def test_percent_variance_exceeds_limit_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1,
size=(7, 7),
n_phases=3,
volume_fraction=(0.3, 0.3, 0.4),
percent_variance=0.5)
def test_mask_two_samples():
from pymks import DiscreteIndicatorBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
X = make_microstructure(n_samples=2,
n_phases=2,
size=(3, 3),
grain_size=(2, 2),
seed=99)
basis = DiscreteIndicatorBasis(n_states=2)
mask = np.ones(X.shape)
mask[:, 0, 0] = 0.
X_corr = correlate(X, basis, confidence_index=mask)
X_result = np.array([[[[1 / 3., 1 / 3., 1 / 3.], [1 / 5., 1 / 5., 1 / 5.],
[1 / 4., 1 / 4., 0]],
[[1 / 5., 1 / 5., 2 / 5.], [1 / 2., 1 / 2., 0],
[1 / 5., 1 / 5., 1 / 5.]],
[[1 / 4., 1 / 4., 1 / 2.], [1 / 5., 1 / 5., 2 / 5.],
[1 / 3., 1 / 3., 0]]],
[[[0., 0., 1 / 3.], [2 / 5., 3 / 5., 0.],
[0., 0., 1 / 2.]],
[[0., 0., 2 / 5.], [3 / 8., 5 / 8., 0],
[0., 0., 3 / 5.]],
[[0., 0., 1 / 2.], [2 / 5., 3 / 5., 0.],
[0., 0., 2 / 3.]]]])
assert np.allclose(X_corr, X_result)
def test_mask_two_samples():
from pymks import DiscreteIndicatorBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
X = make_microstructure(n_samples=2, n_phases=2, size=(3, 3), grain_size=(2, 2), seed=99)
basis = DiscreteIndicatorBasis(n_states=2)
X_ = basis.discretize(X)
mask = np.ones(X.shape)
mask[:, 0, 0] = 0.0
X_corr = correlate(X_, confidence_index=mask)
X_result = np.array(
[
[
[[1 / 3.0, 1 / 3.0, 1 / 3.0], [1 / 5.0, 1 / 5.0, 1 / 5.0], [1 / 4.0, 1 / 4.0, 0]],
[[1 / 5.0, 1 / 5.0, 2 / 5.0], [1 / 2.0, 1 / 2.0, 0], [1 / 5.0, 1 / 5.0, 1 / 5.0]],
[[1 / 4.0, 1 / 4.0, 1 / 2.0], [1 / 5.0, 1 / 5.0, 2 / 5.0], [1 / 3.0, 1 / 3.0, 0]],
],
[
[[0.0, 0.0, 1 / 3.0], [2 / 5.0, 3 / 5.0, 0.0], [0.0, 0.0, 1 / 2.0]],
[[0.0, 0.0, 2 / 5.0], [3 / 8.0, 5 / 8.0, 0], [0.0, 0.0, 3 / 5.0]],
[[0.0, 0.0, 1 / 2.0], [2 / 5.0, 3 / 5.0, 0.0], [0.0, 0.0, 2 / 3.0]],
],
]
)
print np.round(X_corr, decimals=4)
print X_result
assert np.allclose(X_corr, X_result)
def test_mask_two_samples():
from pymks import DiscreteIndicatorBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
X = make_microstructure(n_samples=2, n_phases=2, size=(3, 3),
grain_size=(2, 2), seed=99)
basis = DiscreteIndicatorBasis(n_states=2)
mask = np.ones(X.shape)
mask[:, 0, 0] = 0.
X_corr = correlate(X, basis, confidence_index=mask)
X_result = np.array([[[[1 / 3., 1 / 3., 1 / 3.],
[1 / 5., 1 / 5., 1 / 5.],
[1 / 4., 1 / 4., 0]],
[[1 / 5., 1 / 5., 2 / 5.],
[1 / 2., 1 / 2., 0],
[1 / 5., 1 / 5., 1 / 5.]],
[[1 / 4., 1 / 4., 1 / 2.],
[1 / 5., 1 / 5., 2 / 5.],
[1 / 3., 1 / 3., 0]]],
[[[0., 0., 1 / 3.],
[2 / 5., 3 / 5., 0.],
[0., 0., 1 / 2.]],
[[0., 0., 2 / 5.],
[3 / 8., 5 / 8., 0],
[0., 0., 3 / 5.]],
[[0., 0., 1 / 2.],
[2 / 5., 3 / 5., 0.],
[0., 0., 2 / 3.]]]])
