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-rw-r--r--numpy/matrixlib/tests/test_defmatrix.py200
1 files changed, 99 insertions, 101 deletions
diff --git a/numpy/matrixlib/tests/test_defmatrix.py b/numpy/matrixlib/tests/test_defmatrix.py
index c7645d1e0..6aa24e4ff 100644
--- a/numpy/matrixlib/tests/test_defmatrix.py
+++ b/numpy/matrixlib/tests/test_defmatrix.py
@@ -1,33 +1,36 @@
from __future__ import division, absolute_import, print_function
-from numpy.testing import *
-from numpy.core import *
+import collections
+
+import numpy as np
from numpy import matrix, asmatrix, bmat
+from numpy.testing import (
+ TestCase, run_module_suite, assert_, assert_equal, assert_almost_equal,
+ assert_array_equal, assert_array_almost_equal, assert_raises
+)
from numpy.matrixlib.defmatrix import matrix_power
from numpy.matrixlib import mat
-import numpy as np
-import collections
class TestCtor(TestCase):
def test_basic(self):
- A = array([[1, 2], [3, 4]])
+ A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
- assert_(all(mA.A == A))
+ assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
- D = array([[1, 2, 1, 2],
- [3, 4, 3, 4],
- [1, 2, 1, 2],
- [3, 4, 3, 4]])
- assert_(all(B.A == D))
- assert_(all(C.A == D))
-
- E = array([[5, 6], [7, 8]])
+ D = np.array([[1, 2, 1, 2],
+ [3, 4, 3, 4],
+ [1, 2, 1, 2],
+ [3, 4, 3, 4]])
+ assert_(np.all(B.A == D))
+ assert_(np.all(C.A == D))
+
+ E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
- assert_(all(bmat([A, E]) == AEresult))
+ assert_(np.all(bmat([A, E]) == AEresult))
- vec = arange(5)
+ vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
@@ -36,26 +39,23 @@ class TestCtor(TestCase):
assert_raises(TypeError, matrix, "invalid")
def test_bmat_nondefault_str(self):
- A = array([[1, 2], [3, 4]])
- B = array([[5, 6], [7, 8]])
- Aresult = array([[1, 2, 1, 2],
- [3, 4, 3, 4],
- [1, 2, 1, 2],
- [3, 4, 3, 4]])
- Bresult = array([[5, 6, 5, 6],
- [7, 8, 7, 8],
- [5, 6, 5, 6],
- [7, 8, 7, 8]])
- mixresult = array([[1, 2, 5, 6],
- [3, 4, 7, 8],
- [5, 6, 1, 2],
- [7, 8, 3, 4]])
- assert_(all(bmat("A,A;A,A") == Aresult))
- assert_(all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
+ A = np.array([[1, 2], [3, 4]])
+ B = np.array([[5, 6], [7, 8]])
+ Aresult = np.array([[1, 2, 1, 2],
+ [3, 4, 3, 4],
+ [1, 2, 1, 2],
+ [3, 4, 3, 4]])
+ mixresult = np.array([[1, 2, 5, 6],
+ [3, 4, 7, 8],
+ [5, 6, 1, 2],
+ [7, 8, 3, 4]])
+ assert_(np.all(bmat("A,A;A,A") == Aresult))
+ assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
- assert_(all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
+ assert_(
+ np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
- assert_(all(b2 == mixresult))
+ assert_(np.all(b2 == mixresult))
class TestProperties(TestCase):
@@ -78,7 +78,6 @@ class TestProperties(TestCase):
assert_array_equal(sum1, np.sum(M, axis=1))
assert_equal(sumall, np.sum(M))
-
def test_prod(self):
x = matrix([[1, 2, 3], [4, 5, 6]])
assert_equal(x.prod(), 720)
@@ -115,8 +114,8 @@ class TestProperties(TestCase):
def test_ptp(self):
x = np.arange(4).reshape((2, 2))
assert_(x.ptp() == 3)
- assert_(all(x.ptp(0) == array([2, 2])))
- assert_(all(x.ptp(1) == array([1, 1])))
+ assert_(np.all(x.ptp(0) == np.array([2, 2])))
+ assert_(np.all(x.ptp(1) == np.array([1, 1])))
def test_var(self):
x = np.arange(9).reshape((3, 3))
@@ -127,53 +126,53 @@ class TestProperties(TestCase):
def test_basic(self):
import numpy.linalg as linalg
- A = array([[1., 2.],
- [3., 4.]])
