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-rw-r--r--numpy/matrixlib/tests/test_defmatrix.py202
1 files changed, 101 insertions, 101 deletions
diff --git a/numpy/matrixlib/tests/test_defmatrix.py b/numpy/matrixlib/tests/test_defmatrix.py
index 7cfcdbe27..d1a4e4ab5 100644
--- a/numpy/matrixlib/tests/test_defmatrix.py
+++ b/numpy/matrixlib/tests/test_defmatrix.py
@@ -10,51 +10,51 @@ import collections
class TestCtor(TestCase):
def test_basic(self):
- A = array([[1,2],[3,4]])
+ A = array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(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]])
+ 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]])
- AEresult = matrix([[1,2,5,6],[3,4,7,8]])
- assert_(all(bmat([A,E]) == AEresult))
+ E = array([[5, 6], [7, 8]])
+ AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
+ assert_(all(bmat([A, E]) == AEresult))
vec = arange(5)
mvec = matrix(vec)
- assert_(mvec.shape == (1,5))
+ assert_(mvec.shape == (1, 5))
def test_exceptions(self):
# Check for TypeError when called with invalid string data.
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]])
+ 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))
- 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))
- b2 = bmat("A,B;C,D",ldict={'A':A,'B':B},gdict={'C':B,'D':A})
+ assert_(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))
+ b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(all(b2 == mixresult))
@@ -63,12 +63,12 @@ class TestProperties(TestCase):
"""Test whether matrix.sum(axis=1) preserves orientation.
Fails in NumPy <= 0.9.6.2127.
"""
- M = matrix([[1,2,0,0],
- [3,4,0,0],
- [1,2,1,2],
- [3,4,3,4]])
- sum0 = matrix([8,12,4,6])
- sum1 = matrix([3,7,6,14]).T
+ M = matrix([[1, 2, 0, 0],
+ [3, 4, 0, 0],
+ [1, 2, 1, 2],
+ [3, 4, 3, 4]])
+ sum0 = matrix([8, 12, 4, 6])
+ sum1 = matrix([3, 7, 6, 14]).T
sumall = 30
assert_array_equal(sum0, M.sum(axis=0))
assert_array_equal(sum1, M.sum(axis=1))
@@ -80,46 +80,46 @@ class TestProperties(TestCase):
def test_prod(self):
- x = matrix([[1,2,3],[4,5,6]])
+ x = matrix([[1, 2, 3], [4, 5, 6]])
assert_equal(x.prod(), 720)
- assert_equal(x.prod(0), matrix([[4,10,18]]))
- assert_equal(x.prod(1), matrix([[6],[120]]))
+ assert_equal(x.prod(0), matrix([[4, 10, 18]]))
+ assert_equal(x.prod(1), matrix([[6], [120]]))
assert_equal(np.prod(x), 720)
- assert_equal(np.prod(x, axis=0), matrix([[4,10,18]]))
- assert_equal(np.prod(x, axis=1), matrix([[6],[120]]))
+ assert_equal(np.prod(x, axis=0), matrix([[4, 10, 18]]))
+ assert_equal(np.prod(x, axis=1), matrix([[6], [120]]))
- y = matrix([0,1,3])
+ y = matrix([0, 1, 3])
assert_(y.prod() == 0)
def test_max(self):
- x = matrix([[1,2,3],[4,5,6]])
+ x = matrix([[1, 2, 3], [4, 5, 6]])
assert_equal(x.max(), 6)
- assert_equal(x.max(0), matrix([[4,5,6]]))
- assert_equal(x.max(1), matrix([[3],[6]]))
+ assert_equal(x.max(0), matrix([[4, 5, 6]]))
+ assert_equal(x.max(1), matrix([[3], [6]]))
assert_equal(np.max(x), 6)
- assert_equal(np.max(x, axis=0), matrix([[4,5,6]]))
- assert_equal(np.max(x, axis=1), matrix([[3],[6]]))
