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authorDavid Cournapeau <cournape@gmail.com>2009-03-02 14:18:15 +0000
committerDavid Cournapeau <cournape@gmail.com>2009-03-02 14:18:15 +0000
commit465afd2bd933a69e0bca229284199425acfee1dd (patch)
treeff540008d2ed8a0c4015d30fea61af68accb4930 /numpy
parente9d13fa6167846f89aeef0d3744166ca976a8a26 (diff)
downloadnumpy-465afd2bd933a69e0bca229284199425acfee1dd.tar.gz
Abstract away dtype for norm test.
Diffstat (limited to 'numpy')
-rw-r--r--numpy/linalg/tests/test_linalg.py22
1 files changed, 14 insertions, 8 deletions
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py
index 2d6d29ffa..f6d21fd85 100644
--- a/numpy/linalg/tests/test_linalg.py
+++ b/numpy/linalg/tests/test_linalg.py
@@ -1,6 +1,7 @@
""" Test functions for linalg module
"""
+import numpy as np
from numpy.testing import *
from numpy import array, single, double, csingle, cdouble, dot, identity
from numpy import multiply, atleast_2d, inf, asarray, matrix
@@ -257,17 +258,19 @@ class TestEigh(HermitianTestCase, TestCase):
evalues, evectors = linalg.eig(a)
assert_almost_equal(ev, evalues)
-class TestNorm(TestCase):
+class _TestNorm(TestCase):
+ dt = None
def test_empty(self):
assert_equal(norm([]), 0.0)
- assert_equal(norm(array([], dtype = double)), 0.0)
- assert_equal(norm(atleast_2d(array([], dtype = double))), 0.0)
+ assert_equal(norm(array([], dtype=self.dt)), 0.0)
+ assert_equal(norm(atleast_2d(array([], dtype=self.dt))), 0.0)
def test_vector(self):
a = [1.0,2.0,3.0,4.0]
b = [-1.0,-2.0,-3.0,-4.0]
c = [-1.0, 2.0,-3.0, 4.0]
- for v in (a,array(a),b,array(b),c,array(c)):
+ for v in (a,array(a, dtype=self.dt),b,array(b, dtype=self.dt),c,array(c,
+ dtype=self.dt)):
assert_almost_equal(norm(v), 30**0.5)
assert_almost_equal(norm(v,inf), 4.0)
assert_almost_equal(norm(v,-inf), 1.0)
@@ -283,19 +286,22 @@ class TestNorm(TestCase):
self.assertRaises(ValueError, norm, array([1., 2., 3.]), 'fro')
def test_matrix(self):
- A = matrix([[1.,3.],[5.,7.]], dtype=single)
- A = matrix([[1.,3.],[5.,7.]], dtype=single)
+ A = matrix([[1.,3.],[5.,7.]], dtype=self.dt)
+ A = matrix([[1.,3.],[5.,7.]], dtype=self.dt)
assert_almost_equal(norm(A), 84**0.5)
assert_almost_equal(norm(A,'fro'), 84**0.5)
assert_almost_equal(norm(A,inf), 12.0)
assert_almost_equal(norm(A,-inf), 4.0)
assert_almost_equal(norm(A,1), 10.0)
assert_almost_equal(norm(A,-1), 6.0)
- assert_almost_equal(norm(A,2), 9.12310563)
- assert_almost_equal(norm(A,-2), 0.87689437)
+ assert_almost_equal(norm(A,2), 9.1231056256176615)
+ assert_almost_equal(norm(A,-2), 0.87689437438234041)
self.assertRaises(ValueError, norm, A, 'nofro')
self.assertRaises(ValueError, norm, A, -3)
+class TestNormDouble(_TestNorm):
+ dt = np.double
+
if __name__ == "__main__":
run_module_suite()