import time import shutil import os import sys from datetime import datetime import pytest import numpy as np import h5py from damask import Result from damask import Rotation from damask import Orientation from damask import tensor from damask import mechanics from damask import grid_filters @pytest.fixture def default(tmp_path,reference_dir): """Small Result file in temp location for modification.""" fname = '12grains6x7x8_tensionY.hdf5' shutil.copy(reference_dir/fname,tmp_path) f = Result(tmp_path/fname) f.pick('times',20.0) return f @pytest.fixture def single_phase(tmp_path,reference_dir): """Single phase Result file in temp location for modification.""" fname = '6grains6x7x8_single_phase_tensionY.hdf5' shutil.copy(reference_dir/fname,tmp_path) return Result(tmp_path/fname) @pytest.fixture def reference_dir(reference_dir_base): """Directory containing reference results.""" return reference_dir_base/'Result' class TestResult: def test_self_report(self,default): print(default) def test_pick_all(self,default): default.pick('increments',True) a = default.get_dataset_location('F') default.pick('increments','*') b = default.get_dataset_location('F') default.pick('increments',default.incs_in_range(0,np.iinfo(int).max)) c = default.get_dataset_location('F') default.pick('times',True) d = default.get_dataset_location('F') default.pick('times','*') e = default.get_dataset_location('F') default.pick('times',default.times_in_range(0.0,np.inf)) f = default.get_dataset_location('F') assert a == b == c == d == e ==f @pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations def test_pick_none(self,default,what): default.pick(what,False) a = default.get_dataset_location('F') default.pick(what,[]) b = default.get_dataset_location('F') assert a == b == [] @pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations def test_pick_more(self,default,what): default.pick(what,False) default.pick_more(what,'*') a = default.get_dataset_location('F') default.pick(what,True) b = default.get_dataset_location('F') assert a == b @pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations def test_pick_less(self,default,what): default.pick(what,True) default.pick_less(what,'*') a = default.get_dataset_location('F') default.pick(what,False) b = default.get_dataset_location('F') assert a == b == [] def test_pick_invalid(self,default): with pytest.raises(AttributeError): default.pick('invalid',True) def test_add_absolute(self,default): default.add_absolute('F_e') loc = {'F_e': default.get_dataset_location('F_e'), '|F_e|': default.get_dataset_location('|F_e|')} in_memory = np.abs(default.read_dataset(loc['F_e'],0)) in_file = default.read_dataset(loc['|F_e|'],0) assert np.allclose(in_memory,in_file) @pytest.mark.parametrize('mode',['direct','function']) def test_add_calculation(self,default,tmp_path,mode): if mode == 'direct': default.add_calculation('x','2.0*np.abs(#F#)-1.0','-','my notes') else: with open(tmp_path/'f.py','w') as f: f.write("import numpy as np\ndef my_func(field):\n return 2.0*np.abs(field)-1.0\n") sys.path.insert(0,str(tmp_path)) import f default.enable_user_function(f.my_func) default.add_calculation('x','my_func(#F#)','-','my notes') loc = {'F': default.get_dataset_location('F'), 'x': default.get_dataset_location('x')} in_memory = 2.0*np.abs(default.read_dataset(loc['F'],0))-1.0 in_file = default.read_dataset(loc['x'],0) assert np.allclose(in_memory,in_file) def test_add_stress_Cauchy(self,default): default.add_stress_Cauchy('P','F') loc = {'F': default.get_dataset_location('F'), 'P': default.get_dataset_location('P'), 'sigma':default.get_dataset_location('sigma')} in_memory = mechanics.stress_Cauchy(default.read_dataset(loc['P'],0), default.read_dataset(loc['F'],0)) in_file = default.read_dataset(loc['sigma'],0) assert np.allclose(in_memory,in_file) def test_add_determinant(self,default): default.add_determinant('P') loc = {'P': default.get_dataset_location('P'), 'det(P)':default.get_dataset_location('det(P)')} in_memory = np.linalg.det(default.read_dataset(loc['P'],0)).reshape(-1,1) in_file = default.read_dataset(loc['det(P)'],0) assert np.allclose(in_memory,in_file) def test_add_deviator(self,default): default.add_deviator('P') loc = {'P' :default.get_dataset_location('P'), 's_P':default.get_dataset_location('s_P')} in_memory = tensor.deviatoric(default.read_dataset(loc['P'],0)) in_file = default.read_dataset(loc['s_P'],0) assert np.allclose(in_memory,in_file) @pytest.mark.parametrize('eigenvalue,function',[('max',np.amax),('min',np.amin)]) def