Merge branch '157-better-coefficients-for-cubochoric' into 'development'

Adopt 21-degree polynomial in Rotation._ho2ax

Closes #157

See merge request damask/DAMASK!602
This commit is contained in:
Philip Eisenlohr 2022-06-10 14:33:16 +00:00
commit 98b307f0c0
4 changed files with 23 additions and 22 deletions

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@ -448,9 +448,12 @@ class Orientation(Rotation,Crystal):
elif self.family == 'orthorhombic': elif self.family == 'orthorhombic':
return (np.prod(1. >= rho_abs,axis=-1)).astype(bool) return (np.prod(1. >= rho_abs,axis=-1)).astype(bool)
elif self.family == 'monoclinic': elif self.family == 'monoclinic':
return (1. >= rho_abs[...,1]).astype(bool) return np.logical_or( 1. >= rho_abs[...,1],
np.isnan(rho_abs[...,1]))
elif self.family == 'triclinic':
return np.ones(rho_abs.shape[:-1]).astype(bool)
else: else:
return np.all(np.isfinite(rho_abs),axis=-1) raise TypeError(f'unknown symmetry "{self.family}"')
@property @property

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@ -1372,7 +1372,7 @@ class Rotation:
w[np.isclose(w[...,0],1.0+0.0j),1:] = 0. w[np.isclose(w[...,0],1.0+0.0j),1:] = 0.
w[np.isclose(w[...,1],1.0+0.0j),2:] = 0. w[np.isclose(w[...,1],1.0+0.0j),2:] = 0.
vr = np.swapaxes(vr,-1,-2) vr = np.swapaxes(vr,-1,-2)
ax = np.where(np.abs(diag_delta)<1e-12, ax = np.where(np.abs(diag_delta)<1e-13,
np.real(vr[np.isclose(w,1.0+0.0j)]).reshape(om.shape[:-2]+(3,)), np.real(vr[np.isclose(w,1.0+0.0j)]).reshape(om.shape[:-2]+(3,)),
np.abs(np.real(vr[np.isclose(w,1.0+0.0j)]).reshape(om.shape[:-2]+(3,))) \ np.abs(np.real(vr[np.isclose(w,1.0+0.0j)]).reshape(om.shape[:-2]+(3,))) \
*np.sign(diag_delta)) *np.sign(diag_delta))
@ -1581,14 +1581,13 @@ class Rotation:
@staticmethod @staticmethod
def _ho2ax(ho: np.ndarray) -> np.ndarray: def _ho2ax(ho: np.ndarray) -> np.ndarray:
"""Homochoric vector to axisangle pair.""" """Homochoric vector to axisangle pair."""
tfit = np.array([+1.0000000000018852, -0.5000000002194847, tfit = np.array([+0.9999999999999968, -0.49999999999986866, -0.025000000000632055,
-0.024999992127593126, -0.003928701544781374, -0.003928571496460683, -0.0008164666077062752, -0.00019411896443261646,
-0.0008152701535450438, -0.0002009500426119712, -0.00004985822229871769, -0.000014164962366386031, -1.9000248160936107e-6,
-0.00002397986776071756, -0.00008202868926605841, -5.72184549898506e-6, +7.772149920658778e-6, -0.00001053483452909705,
+0.00012448715042090092, -0.0001749114214822577, +9.528014229335313e-6, -5.660288876265125e-6, +1.2844901692764126e-6,
+0.0001703481934140054, -0.00012062065004116828, +1.1255185726258763e-6, -1.3834391419956455e-6, +7.513691751164847e-7,
+0.000059719705868660826, -0.00001980756723965647, -2.401996891720091e-7, +4.386887017466388e-8, -3.5917775353564864e-9])
+0.000003953714684212874, -0.00000036555001439719544])
hmag_squared = np.sum(ho**2.,axis=-1,keepdims=True) hmag_squared = np.sum(ho**2.,axis=-1,keepdims=True)
s = np.sum(tfit*hmag_squared**np.arange(len(tfit)),axis=-1,keepdims=True) s = np.sum(tfit*hmag_squared**np.arange(len(tfit)),axis=-1,keepdims=True)
with np.errstate(invalid='ignore'): with np.errstate(invalid='ignore'):
@ -1679,7 +1678,7 @@ class Rotation:
""" """
with np.errstate(invalid='ignore',divide='ignore'): with np.errstate(invalid='ignore',divide='ignore'):
# get pyramide and scale by grid parameter ratio # get pyramid and scale by grid parameter ratio
XYZ = np.take_along_axis(cu,Rotation._get_pyramid_order(cu,'forward'),-1) * _sc XYZ = np.take_along_axis(cu,Rotation._get_pyramid_order(cu,'forward'),-1) * _sc
order = np.abs(XYZ[...,1:2]) <= np.abs(XYZ[...,0:1]) order = np.abs(XYZ[...,1:2]) <= np.abs(XYZ[...,0:1])
q = np.pi/12.0 * np.where(order,XYZ[...,1:2],XYZ[...,0:1]) \ q = np.pi/12.0 * np.where(order,XYZ[...,1:2],XYZ[...,0:1]) \

