From cd8c6b00d390b61aaa7d6fd7a391c128cf132e42 Mon Sep 17 00:00:00 2001
From: Olivier Grisel <olivier.grisel@ensta.org>
Date: Mon, 29 Nov 2010 04:37:58 +0100
Subject: [PATCH] one more test for SVD
---
scikits/learn/utils/tests/test_svd.py | 36 +++++++++++++++++++++++++--
1 file changed, 34 insertions(+), 2 deletions(-)
diff --git a/scikits/learn/utils/tests/test_svd.py b/scikits/learn/utils/tests/test_svd.py
index b1f96d9561..6c162a534d 100644
--- a/scikits/learn/utils/tests/test_svd.py
+++ b/scikits/learn/utils/tests/test_svd.py
@@ -12,7 +12,7 @@ from scikits.learn.utils.extmath import fast_svd
from scikits.learn.datasets.samples_generator import low_rank_fat_tail
-def test_fast_svd():
+def test_fast_svd_low_rank():
"""Check that extmath.fast_svd is consistent with linalg.svd"""
n_samples = 100
n_features = 500
@@ -50,7 +50,7 @@ def test_fast_svd():
assert_almost_equal(s[:rank], sa[:rank])
-def test_fast_svd_with_noise():
+def test_fast_svd_low_rank_with_noise():
"""Check that extmath.fast_svd can handle noisy matrices"""
n_samples = 100
n_features = 500
@@ -81,3 +81,35 @@ def test_fast_svd_with_noise():
assert_almost_equal(s[:rank], sap[:rank], decimal=5)
+def test_fast_svd_infinite_rank():
+ """Check that extmath.fast_svd can handle noisy matrices"""
+ n_samples = 100
+ n_features = 500
+ rank = 5
+ k = 10
+
+ # let us try again without 'low_rank component': just regularly but slowly
+ # decreasing singular values: the rank of the data matrix is infinite
+ X = low_rank_fat_tail(n_samples, n_features, effective_rank=rank,
+ tail_strength=1.0, seed=0)
+ assert_equal(X.shape, (n_samples, n_features))
+
+ # compute the singular values of X using the slow exact method
+ _, s, _ = linalg.svd(X, full_matrices=False)
+
+ # compute the singular values of X using the fast approximate method without
+ # the iterated power method
+ _, sa, _ = fast_svd(X, k, q=0)
+
+ # the approximation does not tolerate the noise:
+ assert np.abs(s[:rank] - sa[:rank]).max() > 0.1
+
+ # compute the singular values of X using the fast approximate method with
+ # iterated power method
+ _, sap, _ = fast_svd(X, k, q=7)
+
+ # the iterated power method is still managing to get most of the structure
+ # at the requested rank
+ assert_almost_equal(s[:rank], sap[:rank], decimal=5)
+
+
--
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