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DAMASK_EICMD
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documenting and ensuring consistent argument names 

'name' for a dataset matches the analogy to a file name
This commit is contained in:
Martin Diehl 2021-04-24 07:13:36 +02:00
parent 4d67c85a33
commit 3977e230b3
8 changed files with 329 additions and 88 deletions
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1
examples/config/phase/mechanical/plastic/dislotwin_IF-steel.yaml
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@ -5,6 +5,7 @@ references:
10.1016/j.ijplas.2020.102779
- K. Sedighiani et al.,
Mechanics of Materials, submitted
output: [rho_dip, rho_mob]
N_sl: [12, 12]
b_sl: [2.49e-10, 2.49e-10]
rho_mob_0: [2.81e12, 2.8e12]

26
python/damask/_configmaterial.py
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@ -365,9 +365,12 @@ class ConfigMaterial(Config):
Examples
--------
Create a dual-phase steel microstructure for micromechanical simulations:
>>> import numpy as np
>>> import damask
>>> m = damask.ConfigMaterial().material_add(phase = ['Aluminum','Steel'],
>>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = ['Ferrite','Martensite'],
... O = damask.Rotation.from_random(2),
... homogenization = 'SX')
>>> m
@ -375,38 +378,43 @@ class ConfigMaterial(Config):
- constituents:
- O: [0.577764, -0.146299, -0.617669, 0.513010]
v: 1.0
phase: Aluminum
phase: Ferrite
homogenization: SX
- constituents:
- O: [0.184176, 0.340305, 0.737247, 0.553840]
v: 1.0
phase: Steel
phase: Martensite
homogenization: SX
homogenization: {}
phase: {}
>>> m = damask.ConfigMaterial().material_add(phase = np.array(['Austenite','Martensite']).reshape(1,2),
Create a duplex stainless steel microstructure for forming simulations:
>>> import numpy as np
>>> import damask
>>> m = damask.ConfigMaterial()
>>> m = m.material_add(phase = np.array(['Austenite','Ferrite']).reshape(1,2),
... O = damask.Rotation.from_random((2,2)),
... v = np.array([0.2,0.8]).reshape(1,2),
... homogenization = ['A','B'])
... homogenization = 'Taylor')
>>> m
material:
- constituents:
- phase: Austenite
O: [0.659802978293224, 0.6953785848195171, 0.22426295326327111, -0.17554139512785227]
v: 0.2
- phase: Martensite
- phase: Ferrite
O: [0.49356745891301596, 0.2841806579193434, -0.7487679215072818, -0.339085707289975]
v: 0.8
homogenization: A
homogenization: Taylor
- constituents:
- phase: Austenite
O: [0.26542221365204055, 0.7268854930702071, 0.4474726435701472, -0.44828201137283735]
v: 0.2
- phase: Martensite
- phase: Ferrite
O: [0.6545817158479885, -0.08004812803625233, -0.6226561293931374, 0.4212059104577611]
v: 0.8
homogenization: B
homogenization: Taylor
homogenization: {}
phase: {}

12
python/damask/_orientation.py
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@ -8,15 +8,15 @@ from . import tensor
_parameter_doc = \
"""lattice : str
Either a crystal family out of [triclinic, monoclinic, orthorhombic, tetragonal, hexagonal, cubic]
or a Bravais lattice out of [aP, mP, mS, oP, oS, oI, oF, tP, tI, hP, cP, cI, cF].
When specifying a Bravais lattice, additional lattice parameters might be required:
Either a crystal family out of {triclinic, monoclinic, orthorhombic, tetragonal, hexagonal, cubic}
or a Bravais lattice out of {aP, mP, mS, oP, oS, oI, oF, tP, tI, hP, cP, cI, cF}.
When specifying a Bravais lattice, additional lattice parameters might be required.
a : float, optional
Length of lattice parameter "a".
Length of lattice parameter 'a'.
b : float, optional
Length of lattice parameter "b".
Length of lattice parameter 'b'.
c : float, optional
Length of lattice parameter "c".
Length of lattice parameter 'c'.
alpha : float, optional
Angle between b and c lattice basis.
beta : float, optional

