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DAMASK_EICMD
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simplified interface

This commit is contained in:
Martin Diehl 2020-02-21 07:39:53 +01:00
parent 9beca6488c
commit effaef46db
1 changed files with 43 additions and 75 deletions
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118
python/damask/dadf5.py
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@ -459,7 +459,7 @@ class DADF5():
Label of the dataset containing a scalar, vector, or tensor. Label of the dataset containing a scalar, vector, or tensor.
""" """
def __add_absolute(x): def _add_absolute(x):
return { return {
'data': np.abs(x['data']), 'data': np.abs(x['data']),
@ -471,9 +471,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_absolute,{'x':x})
self.__add_generic_pointwise(__add_absolute,requested)
def add_calculation(self,formula,label,unit='n/a',description=None,vectorized=True): def add_calculation(self,formula,label,unit='n/a',description=None,vectorized=True):
@ -497,7 +495,7 @@ class DADF5():
if vectorized is False: if vectorized is False:
raise NotImplementedError raise NotImplementedError
def __add_calculation(**kwargs): def _add_calculation(**kwargs):
formula = kwargs['formula'] formula = kwargs['formula']
for d in re.findall(r'#(.*?)#',formula): for d in re.findall(r'#(.*?)#',formula):
@ -513,10 +511,10 @@ class DADF5():
} }
} }
requested = [{'label':d,'arg':d} for d in set(re.findall(r'#(.*?)#',formula))] # datasets used in the formula dataset_mapping = {d:d for d in set(re.findall(r'#(.*?)#',formula))} # datasets used in the formula
pass_through = {'formula':formula,'label':label,'unit':unit,'description':description} args = {'formula':formula,'label':label,'unit':unit,'description':description}
self.__add_generic_pointwise(__add_calculation,requested,pass_through) self.__add_generic_pointwise(_add_calculation,dataset_mapping,args)
def add_Cauchy(self,F='F',P='P'): def add_Cauchy(self,F='F',P='P'):
@ -531,7 +529,7 @@ class DADF5():
Label of the dataset containing the deformation gradient. Default value is ‘F’. Label of the dataset containing the deformation gradient. Default value is ‘F’.
""" """
def __add_Cauchy(F,P): def _add_Cauchy(F,P):
return { return {
'data': mechanics.Cauchy(F['data'],P['data']), 'data': mechanics.Cauchy(F['data'],P['data']),
@ -545,10 +543,7 @@ class DADF5():
} }
} }
requested = [{'label':F,'arg':'F'}, self.__add_generic_pointwise(_add_Cauchy,{'F':F,'P':P})
{'label':P,'arg':'P'} ]
self.__add_generic_pointwise(__add_Cauchy,requested)
def add_determinant(self,x): def add_determinant(self,x):
@ -561,7 +556,7 @@ class DADF5():
Label of the dataset containing a tensor. Label of the dataset containing a tensor.
""" """
def __add_determinant(x): def _add_determinant(x):
return { return {
'data': np.linalg.det(x['data']), 'data': np.linalg.det(x['data']),
@ -573,9 +568,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_determinant,{'x':x})
self.__add_generic_pointwise(__add_determinant,requested)
def add_deviator(self,x): def add_deviator(self,x):
@ -588,7 +581,7 @@ class DADF5():
Label of the dataset containing a tensor. Label of the dataset containing a tensor.
""" """
def __add_deviator(x): def _add_deviator(x):
if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])): if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
raise ValueError raise ValueError
@ -603,9 +596,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_deviator,{'x':x})
self.__add_generic_pointwise(__add_deviator,requested)
def add_eigenvalues(self,x): def add_eigenvalues(self,x):
@ -618,7 +609,7 @@ class DADF5():
Label of the dataset containing a symmetric tensor. Label of the dataset containing a symmetric tensor.
""" """
def __add_eigenvalue(x): def _add_eigenvalue(x):
return { return {
'data': mechanics.eigenvalues(x['data']), 'data': mechanics.eigenvalues(x['data']),
@ -629,9 +620,8 @@ class DADF5():
'Creator': 'dadf5.py:add_eigenvalues v{}'.format(version) 'Creator': 'dadf5.py:add_eigenvalues v{}'.format(version)
} }
} }
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_eigenvalue,requested) self.__add_generic_pointwise(_add_eigenvalue,{'x':x})
def add_eigenvectors(self,x): def add_eigenvectors(self,x):
@ -644,7 +634,7 @@ class DADF5():
Label of the dataset containing a symmetric tensor. Label of the dataset containing a symmetric tensor.
