from numpy.core import * from numpy.random import rand, randint from numpy.testing import * from numpy.core.multiarray import dot as dot_ import sys class Vec: def __init__(self,sequence=None): if sequence is None: sequence=[] self.array=array(sequence) def __add__(self,other): out=Vec() out.array=self.array+other.array return out def __sub__(self,other): out=Vec() out.array=self.array-other.array return out def __mul__(self,other): # with scalar out=Vec(self.array.copy()) out.array*=other return out def __rmul__(self,other): return self*other def __abs__(self): out=Vec() out.array=abs(self.array) return out def __repr__(self): return "Vec("+repr(self.array.tolist())+")" __str__=__repr__ class test_dot(NumpyTestCase): def setUp(self): self.A = rand(10,8) self.b1 = rand(8,1) self.b2 = rand(8) self.b3 = rand(1,8) self.b4 = rand(10) self.N = 14 def check_matmat(self): A = self.A c1 = dot(A.transpose(), A) c2 = dot_(A.transpose(), A) assert_almost_equal(c1, c2, decimal=self.N) def check_matvec(self): A, b1 = self.A, self.b1 c1 = dot(A, b1) c2 = dot_(A, b1) assert_almost_equal(c1, c2, decimal=self.N) def check_matvec2(self): A, b2 = self.A, self.b2 c1 = dot(A, b2) c2 = dot_(A, b2) assert_almost_equal(c1, c2, decimal=self.N) def check_vecmat(self): A, b4 = self.A, self.b4 c1 = dot(b4, A) c2 = dot_(b4, A) assert_almost_equal(c1, c2, decimal=self.N) def check_vecmat2(self): b3, A = self.b3, self.A c1 = dot(b3, A.transpose()) c2 = dot_(b3, A.transpose()) assert_almost_equal(c1, c2, decimal=self.N) def check_vecmat3(self): A, b4 = self.A, self.b4 c1 = dot(A.transpose(),b4) c2 = dot_(A.transpose(),b4) assert_almost_equal(c1, c2, decimal=self.N) def check_vecvecouter(self): b1, b3 = self.b1, self.b3 c1 = dot(b1, b3) c2 = dot_(b1, b3) assert_almost_equal(c1, c2, decimal=self.N) def check_vecvecinner(self): b1, b3 = self.b1, self.b3 c1 = dot(b3, b1) c2 = dot_(b3, b1) assert_almost_equal(c1, c2, decimal=self.N) def check_matscalar(self): b1 = matrix(ones((3,3),dtype=complex)) assert_equal(b1*1.0, b1) def check_columnvect(self): b1 = ones((3,1)) b2 = [5.3] c1 = dot(b1,b2) c2 = dot_(b1,b2) assert_almost_equal(c1, c2, decimal=self.N) def check_columnvect(self): b1 = ones((3,1)).transpose() b2 = [6.2] c1 = dot(b2,b1) c2 = dot_(b2,b1) assert_almost_equal(c1, c2, decimal=self.N) def check_vecscalar(self): b1 = rand(1,1) b2 = rand(1,8) c1 = dot(b1,b2) c2 = dot_(b1,b2) assert_almost_equal(c1, c2, decimal=self.N) def check_vecscalar2(self): b1 = rand(8,1) b2 = rand(1,1) c1 = dot(b1,b2) c2 = dot_(b1,b2) assert_almost_equal(c1, c2, decimal=self.N) def check_all(self): dims = [(),(1,),(1,1)] for dim1 in dims: for dim2 in dims: arg1 = rand(*dim1) arg2 = rand(*dim2) c1 = dot(arg1, arg2) c2 = dot_(arg1, arg2) assert (c1.shape == c2.shape) assert_almost_equal(c1, c2, decimal=self.N) def check_vecobject(self): U_non_cont = transpose([[1.,1.],[1.,2.]]) U_cont = ascontiguousarray(U_non_cont) x = array([Vec([1.,0.]),Vec([0.,1.])]) zeros = array([Vec([0.,0.]),Vec([0.,0.])]) zeros_test = dot(U_cont,x) - dot(U_non_cont,x) assert_equal(zeros[0].array, zeros_test[0].array) assert_equal(zeros[1].array, zeros_test[1].array) class test_bool_scalar(NumpyTestCase): def test_logical(self): f = False_ t = True_ s = "xyz" self.failUnless((t and s) is s) self.failUnless((f and s) is f) def test_bitwise_or(self): f = False_ t = True_ self.failUnless((t | t) is t) self.failUnless((f | t) is t) self.failUnless((t | f) is t) self.failUnless((f | f) is f) def test_bitwise_and(self): f = False_ t = True_ self.failUnless((t & t) is t) self.failUnless((f & t) is f) self.failUnless((t & f) is f) self.failUnless((f & f) is f) def test_bitwise_xor(self): f = False_ t = True_ self.failUnless((t ^ t) is f) self.failUnless((f ^ t) is t) self.failUnless((t ^ f) is t) self.failUnless((f ^ f) is f) class test_seterr(NumpyTestCase): def test_set(self): err = seterr() old = seterr(divide='warn') self.failUnless(err == old) new = seterr() self.failUnless(new['divide'] == 'warn') seterr(over='raise') self.failUnless(geterr()['over'] == 'raise') self.failUnless(new['divide'] == 'warn') seterr(**old) self.failUnless(geterr() == old) def test_divideerr(self): seterr(divide='raise') try: array([1.]) / array([0.]) except FloatingPointError: pass else: self.fail() seterr(divide='ignore') array([1.]) / array([0.]) class test_fromiter(NumpyTestCase): def makegen(self): for x in xrange(24): yield x**2 def test_types(self): ai32 = fromiter(self.makegen(), int32) ai64 = fromiter(self.makegen(), int64) af = fromiter(self.makegen(), float) self.failUnless(ai32.dtype == dtype(int32)) self.failUnless(ai64.dtype == dtype(int64)) self.failUnless(af.dtype == dtype(float)) def test_lengths(self): expected = array(list(self.makegen())) a = fromiter(self.makegen(), int) a20 = fromiter(self.makegen(), int, 20) self.failUnless(len(a) == len(expected)) self.failUnless(len(a20) == 20) try: fromiter(self.makegen(), int, len(expected) + 10) except ValueError: pass else: self.fail() def test_values(self): expected = array(list(self.makegen())) a = fromiter(self.makegen(), int) a20 = fromiter(self.makegen(), int, 20) self.failUnless(alltrue(a == expected,axis=0)) self.failUnless(alltrue(a20 == expected[:20],axis=0)) class test_index(NumpyTestCase): def test_boolean(self): a = rand(3,5,8) V = rand(5,8) g1 = randint(0,5,size=15) g2 = randint(0,8,size=15) V[g1,g2] = -V[g1,g2] assert (array([a[0][V>0],a[1][V>0],a[2][V>0]]) == a[:,V>0]).all() class test_binary_repr(NumpyTestCase): def test_zero(self): assert_equal(binary_repr(0),'0') def test_large(self): assert_equal(binary_repr(10736848),'101000111101010011010000') import sys if sys.version_info[:2] >= (2, 5): set_local_path() from test_errstate import * restore_path() if __name__ == '__main__': NumpyTest().run()