diff --git a/python/damask/_orientation.py b/python/damask/_orientation.py index dcc139b7c..4721143da 100644 --- a/python/damask/_orientation.py +++ b/python/damask/_orientation.py @@ -448,9 +448,12 @@ class Orientation(Rotation,Crystal): elif self.family == 'orthorhombic': return (np.prod(1. >= rho_abs,axis=-1)).astype(bool) 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: - return np.all(np.isfinite(rho_abs),axis=-1) + raise TypeError(f'unknown symmetry "{self.family}"') @property diff --git a/python/damask/_rotation.py b/python/damask/_rotation.py index 61529eb46..f93b3b012 100644 --- a/python/damask/_rotation.py +++ b/python/damask/_rotation.py @@ -1372,7 +1372,7 @@ class Rotation: w[np.isclose(w[...,0],1.0+0.0j),1:] = 0. w[np.isclose(w[...,1],1.0+0.0j),2:] = 0. 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.abs(np.real(vr[np.isclose(w,1.0+0.0j)]).reshape(om.shape[:-2]+(3,))) \ *np.sign(diag_delta)) @@ -1581,14 +1581,13 @@ class Rotation: @staticmethod def _ho2ax(ho: np.ndarray) -> np.ndarray: """Homochoric vector to axis–angle pair.""" - tfit = np.array([+1.0000000000018852, -0.5000000002194847, - -0.024999992127593126, -0.003928701544781374, - -0.0008152701535450438, -0.0002009500426119712, - -0.00002397986776071756, -0.00008202868926605841, - +0.00012448715042090092, -0.0001749114214822577, - +0.0001703481934140054, -0.00012062065004116828, - +0.000059719705868660826, -0.00001980756723965647, - +0.000003953714684212874, -0.00000036555001439719544]) + tfit = np.array([+0.9999999999999968, -0.49999999999986866, -0.025000000000632055, + -0.003928571496460683, -0.0008164666077062752, -0.00019411896443261646, + -0.00004985822229871769, -0.000014164962366386031, -1.9000248160936107e-6, + -5.72184549898506e-6, +7.772149920658778e-6, -0.00001053483452909705, + +9.528014229335313e-6, -5.660288876265125e-6, +1.2844901692764126e-6, + +1.1255185726258763e-6, -1.3834391419956455e-6, +7.513691751164847e-7, + -2.401996891720091e-7, +4.386887017466388e-8, -3.5917775353564864e-9]) hmag_squared = np.sum(ho**2.,axis=-1,keepdims=True) s = np.sum(tfit*hmag_squared**np.arange(len(tfit)),axis=-1,keepdims=True) with np.errstate(invalid='ignore'): @@ -1679,7 +1678,7 @@ class Rotation: """ 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 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]) \ diff --git a/python/tests/test_Orientation.py b/python/tests/test_Orientation.py index 5f9b83e70..2cb97d252 100644 --- a/python/tests/test_Orientation.py +++ b/python/tests/test_Orientation.py @@ -224,11 +224,11 @@ class TestOrientation: @pytest.mark.parametrize('family',crystal_families) 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) size = np.ones(3)*np.pi**(2./3.) 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 @pytest.mark.parametrize('family',crystal_families) diff --git a/python/tests/test_Rotation.py b/python/tests/test_Rotation.py index c9dfc68b8..8b1bd0de8 100644 --- a/python/tests/test_Rotation.py +++ b/python/tests/test_Rotation.py @@ -301,14 +301,13 @@ def ro2ho(ro): #---------- Homochoric vector---------- def ho2ax(ho): """Homochoric vector to axis angle pair.""" - tfit = np.array([+1.0000000000018852, -0.5000000002194847, - -0.024999992127593126, -0.003928701544781374, - -0.0008152701535450438, -0.0002009500426119712, - -0.00002397986776071756, -0.00008202868926605841, - +0.00012448715042090092, -0.0001749114214822577, - +0.0001703481934140054, -0.00012062065004116828, - +0.000059719705868660826, -0.00001980756723965647, - +0.000003953714684212874, -0.00000036555001439719544]) + tfit = np.array([+0.9999999999999968, -0.49999999999986866, -0.025000000000632055, + -0.003928571496460683, -0.0008164666077062752, -0.00019411896443261646, + -0.00004985822229871769, -0.000014164962366386031, -1.9000248160936107e-6, + -5.72184549898506e-6, +7.772149920658778e-6, -0.00001053483452909705, + +9.528014229335313e-6, -5.660288876265125e-6, +1.2844901692764126e-6, + +1.1255185726258763e-6, -1.3834391419956455e-6, +7.513691751164847e-7, + -2.401996891720091e-7, +4.386887017466388e-8, -3.5917775353564864e-9]) # normalize h and store the magnitude hmag_squared = np.sum(ho**2.) if iszero(hmag_squared):