def setUp(self):
self.adims = (aobj.DimSweep("f", 1),
aobj.DimMatrix_i("i", 2),
aobj.DimMatrix_j("j", 2))
self.a = aobj.hfarray([[[0, 0j], [0, 0]]], dims=self.adims)
self.bdims = (aobj.DimSweep("f", 10),
aobj.DimMatrix_i("i", 2),
aobj.DimMatrix_j("j", 2))
self.b = aobj.hfarray(np.array([[[1, 2 + 0j], [3, 4]]]) +
np.arange(10)[:, newaxis, newaxis],
dims=self.bdims)
self.c, = aobj.make_same_dims_list([random_value_array(4, 5)])
self.cdims = self.c.dims
self.ddims = self.bdims
self.d = aobj.hfarray(np.array([[[1, 2], [3, 4]]]) +
np.arange(10)[:, newaxis, newaxis],
dims=self.ddims)
self.i1 = i1 = aobj.DimSweep("i1", 1)
self.i2 = i2 = aobj.DimSweep("i2", 1)
self.i3 = i3 = aobj.DimSweep("i3", 1)
self.i4 = i4 = aobj.DimSweep("i4", 1)
self.i5 = i5 = aobj.DimSweep("i5", 1)
self.fi = fi = aobj.DimSweep("f", 2),
self.gi = gi = aobj.DimSweep("g", 3),
self.e = aobj.hfarray(np.zeros((1, 2, 3)), dims=(i1, fi, gi))
self.f = aobj.hfarray(np.zeros((2, 3, 1)), dims=(fi, gi, i1))
self.g = aobj.hfarray(np.zeros((1, 2, 3, 1)), dims=(i2, fi, gi, i1))
dims = (i2, fi, i3, gi, i1)
self.h = aobj.hfarray(np.zeros((1, 2, 1, 3, 1)), dims=dims)
dims = (i4, i5)
def test_defaults(self):
v = random_value_array(4, 5)
a = np.array(v)
r1 = getattr(v, self.methodname)()
r2 = getattr(a, self.methodname)()
r1.verify_dimension()
self.assertTrue(np.allclose(r1, r2))
self.assertIsInstance(r1, v.__class__)
def test_1(methodname="argsort", **kw):
v = random_value_array(4, 5)
a = np.array(v)
for i in range(v.ndim):
r1 = getattr(a, methodname)(axis=i, **kw)
r2 = getattr(v, methodname)(axis=i, **kw)
print(i, np.allclose(r1, r2), isinstance(r2, v.__class__))
return v, a
def test_axis_none(self):
v = random_value_array(4, 5)
a = np.array(v)
args = self.kw.copy()
args.update(axis=None)
r1 = getattr(v, self.methodname)(**args)
r2 = getattr(a, self.methodname)(**args)
r1.verify_dimension()
self.assertTrue(np.allclose(r1, r2))
self.assertIsInstance(r1, v.__class__)
def test_1(self):
v = random_value_array(4, 5, minsize=2)
a = np.array(v)
args = self.kw.copy()
for i in range(v.ndim):
r1 = getattr(v, self.methodname)(axis=i, **args)
r2 = getattr(a, self.methodname)(axis=i, **args)
r1.verify_dimension()
self.assertTrue(np.allclose(r1, r2))
self.assertIsInstance(r1, v.__class__)
def test_4(self):
a = random_value_array(3, 5)
self.assertRaises(aobj.HFArrayShapeDimsMismatchError,
aobj.make_vector, np.array(a), a.dims[:0])
def test_1(self):
a = random_value_array(3, 5)
m = aobj.make_vector(np.array(a), a.dims[:-1])
self.assertAllclose(m, a)
self.assertEqual(m.dims[-1:], (ds.DimMatrix_j("j", a.shape[-1]),))
def test_3(self):
a = random_value_array(3, 5)
self.assertRaises(aobj.HFArrayShapeDimsMismatchError,
aobj.make_matrix, np.array(a), a.dims[:3])
def test_1(self):
a = random_value_array(3, 5)
m = aobj.make_matrix(np.array(a), a.dims[:-2])
self.assertAllclose(m, a)
self.assertEqual(m.dims[-2:], (ds.DimMatrix_i("i", a.shape[-2]),
ds.DimMatrix_j("j", a.shape[-1])))
def test_error_2(self):
v = random_value_array(4, 5)
self.assertRaises(IndexError, getattr(v, self.methodname), (0, 1))
def test_error_1(self):
v = random_value_array(4, 5)
self.assertRaises(aobj.HFArrayError, getattr(v, self.methodname),
None)
def test_index_error_dont_raise(self):
v = random_value_array(4, 5, minsize=2)
method = getattr(v, self.methodname)
q = method("NONEXISTING", dimerror=False)
self.assertAllclose(q, v)
def test_index_error(self):
v = random_value_array(4, 5, minsize=2)
method = getattr(v, self.methodname)
self.assertRaises(IndexError, method, "NONEXISTING")
def test_3(self):
v, = aobj.make_same_dims_list([random_value_array(4, 5)])
a = np.array(v)
facit = np.sqrt((abs(a) ** 2).sum(1))
res = v.rss(1)
self.assertAllclose(res, facit)