+ A = np.array([[1., 2.],
+ [3., 4.]])
mA = matrix(A)
- assert_(allclose(linalg.inv(A), mA.I))
- assert_(all(array(transpose(A) == mA.T)))
- assert_(all(array(transpose(A) == mA.H)))
- assert_(all(A == mA.A))
+ assert_(np.allclose(linalg.inv(A), mA.I))
+ assert_(np.all(np.array(np.transpose(A) == mA.T)))
+ assert_(np.all(np.array(np.transpose(A) == mA.H)))
+ assert_(np.all(A == mA.A))
B = A + 2j*A
mB = matrix(B)
- assert_(allclose(linalg.inv(B), mB.I))
- assert_(all(array(transpose(B) == mB.T)))
- assert_(all(array(conjugate(transpose(B)) == mB.H)))
+ assert_(np.allclose(linalg.inv(B), mB.I))
+ assert_(np.all(np.array(np.transpose(B) == mB.T)))
+ assert_(np.all(np.array(np.transpose(B).conj() == mB.H)))
def test_pinv(self):
- x = matrix(arange(6).reshape(2, 3))
+ x = matrix(np.arange(6).reshape(2, 3))
xpinv = matrix([[-0.77777778, 0.27777778],
[-0.11111111, 0.11111111],
[ 0.55555556, -0.05555556]])
assert_almost_equal(x.I, xpinv)
def test_comparisons(self):
- A = arange(100).reshape(10, 10)
+ A = np.arange(100).reshape(10, 10)
mA = matrix(A)
mB = matrix(A) + 0.1
- assert_(all(mB == A+0.1))
- assert_(all(mB == matrix(A+0.1)))
- assert_(not any(mB == matrix(A-0.1)))
- assert_(all(mA < mB))
- assert_(all(mA <= mB))
- assert_(all(mA <= mA))
- assert_(not any(mA < mA))
-
- assert_(not any(mB < mA))
- assert_(all(mB >= mA))
- assert_(all(mB >= mB))
- assert_(not any(mB > mB))
-
- assert_(all(mA == mA))
- assert_(not any(mA == mB))
- assert_(all(mB != mA))
-
- assert_(not all(abs(mA) > 0))
- assert_(all(abs(mB > 0)))
+ assert_(np.all(mB == A+0.1))
+ assert_(np.all(mB == matrix(A+0.1)))
+ assert_(not np.any(mB == matrix(A-0.1)))
+ assert_(np.all(mA < mB))
+ assert_(np.all(mA <= mB))
+ assert_(np.all(mA <= mA))
+ assert_(not np.any(mA < mA))
+
+ assert_(not np.any(mB < mA))
+ assert_(np.all(mB >= mA))
+ assert_(np.all(mB >= mB))
+ assert_(not np.any(mB > mB))
+
+ assert_(np.all(mA == mA))
+ assert_(not np.any(mA == mB))
+ assert_(np.all(mB != mA))
+
+ assert_(not np.all(abs(mA) > 0))
+ assert_(np.all(abs(mB > 0)))
def test_asmatrix(self):
- A = arange(100).reshape(10, 10)
+ A = np.arange(100).reshape(10, 10)
mA = asmatrix(A)
A[0, 0] = -10
assert_(A[0, 0] == mA[0, 0])
@@ -189,49 +188,48 @@ class TestProperties(TestCase):
class TestCasting(TestCase):
def test_basic(self):
- A = arange(100).reshape(10, 10)
+ A = np.arange(100).reshape(10, 10)
mA = matrix(A)
mB = mA.copy()
- O = ones((10, 10), float64) * 0.1
+ O = np.ones((10, 10), np.float64) * 0.1
mB = mB + O
- assert_(mB.dtype.type == float64)
- assert_(all(mA != mB))
- assert_(all(mB == mA+0.1))
+ assert_(mB.dtype.type == np.float64)
+ assert_(np.all(mA != mB))
+ assert_(np.all(mB == mA+0.1))
mC = mA.copy()
- O = ones((10, 10), complex128)
+ O = np.ones((10, 10), np.complex128)
mC = mC * O
- assert_(mC.dtype.type == complex128)
- assert_(all(mA != mB))
+ assert_(mC.dtype.type == np.complex128)
+ assert_(np.all(mA != mB))
class TestAlgebra(TestCase):
def test_basic(self):
import numpy.linalg as linalg
- A = array([[1., 2.],
- [3., 4.]])
