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author | Charles Harris <charlesr.harris@gmail.com> | 2013-08-18 11:51:25 -0600 |
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committer | Charles Harris <charlesr.harris@gmail.com> | 2013-08-18 11:51:25 -0600 |
commit | fbd6510d58a47ea0d166c48a82793f05425406e4 (patch) | |
tree | 330ce703eb02d20f96099c3fe0fc36ae33d4905b /numpy/matrixlib/tests/test_defmatrix.py | |
parent | 8ddb0ce0acafe75d78df528b4d2540dfbf4b364d (diff) | |
download | numpy-fbd6510d58a47ea0d166c48a82793f05425406e4.tar.gz |
STY: Giant comma spacing fixup.
Run the 2to3 ws_comma fixer on *.py files. Some lines are now too long
and will need to be broken at some point. OTOH, some lines were already
too long and need to be broken at some point. Now seems as good a time
as any to do this with open PRs at a minimum.
Diffstat (limited to 'numpy/matrixlib/tests/test_defmatrix.py')
-rw-r--r-- | numpy/matrixlib/tests/test_defmatrix.py | 202 |
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) |