def test_read_ang(self, ref_path, mode):
if mode == 'path':
new = Table.load_ang(ref_path / 'simple.ang')
elif mode == 'str':
new = Table.load_ang(str(ref_path / 'simple.ang'))
assert new.data.shape == (4,10) and \
new.labels == ['eu', 'pos', 'IQ', 'CI', 'ID', 'intensity', 'fit']
def test_sort(self):
t = Table(np.array([[0,1,],[2,1,]]),
{'v':(2,)},
['test data'])\
.add('s',np.array(['b','a']))\
.sort_by('s')
assert np.all(t.get('v')[:, 0] == np.array([2, 0]))
def test_write_read(self, default, tmp_path, mode):
default.save(tmp_path / 'default.txt')
if mode == 'path':
new = Table.load(tmp_path / 'default.txt')
elif mode == 'str':
new = Table.load(str(tmp_path / 'default.txt'))
assert all(default.data == new.data) and default.shapes == new.shapes
def test_join_invalid(self):
x = np.random.random((5, 13))
a = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
with pytest.raises(KeyError):
a.join(a)
def test_append(self):
x = np.random.random((5, 13))
a = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
b = a.append(a)
assert np.array_equal(b.data[:5].to_numpy(), b.data[5:].to_numpy())
def test_relationship_reference(self, update, ref_path, model, lattice):
reference = ref_path / f'{lattice}_{model}.txt'
o = Orientation(lattice=lattice)
eu = o.related(model).as_Euler_angles(degrees=True)
if update:
coords = np.array([(1, i + 1) for i, x in enumerate(eu)])
Table(eu,{'Eulers':(3,)})\
.add('pos',coords)\
.save(reference)
assert np.allclose(eu, Table.load(reference).get('Eulers'))
def test_from_table(self):
cells = np.random.randint(60,100,3)
size = np.ones(3)+np.random.rand(3)
coords = grid_filters.coordinates0_point(cells,size).reshape(-1,3,order='F')
z=np.ones(cells.prod())
z[cells[:2].prod()*int(cells[2]/2):]=0
t = Table(np.column_stack((coords,z)),{'coords':3,'z':1})
t = t.add('indicator',t.get('coords')[:,0])
g = Grid.from_table(t,'coords',['indicator','z'])
assert g.N_materials == g.cells[0]*2 and (g.material[:,:,-1]-g.material[:,:,0] == cells[0]).all()
def test_sort_scalar(self):
x = np.random.random((5, 13))
t = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
unsort = t.get('s')
sort = t.sort_by('s').get('s')
assert np.all(np.sort(unsort, 0) == sort)
def test_rename_equivalent(self):
x = np.random.random((5, 13))
t = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
s = t.get('s')
u = t.rename('s', 'u').get('u')
assert np.all(s == u)
def test_Schmid(self, update, ref_path, lattice, mode):
L = Orientation(lattice=lattice)
reference = ref_path / f'{lattice}_{mode}.txt'
P = L.Schmid(mode)
if update:
table = Table(P.reshape(-1, 9), {'Schmid': (
3,
3,
)})
table.save(reference)
assert np.allclose(P, Table.load(reference).get('Schmid'))
def test_Schmid(self, update, ref_path, lattice):
O = Orientation(lattice=lattice) # noqa
for mode in ['slip', 'twin']:
reference = ref_path / f'{lattice}_{mode}.txt'
P = O.Schmid(N_slip='*') if mode == 'slip' else O.Schmid(
N_twin='*')
if update:
table = Table(P.reshape(-1, 9), {'Schmid': (
3,
3,
)})
table.save(reference)
assert np.allclose(P, Table.load(reference).get('Schmid'))
def test_append_invalid(self):
x = np.random.random((5, 13))
a = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
b = Table(x, {
'F': (3, 3),
'u': (3, ),
's': (1, )
}, ['random test data'])
with pytest.raises(KeyError):
a.append(b)
def default():
"""Simple Table."""