assert np.allclose(X_corr, X_result)
def test_percent_variance():
X = make_microstructure(n_samples=1,
n_phases=3,
volume_fraction=(0.3, 0.2, 0.5),
percent_variance=.2)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.09, atol=1e-2)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.57, atol=1e-2)
def test_3D_volume_fraction():
X = make_microstructure(n_samples=1,
n_phases=3,
size=(21, 21, 21),
volume_fraction=(0.3, 0.1, 0.6))
assert np.allclose(np.sum(X == 0) / float(X.size), 0.3, rtol=1e-3)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.1, rtol=1e-3)
def test_3D_percent_variance():
X = make_microstructure(n_samples=1,
n_phases=3,
size=(21, 21, 21),
volume_fraction=(0.7, 0.1, 0.2),
percent_variance=.2)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.05, atol=1e-2)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.2, atol=1e-2)
def test_stats_in_parallel():
from pymks.bases import PrimitiveBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
p_basis = PrimitiveBasis(5)
X = make_microstructure(n_samples=5, n_phases=3)
X_corr_actual = correlate(X, p_basis)
for i in range(1, 4):
X_corr_test = correlate(X, p_basis, n_jobs=i)
assert np.allclose(X_corr_actual, X_corr_test)
def test_3D_percent_variance():
volume_fraction = (0.7, 0.1, 0.2)
percent_variance = .2
X = make_microstructure(n_samples=1, n_phases=3, size=(21, 21, 21),
volume_fraction=volume_fraction,
percent_variance=percent_variance)
vf_1 = np.sum(X == 1) / float(X.size)
vf_2 = np.sum(X == 2) / float(X.size)
assert vf_1 > volume_fraction[1] - percent_variance
assert vf_1 < volume_fraction[1] + percent_variance
assert vf_2 > volume_fraction[2] - percent_variance
assert vf_2 < volume_fraction[2] + percent_variance
def test_stats_in_parallel():
import time
from pymks.bases import PrimitiveBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
p_basis = PrimitiveBasis(5)
if p_basis._pyfftw:
X = make_microstructure(n_samples=5, n_phases=3)
t = []
for i in range(1, 4):
t_start = time.time()
correlate(X, p_basis, n_jobs=i)
t.append(time.time() - t_start)
assert t == sorted(t, reverse=True)
else:
pass
def test_stats_in_parallel():
import time
from pymks.bases import PrimitiveBasis
from pymks.stats import correlate
from pymks.datasets import make_microstructure
p_basis = PrimitiveBasis(5)
if p_basis._pyfftw:
X = make_microstructure(n_samples=5, n_phases=3)
t = []
for i in range(1, 4):
t_start = time.time()
correlate(X, p_basis, n_jobs=i)
t.append(time.time() - t_start)
assert t == sorted(t, reverse=True)
else:
pass
def test_volume_fraction_failure():
make_microstructure(n_samples=1, volume_fraction=(0.3, 0.6))
def test_volume_fraction_with_n_phases_failure():
make_microstructure(n_samples=1, size=(7, 7), n_phases=3,
volume_fraction=(0.5, 0.5))
def test_volume_fraction():
X = make_microstructure(n_samples=1,
n_phases=3,
volume_fraction=(0.3, 0.2, 0.5))
assert np.allclose(np.sum(X == 1) / float(X.size), 0.2, rtol=1e-4)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.5, atol=1e-4)
def test_size_and_grain_size_failure():
make_microstructure(n_samples=1, size=(7, 7), grain_size=(8, 1))
def test_volume_fraction_with_n_phases_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1,
size=(7, 7),
n_phases=3,
volume_fraction=(0.5, 0.5))
def test_volume_fraction_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, volume_fraction=(0.3, 0.6))
def test_volume_fraction_with_n_phases_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, size=(7, 7), n_phases=3,
volume_fraction=(0.5, 0.5))
from AbaqusIO import generateAbaqusInp
from pymks.datasets import make_microstructure
X = make_microstructure()
generateAbaqusInp('test_microstructure', X[0], elastic_modulus=(120, 80),
poissions_ratio=(0.3, 0.3))
def test_size_and_grain_size_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, size=(7, 7), grain_size=(8, 1))
def test_3D_percent_variance():
X = make_microstructure(n_samples=1, n_phases=3, size=(21, 21, 21),
volume_fraction=(0.7, 0.1, 0.2),
percent_variance=.2)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.05, atol=1e-2)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.2, atol=1e-2)
def test_3D_volume_fraction():
X = make_microstructure(n_samples=1, n_phases=3, size=(21, 21, 21),
volume_fraction=(0.3, 0.1, 0.6))
assert np.allclose(np.sum(X == 0) / float(X.size), 0.3, rtol=1e-3)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.1, rtol=1e-3)
from pymks.datasets import make_microstructure
from AbaqusIO import generateAbaqusInp
n_phases = 2
grain_size1 = (20, 2, 2)
size = (21, 21, 21)
Long_fiber_x = make_microstructure(n_samples=2, size=size,
n_phases=n_phases, grain_size=grain_size1,
seed=1)
Ab_fiber = Long_fiber_x+1
generateAbaqusInp('test_microstructure', Ab_fiber[1],
elastic_modulus=(120, 80),
poissions_ratio=(0.3, 0.3))
print "Done"
def test_volume_fraction():
X = make_microstructure(n_samples=1, n_phases=3,
volume_fraction=(0.3, 0.2, 0.5))
assert np.allclose(np.sum(X == 1) / float(X.size), 0.2, rtol=1e-4)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.5, atol=1e-4)
def test_percent_variance_exceeds_limit_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, size=(7, 7), n_phases=3,
volume_fraction=(0.3, 0.3, 0.4), percent_variance=0.5)
def test_size_and_grain_size_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, size=(7, 7), grain_size=(8, 1))
def test_percent_variance():
X = make_microstructure(n_samples=1, n_phases=3,
volume_fraction=(0.3, 0.2, 0.5),
percent_variance=.2)
assert np.allclose(np.sum(X == 1) / float(X.size), 0.09, atol=1e-2)
assert np.allclose(np.sum(X == 2) / float(X.size), 0.57, atol=1e-2)
def test_volume_fraction_failure():
with pytest.raises(RuntimeError):
make_microstructure(n_samples=1, volume_fraction=(0.3, 0.6))