+ assert_equal(np.max(x, axis=0), matrix([[4, 5, 6]]))
+ assert_equal(np.max(x, axis=1), matrix([[3], [6]]))
def test_min(self):
- x = matrix([[1,2,3],[4,5,6]])
+ x = matrix([[1, 2, 3], [4, 5, 6]])
assert_equal(x.min(), 1)
- assert_equal(x.min(0), matrix([[1,2,3]]))
- assert_equal(x.min(1), matrix([[1],[4]]))
+ assert_equal(x.min(0), matrix([[1, 2, 3]]))
+ assert_equal(x.min(1), matrix([[1], [4]]))
assert_equal(np.min(x), 1)
- assert_equal(np.min(x, axis=0), matrix([[1,2,3]]))
- assert_equal(np.min(x, axis=1), matrix([[1],[4]]))
+ assert_equal(np.min(x, axis=0), matrix([[1, 2, 3]]))
+ assert_equal(np.min(x, axis=1), matrix([[1], [4]]))
def test_ptp(self):
- x = np.arange(4).reshape((2,2))
+ 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])))
def test_var(self):
- x = np.arange(9).reshape((3,3))
+ x = np.arange(9).reshape((3, 3))
mx = x.view(np.matrix)
assert_equal(x.var(ddof=0), mx.var(ddof=0))
assert_equal(x.var(ddof=1), mx.var(ddof=1))
@@ -142,14 +142,14 @@ class TestProperties(TestCase):
assert_(all(array(conjugate(transpose(B)) == mB.H)))
def test_pinv(self):
- x = matrix(arange(6).reshape(2,3))
+ x = matrix(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 = arange(100).reshape(10, 10)
mA = matrix(A)
mB = matrix(A) + 0.1
assert_(all(mB == A+0.1))
@@ -173,34 +173,34 @@ class TestProperties(TestCase):
assert_(all(abs(mB > 0)))
def test_asmatrix(self):
- A = arange(100).reshape(10,10)
+ A = arange(100).reshape(10, 10)
mA = asmatrix(A)
- A[0,0] = -10
- assert_(A[0,0] == mA[0,0])
+ A[0, 0] = -10
+ assert_(A[0, 0] == mA[0, 0])
def test_noaxis(self):
- A = matrix([[1,0],[0,1]])
+ A = matrix([[1, 0], [0, 1]])
assert_(A.sum() == matrix(2))
assert_(A.mean() == matrix(0.5))
def test_repr(self):
- A = matrix([[1,0],[0,1]])
+ A = matrix([[1, 0], [0, 1]])
assert_(repr(A) == "matrix([[1, 0],\n [0, 1]])")
class TestCasting(TestCase):
def test_basic(self):
- A = arange(100).reshape(10,10)
+ A = arange(100).reshape(10, 10)
mA = matrix(A)
mB = mA.copy()
- O = ones((10,10), float64) * 0.1
+ O = ones((10, 10), float64) * 0.1
mB = mB + O
assert_(mB.dtype.type == float64)
assert_(all(mA != mB))
assert_(all(mB == mA+0.1))
mC = mA.copy()
- O = ones((10,10), complex128)
+ O = ones((10, 10), complex128)
mC = mC * O
assert_(mC.dtype.type == complex128)
assert_(all(mA != mB))
@@ -272,12 +272,12 @@ class TestMatrixReturn(TestCase):
def test_instance_methods(self):
a = matrix([1.0], dtype='f8')
methodargs = {
- 'astype' : ('intc',),
- 'clip' : (0.0, 1.0),
- 'compress' : ([1],),
- 'repeat' : (1,),
- 'reshape' : (1,),
- 'swapaxes' : (0,0),
+ 'astype': ('intc',),
+ 'clip': (0.0, 1.0),
+ 'compress': ([1],),
+ 'repeat': (1,),
+ 'reshape': (1,),
+ 'swapaxes': (0, 0),
'dot': np.array([1.0]),
}
excluded_methods = [
@@ -305,23 +305,23 @@ class TestMatrixReturn(TestCase):
assert_(type(b) is matrix, "%s" % attrib)
assert_(type(a.real) is matrix)
assert_(type(a.imag) is matrix)
- c,d = matrix([0.0]).nonzero()
+ c, d = matrix([0.0]).nonzero()
assert_(type(c) is matrix)
assert_(type(d) is matrix)
class TestIndexing(TestCase):
def test_basic(self):