332
python/damask/_result.py
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@ -34,7 +34,7 @@ def _read(dataset):
return np.array(dataset,dtype=dtype)
def _match(requested,existing):
"""Find matches among two sets of labels."""
"""Find matches among two sets of names."""
def flatten_list(list_of_lists):
return [e for e_ in list_of_lists for e in e_]
@ -57,14 +57,29 @@ def _empty_like(dataset,N_materialpoints,fill_float,fill_int):
class Result:
"""
Add data to and export from DADF5 files.
Add data to and export data from a DADF5 file.
DADF5 (DAMASK HDF5) files contain DAMASK results.
Their group/folder structure reflects the input data in material.yaml.
A DADF5 (DAMASK HDF5) file contain DAMASK results.
Its group/folder structure reflects the layout in material.yaml.
This class provides a custom view on the DADF5 file.
This class provides a customable view on the DADF5 file.
Upon initialization, all attributes are visible.
Derived quantities can be added to the file and existing data can be exported based on the current view.
Derived quantities are added to the file and existing data is
exported based on the current view.
Examples
--------
Open 'my_file.hdf5', which needs to contain deformation gradient 'F'
and first Piola-Kirchhoff stress 'P', add the Mises equivalent of the
Cauchy stress, and export it to VTK (file) and numpy.ndarray (memory).
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_Cauchy()
>>> r.add_equivalent_Mises('sigma')
>>> r.save_VTK()
>>> r_last = r.view('increments',-1)
>>> sigma_vM_last = r_last.get('sigma_vM')
"""
@ -167,6 +182,11 @@ class Result:
Name of datasets; supports '?' and '*' wildcards.
True is equivalent to '*', False is equivalent to [].
Returns
-------
view : damask.Result
Modified or new view on the DADF5 file.
"""
# allow True/False and string arguments
if datasets is True:
@ -180,6 +200,7 @@ class Result:
if what == 'increments':
choice = [c if isinstance(c,str) and c.startswith(inc) else
f'{inc}{c}' for c in choice]
if datasets == -1: choice = [self.increments[-1]]
elif what == 'times':
what = 'increments'
if choice == ['*']:
@ -211,15 +232,31 @@ class Result:
return dup
def allow_modification(self):
"""Allow to overwrite existing data."""
def modification_enable(self):
"""
Allow to modify existing data.
Returns
-------
modified_view : damask.Result
View where data is not write-protected.
"""
print(util.warn('Warning: Modification of existing datasets allowed!'))
dup = self.copy()
dup._allow_modification = True
return dup
def disallow_modification(self):
"""Disallow to overwrite existing data (default case)."""
def modification_disable(self):
"""
Disallow to modify existing data (default case).
Returns
-------
modified_view : damask.Result
View where data is write-protected.
"""
dup = self.copy()
dup._allow_modification = False
return dup
@ -227,7 +264,7 @@ class Result:
def increments_in_range(self,start,end):
"""
Select all increments within a given range.
Get all increments within a given range.
Parameters
----------
@ -236,6 +273,10 @@ class Result:
end : int or str
End increment.
Returns
-------
increments : list of ints
Increment number of all increments within the given bounds.
"""
# compatibility hack
ln = 3 if self.version_minor < 12 else 10
@ -243,13 +284,13 @@ class Result:
for i,inc in enumerate([int(i[ln:]) for i in self.increments]):
s,e = map(lambda x: int(x[ln:] if isinstance(x,str) and x.startswith('inc') else x), (start,end))
if s <= inc <= e:
selected.append(self.increments[i])
selected.append(int(self.increments[i].split('_')[1]))
return selected
def times_in_range(self,start,end):
"""
Select all increments within a given time range.
Get all increments within a given time range.
Parameters
----------
@ -258,6 +299,10 @@ class Result:
end : float
Time of end increment.
Returns
-------
times : list of float
Simulation time of all increments within the given bounds.
"""
selected = []
for i,time in enumerate(self.times):
@ -283,6 +328,20 @@ class Result:
view : damask.Result
View with where selected attributes are visible.
Examples
--------
Get a view that shows only results from the initial configuration:
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r_first = r.view('increment',0)
Get a view that shows all results of in simulation time [10,40]:
