Gentoo Archives: gentoo-commits

From: "Sebastien Fabbro (bicatali)" <bicatali@g.o>
To: gentoo-commits@l.g.o
Subject: [gentoo-commits] gentoo-x86 commit in sci-libs/scikits_learn/files: 0.12.1-linalg.patch
Date: Fri, 30 Nov 2012 00:25:53
Message-Id: 20121130002542.2652920C65@flycatcher.gentoo.org
1 bicatali 12/11/30 00:25:42
2
3 Added: 0.12.1-linalg.patch
4 Log:
5 Version bump
6
7 (Portage version: 2.2.01.21313-prefix/cvs/Linux x86_64, signed Manifest commit with key 0x13CB1360)
8
9 Revision Changes Path
10 1.1 sci-libs/scikits_learn/files/0.12.1-linalg.patch
11
12 file : http://sources.gentoo.org/viewvc.cgi/gentoo-x86/sci-libs/scikits_learn/files/0.12.1-linalg.patch?rev=1.1&view=markup
13 plain: http://sources.gentoo.org/viewvc.cgi/gentoo-x86/sci-libs/scikits_learn/files/0.12.1-linalg.patch?rev=1.1&content-type=text/plain
14
15 Index: 0.12.1-linalg.patch
16 ===================================================================
17 --- a/sklearn/linear_model/least_angle.py
18 +++ b/sklearn/linear_model/least_angle.py
19 @@ -236,8 +236,8 @@ def lars_path(X, y, Xy=None, Gram=None,
20 L_.flat[::n_active + 1] += (2 ** i) * eps
21 least_squares, info = solve_cholesky(L_,
22 sign_active[:n_active], lower=True)
23 - AA = 1. / np.sqrt(np.sum(least_squares
24 - * sign_active[:n_active]))
25 + tmp = max(np.sum(least_squares * sign_active[:n_active]), eps)
26 + AA = 1. / np.sqrt(tmp)
27 i += 1
28 least_squares *= AA
29
30 --- a/sklearn/linear_model/tests/test_least_angle.py
31 +++ b/sklearn/linear_model/tests/test_least_angle.py
32 @@ -101,6 +101,13 @@ def test_collinearity():
33 assert_true(not np.isnan(coef_path_).any())
34 residual = np.dot(X, coef_path_[:, -1]) - y
35 assert_less((residual ** 2).sum(), 1.) # just make sure it's bounded
36 +
37 + n_samples = 10
38 + X = np.random.rand(n_samples, 5)
39 + y = np.zeros(n_samples)
40 + _, _, coef_path_ = linear_model.lars_path(X, y, Gram='auto', copy_X=False,
41 + copy_Gram=False, alpha_min=0., method='lasso', verbose=0, max_iter=500)
42 + assert_array_almost_equal(coef_path_, np.zeros_like(coef_path_))
43
44
45 def test_no_path():