ordered alphabetically
This commit is contained in:
Martin Diehl
parent
6902d3dd0a
commit
285075bb6b
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@ -437,6 +437,76 @@ class DADF5():
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else:
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with h5py.File(self.filename,'r') as f:
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return f['geometry/x_c'][()]
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def add_absolute(self,x):
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"""
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Add absolute value.
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Parameters
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----------
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x : str
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Label of the dataset containing a scalar, vector, or tensor.
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"""
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def __add_absolute(x):
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return {
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'data': np.abs(x['data']),
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'label': '|{}|'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Absolute value of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_abs v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_absolute,requested)
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def add_calculation(self,formula,label,unit='n/a',description=None,vectorized=True):
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"""
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Add result of a general formula.
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Parameters
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----------
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formula : str
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Formula, refer to datasets by ‘#Label#‘.
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label : str
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Label of the dataset containing the result of the calculation.
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unit : str, optional
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Physical unit of the result.
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description : str, optional
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Human readable description of the result.
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vectorized : bool, optional
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Indicate whether the formula is written in vectorized form. Default is ‘True’.
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"""
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if vectorized is not True:
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raise NotImplementedError
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def __add_calculation(**kwargs):
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formula = kwargs['formula']
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for d in re.findall(r'#(.*?)#',formula):
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formula = formula.replace('#{}#'.format(d),"kwargs['{}']['data']".format(d))
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return {
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'data': eval(formula),
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'label': kwargs['label'],
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'meta': {
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'Unit': kwargs['unit'],
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'Description': '{} (formula: {})'.format(kwargs['description'],kwargs['formula']),
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'Creator': 'dadf5.py:add_calculation v{}'.format(version)
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}
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}
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requested = [{'label':d,'arg':d} for d in set(re.findall(r'#(.*?)#',formula))] # datasets used in the formula
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pass_through = {'formula':formula,'label':label,'unit':unit,'description':description}
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self.__add_generic_pointwise(__add_calculation,requested,pass_through)
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def add_Cauchy(self,P='P',F='F'):
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@ -470,6 +540,90 @@ class DADF5():
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self.__add_generic_pointwise(__add_Cauchy,requested)
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def add_determinant(self,x):
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"""
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Add the determinant of a tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a tensor.
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"""
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def __add_determinant(x):
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return {
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'data': np.linalg.det(x['data']),
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'label': 'det({})'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Determinant of tensor {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_determinant v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_determinant,requested)
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def add_deviator(self,x):
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"""
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Add the deviatoric part of a tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a tensor.
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"""
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def __add_deviator(x):
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if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
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raise ValueError
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return {
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'data': mechanics.deviatoric_part(x['data']),
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'label': 's_{}'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Deviator of tensor {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_deviator v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_deviator,requested)
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def add_maximum_shear(self,x):
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"""
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Add maximum shear components of symmetric tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a symmetric tensor.
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"""
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def __add_maximum_shear(x):
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return {
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'data': mechanics.maximum_shear(x['data']),
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'label': 'max_shear({})'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Maximum shear component of of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_maximum_shear v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_maximum_shear,requested)
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def add_Mises(self,x):
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"""
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Add the equivalent Mises stress or strain of a symmetric tensor.
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@ -540,58 +694,33 @@ class DADF5():
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self.__add_generic_pointwise(__add_norm,requested,{'ord':ord})
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def add_absolute(self,x):
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def add_principal_components(self,x):
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"""
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Add absolute value.
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Add principal components of symmetric tensor.
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The principal components are sorted in descending order, each repeated according to its multiplicity.
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Parameters
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----------
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x : str
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Label of the dataset containing a scalar, vector, or tensor.
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Label of the dataset containing a symmetric tensor.
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"""
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def __add_absolute(x):
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def __add_principal_components(x):
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return {
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'data': np.abs(x['data']),
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'label': '|{}|'.format(x['label']),
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'data': mechanics.principal_components(x['data']),
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'label': 'lambda_{}'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Absolute value of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_abs v{}'.format(version)
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'Description': 'Pricipal components of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_principal_components v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_absolute,requested)
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def add_determinant(self,x):
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"""
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Add the determinant of a tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a tensor.
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"""
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def __add_determinant(x):
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return {
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'data': np.linalg.det(x['data']),
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'label': 'det({})'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Determinant of tensor {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_determinant v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_determinant,requested)
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self.__add_generic_pointwise(__add_principal_components,requested)
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def add_spherical(self,x):
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@ -624,79 +753,6 @@ class DADF5():
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self.__add_generic_pointwise(__add_spherical,requested)
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def add_deviator(self,x):
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"""
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Add the deviatoric part of a tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a tensor.
