452 lines
20 KiB
Python
452 lines
20 KiB
Python
import bz2
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import pickle
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import time
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import shutil
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import os
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import sys
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from datetime import datetime
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import pytest
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import numpy as np
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import h5py
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from damask import Result
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from damask import Rotation
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from damask import Orientation
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from damask import tensor
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from damask import mechanics
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from damask import grid_filters
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@pytest.fixture
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def default(tmp_path,ref_path):
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"""Small Result file in temp location for modification."""
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fname = '12grains6x7x8_tensionY.hdf5'
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shutil.copy(ref_path/fname,tmp_path)
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f = Result(tmp_path/fname)
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f.view('times',20.0)
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return f
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@pytest.fixture
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def single_phase(tmp_path,ref_path):
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"""Single phase Result file in temp location for modification."""
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fname = '6grains6x7x8_single_phase_tensionY.hdf5'
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shutil.copy(ref_path/fname,tmp_path)
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return Result(tmp_path/fname)
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@pytest.fixture
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def ref_path(ref_path_base):
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"""Directory containing reference results."""
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return ref_path_base/'Result'
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def dict_equal(d1, d2):
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for k in d1:
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if (k not in d2):
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return False
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else:
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if type(d1[k]) is dict:
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return dict_equal(d1[k],d2[k])
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else:
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if not np.allclose(d1[k],d2[k]):
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return False
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return True
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class TestResult:
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def test_self_report(self,default):
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print(default)
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def test_view_all(self,default):
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default.view('increments',True)
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a = default.get_dataset_location('F')
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default.view('increments','*')
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b = default.get_dataset_location('F')
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default.view('increments',default.increments_in_range(0,np.iinfo(int).max))
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c = default.get_dataset_location('F')
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default.view('times',True)
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d = default.get_dataset_location('F')
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default.view('times','*')
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e = default.get_dataset_location('F')
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default.view('times',default.times_in_range(0.0,np.inf))
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f = default.get_dataset_location('F')
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assert a == b == c == d == e ==f
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@pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations
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def test_view_none(self,default,what):
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default.view(what,False)
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a = default.get_dataset_location('F')
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default.view(what,[])
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b = default.get_dataset_location('F')
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assert a == b == []
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@pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations
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def test_view_more(self,default,what):
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default.view(what,False)
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default.view_more(what,'*')
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a = default.get_dataset_location('F')
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default.view(what,True)
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b = default.get_dataset_location('F')
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assert a == b
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@pytest.mark.parametrize('what',['increments','times','phases']) # ToDo: discuss homogenizations
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def test_view_less(self,default,what):
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default.view(what,True)
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default.view_less(what,'*')
