summaryrefslogtreecommitdiff
path: root/numpy/matrixlib/tests/test_regression.py
diff options
context:
space:
mode:
authorCharles Harris <charlesr.harris@gmail.com>2015-07-25 16:35:01 -0600
committerCharles Harris <charlesr.harris@gmail.com>2015-07-25 16:35:01 -0600
commit0aef5ece227cbbd2247cf57ba402b8a53c504216 (patch)
treecee4a5694864cea4a58831006dc01d32f2e0f513 /numpy/matrixlib/tests/test_regression.py
parent1e99323786809fd2fa0a34818214beb34186799d (diff)
downloadnumpy-0aef5ece227cbbd2247cf57ba402b8a53c504216.tar.gz
STY: PEP8 and pyflakes fixes for numpy/matrixlib/tests.
Diffstat (limited to 'numpy/matrixlib/tests/test_regression.py')
-rw-r--r--numpy/matrixlib/tests/test_regression.py16
1 files changed, 8 insertions, 8 deletions
diff --git a/numpy/matrixlib/tests/test_regression.py b/numpy/matrixlib/tests/test_regression.py
index 40062653f..0839fbf28 100644
--- a/numpy/matrixlib/tests/test_regression.py
+++ b/numpy/matrixlib/tests/test_regression.py
@@ -1,18 +1,18 @@
from __future__ import division, absolute_import, print_function
-from numpy.testing import *
import numpy as np
+from numpy.testing import TestCase, run_module_suite, assert_, assert_equal
rlevel = 1
class TestRegression(TestCase):
- def test_kron_matrix(self,level=rlevel):
- """Ticket #71"""
+ def test_kron_matrix(self, level=rlevel):
+ # Ticket #71
x = np.matrix('[1 0; 1 0]')
assert_equal(type(np.kron(x, x)), type(x))
def test_matrix_properties(self,level=rlevel):
- """Ticket #125"""
+ # Ticket #125
a = np.matrix([1.0], dtype=float)
assert_(type(a.real) is np.matrix)
assert_(type(a.imag) is np.matrix)
@@ -20,15 +20,15 @@ class TestRegression(TestCase):
assert_(type(c) is np.ndarray)
assert_(type(d) is np.ndarray)
- def test_matrix_multiply_by_1d_vector(self, level=rlevel) :
- """Ticket #473"""
- def mul() :
+ def test_matrix_multiply_by_1d_vector(self, level=rlevel):
+ # Ticket #473
+ def mul():
np.mat(np.eye(2))*np.ones(2)
self.assertRaises(ValueError, mul)
def test_matrix_std_argmax(self,level=rlevel):
- """Ticket #83"""
+ # Ticket #83
x = np.asmatrix(np.random.uniform(0, 1, (3, 3)))
self.assertEqual(x.std().shape, ())
self.assertEqual(x.argmax().shape, ())