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r_t10to40 = r.view('times',r.times_in_range(10.0,40.0))
"""
return self._manage_view('set',what,datasets)
@ -304,6 +363,15 @@ class Result:
modified_view : damask.Result
View with more visible attributes.
Examples
--------
Get a view that shows only results from first and last increment:
>>> import damask
>>> r_empty = damask.Result('my_file.hdf5').view('increments',False)
>>> r_first = r_empty.view_more('increments',0)
>>> r_first_and_last = r.first.view_more('increments',-1)
"""
return self._manage_view('add',what,datasets)
@ -325,37 +393,93 @@ class Result:
modified_view : damask.Result
View with less visible attributes.
Examples
--------
Get a view that does not show the undeformed configuration:
>>> import damask
>>> r_all = damask.Result('my_file.hdf5')
>>> r_deformed = r_all.view_less('increments',0)
"""
return self._manage_view('del',what,datasets)
def rename(self,name_old,name_new):
def rename(self,name_src,name_dst):
"""
Rename dataset.
Rename/move datasets (within the same group/folder).
This operation is discouraged because the history of the
data becomes untracable and scientific integrity cannot be
ensured.
Parameters
----------
name_old : str
Name of the dataset to be renamed.
name_new : str
New name of the dataset.
name_src : str
Name of the datasets to be renamed.
name_dst : str
New name of the datasets.
Examples
--------
Rename datasets containing the deformation gradient from 'F' to 'def_grad':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r_unprotected = r.modification_enable()
>>> r_unprotected.rename('F','def_grad')
"""
if not self._allow_modification:
raise PermissionError('Rename operation not permitted')
raise PermissionError('Renaming datasets not permitted')
with h5py.File(self.fname,'a') as f:
for inc in self.visible['increments']:
for ty in ['phase','homogenization']:
for label in self.visible[ty+'s']:
for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
path_old = '/'.join([inc,ty,label,field,name_old])
path_new = '/'.join([inc,ty,label,field,name_new])
if path_old in f.keys():
f[path_new] = f[path_old]
f[path_new].attrs['renamed'] = f'original name: {name_old}' if h5py3 else \
f'original name: {name_old}'.encode()
del f[path_old]
path_src = '/'.join([inc,ty,label,field,name_src])
path_dst = '/'.join([inc,ty,label,field,name_dst])
if path_src in f.keys():
f[path_dst] = f[path_src]
f[path_dst].attrs['renamed'] = f'original name: {name_src}' if h5py3 else \
f'original name: {name_src}'.encode()
del f[path_src]
def remove(self,name):
"""
Remove/delete datasets.
This operation is discouraged because the history of the
data becomes untracable and scientific integrity cannot be
ensured.
Parameters
----------
name : str
Name of the datasets to be deleted.
Examples
--------
Delete the deformation gradient 'F':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r_unprotected = r.modification_enable()
>>> r_unprotected.remove('F')
"""
if not self._allow_modification:
raise PermissionError('Removing datasets not permitted')
with h5py.File(self.fname,'a') as f:
for inc in self.visible['increments']:
for ty in ['phase','homogenization']:
for label in self.visible[ty+'s']:
for field in _match(self.visible['fields'],f['/'.join([inc,ty,label])].keys()):
path = '/'.join([inc,ty,label,field,name])
if path in f.keys(): del f[path]
def list_data(self):
@ -438,7 +562,7 @@ class Result:
Parameters
----------
x : str
Label of scalar, vector, or tensor dataset to take absolute value of.
Name of scalar, vector, or tensor dataset to take absolute value of.
"""
self._add_generic_pointwise(self._add_absolute,{'x':x})
@ -459,24 +583,51 @@ class Result:
'creator': 'add_calculation'
}
}
def add_calculation(self,label,formula,unit='n/a',description=None):
def add_calculation(self,name,formula,unit='n/a',description=None):
"""
Add result of a general formula.
Parameters
----------
label : str
Label of resulting dataset.
name : str
Name of resulting dataset.
formula : str
Formula to calculate resulting dataset. Existing datasets are referenced by '#TheirLabel#'.
Formula to calculate resulting dataset. Existing datasets are referenced by '#TheirName#'.
unit : str, optional
Physical unit of the result.
description : str, optional
Human-readable description of the result.
Examples
--------