x = np.ones((5, 13), dtype=float)
return Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['test data', 'contains five rows of only ones'])
def test_from_table_recover(self,tmp_path):
cells = np.random.randint(60,100,3)
size = np.ones(3)+np.random.rand(3)
s = seeds.from_random(size,np.random.randint(60,100))
grid = Grid.from_Voronoi_tessellation(cells,size,s)
coords = grid_filters.coordinates0_point(cells,size)
t = Table(np.column_stack((coords.reshape(-1,3,order='F'),grid.material.flatten(order='F'))),{'c':3,'m':1})
assert grid_equal(grid.sort().renumber(),Grid.from_table(t,'c',['m']))
def test_from_table(self):
grid = np.random.randint(60,100,3)
size = np.ones(3)+np.random.rand(3)
coords = grid_filters.cell_coord0(grid,size).reshape(-1,3,order='F')
z=np.ones(grid.prod())
z[grid[:2].prod()*int(grid[2]/2):]=0
t = Table(np.column_stack((coords,z)),{'coords':3,'z':1})
g = Geom.from_table(t,'coords',['1_coords','z'])
assert g.N_materials == g.grid[0]*2 and (g.material[:,:,-1]-g.material[:,:,0] == grid[0]).all()
def test_join(self):
x = np.random.random((5, 13))
a = Table(x, {
'F': (3, 3),
'v': (3, ),
's': (1, )
}, ['random test data'])
y = np.random.random((5, 3))
b = Table(y, {'u': (3, )}, ['random test data'])
a.join(b)
assert np.array_equal(a.get('u'), b.get('u'))
def test_from_table(self):
N = np.random.randint(3,10)
a = np.vstack((np.hstack((np.arange(N),np.arange(N)[::-1])),
np.ones(N*2),np.zeros(N*2),np.ones(N*2),np.ones(N*2),
np.ones(N*2),
)).T
t = Table(a,{'varying':1,'constant':4,'ones':1})
c = ConfigMaterial.from_table(t,**{'phase':'varying','O':'constant','homogenization':'ones'})
assert len(c['material']) == N
for i,m in enumerate(c['material']):
assert m['homogenization'] == 1 and (m['constituents'][0]['O'] == [1,0,1,1]).all()
def test_sort_component(self):
x = np.random.random((5, 12))
t = Table(x, {'F': (3, 3), 'v': (3, )}, ['random test data'])
unsort = t.get('4_F')
t.sort_by('4_F')
sort = t.get('4_F')
assert np.all(np.sort(unsort, 0) == sort)
def test_sort(self):
t = Table(np.array([[
0,
1,
], [
2,
1,
]]), {'v': (2, )}, ['test data'])
t.add('s', np.array(['b', 'a']))
t.sort_by('s')
assert np.all(t.get('1_v') == np.array([2, 0]).reshape(2, 1))
def test_from_table(self):
N = np.random.randint(3, 10)
a = np.vstack((np.hstack((np.arange(N), np.arange(N)[::-1])),
np.ones(N * 2), np.zeros(N * 2), np.ones(N * 2))).T
t = Table(a, {'varying': 2, 'constant': 2})
c = ConfigMaterial.from_table(t,
constituents={
'a': 'varying',
'b': '1_constant'
},
c='2_constant')
assert len(c['material']) == N
for i, m in enumerate(c['material']):
c = m['constituents'][0]
assert m['c'] == 1 and c['b'] == 0 and c['a'] == [i, 1]
def test_ODF_cell(self, reference_dir, fractions, degrees, N):
steps = np.array([144, 36, 36])
limits = np.array([360., 90., 90.])
rng = tuple(zip(np.zeros(3), limits))
weights = Table.load(
reference_dir /
'ODF_experimental_cell.txt').get('intensity').flatten()
Eulers = grid_filters.cell_coord0(steps, limits)
Eulers = np.radians(Eulers) if not degrees else Eulers
Eulers_r = Rotation.from_ODF(weights, Eulers.reshape(-1, 3, order='F'),
N, degrees, fractions).as_Eulers(True)
weights_r = np.histogramdd(
Eulers_r, steps, rng)[0].flatten(order='F') / N * np.sum(weights)
if fractions: assert np.sqrt(((weights_r - weights)**2).mean()) < 4
def test_relationship_reference(self, update, reference_dir, model,
lattice):
reference = os.path.join(reference_dir, f'{lattice}_{model}.txt')
ori = Orientation(Rotation(), lattice)
eu = np.array(
[o.rotation.as_Eulers(degrees=True) for o in ori.related(model)])
if update:
coords = np.array([(1, i + 1) for i, x in enumerate(eu)])
table = Table(eu, {'Eulers': (3, )})
table = table.add('pos', coords)
table.save(reference)
assert np.allclose(eu, Table.load(reference).get('Eulers'))
def test_ODF_node(self, reference_dir, degrees, N):
steps = np.array([144, 36, 36])
limits = np.array([360., 90., 90.])
rng = tuple(zip(-limits / steps * .5, limits - limits / steps * .5))
weights = Table.load(reference_dir /
'ODF_experimental.txt').get('intensity')
weights = weights.reshape(steps + 1,
order='F')[:-1, :-1, :-1].reshape(-1,
order='F')
Eulers = grid_filters.node_coord0(steps, limits)[:-1, :-1, :-1]
Eulers = np.radians(Eulers) if not degrees else Eulers
Eulers_r = Rotation.from_ODF(weights, Eulers.reshape(-1, 3, order='F'),
N, degrees).as_Eulers(True)
weights_r = np.histogramdd(
Eulers_r, steps, rng)[0].flatten(order='F') / N * np.sum(weights)
assert np.sqrt(((weights_r - weights)**2).mean()) < 5
def test_read_ang_file(self, ref_path):
f = open(ref_path / 'simple.ang')
new = Table.load_ang(f)
assert new.data.shape == (4,10) and \
new.labels == ['eu', 'pos', 'IQ', 'CI', 'ID', 'intensity', 'fit']
def test_read_strange(self, reference_dir, fname):
with open(os.path.join(reference_dir, fname)) as f:
Table.from_ASCII(f)
def test_read_strange(self, ref_path, fname):
with open(ref_path / fname) as f:
Table.load(f)
def test_invalid_initialization(self):
x = np.random.random((5, 10))
with pytest.raises(ValueError):
Table(x, {'F': (3, 3)})
def test_sort_revert(self):
x = np.random.random((5, 12))
t = Table(x, {'F': (3, 3), 'v': (3, )}, ['random test data'])
sort = t.sort_by('F[1,0]', ascending=False).get('F')[:, 1, 0]
assert np.all(np.sort(sort, 0) == sort[::-1])
def test_write_read_file(self, default, tmp_path):
with open(tmp_path / 'default.txt', 'w') as f:
default.save(f)
with open(tmp_path / 'default.txt') as f:
new = Table.load(f)
assert all(default.data == new.data) and default.shapes == new.shapes
def test_len(self, N):
assert len(Table(np.random.rand(N, 3), {'X': 3})) == N