- x = asmatrix(zeros((3,2),float))
- y = zeros((3,1),float)
- y[:,0] = [0.8,0.2,0.3]
- x[:,1] = y>0.5
- assert_equal(x, [[0,1],[0,0],[0,0]])
+ x = asmatrix(zeros((3, 2), float))
+ y = zeros((3, 1), float)
+ y[:, 0] = [0.8, 0.2, 0.3]
+ x[:, 1] = y>0.5
+ assert_equal(x, [[0, 1], [0, 0], [0, 0]])
class TestNewScalarIndexing(TestCase):
def setUp(self):
- self.a = matrix([[1, 2],[3,4]])
+ self.a = matrix([[1, 2], [3, 4]])
def test_dimesions(self):
a = self.a
@@ -331,64 +331,64 @@ class TestNewScalarIndexing(TestCase):
def test_array_from_matrix_list(self):
a = self.a
x = array([a, a])
- assert_equal(x.shape, [2,2,2])
+ assert_equal(x.shape, [2, 2, 2])
def test_array_to_list(self):
a = self.a
- assert_equal(a.tolist(),[[1, 2], [3, 4]])
+ assert_equal(a.tolist(), [[1, 2], [3, 4]])
def test_fancy_indexing(self):
a = self.a
- x = a[1, [0,1,0]]
+ x = a[1, [0, 1, 0]]
assert_(isinstance(x, matrix))
assert_equal(x, matrix([[3, 4, 3]]))
- x = a[[1,0]]
+ x = a[[1, 0]]
assert_(isinstance(x, matrix))
assert_equal(x, matrix([[3, 4], [1, 2]]))
- x = a[[[1],[0]],[[1,0],[0,1]]]
+ x = a[[[1], [0]], [[1, 0], [0, 1]]]
assert_(isinstance(x, matrix))
assert_equal(x, matrix([[4, 3], [1, 2]]))
def test_matrix_element(self):
- x = matrix([[1,2,3],[4,5,6]])
- assert_equal(x[0][0],matrix([[1,2,3]]))
- assert_equal(x[0][0].shape,(1,3))
- assert_equal(x[0].shape,(1,3))
- assert_equal(x[:,0].shape,(2,1))
+ x = matrix([[1, 2, 3], [4, 5, 6]])
+ assert_equal(x[0][0], matrix([[1, 2, 3]]))
+ assert_equal(x[0][0].shape, (1, 3))
+ assert_equal(x[0].shape, (1, 3))
+ assert_equal(x[:, 0].shape, (2, 1))
x = matrix(0)
- assert_equal(x[0,0],0)
- assert_equal(x[0],0)
- assert_equal(x[:,0].shape,x.shape)
+ assert_equal(x[0, 0], 0)
+ assert_equal(x[0], 0)
+ assert_equal(x[:, 0].shape, x.shape)
def test_scalar_indexing(self):
- x = asmatrix(zeros((3,2),float))
- assert_equal(x[0,0],x[0][0])
+ x = asmatrix(zeros((3, 2), float))
+ assert_equal(x[0, 0], x[0][0])
def test_row_column_indexing(self):
x = asmatrix(np.eye(2))
- assert_array_equal(x[0,:],[[1,0]])
- assert_array_equal(x[1,:],[[0,1]])
- assert_array_equal(x[:,0],[[1],[0]])
- assert_array_equal(x[:,1],[[0],[1]])
+ assert_array_equal(x[0,:], [[1, 0]])
+ assert_array_equal(x[1,:], [[0, 1]])
+ assert_array_equal(x[:, 0], [[1], [0]])
+ assert_array_equal(x[:, 1], [[0], [1]])
def test_boolean_indexing(self):
A = arange(6)
- A.shape = (3,2)
+ 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[:, array([True, False])], x[:, 0])
+ assert_array_equal(x[array([True, False, False]),:], x[0,:])
def test_list_indexing(self):
A = arange(6)
- A.shape = (3,2)
+ A.shape = (3, 2)
x = asmatrix(A)
- assert_array_equal(x[:,[1,0]],x[:,::-1])
- assert_array_equal(x[[2,1,0],:],x[::-1,:])
+ assert_array_equal(x[:, [1, 0]], x[:, ::-1])
+ assert_array_equal(x[[2, 1, 0],:], x[::-1,:])
class TestPower(TestCase):
def test_returntype(self):
- a = array([[0,1],[0,0]])
+ a = array([[0, 1], [0, 0]])
assert_(type(matrix_power(a, 2)) is ndarray)
a = mat(a)
assert_(type(matrix_power(a, 2)) is matrix)
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