name : test_ufunclike.py import numpy as np import numpy.core as nx import numpy.lib.ufunclike as ufl from numpy.testing import ( assert_, assert_equal, assert_array_equal, assert_warns, assert_raises ) class TestUfunclike: def test_isposinf(self): a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0]) out = nx.zeros(a.shape, bool) tgt = nx.array([True, False, False, False, False, False]) res = ufl.isposinf(a) assert_equal(res, tgt) res = ufl.isposinf(a, out) assert_equal(res, tgt) assert_equal(out, tgt) a = a.astype(np.complex_) with assert_raises(TypeError): ufl.isposinf(a) def test_isneginf(self): a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0]) out = nx.zeros(a.shape, bool) tgt = nx.array([False, True, False, False, False, False]) res = ufl.isneginf(a) assert_equal(res, tgt) res = ufl.isneginf(a, out) assert_equal(res, tgt) assert_equal(out, tgt) a = a.astype(np.complex_) with assert_raises(TypeError): ufl.isneginf(a) def test_fix(self): a = nx.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]]) out = nx.zeros(a.shape, float) tgt = nx.array([[1., 1., 1., 1.], [-1., -1., -1., -1.]]) res = ufl.fix(a) assert_equal(res, tgt) res = ufl.fix(a, out) assert_equal(res, tgt) assert_equal(out, tgt) assert_equal(ufl.fix(3.14), 3) def test_fix_with_subclass(self): class MyArray(nx.ndarray): def __new__(cls, data, metadata=None): res = nx.array(data, copy=True).view(cls) res.metadata = metadata return res def __array_wrap__(self, obj, context=None): if isinstance(obj, MyArray): obj.metadata = self.metadata return obj def __array_finalize__(self, obj): self.metadata = getattr(obj, 'metadata', None) return self a = nx.array([1.1, -1.1]) m = MyArray(a, metadata='foo') f = ufl.fix(m) assert_array_equal(f, nx.array([1, -1])) assert_(isinstance(f, MyArray)) assert_equal(f.metadata, 'foo') # check 0d arrays don't decay to scalars m0d = m[0,...] m0d.metadata = 'bar' f0d = ufl.fix(m0d) assert_(isinstance(f0d, MyArray)) assert_equal(f0d.metadata, 'bar') def test_scalar(self): x = np.inf actual = np.isposinf(x) expected = np.True_ assert_equal(actual, expected) assert_equal(type(actual), type(expected)) x = -3.4 actual = np.fix(x) expected = np.float64(-3.0) assert_equal(actual, expected) assert_equal(type(actual), type(expected)) out = np.array(0.0) actual = np.fix(x, out=out) assert_(actual is out)