def test_main(self):
with h5py.File('Cartesian3d_random.hdf5', 'r') as data:
shape = data['/shape'][...]
mat = GMat.Matrix(shape[0], shape[1])
I = data['/cusp/I'][...]
idx = data['/cusp/idx'][...]
K = data['/cusp/K'][...]
G = data['/cusp/G'][...]
epsy = data['/cusp/epsy'][...]
mat.setCusp(I, idx, K, G, epsy)
I = data['/smooth/I'][...]
idx = data['/smooth/idx'][...]
K = data['/smooth/K'][...]
G = data['/smooth/G'][...]
epsy = data['/smooth/epsy'][...]
mat.setSmooth(I, idx, K, G, epsy)
I = data['/elastic/I'][...]
idx = data['/elastic/idx'][...]
K = data['/elastic/K'][...]
G = data['/elastic/G'][...]
mat.setElastic(I, idx, K, G)
for i in range(20):
GradU = data['/random/{0:d}/GradU'.format(i)][...]
Eps = np.einsum('...ijkl,...lk->...ij', mat.I4s(), GradU)
idx = mat.Find(Eps)
self.assertTrue(
np.allclose(mat.Stress(Eps),
data['/random/{0:d}/Stress'.format(i)][...]))
self.assertTrue(
np.allclose(
mat.Tangent(Eps)[1],
data['/random/{0:d}/Tangent'.format(i)][...]))
self.assertTrue(
np.allclose(
mat.Epsy(idx),
data['/random/{0:d}/CurrentYieldLeft'.format(i)][...]))
self.assertTrue(
np.allclose(
mat.Epsy(idx + 1), data[
'/random/{0:d}/CurrentYieldRight'.format(i)][...]))
self.assertTrue(
np.all(
mat.Find(Eps) == data[
'/random/{0:d}/CurrentIndex'.format(i)][...]))
def test_Array2d(self):
K = 12.3
G = 45.6
gamma = 0.02
epsm = 0.12
Eps = np.array([[epsm, gamma, 0.0], [gamma, epsm, 0.0],
[0.0, 0.0, epsm]])
Sig_elas = np.array([[3.0 * K * epsm, 2.0 * G * gamma, 0.0],
[2.0 * G * gamma, 3.0 * K * epsm, 0.0],
[0.0, 0.0, 3.0 * K * epsm]])
Sig_plas = np.array([[3.0 * K * epsm, 0.0, 0.0],
[0.0, 3.0 * K * epsm, 0.0],
[0.0, 0.0, 3.0 * K * epsm]])
nelem = 3
nip = 2
mat = GMat.Array2d([nelem, nip])
ndim = 3
I = np.zeros([nelem, nip], dtype='int')
I[0, :] = 1
mat.setElastic(I, K, G)
I = np.zeros([nelem, nip], dtype='int')
I[1, :] = 1
mat.setCusp(I, K, G, 0.01 + 0.02 * np.arange(100))
I = np.zeros([nelem, nip], dtype='int')
I[2, :] = 1
mat.setSmooth(I, K, G, 0.01 + 0.02 * np.arange(100))
eps = np.zeros((nelem, nip, ndim, ndim))
sig = np.zeros((nelem, nip, ndim, ndim))
epsp = np.zeros((nelem, nip))
for e in range(nelem):
for q in range(nip):
fac = float((e + 1) * nip + (q + 1))
eps[e, q, :, :] = fac * Eps
if e == 0:
sig[e, q, :, :] = fac * Sig_elas
epsp[e, q] = 0.0
else:
sig[e, q, :, :] = fac * Sig_plas
epsp[e, q] = fac * gamma
mat.setStrain(eps)
self.assertTrue(np.allclose(mat.Stress(), sig))
self.assertTrue(np.allclose(mat.Epsp(), epsp))
def test_Elastic(self):
K = 12.3
G = 45.6
gamma = 0.02
epsm = 0.12
Eps = np.array([[epsm, gamma, 0.0], [gamma, epsm, 0.0],
[0.0, 0.0, epsm]])
Sig = np.array([[3.0 * K * epsm, 2.0 * G * gamma, 0.0],
[2.0 * G * gamma, 3.0 * K * epsm, 0.0],
[0.0, 0.0, 3.0 * K * epsm]])
self.assertTrue(np.isclose(float(GMat.Epsd(Eps)), gamma))
mat = GMat.Elastic(K, G)
mat.setStrain(Eps)
self.assertTrue(np.allclose(mat.Stress(), Sig))
def test_Smooth(self):
K = 12.3
G = 45.6
gamma = 0.02
epsm = 0.12
Eps = np.array([[epsm, gamma, 0.0], [gamma, epsm, 0.0],
[0.0, 0.0, epsm]])
Sig = np.array([[3.0 * K * epsm, 0.0, 0.0], [0.0, 3.0 * K * epsm, 0.0],
[0.0, 0.0, 3.0 * K * epsm]])
self.assertTrue(np.isclose(float(GMat.Epsd(Eps)), gamma))
mat = GMat.Smooth(K, G, [0.01, 0.03, 0.10])
mat.setStrain(Eps)
self.assertTrue(np.allclose(mat.Stress(), Sig))
self.assertTrue(np.isclose(mat.epsp(), 0.02))
self.assertTrue(mat.currentIndex() == 1)
with h5py.File('Cartesian3d_random.hdf5', 'w') as data:
nelem = 1000
nip = 4
iden = 3.0 * np.random.random([nelem, nip])
iden = np.where(iden < 1.0, 0.0, iden)
iden = np.where((iden >= 1.0) * (iden < 2.0), 1.0, iden)
iden = np.where(iden >= 2.0, 2.0, iden)
iden = iden.astype(np.int)
shape = np.array([nelem, nip], np.int)
data['/shape'] = shape
mat = GMat.Array2d(shape)
I = np.where(iden == 0, 1, 0).astype(np.int)
n = np.sum(I)
idx = np.zeros(I.size, np.int)
idx[np.argwhere(I.ravel() == 1).ravel()] = np.arange(n)
idx = idx.reshape(I.shape)
epsy = np.cumsum(np.random.random([n, 500]), 1)
K = np.ones(n)
G = np.ones(n)
data['/cusp/I'] = I
data['/cusp/idx'] = idx
data['/cusp/K'] = K
data['/cusp/G'] = G
data['/cusp/epsy'] = epsy