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a = default.get_dataset_location('F')
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default.view(what,False)
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b = default.get_dataset_location('F')
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assert a == b == []
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def test_view_invalid(self,default):
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with pytest.raises(AttributeError):
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default.view('invalid',True)
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def test_add_absolute(self,default):
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default.add_absolute('F_e')
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loc = {'F_e': default.get_dataset_location('F_e'),
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'|F_e|': default.get_dataset_location('|F_e|')}
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in_memory = np.abs(default.read_dataset(loc['F_e'],0))
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in_file = default.read_dataset(loc['|F_e|'],0)
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assert np.allclose(in_memory,in_file)
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@pytest.mark.parametrize('mode',['direct','function'])
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def test_add_calculation(self,default,tmp_path,mode):
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if mode == 'direct':
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default.add_calculation('x','2.0*np.abs(#F#)-1.0','-','my notes')
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else:
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with open(tmp_path/'f.py','w') as f:
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f.write("import numpy as np\ndef my_func(field):\n return 2.0*np.abs(field)-1.0\n")
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sys.path.insert(0,str(tmp_path))
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import f
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default.enable_user_function(f.my_func)
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default.add_calculation('x','my_func(#F#)','-','my notes')
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loc = {'F': default.get_dataset_location('F'),
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'x': default.get_dataset_location('x')}
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in_memory = 2.0*np.abs(default.read_dataset(loc['F'],0))-1.0
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in_file = default.read_dataset(loc['x'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_stress_Cauchy(self,default):
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default.add_stress_Cauchy('P','F')
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loc = {'F': default.get_dataset_location('F'),
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'P': default.get_dataset_location('P'),
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'sigma':default.get_dataset_location('sigma')}
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in_memory = mechanics.stress_Cauchy(default.read_dataset(loc['P'],0),
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default.read_dataset(loc['F'],0))
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in_file = default.read_dataset(loc['sigma'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_determinant(self,default):
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default.add_determinant('P')
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loc = {'P': default.get_dataset_location('P'),
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'det(P)':default.get_dataset_location('det(P)')}
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in_memory = np.linalg.det(default.read_dataset(loc['P'],0)).reshape(-1,1)
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in_file = default.read_dataset(loc['det(P)'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_deviator(self,default):
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default.add_deviator('P')
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loc = {'P' :default.get_dataset_location('P'),
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's_P':default.get_dataset_location('s_P')}
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in_memory = tensor.deviatoric(default.read_dataset(loc['P'],0))
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in_file = default.read_dataset(loc['s_P'],0)
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assert np.allclose(in_memory,in_file)
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@pytest.mark.parametrize('eigenvalue,function',[('max',np.amax),('min',np.amin)])
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def test_add_eigenvalue(self,default,eigenvalue,function):
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default.add_stress_Cauchy('P','F')
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default.add_eigenvalue('sigma',eigenvalue)
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loc = {'sigma' :default.get_dataset_location('sigma'),
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'lambda':default.get_dataset_location(f'lambda_{eigenvalue}(sigma)')}
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in_memory = function(tensor.eigenvalues(default.read_dataset(loc['sigma'],0)),axis=1,keepdims=True)
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in_file = default.read_dataset(loc['lambda'],0)
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assert np.allclose(in_memory,in_file)
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@pytest.mark.parametrize('eigenvalue,idx',[('max',2),('mid',1),('min',0)])
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def test_add_eigenvector(self,default,eigenvalue,idx):
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default.add_stress_Cauchy('P','F')
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default.add_eigenvector('sigma',eigenvalue)
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loc = {'sigma' :default.get_dataset_location('sigma'),
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'v(sigma)':default.get_dataset_location(f'v_{eigenvalue}(sigma)')}
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in_memory = tensor.eigenvectors(default.read_dataset(loc['sigma'],0))[:,idx]
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in_file = default.read_dataset(loc['v(sigma)'],0)
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assert np.allclose(in_memory,in_file)
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@pytest.mark.parametrize('d',[[1,0,0],[0,1,0],[0,0,1]])