""" """
def __add_eigenvector(x): def _add_eigenvector(x):
return { return {
'data': mechanics.eigenvectors(x['data']), 'data': mechanics.eigenvectors(x['data']),
@ -655,9 +645,8 @@ class DADF5():
'Creator': 'dadf5.py:add_eigenvectors v{}'.format(version) 'Creator': 'dadf5.py:add_eigenvectors v{}'.format(version)
} }
} }
requested = [{'label':x,'arg':'x'}]
self.__add_generic_pointwise(__add_eigenvector,requested) self.__add_generic_pointwise(_add_eigenvector,{'x':x})
def add_IPFcolor(self,q,p): def add_IPFcolor(self,q,p):
@ -672,7 +661,7 @@ class DADF5():
Pole direction as Miller indices. Pole direction as Miller indices.
""" """
def __add_IPFcolor(q,p): def _add_IPFcolor(q,p):
pole = np.array(p) pole = np.array(p)
unit_pole = pole/np.linalg.norm(pole) unit_pole = pole/np.linalg.norm(pole)
@ -696,9 +685,7 @@ class DADF5():
} }
} }
requested = [{'label':q,'arg':'q'}] self.__add_generic_pointwise(_add_IPFcolor,{'q':q},{'p':p})
self.__add_generic_pointwise(__add_IPFcolor,requested,{'p':p})
def add_maximum_shear(self,x): def add_maximum_shear(self,x):
@ -711,7 +698,7 @@ class DADF5():
Label of the dataset containing a symmetric tensor. Label of the dataset containing a symmetric tensor.
""" """
def __add_maximum_shear(x): def _add_maximum_shear(x):
return { return {
'data': mechanics.maximum_shear(x['data']), 'data': mechanics.maximum_shear(x['data']),
@ -723,9 +710,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_maximum_shear,{'x':x})
self.__add_generic_pointwise(__add_maximum_shear,requested)
def add_Mises(self,x): def add_Mises(self,x):
@ -738,7 +723,7 @@ class DADF5():
Label of the dataset containing a symmetric stress or strain tensor. Label of the dataset containing a symmetric stress or strain tensor.
""" """
def __add_Mises(x): def _add_Mises(x):
t = 'strain' if x['meta']['Unit'] == '1' else \ t = 'strain' if x['meta']['Unit'] == '1' else \
'stress' 'stress'
@ -752,9 +737,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_Mises,{'x':x})
self.__add_generic_pointwise(__add_Mises,requested)
def add_norm(self,x,ord=None): def add_norm(self,x,ord=None):
@ -769,7 +752,7 @@ class DADF5():
Order of the norm. inf means numpy’s inf object. For details refer to numpy.linalg.norm. Order of the norm. inf means numpy’s inf object. For details refer to numpy.linalg.norm.
""" """
def __add_norm(x,ord): def _add_norm(x,ord):
o = ord o = ord
if len(x['data'].shape) == 2: if len(x['data'].shape) == 2:
@ -793,9 +776,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_norm,{'x':x},{'ord':ord})
self.__add_generic_pointwise(__add_norm,requested,{'ord':ord})
def add_PK2(self,F='F',P='P'): def add_PK2(self,F='F',P='P'):
@ -810,7 +791,7 @@ class DADF5():
Label of the dataset containing the deformation gradient. Default value is ‘F’. Label of the dataset containing the deformation gradient. Default value is ‘F’.
""" """
def __add_PK2(F,P): def _add_PK2(F,P):
return { return {
'data': mechanics.PK2(F['data'],P['data']), 'data': mechanics.PK2(F['data'],P['data']),
@ -824,10 +805,7 @@ class DADF5():
} }
} }
requested = [{'label':F,'arg':'F'}, self.__add_generic_pointwise(_add_PK2,{'F':F,'P':P})
{'label':P,'arg':'P'},]
self.__add_generic_pointwise(__add_PK2,requested)
def add_pole(self,q,p,polar=False): def add_pole(self,q,p,polar=False):
@ -844,7 +822,7 @@ class DADF5():
Give pole in polar coordinates. Default is false. Give pole in polar coordinates. Default is false.
""" """
def __add_pole(q,p,polar): def _add_pole(q,p,polar):
pole = np.array(p) pole = np.array(p)
unit_pole = pole/np.linalg.norm(pole) unit_pole = pole/np.linalg.norm(pole)
@ -868,12 +846,10 @@ class DADF5():
} }
} }
requested = [{'label':q,'arg':'q'}] self.__add_generic_pointwise(_add_pole,{'q':q},{'p':p,'polar':polar})
self.__add_generic_pointwise(__add_pole,requested,{'p':p,'polar':polar})
def add_rotational_part(self,F='F'): def add_rotational_part(self,F):
""" """
Add rotational part of a deformation gradient. Add rotational part of a deformation gradient.