Add total dislocation density, i.e. the sum of mobile dislocation
density 'rho_mob' and dislocation dipole density 'rho_dip' over
all slip systems:
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_calculation('rho_mob_total','np.sum(#rho_mob#,axis=1)',
... '1/m²','total mobile dislocation density')
>>> r.add_calculation('rho_dip_total','np.sum(#rho_dip#,axis=1)',
... '1/m²','total dislocation dipole density')
>>> r.add_calculation('rho_total','#rho_dip_total#+#rho_mob_total',
... '1/m²','total dislocation density')
Add Mises equivalent of the Cauchy stress without storage of
intermediate results. Define a user function for better readability:
>>> import damask
>>> def equivalent_stress(F,P):
... sigma = damask.mechanics.stress_Cauchy(F=F,P=P)
... return damask.mechanics.equivalent_stress_Mises(sigma)
>>> r = damask.Result('my_file.hdf5')
>>> r.enable_user_function(equivalent_stress)
>>> r.add_calculation('sigma_vM','equivalent_stress(#F#,#P#)','Pa',
... 'Mises equivalent of the Cauchy stress')
"""
dataset_mapping = {d:d for d in set(re.findall(r'#(.*?)#',formula))} # datasets used in the formula
args = {'formula':formula,'label':label,'unit':unit,'description':description}
args = {'formula':formula,'label':name,'unit':unit,'description':description}
self._add_generic_pointwise(self._add_calculation,dataset_mapping,args)
@ -500,9 +651,9 @@ class Result:
Parameters
----------
P : str, optional
Label of the dataset containing the first Piola-Kirchhoff stress. Defaults to 'P'.
Name of the dataset containing the first Piola-Kirchhoff stress. Defaults to 'P'.
F : str, optional
Label of the dataset containing the deformation gradient. Defaults to 'F'.
Name of the dataset containing the deformation gradient. Defaults to 'F'.
"""
self._add_generic_pointwise(self._add_stress_Cauchy,{'P':P,'F':F})
@ -526,7 +677,15 @@ class Result:
Parameters
----------
T : str
Label of tensor dataset.
Name of tensor dataset.
Examples
--------
Add the determinant of plastic deformation gradient 'F_p':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_determinant('F_p')
"""
self._add_generic_pointwise(self._add_determinant,{'T':T})
@ -550,7 +709,7 @@ class Result:
Parameters
----------
T : str
Label of tensor dataset.
Name of tensor dataset.
"""
self._add_generic_pointwise(self._add_deviator,{'T':T})
@ -581,7 +740,7 @@ class Result:
Parameters
----------
T_sym : str
Label of symmetric tensor dataset.
Name of symmetric tensor dataset.
eigenvalue : str, optional
Eigenvalue. Select from 'max', 'mid', 'min'. Defaults to 'max'.
@ -614,7 +773,7 @@ class Result:
Parameters
----------
T_sym : str
Label of symmetric tensor dataset.
Name of symmetric tensor dataset.
eigenvalue : str, optional
Eigenvalue to which the eigenvector corresponds.
Select from 'max', 'mid', 'min'. Defaults to 'max'.
@ -654,9 +813,17 @@ class Result:
l : numpy.array of shape (3)
Lab frame direction for inverse pole figure.
q : str
Label of the dataset containing the crystallographic orientation as quaternions.
Name of the dataset containing the crystallographic orientation as quaternions.
Defaults to 'O'.
Examples
--------
Add the IPF color along [0,1,1] for orientation 'O':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_IPF_color(np.array([0,1,1]))
"""
self._add_generic_pointwise(self._add_IPF_color,{'q':q},{'l':l})
@ -679,7 +846,7 @@ class Result:
Parameters
----------
T_sym : str
Label of symmetric tensor dataset.
Name of symmetric tensor dataset.
"""
self._add_generic_pointwise(self._add_maximum_shear,{'T_sym':T_sym})
@ -713,11 +880,25 @@ class Result:
Parameters
----------
T_sym : str
Label of symmetric tensorial stress or strain dataset.
Name of symmetric tensorial stress or strain dataset.
kind : {'stress', 'strain', None}, optional
Kind of the von Mises equivalent. Defaults to None, in which case
it is selected based on the unit of the dataset ('1' -> strain, 'Pa' -> stress).
Examples
--------
Add the Mises equivalent of the Cauchy stress 'sigma':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_equivalent_Mises('sigma')
Add the Mises equivalent of the spatial logarithmic strain 'epsilon_V^0.0(F)':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_equivalent_Mises('epsilon_V^0.0(F)')
"""
self._add_generic_pointwise(self._add_equivalent_Mises,{'T_sym':T_sym},{'kind':kind})
@ -752,7 +933,7 @@ class Result:
Parameters
----------
x : str
Label of vector or tensor dataset.
Name of vector or tensor dataset.
ord : {non-zero int, inf, -inf, 'fro', 'nuc'}, optional
Order of the norm. inf means NumPy’s inf object. For details refer to numpy.linalg.norm.
@ -780,9 +961,9 @@ class Result:
Parameters
----------
P : str, optional
Label of first Piola-Kirchhoff stress dataset. Defaults to 'P'.
Name of first Piola-Kirchhoff stress dataset. Defaults to 'P'.
F : str, optional
Label of deformation gradient dataset. Defaults to 'F'.
Name of deformation gradient dataset. Defaults to 'F'.
"""
self._add_generic_pointwise(self._add_stress_second_Piola_Kirchhoff,{'P':P,'F':F})
@ -821,7 +1002,7 @@ class Result:
# Parameters
# ----------
# q : str
# Label of the dataset containing the crystallographic orientation as quaternions.
# Name of the dataset containing the crystallographic orientation as quaternions.
# p : numpy.array of shape (3)
# Crystallographic direction or plane.
# polar : bool, optional
@ -848,8 +1029,16 @@ class Result:
Parameters
----------
F : str, optional
Label of deformation gradient dataset.
F : str
Name of deformation gradient dataset.
Examples
--------
Add the rotational part of deformation gradient 'F':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_rotation('F')
"""
self._add_generic_pointwise(self._add_rotation,{'F':F})
@ -873,7 +1062,15 @@ class Result:
Parameters
----------
T : str
Label of tensor dataset.
Name of tensor dataset.
Examples
--------
Add the hydrostatic part of the Cauchy stress 'sigma':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.add_spherical('sigma')
"""
self._add_generic_pointwise(self._add_spherical,{'T':T})
@ -899,13 +1096,28 @@ class Result:
Parameters
----------
F : str, optional
Label of deformation gradient dataset. Defaults to 'F'.
Name of deformation gradient dataset. Defaults to 'F'.
t : {'V', 'U'}, optional
Type of the polar decomposition, 'V' for left stretch tensor and 'U' for right stretch tensor.
Defaults to 'V'.
m : float, optional
Order of the strain calculation. Defaults to 0.0.
Examples
--------
Add the Biot strain based on the deformation gradient 'F':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.strain(t='U',m=0.5)
Add the plastic Euler-Almansi strain based on the
plastic deformation gradient 'F_p':
>>> import damask
>>> r = damask.Result('my_file.hdf5')
>>> r.strain('F_p','V',-1)
"""
self._add_generic_pointwise(self._add_strain,{'F':F},{'t':t,'m':m})
@ -929,7 +1141,7 @@ class Result:
Parameters
----------
F : str, optional
Label of deformation gradient dataset. Defaults to 'F'.
Name of deformation gradient dataset. Defaults to 'F'.
t : {'V', 'U'}, optional
Type of the polar decomposition, 'V' for left stretch tensor and 'U' for right stretch tensor.
Defaults to 'V'.
@ -1036,10 +1248,14 @@ class Result:
"""
Write XDMF file to directly visualize data in DADF5 file.
The XDMF format is only supported for structured grids
with single phase and single constituent.
For other cases use `save_VTK`.
Parameters
----------
output : (list of) str
Labels of the datasets to read.
Names of the datasets included in the XDMF file.
Defaults to '*', in which case all datasets are considered.
"""
@ -1169,10 +1385,16 @@ class Result:
"""
Export to VTK cell/point data.
One VTK file per visible increment is created.
For cell data, the VTK format is a rectilinear grid (.vtr) for
grid-based simulations and an unstructured grid (.vtu) for
mesh-baed simulations. For point data, the VTK format is poly
data (.vtp).
Parameters
----------
output : (list of) str, optional
Labels of the datasets to place.
Names of the datasets included in the VTK file.
Defaults to '*', in which case all datasets are exported.
mode : {'cell', 'point'}
Export in cell format or point format.
@ -1251,7 +1473,7 @@ class Result:
Parameters
----------
output : (list of) str
Labels of the datasets to read.
Names of the datasets to read.
Defaults to '*', in which case all datasets are read.
flatten : bool
Remove singular levels of the folder hierarchy.
@ -1303,7 +1525,7 @@ class Result:
Parameters
----------
output : (list of) str, optional
Labels of the datasets to place.
Names of the datasets to read.
Defaults to '*', in which case all datasets are placed.
flatten : bool
Remove singular levels of the folder hierarchy.