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"""
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def __add_deviator(x):
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if not np.all(np.array(x['data'].shape[1:]) == np.array([3,3])):
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raise ValueError
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return {
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'data': mechanics.deviatoric_part(x['data']),
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'label': 's_{}'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Deviator of tensor {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_deviator v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_deviator,requested)
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def add_calculation(self,formula,label,unit='n/a',description=None,vectorized=True):
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"""
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Add result of a general formula.
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Parameters
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----------
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formula : str
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Formula, refer to datasets by ‘#Label#‘.
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label : str
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Label of the dataset containing the result of the calculation.
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unit : str, optional
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Physical unit of the result.
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description : str, optional
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Human readable description of the result.
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vectorized : bool, optional
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Indicate whether the formula is written in vectorized form. Default is ‘True’.
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"""
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if vectorized is not True:
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raise NotImplementedError
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def __add_calculation(**kwargs):
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formula = kwargs['formula']
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for d in re.findall(r'#(.*?)#',formula):
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formula = formula.replace('#{}#'.format(d),"kwargs['{}']['data']".format(d))
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return {
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'data': eval(formula),
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'label': kwargs['label'],
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'meta': {
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'Unit': kwargs['unit'],
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'Description': '{} (formula: {})'.format(kwargs['description'],kwargs['formula']),
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'Creator': 'dadf5.py:add_calculation v{}'.format(version)
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}
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}
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requested = [{'label':d,'arg':d} for d in set(re.findall(r'#(.*?)#',formula))] # datasets used in the formula
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pass_through = {'formula':formula,'label':label,'unit':unit,'description':description}
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self.__add_generic_pointwise(__add_calculation,requested,pass_through)
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def add_strain_tensor(self,F='F',t='U',m=0):
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"""
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Add strain tensor calculated from a deformation gradient.
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@ -729,62 +785,6 @@ class DADF5():
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requested = [{'label':F,'arg':'F'}]
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self.__add_generic_pointwise(__add_strain_tensor,requested,{'t':t,'m':m})
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def add_principal_components(self,x):
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"""
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Add principal components of symmetric tensor.
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The principal components are sorted in descending order, each repeated according to its multiplicity.
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Parameters
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----------
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x : str
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Label of the dataset containing a symmetric tensor.
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"""
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def __add_principal_components(x):
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return {
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'data': mechanics.principal_components(x['data']),
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'label': 'lambda_{}'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Pricipal components of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_principal_components v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_principal_components,requested)
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def add_maximum_shear(self,x):
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"""
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Add maximum shear components of symmetric tensor.
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Parameters
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----------
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x : str
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Label of the dataset containing a symmetric tensor.
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"""
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def __add_maximum_shear(x):
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return {
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'data': mechanics.maximum_shear(x['data']),
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'label': 'max_shear({})'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Maximum shear component of of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_maximum_shear v{}'.format(version)
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}
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}
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requested = [{'label':x,'arg':'x'}]
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self.__add_generic_pointwise(__add_maximum_shear,requested)
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def __add_generic_pointwise(self,func,datasets_requested,extra_args={}):
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@ -28,14 +28,15 @@ class TestDADF5:
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shape = default.read_dataset(default.get_dataset_location('F'),0).shape
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default.set_by_time(0.0,20.0)
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for i in default.iter_visible('increments'):
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assert shape == default.read_dataset(default.get_dataset_location('F'),0).shape
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assert shape == default.read_dataset(default.get_dataset_location('F'),0).shape
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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 = mechanics.deviatoric_part(default.read_dataset(loc['P'],0))
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in_file = default.read_dataset(loc['s_P'],0)
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def test_add_absolute(self,default):
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default.add_absolute('Fe')
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loc = {'Fe': default.get_dataset_location('Fe'),
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'|Fe|': default.get_dataset_location('|Fe|')}
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in_memory = np.abs(default.read_dataset(loc['Fe'],0))
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in_file = default.read_dataset(loc['|Fe|'],0)
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assert np.allclose(in_memory,in_file)
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def test_add_Cauchy(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))
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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 = mechanics.deviatoric_part(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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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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@ -64,14 +73,6 @@ class TestDADF5:
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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_absolute(self,default):
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default.add_absolute('Fe')
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loc = {'Fe': default.get_dataset_location('Fe'),
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'|Fe|': default.get_dataset_location('|Fe|')}
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in_memory = np.abs(default.read_dataset(loc['Fe'],0))
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in_file = default.read_dataset(loc['|Fe|'],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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