test_add_eigenvalue(self,default,eigenvalue,function): default.add_stress_Cauchy('P','F') default.add_eigenvalue('sigma',eigenvalue) loc = {'sigma' :default.get_dataset_location('sigma'), 'lambda':default.get_dataset_location(f'lambda_{eigenvalue}(sigma)')} in_memory = function(tensor.eigenvalues(default.read_dataset(loc['sigma'],0)),axis=1,keepdims=True) in_file = default.read_dataset(loc['lambda'],0) assert np.allclose(in_memory,in_file) @pytest.mark.parametrize('eigenvalue,idx',[('max',2),('mid',1),('min',0)]) def test_add_eigenvector(self,default,eigenvalue,idx): default.add_stress_Cauchy('P','F') default.add_eigenvector('sigma',eigenvalue) loc = {'sigma' :default.get_dataset_location('sigma'), 'v(sigma)':default.get_dataset_location(f'v_{eigenvalue}(sigma)')} in_memory = tensor.eigenvectors(default.read_dataset(loc['sigma'],0))[:,idx] in_file = default.read_dataset(loc['v(sigma)'],0) assert np.allclose(in_memory,in_file) @pytest.mark.parametrize('d',[[1,0,0],[0,1,0],[0,0,1]]) def test_add_IPF_color(self,default,d): default.add_IPF_color('O',np.array(d)) loc = {'O': default.get_dataset_location('O'), 'color': default.get_dataset_location('IPFcolor_[{} {} {}]'.format(*d))} qu = default.read_dataset(loc['O']).view(np.double).squeeze() crystal_structure = default.get_crystal_structure() c = Orientation(rotation=qu, lattice={'fcc':'cF', 'bcc':'cI', 'hex':'hP'}[crystal_structure]) in_memory = np.uint8(c.IPF_color(np.array(d))*255) in_file = default.read_dataset(loc['color']) assert np.allclose(in_memory,in_file) def test_add_maximum_shear(self,default): default.add_stress_Cauchy('P','F') default.add_maximum_shear('sigma') loc = {'sigma' :default.get_dataset_location('sigma'), 'max_shear(sigma)':default.get_dataset_location('max_shear(sigma)')} in_memory = mechanics.maximum_shear(default.read_dataset(loc['sigma'],0)).reshape(-1,1) in_file = default.read_dataset(loc['max_shear(sigma)'],0) assert np.allclose(in_memory,in_file) def test_add_Mises_strain(self,default): t = ['V','U'][np.random.randint(0,2)] m = np.random.random()*2.0 - 1.0 default.add_strain('F',t,m) label = f'epsilon_{t}^{m}(F)' default.add_equivalent_Mises(label) loc = {label :default.get_dataset_location(label), label+'_vM':default.get_dataset_location(label+'_vM')} in_memory = mechanics.equivalent_strain_Mises(default.read_dataset(loc[label],0)).reshape(-1,1) in_file = default.read_dataset(loc[label+'_vM'],0) assert np.allclose(in_memory,in_file) def test_add_Mises_stress(self,default): default.add_stress_Cauchy('P','F') default.add_equivalent_Mises('sigma') loc = {'sigma' :default.get_dataset_location('sigma'), 'sigma_vM':default.get_dataset_location('sigma_vM')} in_memory = mechanics.equivalent_stress_Mises(default.read_dataset(loc['sigma'],0)).reshape(-1,1) in_file = default.read_dataset(loc['sigma_vM'],0) assert np.allclose(in_memory,in_file) def test_add_Mises_invalid(self,default): default.add_stress_Cauchy('P','F') default.add_calculation('sigma_y','#sigma#',unit='y') default.add_equivalent_Mises('sigma_y') assert default.get_dataset_location('sigma_y_vM') == [] def test_add_Mises_stress_strain(self,default): default.add_stress_Cauchy('P','F') default.add_calculation('sigma_y','#sigma#',unit='y') default.add_calculation('sigma_x','#sigma#',unit='x') default.add_equivalent_Mises('sigma_y',kind='strain') default.add_equivalent_Mises('sigma_x',kind='stress') loc = {'y' :default.get_dataset_location('sigma_y_vM'), 'x' :default.get_dataset_location('sigma_x_vM')} assert not np.allclose(default.read_dataset(loc['y'],0),default.read_dataset(loc['x'],0)) def test_add_norm(self,default): default.add_norm('F',1) loc = {'F': default.get_dataset_location('F'), '|F|_1':default.get_dataset_location('|F|_1')} in_memory = np.linalg.norm(default.read_dataset(loc['F'],0),ord=1,axis=(1,2),keepdims=True) in_file = default.read_dataset(loc['|F|_1'],0) assert np.allclose(in_memory,in_file) def test_add_stress_second_Piola_Kirchhoff(self,default): default.add_stress_second_Piola_Kirchhoff('P','F') loc = {'F':default.get_dataset_location('F'), 'P':default.get_dataset_location('P'), 'S':default.get_dataset_location('S')} in_memory = mechanics.stress_second_Piola_Kirchhoff(default.read_dataset(loc['P'],0), default.read_dataset(loc['F'],0)) in_file = default.read_dataset(loc['S'],0) assert np.allclose(in_memory,in_file) @pytest.mark.skip(reason='requires rework of lattice.f90') @pytest.mark.parametrize('polar',[True,False]) def test_add_pole(self,default,polar): pole = np.array([1.,0.,0.]) default.add_pole('O',pole,polar) loc = {'O': default.get_dataset_location('O'), 'pole': default.get_dataset_location('p^{}_[1 0 0)'.format(u'rφ' if polar else 'xy'))} rot = Rotation(default.read_dataset(loc['O']).view(np.double)) rotated_pole = rot * np.broadcast_to(pole,rot.shape+(3,)) xy = rotated_pole[:,0:2]/(1.