DAMASK_EICMD/python/tests/test_Result.py

298 lines
13 KiB
Python

import time
import shutil
import os
from datetime import datetime
import pytest
import numpy as np
import h5py
import damask
from damask import Result
from damask import mechanics
@pytest.fixture
def default(tmp_path,reference_dir):
"""Small Result file in temp location for modification."""
fname = '12grains6x7x8_tensionY.hdf5'
shutil.copy(os.path.join(reference_dir,fname),tmp_path)
f = Result(os.path.join(tmp_path,fname))
f.pick('times',20.0)
return f
@pytest.fixture
def reference_dir(reference_dir_base):
"""Directory containing reference results."""
return os.path.join(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','constituents']) # ToDo: discuss materialpoints
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','constituents']) # ToDo: discuss materialpoints
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','constituents']) # ToDo: discuss materialpoints
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_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_Cauchy()
dset = default.groups_with_datasets('sigma')[0]+'/sigma'
with h5py.File(default.fname,'r') as f:
created_first = f[dset].attrs['Created'].decode()
created_first = datetime.strptime(created_first,'%Y-%m-%d %H:%M:%S%z')
if overwrite == 'on':
default.enable_overwrite()
else:
default.disable_overwrite()
time.sleep(2.)
default.add_Cauchy()
with h5py.File(default.fname,'r') as f:
created_second = f[dset].attrs['Created'].decode()
created_second = datetime.strptime(created_second,'%Y-%m-%d %H:%M:%S%z')
if overwrite == 'on':
assert created_first < created_second
else:
assert created_first == created_second
def test_add_absolute(self,default):
default.add_absolute('Fe')
loc = {'Fe': default.get_dataset_location('Fe'),
'|Fe|': default.get_dataset_location('|Fe|')}
in_memory = np.abs(default.read_dataset(loc['Fe'],0))
in_file = default.read_dataset(loc['|Fe|'],0)
assert np.allclose(in_memory,in_file)
def test_add_calculation(self,default):
default.add_calculation('x','2.0*np.abs(#F#)-1.0','-','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_Cauchy(self,default):
default.add_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.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 = mechanics.deviatoric_part(default.read_dataset(loc['P'],0))
in_file = default.read_dataset(loc['s_P'],0)
assert np.allclose(in_memory,in_file)
def test_add_eigenvalues(self,default):
default.add_Cauchy('P','F')
default.add_eigenvalues('sigma')
loc = {'sigma' :default.get_dataset_location('sigma'),
'lambda(sigma)':default.get_dataset_location('lambda(sigma)')}
in_memory = mechanics.eigenvalues(default.read_dataset(loc['sigma'],0))
in_file = default.read_dataset(loc['lambda(sigma)'],0)
assert np.allclose(in_memory,in_file)
def test_add_eigenvectors(self,default):
default.add_Cauchy('P','F')
default.add_eigenvectors('sigma')
loc = {'sigma' :default.get_dataset_location('sigma'),
'v(sigma)':default.get_dataset_location('v(sigma)')}
in_memory = mechanics.eigenvectors(default.read_dataset(loc['sigma'],0))
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_IPFcolor(self,default,d):
default.add_IPFcolor('orientation',d)
loc = {'orientation': default.get_dataset_location('orientation'),
'color': default.get_dataset_location('IPFcolor_[{} {} {}]'.format(*d))}
qu = default.read_dataset(loc['orientation']).view(np.double).reshape(-1,4)
crystal_structure = default.get_crystal_structure()
in_memory = np.empty((qu.shape[0],3),np.uint8)
for i,q in enumerate(qu):
o = damask.Orientation(q,crystal_structure).reduced()
in_memory[i] = np.uint8(o.IPFcolor(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_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_tensor('F',t,m)
label = 'epsilon_{}^{}(F)'.format(t,m)
default.add_Mises(label)
loc = {label :default.get_dataset_location(label),
label+'_vM':default.get_dataset_location(label+'_vM')}
in_memory = mechanics.Mises_strain(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_Cauchy('P','F')
default.add_Mises('sigma')
loc = {'sigma' :default.get_dataset_location('sigma'),
'sigma_vM':default.get_dataset_location('sigma_vM')}
in_memory = mechanics.Mises_stress(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_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_PK2(self,default):
default.add_PK2('P','F')
loc = {'F':default.get_dataset_location('F'),
'P':default.get_dataset_location('P'),
'S':default.get_dataset_location('S')}
in_memory = mechanics.PK2(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.parametrize('polar',[True,False])
def test_add_pole(self,default,polar):
pole = np.array([1.,0.,0.])
default.add_pole('orientation',pole,polar)
loc = {'orientation': default.get_dataset_location('orientation'),
'pole': default.get_dataset_location('p^{}_[1 0 0)'.format(u'' if polar else 'xy'))}
rot = damask.Rotation(default.read_dataset(loc['orientation']).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_rotational_part(self,default):
default.add_rotational_part('F')
loc = {'F': default.get_dataset_location('F'),
'R(F)': default.get_dataset_location('R(F)')}
in_memory = mechanics.rotational_part(default.read_dataset(loc['F'],0))
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 = mechanics.spherical_part(default.read_dataset(loc['P'],0)).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_tensor('F',t,m)
label = 'epsilon_{}^{}(F)'.format(t,m)
loc = {'F': default.get_dataset_location('F'),
label: default.get_dataset_location(label)}
in_memory = mechanics.strain_tensor(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.right_stretch(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.left_stretch(default.read_dataset(loc['F'],0))
in_file = default.read_dataset(loc['V(F)'],0)
assert np.allclose(in_memory,in_file)
@pytest.mark.parametrize('output',['F',[],['F','P']])
def test_vtk(self,tmp_path,default,output):
os.chdir(tmp_path)
default.to_vtk(output)