def test_custom_dtype_duck(self):
class MyArray(list):
@property
def dtype(self):
return complex
a = MyArray([1 + 0j, 2 + 0j, 3 + 0j])
assert_(iscomplexobj(a))
def test_duck(self):
class DummyComplexArray:
@property
def dtype(self):
return np.dtype(complex)
dummy = DummyComplexArray()
assert_(iscomplexobj(dummy))
def test_basic(self):
a = np.random.rand(10)
b = real_if_close(a + 1e-15j)
assert_all(isrealobj(b))
assert_array_equal(a, b)
b = real_if_close(a + 1e-7j)
assert_all(iscomplexobj(b))
b = real_if_close(a + 1e-7j, tol=1e-6)
assert_all(isrealobj(b))
def test_pandas_duck(self):
# This tests a custom np.dtype duck-typed class, such as used by pandas
# (pandas.core.dtypes)
class PdComplex(np.complex128):
pass
class PdDtype(object):
name = 'category'
names = None
type = PdComplex
kind = 'c'
str = '<c16'
base = np.dtype('complex128')
class DummyPd:
@property
def dtype(self):
return PdDtype
dummy = DummyPd()
assert_(iscomplexobj(dummy))
def test_list(self):
assert_(iscomplexobj([3, 1 + 0j, True]))
assert_(not iscomplexobj([3, 1, True]))
def test_scalar(self):
assert_(not iscomplexobj(1.0))
assert_(iscomplexobj(1 + 0j))
def test_basic(self):
z = np.array([-1, 0, 1])
assert_(not iscomplexobj(z))
z = np.array([-1j, 0, -1])
assert_(iscomplexobj(z))