def test_astensor(self):
# astensor converts python object to ctf tensor
a0 = ctf.astensor((1,2,3))
a0 = ctf.astensor([1,2.,3])
a0 = ctf.astensor([(1,2), (3,4)])
a0 = ctf.astensor(numpy.arange(3))
a0 = ctf.astensor([numpy.array((1,2)), numpy.array((3,4))+1j])
a1 = ctf.astensor(a0)
a1[:] = 0
self.assertTrue(ctf.all(a0==0))
self.assertTrue(ctf.all(a1==0))
a0 = numpy.asarray(a1)
# self.assertTrue(ctf.asarray(a0).__class__ == ctf.astensor(a0).__class__)
a0 = ctf.astensor([1,2.,3], dtype='D')
self.assertTrue(a0.dtype == numpy.complex128)
with self.assertRaises(TypeError):
ctf.astensor([1j,2j], dtype='d')
a0 = numpy.arange(4.).reshape(2,2)
a1 = ctf.to_nparray(ctf.from_nparray(a0))
self.assertTrue(ctf.all(a0==a1))
try:
a1 = ctf.from_nparray(a1).to_nparray()
self.assertTrue(ctf.all(a0==a1))
except AttributeError:
pass
a0 = ctf.from_nparray(numpy.arange(3))
a1 = ctf.from_nparray(a0)
a1[:] = 0
self.assertTrue(ctf.all(a0==0))
self.assertTrue(ctf.all(a1==0))
a0 = numpy.arange(6).reshape(2,3)
a1 = ctf.array(a0)
self.assertTrue(ctf.all(a0==a1))
self.assertTrue(ctf.all(a1==a0))
a1 = ctf.array(a0, copy=False)
self.assertTrue(ctf.all(a1==0))
def test_svd(self):
m = 9
n = 5
k = 5
for dt in [numpy.float32, numpy.float64]:
A = ctf.random.random((m,n))
A = ctf.astensor(A,dtype=dt)
[U,S,VT]=ctf.svd(A,k)
[U1,S1,VT1]=la.svd(ctf.to_nparray(A),full_matrices=False)
self.assertTrue(allclose(A, ctf.dot(U,ctf.dot(ctf.diag(S),VT))))
self.assertTrue(allclose(ctf.eye(k), ctf.dot(U.T(), U)))
self.assertTrue(allclose(ctf.eye(k), ctf.dot(VT, VT.T())))
A = ctf.tensor((m,n),dtype=numpy.complex64)
rA = ctf.tensor((m,n),dtype=numpy.float32)
rA.fill_random()
A.real(rA)
iA = ctf.tensor((m,n),dtype=numpy.float32)
iA.fill_random()
A.imag(iA)
[U,S,VT]=ctf.svd(A,k)
self.assertTrue(allclose(A, ctf.dot(U,ctf.dot(ctf.diag(S),VT))))
self.assertTrue(allclose(ctf.eye(k,dtype=numpy.complex64), ctf.dot(ctf.conj(U.T()), U)))
self.assertTrue(allclose(ctf.eye(k,dtype=numpy.complex64), ctf.dot(VT, ctf.conj(VT.T()))))
A = ctf.tensor((m,n),dtype=numpy.complex128)
rA = ctf.tensor((m,n),dtype=numpy.float64)
rA.fill_random()
A.real(rA)
iA = ctf.tensor((m,n),dtype=numpy.float64)
iA.fill_random()
A.imag(iA)
[U,S,VT]=ctf.svd(A,k)
self.assertTrue(allclose(A, ctf.dot(U,ctf.dot(ctf.diag(S),VT))))
self.assertTrue(allclose(ctf.eye(k,dtype=numpy.complex128), ctf.dot(ctf.conj(U.T()), U)))
self.assertTrue(allclose(ctf.eye(k,dtype=numpy.complex128), ctf.dot(VT, ctf.conj(VT.T()))))
def allclose(a, b):
return abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() < 1e-14
def allclose(a, b):
if abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() > 1e-4:
print(ctf.to_nparray(a))
print(ctf.to_nparray(b))
return abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() <= 1e-4
def allclose(a, b):
return abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() <= 1e-5
# eris.foo = eris.fock[:,:nocc,:nocc] * 0
# eris.fvv = eris.fock[:,nocc:,nocc:] * 0
# eris.fov = eris.fock[:,:nocc,nocc:]
eris = mycc.ao2mo()
# print(abs(ctf.to_nparray(eris1.oooo) - eris.oooo).max())
# print(abs(ctf.to_nparray(eris1.ooov) - eris.ooov).max())
# print(abs(ctf.to_nparray(eris1.oovv) - eris.oovv).max())
# print(abs(ctf.to_nparray(eris1.ovov) - eris.ovov).max())
# print(abs(ctf.to_nparray(eris1.voov) - eris.voov).max())
# print(abs(ctf.to_nparray(eris1.vovv) - eris.vovv).max())
# print(abs(ctf.to_nparray(eris1.vvvv) - eris.vvvv).max())
emp2, t1, t2 = mycc.init_amps(eris)
print(emp2 - -0.131341714277)
print(
lib.finger(ctf.to_nparray(t2)) - (-0.0576606747244 + 0.0336759095279j))
nkpts = kpts.shape[0]
numpy.random.seed(1)
no = mycc.nocc
nv = mycc.nmo - no
t2 = eris.oovv
t1 = (numpy.random.random((nkpts, no, nv)) - .5 + numpy.random.random(
(nkpts, no, nv)) * .1j)
t1 = ctf.astensor(t1)
t2 = ctf.astensor(t2)
t1b, t2b = mycc.update_amps(t1, t2, eris)
print(
lib.finger(ctf.to_nparray(t1b)) -
(0.17663716146287139 - 0.16562727702376817j))
def allclose(a, b):
if abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() > 1e-4:
print(ctf.to_nparray(a))
print(ctf.to_nparray(b))
return abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() <= 1e-4
def allclose(a, b):
#if abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() > 1e-3:
# print(ctf.to_nparray(a))
# print(ctf.to_nparray(b))
return (ctf.to_nparray(a).shape == ctf.to_nparray(b).shape
) and abs(ctf.to_nparray(a) - ctf.to_nparray(b)).sum() <= 1e-3