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from numpy.testing import * from numpy.core import * from numpy import matrix, asmatrix, bmat from numpy.matrixlib.defmatrix import matrix_power from numpy.matrixlib import mat import numpy as np
class TestCtor(TestCase): def test_basic(self): 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]]) 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)
vec = arange(5) mvec = matrix(vec) assert mvec.shape == (1,5)
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) 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)
class TestProperties(TestCase): def test_sum(self): """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 sumall = 30 assert_array_equal(sum0, M.sum(axis=0)) assert_array_equal(sum1, M.sum(axis=1)) assert sumall == M.sum()
def test_prod(self): x = matrix([[1,2,3],[4,5,6]]) assert x.prod() == 720 assert all(x.prod(0) == matrix([[4,10,18]])) assert all(x.prod(1) == matrix([[6],[120]]))
y = matrix([0,1,3]) assert y.prod() == 0
def test_max(self): x = matrix([[1,2,3],[4,5,6]]) assert x.max() == 6 assert all(x.max(0) == matrix([[4,5,6]])) assert all(x.max(1) == matrix([[3],[6]]))
def test_min(self): x = matrix([[1,2,3],[4,5,6]]) assert x.min() == 1 assert all(x.min(0) == matrix([[1,2,3]])) assert all(x.min(1) == matrix([[1],[4]]))
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]))
def test_var(self): 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))
def test_basic(self): import numpy.linalg as linalg
A = 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)
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))
def test_pinv(self): 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) 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))
def test_asmatrix(self): A = arange(100).reshape(10,10) mA = asmatrix(A) A[0,0] = -10 assert A[0,0] == mA[0,0]
def test_noaxis(self): 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]]) assert repr(A) == "matrix([[1, 0],\n [0, 1]])"
class TestCasting(TestCase): def test_basic(self): A = arange(100).reshape(10,10) mA = matrix(A)
mB = mA.copy() 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) mC = mC * O assert mC.dtype.type == complex128 assert all(mA != mB)
class TestAlgebra(TestCase): def test_basic(self): import numpy.linalg as linalg
A = array([[1., 2.], [3., 4.]]) mA = matrix(A)
B = identity(2) for i in xrange(6): assert allclose((mA ** i).A, B) B = dot(B, A)
Ainv = linalg.inv(A) B = identity(2) for i in xrange(6): assert allclose((mA ** -i).A, B) B = 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))
mA2 = matrix(A) mA2 *= 3 assert allclose(mA2.A, 3*A)
def test_pow(self): """Test raising a matrix to an integer power works as expected.""" m = matrix("1. 2.; 3. 4.") m2 = m.copy() m2 **= 2 mi = m.copy() mi **= -1 m4 = m2.copy() m4 **= 2 assert_array_almost_equal(m2, m**2) assert_array_almost_equal(m4, np.dot(m2, m2)) assert_array_almost_equal(np.dot(mi, m), np.eye(2))
def test_notimplemented(self): '''Check that 'not implemented' operations produce a failure.''' A = matrix([[1., 2.], [3., 4.]])
# __rpow__ try: 1.0**A except TypeError: pass else: self.fail("matrix.__rpow__ doesn't raise a TypeError")
# __mul__ with something not a list, ndarray, tuple, or scalar try: A*object() except TypeError: pass else: self.fail("matrix.__mul__ with non-numeric object doesn't raise" "a TypeError")
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) } excluded_methods = [ 'argmin', 'choose', 'dump', 'dumps', 'fill', 'getfield', 'getA', 'getA1', 'item', 'nonzero', 'put', 'putmask', 'resize', 'searchsorted', 'setflags', 'setfield', 'sort', 'take', 'tofile', 'tolist', 'tostring', 'all', 'any', 'sum', 'argmax', 'argmin', 'min', 'max', 'mean', 'var', 'ptp', 'prod', 'std', 'ctypes', 'itemset' ] for attrib in dir(a): if attrib.startswith('_') or attrib in excluded_methods: continue f = eval('a.%s' % attrib) if callable(f): # reset contents of a a.astype('f8') a.fill(1.0) if attrib in methodargs: args = methodargs[attrib] else: args = () b = f(*args) 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() 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]])
class TestNewScalarIndexing(TestCase): def setUp(self): self.a = matrix([[1, 2],[3,4]])
def test_dimesions(self): a = self.a x = a[0] assert_equal(x.ndim, 2)
def test_array_from_matrix_list(self): a = self.a x = array([a, a]) assert_equal(x.shape, [2,2,2])
def test_array_to_list(self): a = self.a assert_equal(a.tolist(),[[1, 2], [3, 4]])
def test_fancy_indexing(self): a = self.a x = a[1, [0,1,0]] assert isinstance(x, matrix) assert_equal(x, matrix([[3, 4, 3]])) x = a[[1,0]] assert isinstance(x, matrix) assert_equal(x, matrix([[3, 4], [1, 2]])) 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(0) 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])
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]])
def test_boolean_indexing(self): A = 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,:])
def test_list_indexing(self): A = arange(6) A.shape = (3,2) x = asmatrix(A) 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]]) assert type(matrix_power(a, 2)) is ndarray a = mat(a) assert type(matrix_power(a, 2)) is matrix
def test_list(self): assert_array_equal(matrix_power([[0, 1], [0, 0]], 2), [[0, 0], [0, 0]])
if __name__ == "__main__": run_module_suite()
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