+abs(pole[2])) in_memory = xy if not polar else \ np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])]) in_file = default.read_dataset(loc['pole']) assert np.allclose(in_memory,in_file) def test_add_rotation(self,default): default.add_rotation('F') loc = {'F': default.get_dataset_location('F'), 'R(F)': default.get_dataset_location('R(F)')} in_memory = mechanics.rotation(default.read_dataset(loc['F'],0)).as_matrix() in_file = default.read_dataset(loc['R(F)'],0) assert np.allclose(in_memory,in_file) def test_add_spherical(self,default): default.add_spherical('P') loc = {'P': default.get_dataset_location('P'), 'p_P': default.get_dataset_location('p_P')} in_memory = tensor.spherical(default.read_dataset(loc['P'],0),False).reshape(-1,1) in_file = default.read_dataset(loc['p_P'],0) assert np.allclose(in_memory,in_file) def test_add_strain(self,default): t = ['V','U'][np.random.randint(0,2)] m = np.random.random()*2.0 - 1.0 default.add_strain('F',t,m) label = f'epsilon_{t}^{m}(F)' loc = {'F': default.get_dataset_location('F'), label: default.get_dataset_location(label)} in_memory = mechanics.strain(default.read_dataset(loc['F'],0),t,m) in_file = default.read_dataset(loc[label],0) assert np.allclose(in_memory,in_file) def test_add_stretch_right(self,default): default.add_stretch_tensor('F','U') loc = {'F': default.get_dataset_location('F'), 'U(F)': default.get_dataset_location('U(F)')} in_memory = mechanics.stretch_right(default.read_dataset(loc['F'],0)) in_file = default.read_dataset(loc['U(F)'],0) assert np.allclose(in_memory,in_file) def test_add_stretch_left(self,default): default.add_stretch_tensor('F','V') loc = {'F': default.get_dataset_location('F'), 'V(F)': default.get_dataset_location('V(F)')} in_memory = mechanics.stretch_left(default.read_dataset(loc['F'],0)) in_file = default.read_dataset(loc['V(F)'],0) assert np.allclose(in_memory,in_file) def test_add_invalid(self,default): with pytest.raises(TypeError): default.add_calculation('#invalid#*2') @pytest.mark.parametrize('overwrite',['off','on']) def test_add_overwrite(self,default,overwrite): default.pick('times',default.times_in_range(0,np.inf)[-1]) default.add_stress_Cauchy() loc = default.get_dataset_location('sigma') with h5py.File(default.fname,'r') as f: # h5py3 compatibility try: created_first = f[loc[0]].attrs['Created'].decode() except AttributeError: created_first = f[loc[0]].attrs['Created'] created_first = datetime.strptime(created_first,'%Y-%m-%d %H:%M:%S%z') if overwrite == 'on': default.allow_modification() else: default.disallow_modification() time.sleep(2.) try: default.add_calculation('sigma','#sigma#*0.0+311.','not the Cauchy stress') except ValueError: pass with h5py.File(default.fname,'r') as f: # h5py3 compatibility try: created_second = f[loc[0]].attrs['Created'].decode() except AttributeError: created_second = f[loc[0]].attrs['Created'] created_second = datetime.strptime(created_second,'%Y-%m-%d %H:%M:%S%z') if overwrite == 'on': assert created_first < created_second and np.allclose(default.read_dataset(loc),311.) else: assert created_first == created_second and not np.allclose(default.read_dataset(loc),311.) @pytest.mark.parametrize('allowed',['off','on']) def test_rename(self,default,allowed): if allowed == 'on': F = default.read_dataset(default.get_dataset_location('F')) default.allow_modification() default.rename('F','new_name') assert np.all(F == default.read_dataset(default.get_dataset_location('new_name'))) default.disallow_modification() with pytest.raises(PermissionError): default.rename('P','another_new_name') @pytest.mark.parametrize('mode',['cell','node']) def test_coordinates(self,default,mode): if mode == 'cell': a = grid_filters.cell_coord0(default.grid,default.size,default.origin) b = default.cell_coordinates.reshape(tuple(default.grid)+(3,),order='F') elif mode == 'node': a = grid_filters.node_coord0(default.grid,default.size,default.origin) b = default.node_coordinates.reshape(tuple(default.grid+1)+(3,),order='F') assert np.allclose(a,b) @pytest.mark.parametrize('output',['F',[],['F','P']]) def test_vtk(self,tmp_path,default,output): os.chdir(tmp_path) default.save_vtk(output) @pytest.mark.parametrize('mode',['point','cell']) def test_vtk_mode(self,tmp_path,single_phase,mode): os.chdir(tmp_path) single_phase.save_vtk(mode=mode) def test_XDMF(self,tmp_path,single_phase): os.chdir(tmp_path) single_phase.save_XDMF()