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def test_add_IPF_color(self,default,d):
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default.add_IPF_color(d,'O')
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loc = {'O': default.get_dataset_location('O'),
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'color': default.get_dataset_location('IPFcolor_[{} {} {}]'.format(*d))}
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qu = default.read_dataset(loc['O']).view(np.double).squeeze()
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crystal_structure = default._get_attribute(default.get_dataset_location('O')[0],'lattice')
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c = Orientation(rotation=qu,lattice=crystal_structure)
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in_memory = np.uint8(c.IPF_color(np.array(d))*255)
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in_file = default.read_dataset(loc['color'])
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assert np.allclose(in_memory,in_file)
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def test_add_maximum_shear(self,default):
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default.add_stress_Cauchy('P','F')
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default.add_maximum_shear('sigma')
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loc = {'sigma' :default.get_dataset_location('sigma'),
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'max_shear(sigma)':default.get_dataset_location('max_shear(sigma)')}
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in_memory = mechanics.maximum_shear(default.read_dataset(loc['sigma'],0)).reshape(-1,1)
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in_file = default.read_dataset(loc['max_shear(sigma)'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_Mises_strain(self,default):
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t = ['V','U'][np.random.randint(0,2)]
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m = np.random.random()*2.0 - 1.0
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default.add_strain('F',t,m)
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label = f'epsilon_{t}^{m}(F)'
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default.add_equivalent_Mises(label)
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loc = {label :default.get_dataset_location(label),
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label+'_vM':default.get_dataset_location(label+'_vM')}
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in_memory = mechanics.equivalent_strain_Mises(default.read_dataset(loc[label],0)).reshape(-1,1)
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in_file = default.read_dataset(loc[label+'_vM'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_Mises_stress(self,default):
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default.add_stress_Cauchy('P','F')
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default.add_equivalent_Mises('sigma')
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loc = {'sigma' :default.get_dataset_location('sigma'),
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'sigma_vM':default.get_dataset_location('sigma_vM')}
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in_memory = mechanics.equivalent_stress_Mises(default.read_dataset(loc['sigma'],0)).reshape(-1,1)
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in_file = default.read_dataset(loc['sigma_vM'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_Mises_invalid(self,default):
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default.add_stress_Cauchy('P','F')
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default.add_calculation('sigma_y','#sigma#',unit='y')
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default.add_equivalent_Mises('sigma_y')
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assert default.get_dataset_location('sigma_y_vM') == []
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def test_add_Mises_stress_strain(self,default):
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default.add_stress_Cauchy('P','F')
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default.add_calculation('sigma_y','#sigma#',unit='y')
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default.add_calculation('sigma_x','#sigma#',unit='x')
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default.add_equivalent_Mises('sigma_y',kind='strain')
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default.add_equivalent_Mises('sigma_x',kind='stress')
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loc = {'y' :default.get_dataset_location('sigma_y_vM'),
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'x' :default.get_dataset_location('sigma_x_vM')}
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assert not np.allclose(default.read_dataset(loc['y'],0),default.read_dataset(loc['x'],0))
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def test_add_norm(self,default):
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default.add_norm('F',1)
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loc = {'F': default.get_dataset_location('F'),
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'|F|_1':default.get_dataset_location('|F|_1')}
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in_memory = np.linalg.norm(default.read_dataset(loc['F'],0),ord=1,axis=(1,2),keepdims=True)
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in_file = default.read_dataset(loc['|F|_1'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_stress_second_Piola_Kirchhoff(self,default):
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default.add_stress_second_Piola_Kirchhoff('P','F')
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loc = {'F':default.get_dataset_location('F'),
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'P':default.get_dataset_location('P'),
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'S':default.get_dataset_location('S')}
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in_memory = mechanics.stress_second_Piola_Kirchhoff(default.read_dataset(loc['P'],0),
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default.read_dataset(loc['F'],0))
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in_file = default.read_dataset(loc['S'],0)
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assert np.allclose(in_memory,in_file)
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@pytest.mark.skip(reason='requires rework of lattice.f90')
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@pytest.mark.parametrize('polar',[True,False])
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def test_add_pole(self,default,polar):