+ A = np.array([[1., 2.], [3., 4.]])
mA = matrix(A)
- B = identity(2)
+ B = np.identity(2)
for i in range(6):
- assert_(allclose((mA ** i).A, B))
- B = dot(B, A)
+ assert_(np.allclose((mA ** i).A, B))
+ B = np.dot(B, A)
Ainv = linalg.inv(A)
- B = identity(2)
+ B = np.identity(2)
for i in range(6):
- assert_(allclose((mA ** -i).A, B))
- B = dot(B, Ainv)
+ assert_(np.allclose((mA ** -i).A, B))
+ B = np.dot(B, Ainv)
- assert_(allclose((mA * mA).A, dot(A, A)))
- assert_(allclose((mA + mA).A, (A + A)))
- assert_(allclose((3*mA).A, (3*A)))
+ assert_(np.allclose((mA * mA).A, np.dot(A, A)))
+ assert_(np.allclose((mA + mA).A, (A + A)))
+ assert_(np.allclose((3*mA).A, (3*A)))
mA2 = matrix(A)
mA2 *= 3
- assert_(allclose(mA2.A, 3*A))
+ assert_(np.allclose(mA2.A, 3*A))
def test_pow(self):
"""Test raising a matrix to an integer power works as expected."""
@@ -312,10 +310,10 @@ class TestMatrixReturn(TestCase):
class TestIndexing(TestCase):
def test_basic(self):
- x = asmatrix(zeros((3, 2), float))
- y = zeros((3, 1), float)
+ x = asmatrix(np.zeros((3, 2), float))
+ y = np.zeros((3, 1), float)
y[:, 0] = [0.8, 0.2, 0.3]
- x[:, 1] = y>0.5
+ x[:, 1] = y > 0.5
assert_equal(x, [[0, 1], [0, 0], [0, 0]])
@@ -330,7 +328,7 @@ class TestNewScalarIndexing(TestCase):
def test_array_from_matrix_list(self):
a = self.a
- x = array([a, a])
+ x = np.array([a, a])
assert_equal(x.shape, [2, 2, 2])
def test_array_to_list(self):
@@ -362,7 +360,7 @@ class TestNewScalarIndexing(TestCase):
assert_equal(x[:, 0].shape, x.shape)
def test_scalar_indexing(self):
- x = asmatrix(zeros((3, 2), float))
+ x = asmatrix(np.zeros((3, 2), float))
assert_equal(x[0, 0], x[0][0])
def test_row_column_indexing(self):
@@ -373,14 +371,14 @@ class TestNewScalarIndexing(TestCase):
assert_array_equal(x[:, 1], [[0], [1]])
def test_boolean_indexing(self):
- A = arange(6)
+ A = np.arange(6)
A.shape = (3, 2)
x = asmatrix(A)
- assert_array_equal(x[:, array([True, False])], x[:, 0])
- assert_array_equal(x[array([True, False, False]),:], x[0,:])
+ assert_array_equal(x[:, np.array([True, False])], x[:, 0])
+ assert_array_equal(x[np.array([True, False, False]),:], x[0,:])
def test_list_indexing(self):
- A = arange(6)
+ A = np.arange(6)
A.shape = (3, 2)
x = asmatrix(A)
assert_array_equal(x[:, [1, 0]], x[:, ::-1])
@@ -389,8 +387,8 @@ class TestNewScalarIndexing(TestCase):
class TestPower(TestCase):
def test_returntype(self):
- a = array([[0, 1], [0, 0]])
- assert_(type(matrix_power(a, 2)) is ndarray)
+ a = np.array([[0, 1], [0, 0]])
+ assert_(type(matrix_power(a, 2)) is np.ndarray)
a = mat(a)
assert_(type(matrix_power(a, 2)) is matrix)
@@ -400,7 +398,7 @@ class TestPower(TestCase):
class TestShape(TestCase):
def setUp(self):
- self.a = array([[1], [2]])
+ self.a = np.array([[1], [2]])
self.m = matrix([[1], [2]])
def test_shape(self):
@@ -420,7 +418,7 @@ class TestShape(TestCase):
assert_equal(self.m.flatten().shape, (1, 2))
def test_numpy_ravel_order(self):
- x = array([[1, 2, 3], [4, 5, 6]])
+ x = np.array([[1, 2, 3], [4, 5, 6]])
assert_equal(np.ravel(x), [1, 2, 3, 4, 5, 6])
assert_equal(np.ravel(x, order='F'), [1, 4, 2, 5, 3, 6])
assert_equal(np.ravel(x.T), [1, 4, 2, 5, 3, 6])
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