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@ -224,11 +224,11 @@ class TestOrientation:
@pytest.mark.parametrize('family',crystal_families) @pytest.mark.parametrize('family',crystal_families)
def test_reduced_corner_cases(self,family): def test_reduced_corner_cases(self,family):
# test whether there is always a sym-eq rotation that falls into the FZ # test whether there is always exactly one sym-eq rotation that falls into the FZ
N = np.random.randint(10,40) N = np.random.randint(10,40)
size = np.ones(3)*np.pi**(2./3.) size = np.ones(3)*np.pi**(2./3.)
grid = grid_filters.coordinates0_node([N+1,N+1,N+1],size,-size*.5) grid = grid_filters.coordinates0_node([N+1,N+1,N+1],size,-size*.5)
evenly_distributed = Orientation.from_cubochoric(x=grid[:-2,:-2,:-2],family=family) evenly_distributed = Orientation.from_cubochoric(x=grid,family=family)
assert evenly_distributed.shape == evenly_distributed.reduced.shape assert evenly_distributed.shape == evenly_distributed.reduced.shape
@pytest.mark.parametrize('family',crystal_families) @pytest.mark.parametrize('family',crystal_families)

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@ -301,14 +301,13 @@ def ro2ho(ro):
#---------- Homochoric vector---------- #---------- Homochoric vector----------
def ho2ax(ho): def ho2ax(ho):
"""Homochoric vector to axis angle pair.""" """Homochoric vector to axis angle pair."""
tfit = np.array([+1.0000000000018852, -0.5000000002194847, tfit = np.array([+0.9999999999999968, -0.49999999999986866, -0.025000000000632055,
-0.024999992127593126, -0.003928701544781374, -0.003928571496460683, -0.0008164666077062752, -0.00019411896443261646,
-0.0008152701535450438, -0.0002009500426119712, -0.00004985822229871769, -0.000014164962366386031, -1.9000248160936107e-6,
-0.00002397986776071756, -0.00008202868926605841, -5.72184549898506e-6, +7.772149920658778e-6, -0.00001053483452909705,
+0.00012448715042090092, -0.0001749114214822577, +9.528014229335313e-6, -5.660288876265125e-6, +1.2844901692764126e-6,
+0.0001703481934140054, -0.00012062065004116828, +1.1255185726258763e-6, -1.3834391419956455e-6, +7.513691751164847e-7,
+0.000059719705868660826, -0.00001980756723965647, -2.401996891720091e-7, +4.386887017466388e-8, -3.5917775353564864e-9])
+0.000003953714684212874, -0.00000036555001439719544])
# normalize h and store the magnitude # normalize h and store the magnitude
hmag_squared = np.sum(ho**2.) hmag_squared = np.sum(ho**2.)
if iszero(hmag_squared): if iszero(hmag_squared):