@ -883,7 +859,7 @@ class DADF5():
Label of the dataset containing a deformation gradient. Default value is ‘F’. Label of the dataset containing a deformation gradient. Default value is ‘F’.
""" """
def __add_rotational_part(F): def _add_rotational_part(F):
return { return {
'data': mechanics.rotational_part(F['data']), 'data': mechanics.rotational_part(F['data']),
@ -895,9 +871,7 @@ class DADF5():
} }
} }
requested = [{'label':F,'arg':'F'}] self.__add_generic_pointwise(_add_rotational_part,{'F':F})
self.__add_generic_pointwise(__add_rotational_part,requested)
def add_spherical(self,x): def add_spherical(self,x):
@ -910,7 +884,7 @@ class DADF5():
Label of the dataset containing a tensor. Label of the dataset containing a tensor.
""" """
def __add_spherical(x): def _add_spherical(x):
if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])): if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
raise ValueError raise ValueError
@ -925,9 +899,7 @@ class DADF5():
} }
} }
requested = [{'label':x,'arg':'x'}] self.__add_generic_pointwise(_add_spherical,{'x':x})
self.__add_generic_pointwise(__add_spherical,requested)
def add_strain_tensor(self,F='F',t='U',m=0): def add_strain_tensor(self,F='F',t='U',m=0):
@ -947,7 +919,7 @@ class DADF5():
Order of the strain calculation. Default value is ‘0.0’. Order of the strain calculation. Default value is ‘0.0’.
""" """
def __add_strain_tensor(F,t,m): def _add_strain_tensor(F,t,m):
return { return {
'data': mechanics.strain_tensor(F['data'],t,m), 'data': mechanics.strain_tensor(F['data'],t,m),
@ -959,9 +931,7 @@ class DADF5():
} }
} }
requested = [{'label':F,'arg':'F'}] self.__add_generic_pointwise(_add_strain_tensor,{'F':F},{'t':t,'m':m})
self.__add_generic_pointwise(__add_strain_tensor,requested,{'t':t,'m':m})
def add_stretch_tensor(self,F='F',t='U'): def add_stretch_tensor(self,F='F',t='U'):
@ -977,7 +947,7 @@ class DADF5():
Default value is ‘U’. Default value is ‘U’.
""" """
def __add_stretch_tensor(F,t): def _add_stretch_tensor(F,t):
return { return {
'data': mechanics.left_stretch(F['data']) if t == 'V' else mechanics.right_stretch(F['data']), 'data': mechanics.left_stretch(F['data']) if t == 'V' else mechanics.right_stretch(F['data']),
@ -990,12 +960,10 @@ class DADF5():
} }
} }
requested = [{'label':F,'arg':'F'}] self.__add_generic_pointwise(_add_stretch_tensor,{'F':F},{'t':t})
self.__add_generic_pointwise(__add_stretch_tensor,requested,{'t':t})
def __add_generic_pointwise(self,func,datasets_requested,extra_args={}): def __add_generic_pointwise(self,func,dataset_mapping,args={}):
""" """
General function to add pointwise data. General function to add pointwise data.
@ -1022,16 +990,16 @@ class DADF5():
todo = [] todo = []
# ToDo: It would be more memory efficient to read only from file when required, i.e. do to it in pool.add_task # ToDo: It would be more memory efficient to read only from file when required, i.e. do to it in pool.add_task
for group in self.groups_with_datasets([d['label'] for d in datasets_requested]): for group in self.groups_with_datasets(dataset_mapping.values()):
with h5py.File(self.fname,'r') as f: with h5py.File(self.fname,'r') as f:
datasets_in = {} datasets_in = {}
for d in datasets_requested: for arg,label in dataset_mapping.items():
loc = f[group+'/'+d['label']] loc = f[group+'/'+label]
data = loc[()] data = loc[()]
meta = {k:loc.attrs[k].decode() for k in loc.attrs.keys()} meta = {k:loc.attrs[k].decode() for k in loc.attrs.keys()}
datasets_in[d['arg']] = {'data': data, 'meta' : meta, 'label' : d['label']} datasets_in[arg] = {'data': data, 'meta': meta, 'label': label}
todo.append({'in':{**datasets_in,**extra_args},'func':func,'group':group,'results':results}) todo.append({'in':{**datasets_in,**args},'func':func,'group':group,'results':results})
pool.map(job, todo[:N_added]) # initialize pool.map(job, todo[:N_added]) # initialize