def _get_color_blend():
colors = get_picklecached_thing(FILEPATH+os.sep+'colormatrix.pickle.gz', _make_color_matrix)
cnet = get_picklecached_thing(FILEPATH+os.sep+'cnet.pickle.gz', lambda: conceptnet_2d_from_db('en'))
colorblend = Blend([colors, cnet]).normalized(mode=[0,1]).bake()
return colorblend
def make_blend(other):
return Blend([cnet, other])
def test_blend_mean_subtracted():
from csc.divisi.blend import Blend
Blend([tensor.mean_subtracted()])
from csc.conceptnet4.analogyspace import conceptnet_by_relations, identities_for_all_relations
from csc.divisi.blend import Blend
from csc.divisi import export_svdview
byrel = conceptnet_by_relations('en')
t = identities_for_all_relations(byrel)
b = Blend(byrel.values() + [t])
s = b.svd()
export_svdview.write_packed(s.u, 'littleblend', lambda x: x)
s.summarize()
