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The function truncated_svd() should not return negative singular values. #1059

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Merged
merged 1 commit into from
Apr 2, 2019
Merged

The function truncated_svd() should not return negative singular values. #1059

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12 changes: 9 additions & 3 deletions learning.py
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Original file line number Diff line number Diff line change
Expand Up @@ -460,9 +460,15 @@ def remove_component(X):

projected_X = matrix_multiplication(A, [[x] for x in X])
projected_X = [x[0] for x in projected_X]
eivals.append(norm(projected_X, 1)/norm(X, 1))
eivec_m.append(X[:m])
eivec_n.append(X[m:])
new_eigenvalue = norm(projected_X, 1)/norm(X, 1)
ev_m = X[:m]
ev_n = X[m:]
if new_eigenvalue < 0:
new_eigenvalue = -new_eigenvalue
ev_m = [-ev_m_i for ev_m_i in ev_m]
eivals.append(new_eigenvalue)
eivec_m.append(ev_m)
eivec_n.append(ev_n)
return (eivec_m, eivec_n, eivals)

# ______________________________________________________________________________
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16 changes: 8 additions & 8 deletions tests/test_learning.py
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Expand Up @@ -143,28 +143,28 @@ def test_truncated_svd():
test_mat = [[17, 0],
[0, 11]]
_, _, eival = truncated_svd(test_mat)
assert isclose(abs(eival[0]), 17)
assert isclose(abs(eival[1]), 11)
assert isclose(eival[0], 17)
assert isclose(eival[1], 11)

test_mat = [[17, 0],
[0, -34]]
_, _, eival = truncated_svd(test_mat)
assert isclose(abs(eival[0]), 34)
assert isclose(abs(eival[1]), 17)
assert isclose(eival[0], 34)
assert isclose(eival[1], 17)

test_mat = [[1, 0, 0, 0, 2],
[0, 0, 3, 0, 0],
[0, 0, 0, 0, 0],
[0, 2, 0, 0, 0]]
_, _, eival = truncated_svd(test_mat)
assert isclose(abs(eival[0]), 3)
assert isclose(abs(eival[1]), 5**0.5)
assert isclose(eival[0], 3)
assert isclose(eival[1], 5**0.5)

test_mat = [[3, 2, 2],
[2, 3, -2]]
_, _, eival = truncated_svd(test_mat)
assert isclose(abs(eival[0]), 5)
assert isclose(abs(eival[1]), 3)
assert isclose(eival[0], 5)
assert isclose(eival[1], 3)


def test_decision_tree_learner():
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