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pole = np.array([1.,0.,0.])
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default.add_pole('O',pole,polar)
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loc = {'O': default.get_dataset_location('O'),
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'pole': default.get_dataset_location('p^{}_[1 0 0)'.format(u'rφ' if polar else 'xy'))}
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rot = Rotation(default.read_dataset(loc['O']).view(np.double))
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rotated_pole = rot * np.broadcast_to(pole,rot.shape+(3,))
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xy = rotated_pole[:,0:2]/(1.+abs(pole[2]))
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in_memory = xy if not polar else \
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np.block([np.sqrt(xy[:,0:1]*xy[:,0:1]+xy[:,1:2]*xy[:,1:2]),np.arctan2(xy[:,1:2],xy[:,0:1])])
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in_file = default.read_dataset(loc['pole'])
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assert np.allclose(in_memory,in_file)
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def test_add_rotation(self,default):
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default.add_rotation('F')
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loc = {'F': default.get_dataset_location('F'),
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'R(F)': default.get_dataset_location('R(F)')}
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in_memory = mechanics.rotation(default.read_dataset(loc['F'],0)).as_matrix()
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in_file = default.read_dataset(loc['R(F)'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_spherical(self,default):
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default.add_spherical('P')
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loc = {'P': default.get_dataset_location('P'),
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'p_P': default.get_dataset_location('p_P')}
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in_memory = tensor.spherical(default.read_dataset(loc['P'],0),False).reshape(-1,1)
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in_file = default.read_dataset(loc['p_P'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_strain(self,default):
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t = ['V','U'][np.random.randint(0,2)]
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m = np.random.random()*2.0 - 1.0
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default.add_strain('F',t,m)
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label = f'epsilon_{t}^{m}(F)'
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loc = {'F': default.get_dataset_location('F'),
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label: default.get_dataset_location(label)}
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in_memory = mechanics.strain(default.read_dataset(loc['F'],0),t,m)
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in_file = default.read_dataset(loc[label],0)
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assert np.allclose(in_memory,in_file)
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def test_add_stretch_right(self,default):
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default.add_stretch_tensor('F','U')
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loc = {'F': default.get_dataset_location('F'),
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'U(F)': default.get_dataset_location('U(F)')}
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in_memory = mechanics.stretch_right(default.read_dataset(loc['F'],0))
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in_file = default.read_dataset(loc['U(F)'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_stretch_left(self,default):
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default.add_stretch_tensor('F','V')
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loc = {'F': default.get_dataset_location('F'),
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'V(F)': default.get_dataset_location('V(F)')}
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in_memory = mechanics.stretch_left(default.read_dataset(loc['F'],0))
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in_file = default.read_dataset(loc['V(F)'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_invalid(self,default):
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with pytest.raises(TypeError):
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default.add_calculation('#invalid#*2')
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@pytest.mark.parametrize('overwrite',['off','on'])
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def test_add_overwrite(self,default,overwrite):
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default.view('times',default.times_in_range(0,np.inf)[-1])
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default.add_stress_Cauchy()
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loc = default.get_dataset_location('sigma')
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with h5py.File(default.fname,'r') as f:
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# h5py3 compatibility
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try:
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created_first = f[loc[0]].attrs['created'].decode()
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except AttributeError:
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created_first = f[loc[0]].attrs['created']
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created_first = datetime.strptime(created_first,'%Y-%m-%d %H:%M:%S%z')
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if overwrite == 'on':
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default.allow_modification()
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else:
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default.disallow_modification()
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time.sleep(2.)
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try:
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default.add_calculation('sigma','#sigma#*0.0+311.','not the Cauchy stress')
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except ValueError:
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pass
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with h5py.File(default.fname,'r') as f:
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# h5py3 compatibility
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try:
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created_second = f[loc[0]].attrs['created'].decode()
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except AttributeError:
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created_second = f[loc[0]].attrs['created']
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created_second = datetime.strptime(created_second,'%Y-%m-%d %H:%M:%S%z')
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if overwrite == 'on':
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assert created_first < created_second and np.allclose(default.read_dataset(loc),311.)
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else:
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assert created_first == created_second and not np.allclose(default.read_dataset(loc),311.)
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@pytest.mark.parametrize('allowed',['off','on'])
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def test_rename(self,default,allowed):
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if allowed == 'on':
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F = default.read_dataset(default.get_dataset_location('F'))
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default.allow_modification()
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default.rename('F','new_name')
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assert np.all(F == default.read_dataset(default.get_dataset_location('new_name')))
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default.disallow_modification()
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with pytest.raises(PermissionError):
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default.rename('P','another_new_name')
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@pytest.mark.parametrize('mode',['cell','node'])
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def test_coordinates(self,default,mode):
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if mode == 'cell':
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a = grid_filters.coordinates0_point(default.cells,default.size,default.origin)
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b = default.coordinates0_point.reshape(tuple(default.cells)+(3,),order='F')
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elif mode == 'node':
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a = grid_filters.coordinates0_node(default.cells,default.size,default.origin)
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b = default.coordinates0_node.reshape(tuple(default.cells+1)+(3,),order='F')
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assert np.allclose(a,b)
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@pytest.mark.parametrize('output',['F',[],['F','P']])
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def test_vtk(self,tmp_path,default,output):
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os.chdir(tmp_path)
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default.save_VTK(output)
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@pytest.mark.parametrize('mode',['point','cell'])
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def test_vtk_mode(self,tmp_path,single_phase,mode):
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os.chdir(tmp_path)
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single_phase.save_VTK(mode=mode)
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def test_XDMF(self,tmp_path,single_phase,update,ref_path):
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for shape in [('scalar',()),('vector',(3,)),('tensor',(3,3)),('matrix',(12,))]:
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for dtype in ['f4','f8','i1','i2','i4','i8','u1','u2','u4','u8']:
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single_phase.add_calculation(f'{shape[0]}_{dtype}',f"np.ones(np.shape(#F#)[0:1]+{shape[1]},'{dtype}')")
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fname = os.path.splitext(os.path.basename(single_phase.fname))[0]+'.xdmf'
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os.chdir(tmp_path)
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single_phase.save_XDMF()
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if update:
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shutil.copy(tmp_path/fname,ref_path/fname)
|
|
assert sorted(open(tmp_path/fname).read()) == sorted(open(ref_path/fname).read()) # XML is not ordered
|
|
|
|
def test_XDMF_invalid(self,default):
|
|
with pytest.raises(TypeError):
|
|
default.save_XDMF()
|
|
|
|
@pytest.mark.parametrize('view,output,compress,strip',
|
|
[({},['F','P','F','L_p','F_e','F_p'],True,True),
|
|
({'increments':3},'F',True,True),
|
|
({'increments':[1,8,3,4,5,6,7]},['F','P'],True,True),
|
|
({'phases':['A','B']},['F','P'],True,True),
|
|
({'phases':['A','C'],'homogenizations':False},['F','P','O'],True,True),
|
|
({'phases':False,'homogenizations':False},['F','P','O'],True,True),
|
|
({'phases':False},['Delta_V'],True,True),
|
|
({},['u_p','u_n'],False,False)],
|
|
ids=list(range(8)))
|
|
def test_read(self,update,request,ref_path,view,output,compress,strip):
|
|
result = Result(ref_path/'4grains2x4x3_compressionY.hdf5')
|
|
for key,value in view.items():
|
|
result.view(key,value)
|
|
|
|
N = request.node.name[8:].split('[')[1].split(']')[0]
|
|
cur = result.read(output,compress,strip)
|
|
if update:
|
|
with bz2.BZ2File(ref_path/f'read_{N}.pbz2','w') as f:
|
|
pickle.dump(cur,f)
|
|
|
|
with bz2.BZ2File(ref_path/f'read_{N}.pbz2') as f:
|
|
assert dict_equal(cur,pickle.load(f))
|
|
|
|
|
|
@pytest.mark.parametrize('view,output,compress,constituents,strip',
|
|
[({},['F','P','F','L_p','F_e','F_p'],True,True,None),
|
|
({'increments':3},'F',True,True,[0,1,2,3,4,5,6,7]),
|
|
({'increments':[1,8,3,4,5,6,7]},['F','P'],True,True,1),
|
|
({'phases':['A','B']},['F','P'],True,True,[1,2]),
|
|
({'phases':['A','C'],'homogenizations':False},['F','P','O'],True,True,[0,7]),
|
|
({'phases':False,'homogenizations':False},['F','P','O'],True,True,[1,2,3,4]),
|
|
({'phases':False},['Delta_V'],True,True,[1,2,4]),
|
|
({},['u_p','u_n'],False,False,None)],
|
|
ids=list(range(8)))
|
|
def test_place(self,update,request,ref_path,view,output,compress,strip,constituents):
|
|
result = Result(ref_path/'4grains2x4x3_compressionY.hdf5')
|
|
for key,value in view.items():
|
|
result.view(key,value)
|
|
|
|
N = request.node.name[8:].split('[')[1].split(']')[0]
|
|
cur = result.place(output,compress,strip,constituents)
|
|
if update:
|
|
with bz2.BZ2File(ref_path/f'place_{N}.pbz2','w') as f:
|
|
pickle.dump(cur,f)
|
|
|
|
with bz2.BZ2File(ref_path/f'place_{N}.pbz2') as f:
|
|
assert dict_equal(cur,pickle.load(f))
|