6
python/damask/_table.py
View File

@ -49,7 +49,7 @@ class Table:
Returns
-------
slice : Table
slice : damask.Table
Sliced part of the Table.
Examples
@ -157,7 +157,7 @@ class Table:
Parameters
----------
other : Table
other : damask.Table
Table to compare against.
rtol : float, optional
Relative tolerance of equality.
@ -185,7 +185,7 @@ class Table:
Parameters
----------
other : Table
other : damask.Table
Table to compare against.
rtol : float, optional
Relative tolerance of equality.

10
python/damask/_vtk.py
View File

@ -137,8 +137,8 @@ class VTK:
fname : str or pathlib.Path
Filename for reading. Valid extensions are .vtr, .vtu, .vtp, and .vtk.
dataset_type : str, optional
Name of the vtk.vtkDataSet subclass when opening a .vtk file. Valid types are vtkRectilinearGrid,
vtkUnstructuredGrid, and vtkPolyData.
Name of the vtk.vtkDataSet subclass when opening a .vtk file.
Valid types are vtkRectilinearGrid, vtkUnstructuredGrid, and vtkPolyData.
"""
if not os.path.isfile(fname): # vtk has a strange error handling
@ -149,13 +149,13 @@ class VTK:
reader.SetFileName(str(fname))
if dataset_type is None:
raise TypeError('Dataset type for *.vtk file not given.')
elif dataset_type.lower().endswith('rectilineargrid'):
elif dataset_type.lower().endswith(('rectilineargrid','rectilinear_grid')):
reader.Update()
vtk_data = reader.GetRectilinearGridOutput()
elif dataset_type.lower().endswith('unstructuredgrid'):
elif dataset_type.lower().endswith(('unstructuredgrid','unstructured_grid')):
reader.Update()
vtk_data = reader.GetUnstructuredGridOutput()
elif dataset_type.lower().endswith('polydata'):
elif dataset_type.lower().endswith(('polydata','poly_data')):
reader.Update()
vtk_data = reader.GetPolyDataOutput()
else:

2
python/damask/mechanics.py
View File

@ -3,7 +3,7 @@ Finite-strain continuum mechanics.
Notes
-----
Collection of routines to operate on numpy.ndarrays of shape (...,3,3).
All routines operate on numpy.ndarrays of shape (...,3,3).
"""

20
python/tests/test_Result.py
View File

@ -271,7 +271,7 @@ class TestResult:
@pytest.mark.parametrize('overwrite',['off','on'])
def test_add_overwrite(self,default,overwrite):
last = default.view('times',default.times_in_range(0,np.inf)[-1])
last = default.view('increments',-1)
last.add_stress_Cauchy()
@ -279,9 +279,9 @@ class TestResult:
created_first = datetime.strptime(created_first,'%Y-%m-%d %H:%M:%S%z')
if overwrite == 'on':
last = last.allow_modification()
last = last.modification_enable()
else:
last = last.disallow_modification()
last = last.modification_disable()
time.sleep(2.)
try:
@ -301,14 +301,24 @@ class TestResult:
def test_rename(self,default,allowed):
if allowed == 'on':
F = default.place('F')
default = default.allow_modification()
default = default.modification_enable()
default.rename('F','new_name')
assert np.all(F == default.place('new_name'))
default = default.disallow_modification()
default = default.modification_disable()
with pytest.raises(PermissionError):
default.rename('P','another_new_name')
@pytest.mark.parametrize('allowed',['off','on'])
def test_remove(self,default,allowed):
if allowed == 'on':
unsafe = default.modification_enable()
unsafe.remove('F')
assert unsafe.get('F') is None
else:
with pytest.raises(PermissionError):
default.remove('F')
@pytest.mark.parametrize('mode',['cell','node'])
def test_coordinates(self,default,mode):
if mode == 'cell':